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2008.10114
Roohallah Alizadehsani
Roohallah Alizadehsani, Mohamad Roshanzamir, Sadiq Hussain, Abbas Khosravi, Afsaneh Koohestani, Mohammad Hossein Zangooei, Moloud Abdar, Adham Beykikhoshk, Afshin Shoeibi, Assef Zare, Maryam Panahiazar, Saeid Nahavandi, Dipti Srinivasan, Amir F. Atiya, U. Rajendra Acharya
Handling of uncertainty in medical data using machine learning and probability theory techniques: A review of 30 years (1991-2020)
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Understanding data and reaching valid conclusions are of paramount importance in the present era of big data. Machine learning and probability theory methods have widespread application for this purpose in different fields. One critically important yet less explored aspect is how data and model uncertainties are capt...
[ { "created": "Sun, 23 Aug 2020 21:54:27 GMT", "version": "v1" } ]
2020-08-25
[ [ "Alizadehsani", "Roohallah", "" ], [ "Roshanzamir", "Mohamad", "" ], [ "Hussain", "Sadiq", "" ], [ "Khosravi", "Abbas", "" ], [ "Koohestani", "Afsaneh", "" ], [ "Zangooei", "Mohammad Hossein", "" ], [ "Abdar", ...
Understanding data and reaching valid conclusions are of paramount importance in the present era of big data. Machine learning and probability theory methods have widespread application for this purpose in different fields. One critically important yet less explored aspect is how data and model uncertainties are captur...
2308.02180
Cliff Wong
Cliff Wong, Sheng Zhang, Yu Gu, Christine Moung, Jacob Abel, Naoto Usuyama, Roshanthi Weerasinghe, Brian Piening, Tristan Naumann, Carlo Bifulco, Hoifung Poon
Scaling Clinical Trial Matching Using Large Language Models: A Case Study in Oncology
24 pages, 5 figures, accepted at Machine Learning for Healthcare (MLHC) 2023
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Clinical trial matching is a key process in health delivery and discovery. In practice, it is plagued by overwhelming unstructured data and unscalable manual processing. In this paper, we conduct a systematic study on scaling clinical trial matching using large language models (LLMs), with oncology as the focus area....
[ { "created": "Fri, 4 Aug 2023 07:51:15 GMT", "version": "v1" }, { "created": "Mon, 7 Aug 2023 02:53:06 GMT", "version": "v2" }, { "created": "Fri, 18 Aug 2023 20:05:45 GMT", "version": "v3" } ]
2023-08-22
[ [ "Wong", "Cliff", "" ], [ "Zhang", "Sheng", "" ], [ "Gu", "Yu", "" ], [ "Moung", "Christine", "" ], [ "Abel", "Jacob", "" ], [ "Usuyama", "Naoto", "" ], [ "Weerasinghe", "Roshanthi", "" ], [ "Piening...
Clinical trial matching is a key process in health delivery and discovery. In practice, it is plagued by overwhelming unstructured data and unscalable manual processing. In this paper, we conduct a systematic study on scaling clinical trial matching using large language models (LLMs), with oncology as the focus area. O...
1707.09681
Mohamed A. Abd-Elmagid
Mohamed A. Abd-Elmagid, Tamer ElBatt, Karim G. Seddik, Ozgur Ercetin
Stable Throughput of Cooperative Cognitive Networks with Energy Harvesting: Finite Relay Buffer and Finite Battery Capacity
Accepted at IEEE Transactions on Cognitive Communications and Networking with minor revision
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies a generic model for cooperative cognitive radio networks where the secondary user is equipped with a finite relay queue as well as a finite battery queue. Our prime objective is to characterize the stable throughput region. Nevertheless, the complete characterization of the stable throughput region...
[ { "created": "Sun, 30 Jul 2017 23:16:38 GMT", "version": "v1" }, { "created": "Sat, 24 Feb 2018 02:19:14 GMT", "version": "v2" }, { "created": "Sun, 10 Jun 2018 12:53:26 GMT", "version": "v3" }, { "created": "Mon, 18 Jun 2018 11:14:20 GMT", "version": "v4" } ]
2018-06-19
[ [ "Abd-Elmagid", "Mohamed A.", "" ], [ "ElBatt", "Tamer", "" ], [ "Seddik", "Karim G.", "" ], [ "Ercetin", "Ozgur", "" ] ]
This paper studies a generic model for cooperative cognitive radio networks where the secondary user is equipped with a finite relay queue as well as a finite battery queue. Our prime objective is to characterize the stable throughput region. Nevertheless, the complete characterization of the stable throughput region f...
2210.11592
Miguel Ramirez
Miguel A. Ramirez, Sangyoung Yoon, Ernesto Damiani, Hussam Al Hamadi, Claudio Agostino Ardagna, Nicola Bena, Young-Ji Byon, Tae-Yeon Kim, Chung-Suk Cho, and Chan Yeob Yeun
New data poison attacks on machine learning classifiers for mobile exfiltration
arXiv admin note: substantial text overlap with arXiv:2202.10276
null
null
null
cs.CR cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
Most recent studies have shown several vulnerabilities to attacks with the potential to jeopardize the integrity of the model, opening in a few recent years a new window of opportunity in terms of cyber-security. The main interest of this paper is directed towards data poisoning attacks involving label-flipping, this...
[ { "created": "Thu, 20 Oct 2022 21:05:03 GMT", "version": "v1" } ]
2022-10-24
[ [ "Ramirez", "Miguel A.", "" ], [ "Yoon", "Sangyoung", "" ], [ "Damiani", "Ernesto", "" ], [ "Hamadi", "Hussam Al", "" ], [ "Ardagna", "Claudio Agostino", "" ], [ "Bena", "Nicola", "" ], [ "Byon", "Young-Ji", ...
Most recent studies have shown several vulnerabilities to attacks with the potential to jeopardize the integrity of the model, opening in a few recent years a new window of opportunity in terms of cyber-security. The main interest of this paper is directed towards data poisoning attacks involving label-flipping, this k...
2004.01864
Benyamin Ghojogh
Benyamin Ghojogh, Fakhri Karray, Mark Crowley
Theoretical Insights into the Use of Structural Similarity Index In Generative Models and Inferential Autoencoders
Accepted (to appear) in International Conference on Image Analysis and Recognition (ICIAR) 2020, Springer
International Conference on Image Analysis and Recognition, vol 2, pp. 112-117. Springer, Cham, 2020
10.1007/978-3-030-50516-5_10
null
cs.LG cs.CV eess.IV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative models and inferential autoencoders mostly make use of $\ell_2$ norm in their optimization objectives. In order to generate perceptually better images, this short paper theoretically discusses how to use Structural Similarity Index (SSIM) in generative models and inferential autoencoders. We first review S...
[ { "created": "Sat, 4 Apr 2020 05:39:15 GMT", "version": "v1" } ]
2020-07-01
[ [ "Ghojogh", "Benyamin", "" ], [ "Karray", "Fakhri", "" ], [ "Crowley", "Mark", "" ] ]
Generative models and inferential autoencoders mostly make use of $\ell_2$ norm in their optimization objectives. In order to generate perceptually better images, this short paper theoretically discusses how to use Structural Similarity Index (SSIM) in generative models and inferential autoencoders. We first review SSI...
1809.08207
Nof Abuzainab
Nof Abuzainab and Walid Saad
A Graphical Bayesian Game for Secure Sensor Activation in Internet of Battlefield Things
null
null
null
null
cs.IT cs.GT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, the problem of secure sensor activation is studied for an Internet of Battlefield Things (IoBT) system in which an attacker compromises a set of the IoBT sensors for the purpose of eavesdropping and acquiring information about the battlefield. In the considered model, each IoBT sensor seeks to decide w...
[ { "created": "Fri, 21 Sep 2018 16:54:04 GMT", "version": "v1" } ]
2018-09-24
[ [ "Abuzainab", "Nof", "" ], [ "Saad", "Walid", "" ] ]
In this paper, the problem of secure sensor activation is studied for an Internet of Battlefield Things (IoBT) system in which an attacker compromises a set of the IoBT sensors for the purpose of eavesdropping and acquiring information about the battlefield. In the considered model, each IoBT sensor seeks to decide whe...
1909.04404
Martin Klein
Martin Klein, Harihar Shankar, Lyudmila Balakireva, Herbert Van de Sompel
The Memento Tracer Framework: Balancing Quality and Scalability for Web Archiving
Accepted for publication at TPDL 2019
null
10.1007/978-3-030-30760-8_15
null
cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Web archiving frameworks are commonly assessed by the quality of their archival records and by their ability to operate at scale. The ubiquity of dynamic web content poses a significant challenge for crawler-based solutions such as the Internet Archive that are optimized for scale. Human driven services such as the W...
[ { "created": "Tue, 10 Sep 2019 11:02:11 GMT", "version": "v1" } ]
2019-09-11
[ [ "Klein", "Martin", "" ], [ "Shankar", "Harihar", "" ], [ "Balakireva", "Lyudmila", "" ], [ "Van de Sompel", "Herbert", "" ] ]
Web archiving frameworks are commonly assessed by the quality of their archival records and by their ability to operate at scale. The ubiquity of dynamic web content poses a significant challenge for crawler-based solutions such as the Internet Archive that are optimized for scale. Human driven services such as the Web...
1808.04963
Jingkang Wang
Jingkang Wang, Jianing Zhou, Jie Zhou, Gongshen Liu
Multiple Character Embeddings for Chinese Word Segmentation
To appear in ACL-SRW 2019
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Chinese word segmentation (CWS) is often regarded as a character-based sequence labeling task in most current works which have achieved great success with the help of powerful neural networks. However, these works neglect an important clue: Chinese characters incorporate both semantic and phonetic meanings. In this p...
[ { "created": "Wed, 15 Aug 2018 04:10:35 GMT", "version": "v1" }, { "created": "Tue, 2 Oct 2018 02:32:34 GMT", "version": "v2" }, { "created": "Thu, 30 May 2019 13:07:58 GMT", "version": "v3" } ]
2019-05-31
[ [ "Wang", "Jingkang", "" ], [ "Zhou", "Jianing", "" ], [ "Zhou", "Jie", "" ], [ "Liu", "Gongshen", "" ] ]
Chinese word segmentation (CWS) is often regarded as a character-based sequence labeling task in most current works which have achieved great success with the help of powerful neural networks. However, these works neglect an important clue: Chinese characters incorporate both semantic and phonetic meanings. In this pap...
1805.08914
Ruixi Lin
Ruixi Lin, Charles Costello, Charles Jankowski
Enhancing Chinese Intent Classification by Dynamically Integrating Character Features into Word Embeddings with Ensemble Techniques
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Intent classification has been widely researched on English data with deep learning approaches that are based on neural networks and word embeddings. The challenge for Chinese intent classification stems from the fact that, unlike English where most words are made up of 26 phonologic alphabet letters, Chinese is logo...
[ { "created": "Wed, 23 May 2018 00:18:42 GMT", "version": "v1" } ]
2018-05-24
[ [ "Lin", "Ruixi", "" ], [ "Costello", "Charles", "" ], [ "Jankowski", "Charles", "" ] ]
Intent classification has been widely researched on English data with deep learning approaches that are based on neural networks and word embeddings. The challenge for Chinese intent classification stems from the fact that, unlike English where most words are made up of 26 phonologic alphabet letters, Chinese is logogr...
2307.06092
Boris Hanin
Stefano Favaro, Boris Hanin, Domenico Marinucci, Ivan Nourdin, Giovanni Peccati
Quantitative CLTs in Deep Neural Networks
null
null
null
null
cs.LG cs.AI math.PR stat.ML
http://creativecommons.org/licenses/by/4.0/
We study the distribution of a fully connected neural network with random Gaussian weights and biases in which the hidden layer widths are proportional to a large constant $n$. Under mild assumptions on the non-linearity, we obtain quantitative bounds on normal approximations valid at large but finite $n$ and any fix...
[ { "created": "Wed, 12 Jul 2023 11:35:37 GMT", "version": "v1" }, { "created": "Thu, 20 Jul 2023 12:54:32 GMT", "version": "v2" }, { "created": "Fri, 21 Jul 2023 10:04:23 GMT", "version": "v3" }, { "created": "Thu, 5 Oct 2023 15:43:42 GMT", "version": "v4" }, { "cr...
2024-06-18
[ [ "Favaro", "Stefano", "" ], [ "Hanin", "Boris", "" ], [ "Marinucci", "Domenico", "" ], [ "Nourdin", "Ivan", "" ], [ "Peccati", "Giovanni", "" ] ]
We study the distribution of a fully connected neural network with random Gaussian weights and biases in which the hidden layer widths are proportional to a large constant $n$. Under mild assumptions on the non-linearity, we obtain quantitative bounds on normal approximations valid at large but finite $n$ and any fixed...
1911.11071
Sami Khairy
Sami Khairy, Ruslan Shaydulin, Lukasz Cincio, Yuri Alexeev, Prasanna Balaprakash
Learning to Optimize Variational Quantum Circuits to Solve Combinatorial Problems
To appear in the proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), New York, USA, February 2020
Proceedings of the AAAI Conference on Artificial Intelligence, 34(03), 2367-2375 (2020)
10.1609/aaai.v34i03.5616
LA-UR-19-28945
cs.LG quant-ph stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Quantum computing is a computational paradigm with the potential to outperform classical methods for a variety of problems. Proposed recently, the Quantum Approximate Optimization Algorithm (QAOA) is considered as one of the leading candidates for demonstrating quantum advantage in the near term. QAOA is a variationa...
[ { "created": "Mon, 25 Nov 2019 17:23:41 GMT", "version": "v1" } ]
2022-06-16
[ [ "Khairy", "Sami", "" ], [ "Shaydulin", "Ruslan", "" ], [ "Cincio", "Lukasz", "" ], [ "Alexeev", "Yuri", "" ], [ "Balaprakash", "Prasanna", "" ] ]
Quantum computing is a computational paradigm with the potential to outperform classical methods for a variety of problems. Proposed recently, the Quantum Approximate Optimization Algorithm (QAOA) is considered as one of the leading candidates for demonstrating quantum advantage in the near term. QAOA is a variational ...
2207.04182
Weijie Yu
Weijie Yu, Zhongxiang Sun, Jun Xu, Zhenhua Dong, Xu Chen, Hongteng Xu, and Ji-Rong Wen
Explainable Legal Case Matching via Inverse Optimal Transport-based Rationale Extraction
to be published in SIGIR 2022
null
10.1145/3477495.3531974
null
cs.IR
http://creativecommons.org/licenses/by/4.0/
As an essential operation of legal retrieval, legal case matching plays a central role in intelligent legal systems. This task has a high demand on the explainability of matching results because of its critical impacts on downstream applications -- the matched legal cases may provide supportive evidence for the judgm...
[ { "created": "Sat, 9 Jul 2022 02:58:51 GMT", "version": "v1" } ]
2022-07-12
[ [ "Yu", "Weijie", "" ], [ "Sun", "Zhongxiang", "" ], [ "Xu", "Jun", "" ], [ "Dong", "Zhenhua", "" ], [ "Chen", "Xu", "" ], [ "Xu", "Hongteng", "" ], [ "Wen", "Ji-Rong", "" ] ]
As an essential operation of legal retrieval, legal case matching plays a central role in intelligent legal systems. This task has a high demand on the explainability of matching results because of its critical impacts on downstream applications -- the matched legal cases may provide supportive evidence for the judgmen...
1512.04255
Guillermo P\'erez
Guillermo A. P\'erez
The Fixed Initial Credit Problem for Partial-Observation Energy Games is Ack-complete
null
null
null
null
cs.LO cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we study two-player games with asymmetric partial observation and an energy objective. Such games are played on a weighted automaton by Eve, choosing actions, and Adam, choosing a transition labelled with the given action. Eve attempts to maintain the sum of the weights (of the transitions taken) non-ne...
[ { "created": "Mon, 14 Dec 2015 11:06:33 GMT", "version": "v1" }, { "created": "Tue, 15 Dec 2015 15:08:23 GMT", "version": "v2" }, { "created": "Sun, 27 Dec 2015 18:47:29 GMT", "version": "v3" }, { "created": "Thu, 21 Jan 2016 17:04:08 GMT", "version": "v4" }, { "c...
2016-11-17
[ [ "Pérez", "Guillermo A.", "" ] ]
In this paper we study two-player games with asymmetric partial observation and an energy objective. Such games are played on a weighted automaton by Eve, choosing actions, and Adam, choosing a transition labelled with the given action. Eve attempts to maintain the sum of the weights (of the transitions taken) non-nega...
2306.02003
Banghua Zhu
Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark Barrett, Michael I. Jordan, Jiantao Jiao
On Optimal Caching and Model Multiplexing for Large Model Inference
null
null
null
null
cs.LG cs.AI cs.PF cs.SY eess.SY stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large Language Models (LLMs) and other large foundation models have achieved noteworthy success, but their size exacerbates existing resource consumption and latency challenges. In particular, the large-scale deployment of these models is hindered by the significant resource requirements during inference. In this pap...
[ { "created": "Sat, 3 Jun 2023 05:01:51 GMT", "version": "v1" }, { "created": "Tue, 29 Aug 2023 00:59:44 GMT", "version": "v2" } ]
2023-08-30
[ [ "Zhu", "Banghua", "" ], [ "Sheng", "Ying", "" ], [ "Zheng", "Lianmin", "" ], [ "Barrett", "Clark", "" ], [ "Jordan", "Michael I.", "" ], [ "Jiao", "Jiantao", "" ] ]
Large Language Models (LLMs) and other large foundation models have achieved noteworthy success, but their size exacerbates existing resource consumption and latency challenges. In particular, the large-scale deployment of these models is hindered by the significant resource requirements during inference. In this paper...
2403.19101
Benhao Huang
Benhao Huang
AAPMT: AGI Assessment Through Prompt and Metric Transformer
null
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
The emergence of text-to-image models marks a significant milestone in the evolution of AI-generated images (AGIs), expanding their use in diverse domains like design, entertainment, and more. Despite these breakthroughs, the quality of AGIs often remains suboptimal, highlighting the need for effective evaluation met...
[ { "created": "Thu, 28 Mar 2024 02:31:06 GMT", "version": "v1" } ]
2024-03-29
[ [ "Huang", "Benhao", "" ] ]
The emergence of text-to-image models marks a significant milestone in the evolution of AI-generated images (AGIs), expanding their use in diverse domains like design, entertainment, and more. Despite these breakthroughs, the quality of AGIs often remains suboptimal, highlighting the need for effective evaluation metho...
2112.12047
Jin Li
Jin Li, Benjamin J. Cairns, Jingsong Li, Tingting Zhu
Generating Synthetic Mixed-type Longitudinal Electronic Health Records for Artificial Intelligent Applications
Main article (22 pages, 7 figures); Appendix (15 pages, 8 figures)
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
The recent availability of electronic health records (EHRs) have provided enormous opportunities to develop artificial intelligence (AI) algorithms. However, patient privacy has become a major concern that limits data sharing across hospital settings and subsequently hinders the advances in AI. Synthetic data, which ...
[ { "created": "Wed, 22 Dec 2021 17:17:34 GMT", "version": "v1" }, { "created": "Tue, 31 Jan 2023 02:08:08 GMT", "version": "v2" } ]
2023-02-01
[ [ "Li", "Jin", "" ], [ "Cairns", "Benjamin J.", "" ], [ "Li", "Jingsong", "" ], [ "Zhu", "Tingting", "" ] ]
The recent availability of electronic health records (EHRs) have provided enormous opportunities to develop artificial intelligence (AI) algorithms. However, patient privacy has become a major concern that limits data sharing across hospital settings and subsequently hinders the advances in AI. Synthetic data, which be...
2303.04636
Sanju Xaviar
Sanju Xaviar, Xin Yang and Omid Ardakanian
Robust Multimodal Fusion for Human Activity Recognition
13 pages
null
null
null
cs.LG eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The proliferation of IoT and mobile devices equipped with heterogeneous sensors has enabled new applications that rely on the fusion of time-series data generated by multiple sensors with different modalities. While there are promising deep neural network architectures for multimodal fusion, their performance falls a...
[ { "created": "Wed, 8 Mar 2023 14:56:11 GMT", "version": "v1" } ]
2023-03-09
[ [ "Xaviar", "Sanju", "" ], [ "Yang", "Xin", "" ], [ "Ardakanian", "Omid", "" ] ]
The proliferation of IoT and mobile devices equipped with heterogeneous sensors has enabled new applications that rely on the fusion of time-series data generated by multiple sensors with different modalities. While there are promising deep neural network architectures for multimodal fusion, their performance falls apa...
2306.00848
Raul Tapia
Raul Tapia, Alvaro Cesar Satue, Saeed Rafee Nekoo, Jos\'e Ramiro Mart\'inez-de Dios, Anibal Ollero
Experimental Energy Consumption Analysis of a Flapping-Wing Robot
null
null
null
null
cs.RO
http://creativecommons.org/licenses/by-nc-nd/4.0/
One of the motivations for exploring flapping-wing aerial robotic systems is to seek energy reduction, by maintaining manoeuvrability, compared to conventional unmanned aerial systems. A Flapping Wing Flying Robot (FWFR) can glide in favourable wind conditions, decreasing energy consumption significantly. In addition...
[ { "created": "Thu, 1 Jun 2023 16:06:23 GMT", "version": "v1" } ]
2023-06-02
[ [ "Tapia", "Raul", "" ], [ "Satue", "Alvaro Cesar", "" ], [ "Nekoo", "Saeed Rafee", "" ], [ "Dios", "José Ramiro Martínez-de", "" ], [ "Ollero", "Anibal", "" ] ]
One of the motivations for exploring flapping-wing aerial robotic systems is to seek energy reduction, by maintaining manoeuvrability, compared to conventional unmanned aerial systems. A Flapping Wing Flying Robot (FWFR) can glide in favourable wind conditions, decreasing energy consumption significantly. In addition, ...
2402.02239
Hugues Van Assel
Hugues Van Assel, C\'edric Vincent-Cuaz, Nicolas Courty, R\'emi Flamary, Pascal Frossard, Titouan Vayer
Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-Wasserstein
38 pages, 15 figures
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Unsupervised learning aims to capture the underlying structure of potentially large and high-dimensional datasets. Traditionally, this involves using dimensionality reduction (DR) methods to project data onto lower-dimensional spaces or organizing points into meaningful clusters (clustering). In this work, we revisit...
[ { "created": "Sat, 3 Feb 2024 19:00:19 GMT", "version": "v1" }, { "created": "Wed, 22 May 2024 15:34:07 GMT", "version": "v2" } ]
2024-05-24
[ [ "Van Assel", "Hugues", "" ], [ "Vincent-Cuaz", "Cédric", "" ], [ "Courty", "Nicolas", "" ], [ "Flamary", "Rémi", "" ], [ "Frossard", "Pascal", "" ], [ "Vayer", "Titouan", "" ] ]
Unsupervised learning aims to capture the underlying structure of potentially large and high-dimensional datasets. Traditionally, this involves using dimensionality reduction (DR) methods to project data onto lower-dimensional spaces or organizing points into meaningful clusters (clustering). In this work, we revisit t...
2405.12944
Zizhao Chen
Zizhao Chen, Yeqiang Qian, Xiaoxiao Yang, Chunxiang Wang and Ming Yang
AMFD: Distillation via Adaptive Multimodal Fusion for Multispectral Pedestrian Detection
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Multispectral pedestrian detection has been shown to be effective in improving performance within complex illumination scenarios. However, prevalent double-stream networks in multispectral detection employ two separate feature extraction branches for multi-modal data, leading to nearly double the inference time compa...
[ { "created": "Tue, 21 May 2024 17:17:17 GMT", "version": "v1" } ]
2024-05-22
[ [ "Chen", "Zizhao", "" ], [ "Qian", "Yeqiang", "" ], [ "Yang", "Xiaoxiao", "" ], [ "Wang", "Chunxiang", "" ], [ "Yang", "Ming", "" ] ]
Multispectral pedestrian detection has been shown to be effective in improving performance within complex illumination scenarios. However, prevalent double-stream networks in multispectral detection employ two separate feature extraction branches for multi-modal data, leading to nearly double the inference time compare...
2011.13776
Hao Chen
Hao Chen, Benoit Lagadec, Francois Bremond
Enhancing Diversity in Teacher-Student Networks via Asymmetric branches for Unsupervised Person Re-identification
WACV 2021
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The objective of unsupervised person re-identification (Re-ID) is to learn discriminative features without labor-intensive identity annotations. State-of-the-art unsupervised Re-ID methods assign pseudo labels to unlabeled images in the target domain and learn from these noisy pseudo labels. Recently introduced Mean ...
[ { "created": "Fri, 27 Nov 2020 15:17:10 GMT", "version": "v1" } ]
2020-11-30
[ [ "Chen", "Hao", "" ], [ "Lagadec", "Benoit", "" ], [ "Bremond", "Francois", "" ] ]
The objective of unsupervised person re-identification (Re-ID) is to learn discriminative features without labor-intensive identity annotations. State-of-the-art unsupervised Re-ID methods assign pseudo labels to unlabeled images in the target domain and learn from these noisy pseudo labels. Recently introduced Mean Te...
2404.14771
Hong Huang
Hong Huang, Yuyi Wang, Luyao Li, Jun Lin
Music Style Transfer With Diffusion Model
8 pages, 6 figures, ICMC 2023
International Computer Music Conference (ICMC 2023) pp. 40-47, October 2023
null
null
cs.SD cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Previous studies on music style transfer have mainly focused on one-to-one style conversion, which is relatively limited. When considering the conversion between multiple styles, previous methods required designing multiple modes to disentangle the complex style of the music, resulting in large computational costs an...
[ { "created": "Tue, 23 Apr 2024 06:22:19 GMT", "version": "v1" } ]
2024-04-24
[ [ "Huang", "Hong", "" ], [ "Wang", "Yuyi", "" ], [ "Li", "Luyao", "" ], [ "Lin", "Jun", "" ] ]
Previous studies on music style transfer have mainly focused on one-to-one style conversion, which is relatively limited. When considering the conversion between multiple styles, previous methods required designing multiple modes to disentangle the complex style of the music, resulting in large computational costs and ...
1905.04689
Mani A
A. Mani
Rough Contact in General Rough Mereology
11 Pages. Women in Logic Workshop, Vancouver'2019: 34th Annual ACM/IEEE Symposium on Logic in Computer Science (LICS) 2019. This preprint uses the same updated framework of arXiv:1811.06560
null
null
null
cs.LO cs.AI math.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Theories of rough mereology have originated from diverse semantic considerations from contexts relating to study of databases, to human reasoning. These ideas of origin, especially in the latter context, are intensely complex. In this research, concepts of rough contact relations are introduced and rough mereologies ...
[ { "created": "Sun, 12 May 2019 10:42:20 GMT", "version": "v1" } ]
2019-07-15
[ [ "Mani", "A.", "" ] ]
Theories of rough mereology have originated from diverse semantic considerations from contexts relating to study of databases, to human reasoning. These ideas of origin, especially in the latter context, are intensely complex. In this research, concepts of rough contact relations are introduced and rough mereologies ar...
2408.05745
Zhaoyu Chen
Haijing Guo, Jiafeng Wang, Zhaoyu Chen, Kaixun Jiang, Lingyi Hong, Pinxue Guo, Jinglun Li, Wenqiang Zhang
Improving Adversarial Transferability with Neighbourhood Gradient Information
null
null
null
null
cs.CV cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep neural networks (DNNs) are known to be susceptible to adversarial examples, leading to significant performance degradation. In black-box attack scenarios, a considerable attack performance gap between the surrogate model and the target model persists. This work focuses on enhancing the transferability of adversa...
[ { "created": "Sun, 11 Aug 2024 10:46:49 GMT", "version": "v1" } ]
2024-08-13
[ [ "Guo", "Haijing", "" ], [ "Wang", "Jiafeng", "" ], [ "Chen", "Zhaoyu", "" ], [ "Jiang", "Kaixun", "" ], [ "Hong", "Lingyi", "" ], [ "Guo", "Pinxue", "" ], [ "Li", "Jinglun", "" ], [ "Zhang", "We...
Deep neural networks (DNNs) are known to be susceptible to adversarial examples, leading to significant performance degradation. In black-box attack scenarios, a considerable attack performance gap between the surrogate model and the target model persists. This work focuses on enhancing the transferability of adversari...
1811.07323
Nikhil Potu Surya Prakash
Nikhil Potu Surya Prakash
Nonlinear control of a swinging pendulum on a wheeled mobile robot with nonholonomic constraints
8 pages, 3 figures
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a nonlinear control strategy for swinging up a pendulum to its upright equilibrium position by shaping its swinging energy along with regulating the cart to a desired location. While the base of a usual cart-pole system is restricted to move in a straight line, the present system is allowed ...
[ { "created": "Sun, 18 Nov 2018 12:48:15 GMT", "version": "v1" } ]
2018-11-20
[ [ "Prakash", "Nikhil Potu Surya", "" ] ]
In this paper, we propose a nonlinear control strategy for swinging up a pendulum to its upright equilibrium position by shaping its swinging energy along with regulating the cart to a desired location. While the base of a usual cart-pole system is restricted to move in a straight line, the present system is allowed to...
1804.07739
Guha Balakrishnan
Guha Balakrishnan, Amy Zhao, Adrian V. Dalca, Fredo Durand, John Guttag
Synthesizing Images of Humans in Unseen Poses
CVPR 2018
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We address the computational problem of novel human pose synthesis. Given an image of a person and a desired pose, we produce a depiction of that person in that pose, retaining the appearance of both the person and background. We present a modular generative neural network that synthesizes unseen poses using training...
[ { "created": "Fri, 20 Apr 2018 17:34:44 GMT", "version": "v1" } ]
2018-04-23
[ [ "Balakrishnan", "Guha", "" ], [ "Zhao", "Amy", "" ], [ "Dalca", "Adrian V.", "" ], [ "Durand", "Fredo", "" ], [ "Guttag", "John", "" ] ]
We address the computational problem of novel human pose synthesis. Given an image of a person and a desired pose, we produce a depiction of that person in that pose, retaining the appearance of both the person and background. We present a modular generative neural network that synthesizes unseen poses using training p...
1706.01734
Komal Janghel
Komal Janghel and Shankar Prakriya
Performance of DF Incremental Relaying with Energy Harvesting Relays in Underlay CRNs
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we analyze the throughput performance of incremental relaying using energy harvesting (EH) decode-and-forward (DF) relays in underlay cognitive radio networks (CRNs). The destination combines the direct and relayed signals when the direct link is in outage. From the derived closed-form expressions, we ...
[ { "created": "Tue, 6 Jun 2017 12:34:31 GMT", "version": "v1" }, { "created": "Fri, 1 Sep 2017 06:07:19 GMT", "version": "v2" } ]
2017-09-04
[ [ "Janghel", "Komal", "" ], [ "Prakriya", "Shankar", "" ] ]
In this paper, we analyze the throughput performance of incremental relaying using energy harvesting (EH) decode-and-forward (DF) relays in underlay cognitive radio networks (CRNs). The destination combines the direct and relayed signals when the direct link is in outage. From the derived closed-form expressions, we pr...
2201.05489
Yuqi Wang
Yuqi Wang, Xu-Yao Zhang, Cheng-Lin Liu, Zhaoxiang Zhang
Emergence of Machine Language: Towards Symbolic Intelligence with Neural Networks
null
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Representation is a core issue in artificial intelligence. Humans use discrete language to communicate and learn from each other, while machines use continuous features (like vector, matrix, or tensor in deep neural networks) to represent cognitive patterns. Discrete symbols are low-dimensional, decoupled, and have s...
[ { "created": "Fri, 14 Jan 2022 14:54:58 GMT", "version": "v1" } ]
2022-01-17
[ [ "Wang", "Yuqi", "" ], [ "Zhang", "Xu-Yao", "" ], [ "Liu", "Cheng-Lin", "" ], [ "Zhang", "Zhaoxiang", "" ] ]
Representation is a core issue in artificial intelligence. Humans use discrete language to communicate and learn from each other, while machines use continuous features (like vector, matrix, or tensor in deep neural networks) to represent cognitive patterns. Discrete symbols are low-dimensional, decoupled, and have str...
2111.04617
Yury Elkin
Yury Elkin and Vitaliy Kurlin
Isometry invariant shape recognition of projectively perturbed point clouds by the mergegram extending 0D persistence
arXiv admin note: substantial text overlap with arXiv:2007.11278
Mathematics 9 (2021) no.17, 2121
null
null
cs.CG
http://creativecommons.org/licenses/by/4.0/
Rigid shapes should be naturally compared up to rigid motion or isometry, which preserves all inter-point distances. The same rigid shape can be often represented by noisy point clouds of different sizes. Hence the isometry shape recognition problem requires methods that are independent of a cloud size. This paper st...
[ { "created": "Mon, 8 Nov 2021 16:39:05 GMT", "version": "v1" } ]
2021-11-09
[ [ "Elkin", "Yury", "" ], [ "Kurlin", "Vitaliy", "" ] ]
Rigid shapes should be naturally compared up to rigid motion or isometry, which preserves all inter-point distances. The same rigid shape can be often represented by noisy point clouds of different sizes. Hence the isometry shape recognition problem requires methods that are independent of a cloud size. This paper stud...
2310.03094
Murong Yue
Murong Yue, Jie Zhao, Min Zhang, Liang Du, Ziyu Yao
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Accepted to ICLR 2024
null
null
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models (LLMs) such as GPT-4 have exhibited remarkable performance in a variety of tasks, but this strong performance often comes with the high expense of using paid API services. In this paper, we are motivated to study building an LLM cascade to save the cost of using LLMs, particularly for performing...
[ { "created": "Wed, 4 Oct 2023 18:21:17 GMT", "version": "v1" }, { "created": "Sat, 7 Oct 2023 01:16:45 GMT", "version": "v2" }, { "created": "Thu, 8 Feb 2024 22:02:22 GMT", "version": "v3" } ]
2024-02-12
[ [ "Yue", "Murong", "" ], [ "Zhao", "Jie", "" ], [ "Zhang", "Min", "" ], [ "Du", "Liang", "" ], [ "Yao", "Ziyu", "" ] ]
Large language models (LLMs) such as GPT-4 have exhibited remarkable performance in a variety of tasks, but this strong performance often comes with the high expense of using paid API services. In this paper, we are motivated to study building an LLM cascade to save the cost of using LLMs, particularly for performing r...
2001.04756
Shiqiang Wang
Pengchao Han, Shiqiang Wang, Kin K. Leung
Adaptive Gradient Sparsification for Efficient Federated Learning: An Online Learning Approach
Accepted at IEEE ICDCS 2020
null
null
null
cs.LG cs.DC math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Federated learning (FL) is an emerging technique for training machine learning models using geographically dispersed data collected by local entities. It includes local computation and synchronization steps. To reduce the communication overhead and improve the overall efficiency of FL, gradient sparsification (GS) ca...
[ { "created": "Tue, 14 Jan 2020 13:09:23 GMT", "version": "v1" }, { "created": "Thu, 16 Jan 2020 17:56:09 GMT", "version": "v2" }, { "created": "Fri, 20 Mar 2020 16:34:48 GMT", "version": "v3" } ]
2020-03-23
[ [ "Han", "Pengchao", "" ], [ "Wang", "Shiqiang", "" ], [ "Leung", "Kin K.", "" ] ]
Federated learning (FL) is an emerging technique for training machine learning models using geographically dispersed data collected by local entities. It includes local computation and synchronization steps. To reduce the communication overhead and improve the overall efficiency of FL, gradient sparsification (GS) can ...
2211.15248
Marcin Przyby{\l}ko
Carsten Lutz and Marcin Przybylko
Efficient Answer Enumeration in Description Logics with Functional Roles -- Extended Version
This is an extended version of a paper accepted to AAAI'23
null
null
null
cs.LO
http://creativecommons.org/licenses/by/4.0/
We study the enumeration of answers to ontology-mediated queries when the ontology is formulated in a description logic that supports functional roles and the query is a CQ. In particular, we show that enumeration is possible with linear preprocessing and constant delay when a certain extension of the CQ (pertaining ...
[ { "created": "Mon, 28 Nov 2022 11:54:17 GMT", "version": "v1" } ]
2022-11-29
[ [ "Lutz", "Carsten", "" ], [ "Przybylko", "Marcin", "" ] ]
We study the enumeration of answers to ontology-mediated queries when the ontology is formulated in a description logic that supports functional roles and the query is a CQ. In particular, we show that enumeration is possible with linear preprocessing and constant delay when a certain extension of the CQ (pertaining to...
1208.0712
Bojan Marinkovi\'c
Bojan Marinkovi\'c, Paola Glavan, Zoran Ognjanovi\'c
Description of the Chord Protocol using ASMs Formalism
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper describes the overlay protocol Chord using the formalism of Abstract State Machines. The formalization concerns Chord actions that maintain ring topology and manipulate distributed keys. We define a class of runs and prove the correctness of our formalization with respect to it.
[ { "created": "Fri, 3 Aug 2012 11:17:57 GMT", "version": "v1" }, { "created": "Mon, 23 Sep 2013 13:23:08 GMT", "version": "v2" } ]
2013-09-24
[ [ "Marinković", "Bojan", "" ], [ "Glavan", "Paola", "" ], [ "Ognjanović", "Zoran", "" ] ]
This paper describes the overlay protocol Chord using the formalism of Abstract State Machines. The formalization concerns Chord actions that maintain ring topology and manipulate distributed keys. We define a class of runs and prove the correctness of our formalization with respect to it.
2011.08398
Tong Wang
Tong Wang and Maytal Saar-Tsechansky
Augmented Fairness: An Interpretable Model Augmenting Decision-Makers' Fairness
null
null
null
null
cs.LG cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a model-agnostic approach for mitigating the prediction bias of a black-box decision-maker, and in particular, a human decision-maker. Our method detects in the feature space where the black-box decision-maker is biased and replaces it with a few short decision rules, acting as a "fair surrogate". The rule...
[ { "created": "Tue, 17 Nov 2020 03:25:44 GMT", "version": "v1" } ]
2020-11-18
[ [ "Wang", "Tong", "" ], [ "Saar-Tsechansky", "Maytal", "" ] ]
We propose a model-agnostic approach for mitigating the prediction bias of a black-box decision-maker, and in particular, a human decision-maker. Our method detects in the feature space where the black-box decision-maker is biased and replaces it with a few short decision rules, acting as a "fair surrogate". The rule-b...
2306.09030
Hengli Li
Hengli Li, Song-Chun Zhu, Zilong Zheng
DiPlomat: A Dialogue Dataset for Situated Pragmatic Reasoning
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Pragmatic reasoning plays a pivotal role in deciphering implicit meanings that frequently arise in real-life conversations and is essential for the development of communicative social agents. In this paper, we introduce a novel challenge, DiPlomat, aiming at benchmarking machines' capabilities on pragmatic reasoning ...
[ { "created": "Thu, 15 Jun 2023 10:41:23 GMT", "version": "v1" }, { "created": "Mon, 19 Jun 2023 07:31:55 GMT", "version": "v2" } ]
2023-06-21
[ [ "Li", "Hengli", "" ], [ "Zhu", "Song-Chun", "" ], [ "Zheng", "Zilong", "" ] ]
Pragmatic reasoning plays a pivotal role in deciphering implicit meanings that frequently arise in real-life conversations and is essential for the development of communicative social agents. In this paper, we introduce a novel challenge, DiPlomat, aiming at benchmarking machines' capabilities on pragmatic reasoning an...
1908.08156
Qi Bi
Qi Bi, Kun Qin, Zhili Li, Han Zhang, Kai Xu
Multiple instance dense connected convolution neural network for aerial image scene classification
5 pages,3 figures, a conference paper accepted by IEEE ICIP 2019
null
10.1109/TIP.2020.2975718
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the development of deep learning, many state-of-the-art natural image scene classification methods have demonstrated impressive performance. While the current convolution neural network tends to extract global features and global semantic information in a scene, the geo-spatial objects can be located at anywhere...
[ { "created": "Thu, 22 Aug 2019 00:59:47 GMT", "version": "v1" } ]
2020-04-22
[ [ "Bi", "Qi", "" ], [ "Qin", "Kun", "" ], [ "Li", "Zhili", "" ], [ "Zhang", "Han", "" ], [ "Xu", "Kai", "" ] ]
With the development of deep learning, many state-of-the-art natural image scene classification methods have demonstrated impressive performance. While the current convolution neural network tends to extract global features and global semantic information in a scene, the geo-spatial objects can be located at anywhere i...
2209.08691
Francesco Ragusa
Francesco Ragusa and Antonino Furnari and Giovanni Maria Farinella
MECCANO: A Multimodal Egocentric Dataset for Humans Behavior Understanding in the Industrial-like Domain
arXiv admin note: text overlap with arXiv:2010.05654
Computer Vision and Image Understanding 2023
10.1016/S1077-3142(23)00144-3
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Wearable cameras allow to acquire images and videos from the user's perspective. These data can be processed to understand humans behavior. Despite human behavior analysis has been thoroughly investigated in third person vision, it is still understudied in egocentric settings and in particular in industrial scenarios...
[ { "created": "Mon, 19 Sep 2022 00:52:42 GMT", "version": "v1" } ]
2023-07-06
[ [ "Ragusa", "Francesco", "" ], [ "Furnari", "Antonino", "" ], [ "Farinella", "Giovanni Maria", "" ] ]
Wearable cameras allow to acquire images and videos from the user's perspective. These data can be processed to understand humans behavior. Despite human behavior analysis has been thoroughly investigated in third person vision, it is still understudied in egocentric settings and in particular in industrial scenarios. ...
2111.02844
Tan Huang
Tan Huang
A text autoencoder from transformer for fast encoding language representation
8 pages, 8 figures. arXiv admin note: text overlap with arXiv:2004.08097 by other authors
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years BERT shows apparent advantages and great potential in natural language processing tasks. However, both training and applying BERT requires intensive time and resources for computing contextual language representations, which hinders its universality and applicability. To overcome this bottleneck, we p...
[ { "created": "Thu, 4 Nov 2021 13:09:10 GMT", "version": "v1" } ]
2021-11-05
[ [ "Huang", "Tan", "" ] ]
In recent years BERT shows apparent advantages and great potential in natural language processing tasks. However, both training and applying BERT requires intensive time and resources for computing contextual language representations, which hinders its universality and applicability. To overcome this bottleneck, we pro...
2407.20192
Abhinav Garg
Abhinav Garg, Naman Shukla, Maarten Wormer
Time series forecasting with high stakes: A field study of the air cargo industry
The 10th Mining and Learning from Time Series Workshop: From Classical Methods to LLMs. SIGKDD, Barcelona, Spain, 6 page
null
null
null
cs.LG cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
Time series forecasting in the air cargo industry presents unique challenges due to volatile market dynamics and the significant impact of accurate forecasts on generated revenue. This paper explores a comprehensive approach to demand forecasting at the origin-destination (O\&D) level, focusing on the development and...
[ { "created": "Mon, 29 Jul 2024 17:19:40 GMT", "version": "v1" }, { "created": "Tue, 13 Aug 2024 21:40:07 GMT", "version": "v2" } ]
2024-08-15
[ [ "Garg", "Abhinav", "" ], [ "Shukla", "Naman", "" ], [ "Wormer", "Maarten", "" ] ]
Time series forecasting in the air cargo industry presents unique challenges due to volatile market dynamics and the significant impact of accurate forecasts on generated revenue. This paper explores a comprehensive approach to demand forecasting at the origin-destination (O\&D) level, focusing on the development and i...
2308.07264
Alexander Kyuroson
Alexander Kyuroson, Anton Koval and George Nikolakopoulos
Efficient Real-time Smoke Filtration with 3D LiDAR for Search and Rescue with Autonomous Heterogeneous Robotic Systems
Accepted in the 49th Annual Conference of the IEEE Industrial Electronics Society [IECON2023]
null
10.1109/IECON51785.2023.10312303
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Search and Rescue (SAR) missions in harsh and unstructured Sub-Terranean (Sub-T) environments in the presence of aerosol particles have recently become the main focus in the field of robotics. Aerosol particles such as smoke and dust directly affect the performance of any mobile robotic platform due to their reliance...
[ { "created": "Mon, 14 Aug 2023 16:48:57 GMT", "version": "v1" } ]
2024-06-18
[ [ "Kyuroson", "Alexander", "" ], [ "Koval", "Anton", "" ], [ "Nikolakopoulos", "George", "" ] ]
Search and Rescue (SAR) missions in harsh and unstructured Sub-Terranean (Sub-T) environments in the presence of aerosol particles have recently become the main focus in the field of robotics. Aerosol particles such as smoke and dust directly affect the performance of any mobile robotic platform due to their reliance o...
2006.03007
H\"usrev C{\i}lasun
H\"usrev C{\i}lasun, Salonik Resch, Zamshed I. Chowdhury, Erin Olson, Masoud Zabihi, Zhengyang Zhao, Thomas Peterson, Keshab Parhi, Jian-Ping Wang, Sachin S. Sapatnekar, Ulya Karpuzcu
An Inference and Learning Engine for Spiking Neural Networks in Computational RAM (CRAM)
null
ACM Transactions on Architecture and Code Optimization Volume 18 Issue 4 December 2021 Article No.: 59
10.1145/3475963
null
cs.ET
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Spiking Neural Networks (SNN) represent a biologically inspired computation model capable of emulating neural computation in human brain and brain-like structures. The main promise is very low energy consumption. Unfortunately, classic Von Neumann architecture based SNN accelerators often fail to address demanding co...
[ { "created": "Thu, 4 Jun 2020 16:54:13 GMT", "version": "v1" } ]
2021-10-05
[ [ "Cılasun", "Hüsrev", "" ], [ "Resch", "Salonik", "" ], [ "Chowdhury", "Zamshed I.", "" ], [ "Olson", "Erin", "" ], [ "Zabihi", "Masoud", "" ], [ "Zhao", "Zhengyang", "" ], [ "Peterson", "Thomas", "" ], ...
Spiking Neural Networks (SNN) represent a biologically inspired computation model capable of emulating neural computation in human brain and brain-like structures. The main promise is very low energy consumption. Unfortunately, classic Von Neumann architecture based SNN accelerators often fail to address demanding comp...
2309.13373
Xiang Lee
Xiang Li, Junhao Chen, Chao Li, Hongwu Lv
Asca: less audio data is more insightful
6 pages,3 figures
null
null
null
cs.SD cs.LG eess.AS
http://creativecommons.org/licenses/by/4.0/
Audio recognition in specialized areas such as birdsong and submarine acoustics faces challenges in large-scale pre-training due to the limitations in available samples imposed by sampling environments and specificity requirements. While the Transformer model excels in audio recognition, its dependence on vast amount...
[ { "created": "Sat, 23 Sep 2023 13:24:06 GMT", "version": "v1" } ]
2023-09-26
[ [ "Li", "Xiang", "" ], [ "Chen", "Junhao", "" ], [ "Li", "Chao", "" ], [ "Lv", "Hongwu", "" ] ]
Audio recognition in specialized areas such as birdsong and submarine acoustics faces challenges in large-scale pre-training due to the limitations in available samples imposed by sampling environments and specificity requirements. While the Transformer model excels in audio recognition, its dependence on vast amounts ...
cs/0307065
Stanimire Tomov
Stanimire Tomov (1), Robert Bennett (1), Michael McGuigan (1), Arnold Peskin (1), Gordon Smith (1), John Spiletic (1) ((1) Brookhaven National Laboratory)
Application of interactive parallel visualization for commodity-based clusters using visualization APIs
12 pages, 4 figures
null
null
null
cs.GR
null
We present an efficient and inexpensive to develop application for interactive high-performance parallel visualization. We extend popular APIs such as Open Inventor and VTK to support commodity-based cluster visualization. Our implementation follows a standard master/slave concept: the general idea is to have a ``Mas...
[ { "created": "Tue, 29 Jul 2003 13:40:12 GMT", "version": "v1" } ]
2007-05-23
[ [ "Tomov", "Stanimire", "" ], [ "Bennett", "Robert", "" ], [ "McGuigan", "Michael", "" ], [ "Peskin", "Arnold", "" ], [ "Smith", "Gordon", "" ], [ "Spiletic", "John", "" ] ]
We present an efficient and inexpensive to develop application for interactive high-performance parallel visualization. We extend popular APIs such as Open Inventor and VTK to support commodity-based cluster visualization. Our implementation follows a standard master/slave concept: the general idea is to have a ``Maste...
2304.08490
Yuexi Du
Yuexi Du, Ziyang Chen, Justin Salamon, Bryan Russell and Andrew Owens
Conditional Generation of Audio from Video via Foley Analogies
CVPR 2023
null
null
null
cs.CV cs.MM cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The sound effects that designers add to videos are designed to convey a particular artistic effect and, thus, may be quite different from a scene's true sound. Inspired by the challenges of creating a soundtrack for a video that differs from its true sound, but that nonetheless matches the actions occurring on screen...
[ { "created": "Mon, 17 Apr 2023 17:59:45 GMT", "version": "v1" } ]
2023-04-18
[ [ "Du", "Yuexi", "" ], [ "Chen", "Ziyang", "" ], [ "Salamon", "Justin", "" ], [ "Russell", "Bryan", "" ], [ "Owens", "Andrew", "" ] ]
The sound effects that designers add to videos are designed to convey a particular artistic effect and, thus, may be quite different from a scene's true sound. Inspired by the challenges of creating a soundtrack for a video that differs from its true sound, but that nonetheless matches the actions occurring on screen, ...
2310.18729
Jaromir Savelka
Jakub Dr\'apal, Hannes Westermann, Jaromir Savelka
Using Large Language Models to Support Thematic Analysis in Empirical Legal Studies
10 pages, 5 figures, 3 tables
The Thirty-sixth Annual Conference on Legal Knowledge and Information Systems (JURIX 2023), Maastricht, The Netherlands
null
null
cs.AI cs.CL cs.HC
http://creativecommons.org/licenses/by/4.0/
Thematic analysis and other variants of inductive coding are widely used qualitative analytic methods within empirical legal studies (ELS). We propose a novel framework facilitating effective collaboration of a legal expert with a large language model (LLM) for generating initial codes (phase 2 of thematic analysis),...
[ { "created": "Sat, 28 Oct 2023 15:20:44 GMT", "version": "v1" } ]
2023-10-31
[ [ "Drápal", "Jakub", "" ], [ "Westermann", "Hannes", "" ], [ "Savelka", "Jaromir", "" ] ]
Thematic analysis and other variants of inductive coding are widely used qualitative analytic methods within empirical legal studies (ELS). We propose a novel framework facilitating effective collaboration of a legal expert with a large language model (LLM) for generating initial codes (phase 2 of thematic analysis), s...
1512.03274
Lorenzo Maggi
Lorenzo Maggi, Lazaros Gkatzikis, Georgios Paschos, and J\'er\'emie Leguay
Adapting Caching to Audience Retention Rate: Which Video Chunk to Store?
11 pages, under submission
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Rarely do users watch online contents entirely. We study how to take this into account to improve the performance of cache systems for video-on-demand and video-sharing platforms in terms of traffic reduction on the core network. We exploit the notion of "Audience retention rate", introduced by mainstream online cont...
[ { "created": "Thu, 10 Dec 2015 14:58:30 GMT", "version": "v1" } ]
2015-12-11
[ [ "Maggi", "Lorenzo", "" ], [ "Gkatzikis", "Lazaros", "" ], [ "Paschos", "Georgios", "" ], [ "Leguay", "Jérémie", "" ] ]
Rarely do users watch online contents entirely. We study how to take this into account to improve the performance of cache systems for video-on-demand and video-sharing platforms in terms of traffic reduction on the core network. We exploit the notion of "Audience retention rate", introduced by mainstream online conten...
2208.03567
Hengrui Jia
Congyu Fang, Hengrui Jia, Anvith Thudi, Mohammad Yaghini, Christopher A. Choquette-Choo, Natalie Dullerud, Varun Chandrasekaran, Nicolas Papernot
Proof-of-Learning is Currently More Broken Than You Think
Published in IEEE EuroS&P 2023
null
null
null
cs.LG cs.AI cs.CR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Proof-of-Learning (PoL) proposes that a model owner logs training checkpoints to establish a proof of having expended the computation necessary for training. The authors of PoL forego cryptographic approaches and trade rigorous security guarantees for scalability to deep learning. They empirically argued the benefit ...
[ { "created": "Sat, 6 Aug 2022 19:07:07 GMT", "version": "v1" }, { "created": "Mon, 17 Apr 2023 04:07:52 GMT", "version": "v2" } ]
2023-04-18
[ [ "Fang", "Congyu", "" ], [ "Jia", "Hengrui", "" ], [ "Thudi", "Anvith", "" ], [ "Yaghini", "Mohammad", "" ], [ "Choquette-Choo", "Christopher A.", "" ], [ "Dullerud", "Natalie", "" ], [ "Chandrasekaran", "Varun"...
Proof-of-Learning (PoL) proposes that a model owner logs training checkpoints to establish a proof of having expended the computation necessary for training. The authors of PoL forego cryptographic approaches and trade rigorous security guarantees for scalability to deep learning. They empirically argued the benefit of...
2007.02719
Praneeth Vepakomma
Praneeth Vepakomma, Julia Balla, Ramesh Raskar
Splintering with distributions: A stochastic decoy scheme for private computation
section 8 -found an error! We will upload a fixed version
null
null
null
cs.LG cs.CR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Performing computations while maintaining privacy is an important problem in todays distributed machine learning solutions. Consider the following two set ups between a client and a server, where in setup i) the client has a public data vector $\mathbf{x}$, the server has a large private database of data vectors $\ma...
[ { "created": "Mon, 6 Jul 2020 13:06:49 GMT", "version": "v1" }, { "created": "Tue, 7 Jul 2020 19:23:39 GMT", "version": "v2" }, { "created": "Wed, 26 Jan 2022 17:22:40 GMT", "version": "v3" } ]
2022-01-27
[ [ "Vepakomma", "Praneeth", "" ], [ "Balla", "Julia", "" ], [ "Raskar", "Ramesh", "" ] ]
Performing computations while maintaining privacy is an important problem in todays distributed machine learning solutions. Consider the following two set ups between a client and a server, where in setup i) the client has a public data vector $\mathbf{x}$, the server has a large private database of data vectors $\math...
2103.10452
Eric Qin
Eric Qin, Geonhwa Jeong, William Won, Sheng-Chun Kao, Hyoukjun Kwon, Sudarshan Srinivasan, Dipankar Das, Gordon E. Moon, Sivasankaran Rajamanickam, Tushar Krishna
Extending Sparse Tensor Accelerators to Support Multiple Compression Formats
Accepted for publication at the 35th IEEE International Parallel & Distributed Processing Symposium (IPDPS 2021)
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sparsity, which occurs in both scientific applications and Deep Learning (DL) models, has been a key target of optimization within recent ASIC accelerators due to the potential memory and compute savings. These applications use data stored in a variety of compression formats. We demonstrate that both the compactness ...
[ { "created": "Thu, 18 Mar 2021 18:08:56 GMT", "version": "v1" } ]
2021-03-22
[ [ "Qin", "Eric", "" ], [ "Jeong", "Geonhwa", "" ], [ "Won", "William", "" ], [ "Kao", "Sheng-Chun", "" ], [ "Kwon", "Hyoukjun", "" ], [ "Srinivasan", "Sudarshan", "" ], [ "Das", "Dipankar", "" ], [ "M...
Sparsity, which occurs in both scientific applications and Deep Learning (DL) models, has been a key target of optimization within recent ASIC accelerators due to the potential memory and compute savings. These applications use data stored in a variety of compression formats. We demonstrate that both the compactness of...
2407.13515
Jaewook Lee
Jaewook Lee, Andrew D. Tjahjadi, Jiho Kim, Junpu Yu, Minji Park, Jiawen Zhang, Jon E. Froehlich, Yapeng Tian, Yuhang Zhao
CookAR: Affordance Augmentations in Wearable AR to Support Kitchen Tool Interactions for People with Low Vision
null
null
null
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
Cooking is a central activity of daily living, supporting independence as well as mental and physical health. However, prior work has highlighted key barriers for people with low vision (LV) to cook, particularly around safely interacting with tools, such as sharp knives or hot pans. Drawing on recent advancements in...
[ { "created": "Thu, 18 Jul 2024 13:46:15 GMT", "version": "v1" }, { "created": "Sun, 28 Jul 2024 00:00:10 GMT", "version": "v2" } ]
2024-07-30
[ [ "Lee", "Jaewook", "" ], [ "Tjahjadi", "Andrew D.", "" ], [ "Kim", "Jiho", "" ], [ "Yu", "Junpu", "" ], [ "Park", "Minji", "" ], [ "Zhang", "Jiawen", "" ], [ "Froehlich", "Jon E.", "" ], [ "Tian", ...
Cooking is a central activity of daily living, supporting independence as well as mental and physical health. However, prior work has highlighted key barriers for people with low vision (LV) to cook, particularly around safely interacting with tools, such as sharp knives or hot pans. Drawing on recent advancements in c...
2111.02583
Karthik Garimella
Karthik Garimella, Nandan Kumar Jha, Zahra Ghodsi, Siddharth Garg, Brandon Reagen
CryptoNite: Revealing the Pitfalls of End-to-End Private Inference at Scale
4 Figures and 3 Tables
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The privacy concerns of providing deep learning inference as a service have underscored the need for private inference (PI) protocols that protect users' data and the service provider's model using cryptographic methods. Recently proposed PI protocols have achieved significant reductions in PI latency by moving the c...
[ { "created": "Thu, 4 Nov 2021 01:55:30 GMT", "version": "v1" }, { "created": "Mon, 18 Jul 2022 15:06:45 GMT", "version": "v2" } ]
2022-07-19
[ [ "Garimella", "Karthik", "" ], [ "Jha", "Nandan Kumar", "" ], [ "Ghodsi", "Zahra", "" ], [ "Garg", "Siddharth", "" ], [ "Reagen", "Brandon", "" ] ]
The privacy concerns of providing deep learning inference as a service have underscored the need for private inference (PI) protocols that protect users' data and the service provider's model using cryptographic methods. Recently proposed PI protocols have achieved significant reductions in PI latency by moving the com...
1906.02777
Ashok Makkuva
Ashok Vardhan Makkuva, Sewoong Oh, Sreeram Kannan, Pramod Viswanath
Learning in Gated Neural Networks
null
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
Gating is a key feature in modern neural networks including LSTMs, GRUs and sparsely-gated deep neural networks. The backbone of such gated networks is a mixture-of-experts layer, where several experts make regression decisions and gating controls how to weigh the decisions in an input-dependent manner. Despite havin...
[ { "created": "Thu, 6 Jun 2019 19:04:11 GMT", "version": "v1" }, { "created": "Wed, 17 Jun 2020 19:55:28 GMT", "version": "v2" } ]
2020-06-19
[ [ "Makkuva", "Ashok Vardhan", "" ], [ "Oh", "Sewoong", "" ], [ "Kannan", "Sreeram", "" ], [ "Viswanath", "Pramod", "" ] ]
Gating is a key feature in modern neural networks including LSTMs, GRUs and sparsely-gated deep neural networks. The backbone of such gated networks is a mixture-of-experts layer, where several experts make regression decisions and gating controls how to weigh the decisions in an input-dependent manner. Despite having ...
2407.09187
A B M Muntasir Rahman
Saad Ahmed Sazan, Mahdi H. Miraz, A B M Muntasir Rahman
Enhancing Depressive Post Detection in Bangla: A Comparative Study of TF-IDF, BERT and FastText Embeddings
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Due to massive adoption of social media, detection of users' depression through social media analytics bears significant importance, particularly for underrepresented languages, such as Bangla. This study introduces a well-grounded approach to identify depressive social media posts in Bangla, by employing advanced na...
[ { "created": "Fri, 12 Jul 2024 11:40:17 GMT", "version": "v1" } ]
2024-07-15
[ [ "Sazan", "Saad Ahmed", "" ], [ "Miraz", "Mahdi H.", "" ], [ "Rahman", "A B M Muntasir", "" ] ]
Due to massive adoption of social media, detection of users' depression through social media analytics bears significant importance, particularly for underrepresented languages, such as Bangla. This study introduces a well-grounded approach to identify depressive social media posts in Bangla, by employing advanced natu...
1811.08846
Zhe Xu
Zhe Xu, Melkior Ornik, A. Agung Julius and Ufuk Topcu
Information-Guided Temporal Logic Inference with Prior Knowledge
null
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper investigates the problem of inferring knowledge from data so that the inferred knowledge is interpretable and informative to humans who have prior knowledge. Given a dataset as a collection of system trajectories, we infer parametric linear temporal logic (pLTL) formulas that are informative and satisfied ...
[ { "created": "Wed, 21 Nov 2018 17:48:59 GMT", "version": "v1" } ]
2018-11-22
[ [ "Xu", "Zhe", "" ], [ "Ornik", "Melkior", "" ], [ "Julius", "A. Agung", "" ], [ "Topcu", "Ufuk", "" ] ]
This paper investigates the problem of inferring knowledge from data so that the inferred knowledge is interpretable and informative to humans who have prior knowledge. Given a dataset as a collection of system trajectories, we infer parametric linear temporal logic (pLTL) formulas that are informative and satisfied by...
2001.05031
Yanpei Shi
Yanpei Shi, Qiang Huang, Thomas Hain
Robust Speaker Recognition Using Speech Enhancement And Attention Model
Acceptted by Odyssey 2020
null
null
null
cs.CL cs.LG cs.SD eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, a novel architecture for speaker recognition is proposed by cascading speech enhancement and speaker processing. Its aim is to improve speaker recognition performance when speech signals are corrupted by noise. Instead of individually processing speech enhancement and speaker recognition, the two modul...
[ { "created": "Tue, 14 Jan 2020 20:03:07 GMT", "version": "v1" }, { "created": "Fri, 22 May 2020 09:16:56 GMT", "version": "v2" } ]
2020-05-25
[ [ "Shi", "Yanpei", "" ], [ "Huang", "Qiang", "" ], [ "Hain", "Thomas", "" ] ]
In this paper, a novel architecture for speaker recognition is proposed by cascading speech enhancement and speaker processing. Its aim is to improve speaker recognition performance when speech signals are corrupted by noise. Instead of individually processing speech enhancement and speaker recognition, the two modules...
2010.07581
Mazeyar Moeini Feizabadi
Mazeyar Moeini Feizabadi, Ali Mohammed Shujjat, Sarah Shahid, Zainab Hasnain (Habib University)
Interactive Latent Interpolation on MNIST Dataset
For associated demonstration and code repository, see https://mazy1998.github.io/browserGAN/ and https://github.com/mazy1998/browserGAN respectively
null
null
null
cs.CV eess.IV
http://creativecommons.org/publicdomain/zero/1.0/
This paper will discuss the potential of dimensionality reduction with a web-based use of GANs. Throughout a variety of experiments, we show synthesizing visually-appealing samples, interpolating meaningfully between samples, and performing linear arithmetic with latent vectors. GANs have proved to be a remarkable te...
[ { "created": "Thu, 15 Oct 2020 08:04:48 GMT", "version": "v1" } ]
2020-10-16
[ [ "Feizabadi", "Mazeyar Moeini", "", "Habib University" ], [ "Shujjat", "Ali Mohammed", "", "Habib University" ], [ "Shahid", "Sarah", "", "Habib University" ], [ "Hasnain", "Zainab", "", "Habib University" ] ]
This paper will discuss the potential of dimensionality reduction with a web-based use of GANs. Throughout a variety of experiments, we show synthesizing visually-appealing samples, interpolating meaningfully between samples, and performing linear arithmetic with latent vectors. GANs have proved to be a remarkable tech...
2012.13129
Ankush Das
Ankush Das and Frank Pfenning
Rast: A Language for Resource-Aware Session Types
null
Logical Methods in Computer Science, Volume 18, Issue 1 (January 12, 2022) lmcs:7024
10.46298/lmcs-18(1:9)2022
null
cs.PL cs.LO
http://creativecommons.org/licenses/by/4.0/
Traditional session types prescribe bidirectional communication protocols for concurrent computations, where well-typed programs are guaranteed to adhere to the protocols. However, simple session types cannot capture properties beyond the basic type of the exchanged messages. In response, recent work has extended ses...
[ { "created": "Thu, 24 Dec 2020 06:30:00 GMT", "version": "v1" }, { "created": "Fri, 17 Sep 2021 07:03:42 GMT", "version": "v2" }, { "created": "Tue, 11 Jan 2022 09:02:14 GMT", "version": "v3" } ]
2023-06-22
[ [ "Das", "Ankush", "" ], [ "Pfenning", "Frank", "" ] ]
Traditional session types prescribe bidirectional communication protocols for concurrent computations, where well-typed programs are guaranteed to adhere to the protocols. However, simple session types cannot capture properties beyond the basic type of the exchanged messages. In response, recent work has extended sessi...
2106.03596
Dirk van der Hoeven
Dirk van der Hoeven and Federico Fusco and Nicol\`o Cesa-Bianchi
Beyond Bandit Feedback in Online Multiclass Classification
null
35th Conference on Neural Information Processing Systems (NeurIPS 2021)
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of online multiclass classification in a setting where the learner's feedback is determined by an arbitrary directed graph. While including bandit feedback as a special case, feedback graphs allow a much richer set of applications, including filtering and label efficient classification. We introd...
[ { "created": "Mon, 7 Jun 2021 13:22:30 GMT", "version": "v1" } ]
2024-02-20
[ [ "van der Hoeven", "Dirk", "" ], [ "Fusco", "Federico", "" ], [ "Cesa-Bianchi", "Nicolò", "" ] ]
We study the problem of online multiclass classification in a setting where the learner's feedback is determined by an arbitrary directed graph. While including bandit feedback as a special case, feedback graphs allow a much richer set of applications, including filtering and label efficient classification. We introduc...
2402.12647
Takuya Ikeda
Takuya Ikeda, Sergey Zakharov, Tianyi Ko, Muhammad Zubair Irshad, Robert Lee, Katherine Liu, Rares Ambrus, Koichi Nishiwaki
DiffusionNOCS: Managing Symmetry and Uncertainty in Sim2Real Multi-Modal Category-level Pose Estimation
8 pages. 9 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
null
null
null
cs.CV cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper addresses the challenging problem of category-level pose estimation. Current state-of-the-art methods for this task face challenges when dealing with symmetric objects and when attempting to generalize to new environments solely through synthetic data training. In this work, we address these challenges by ...
[ { "created": "Tue, 20 Feb 2024 01:48:33 GMT", "version": "v1" }, { "created": "Tue, 5 Mar 2024 07:12:34 GMT", "version": "v2" } ]
2024-03-06
[ [ "Ikeda", "Takuya", "" ], [ "Zakharov", "Sergey", "" ], [ "Ko", "Tianyi", "" ], [ "Irshad", "Muhammad Zubair", "" ], [ "Lee", "Robert", "" ], [ "Liu", "Katherine", "" ], [ "Ambrus", "Rares", "" ], [ ...
This paper addresses the challenging problem of category-level pose estimation. Current state-of-the-art methods for this task face challenges when dealing with symmetric objects and when attempting to generalize to new environments solely through synthetic data training. In this work, we address these challenges by pr...
2106.01425
Enmao Diao
Enmao Diao, Jie Ding, Vahid Tarokh
GAL: Gradient Assisted Learning for Decentralized Multi-Organization Collaborations
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Collaborations among multiple organizations, such as financial institutions, medical centers, and retail markets in decentralized settings are crucial to providing improved service and performance. However, the underlying organizations may have little interest in sharing their local data, models, and objective functi...
[ { "created": "Wed, 2 Jun 2021 19:12:03 GMT", "version": "v1" }, { "created": "Thu, 7 Oct 2021 19:44:19 GMT", "version": "v2" }, { "created": "Sat, 29 Jan 2022 01:39:58 GMT", "version": "v3" }, { "created": "Tue, 11 Oct 2022 06:28:58 GMT", "version": "v4" } ]
2022-10-12
[ [ "Diao", "Enmao", "" ], [ "Ding", "Jie", "" ], [ "Tarokh", "Vahid", "" ] ]
Collaborations among multiple organizations, such as financial institutions, medical centers, and retail markets in decentralized settings are crucial to providing improved service and performance. However, the underlying organizations may have little interest in sharing their local data, models, and objective function...
2211.02987
Ari Azarafrooz
Ari Azarafrooz
Differentiable Neural Computers with Memory Demon
NeurIPS 2022 Workshop On Memory in Artificial and Real Intelligence
null
null
null
cs.LG cs.NE
http://creativecommons.org/publicdomain/zero/1.0/
A Differentiable Neural Computer (DNC) is a neural network with an external memory which allows for iterative content modification via read, write and delete operations. We show that information theoretic properties of the memory contents play an important role in the performance of such architectures. We introduce...
[ { "created": "Sat, 5 Nov 2022 22:24:47 GMT", "version": "v1" } ]
2022-11-08
[ [ "Azarafrooz", "Ari", "" ] ]
A Differentiable Neural Computer (DNC) is a neural network with an external memory which allows for iterative content modification via read, write and delete operations. We show that information theoretic properties of the memory contents play an important role in the performance of such architectures. We introduce a n...
2303.06654
Esther Derman
Esther Derman, Yevgeniy Men, Matthieu Geist, Shie Mannor
Twice Regularized Markov Decision Processes: The Equivalence between Robustness and Regularization
Extended version of NeuIPS paper: arXiv:2110.06267
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Robust Markov decision processes (MDPs) aim to handle changing or partially known system dynamics. To solve them, one typically resorts to robust optimization methods. However, this significantly increases computational complexity and limits scalability in both learning and planning. On the other hand, regularized MD...
[ { "created": "Sun, 12 Mar 2023 13:03:28 GMT", "version": "v1" } ]
2023-03-14
[ [ "Derman", "Esther", "" ], [ "Men", "Yevgeniy", "" ], [ "Geist", "Matthieu", "" ], [ "Mannor", "Shie", "" ] ]
Robust Markov decision processes (MDPs) aim to handle changing or partially known system dynamics. To solve them, one typically resorts to robust optimization methods. However, this significantly increases computational complexity and limits scalability in both learning and planning. On the other hand, regularized MDPs...
2401.08953
Faisal Haque Bappy
Tariqul Islam, Faisal Haque Bappy, Md Nafis Ul Haque Shifat, Farhan Ahmad, Kamrul Hasan, Tarannum Shaila Zaman
An Efficient and Scalable Auditing Scheme for Cloud Data Storage using an Enhanced B-tree
null
null
null
null
cs.CR cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An efficient, scalable, and provably secure dynamic auditing scheme is highly desirable in the cloud storage environment for verifying the integrity of the outsourced data. Most of the existing work on remote integrity checking focuses on static archival data and therefore cannot be applied to cases where dynamic dat...
[ { "created": "Wed, 17 Jan 2024 04:01:18 GMT", "version": "v1" } ]
2024-01-18
[ [ "Islam", "Tariqul", "" ], [ "Bappy", "Faisal Haque", "" ], [ "Shifat", "Md Nafis Ul Haque", "" ], [ "Ahmad", "Farhan", "" ], [ "Hasan", "Kamrul", "" ], [ "Zaman", "Tarannum Shaila", "" ] ]
An efficient, scalable, and provably secure dynamic auditing scheme is highly desirable in the cloud storage environment for verifying the integrity of the outsourced data. Most of the existing work on remote integrity checking focuses on static archival data and therefore cannot be applied to cases where dynamic data ...
2205.08297
Christoph Weidenbach
Hendrik Leidinger and Christoph Weidenbach
SCL(EQ): SCL for First-Order Logic with Equality
null
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a new calculus SCL(EQ) for first-order logic with equality that only learns non-redundant clauses. Following the idea of CDCL (Conflict Driven Clause Learning) and SCL (Clause Learning from Simple Models) a ground literal model assumption is used to guide inferences that are then guaranteed to be non-redun...
[ { "created": "Tue, 17 May 2022 12:52:26 GMT", "version": "v1" } ]
2022-05-18
[ [ "Leidinger", "Hendrik", "" ], [ "Weidenbach", "Christoph", "" ] ]
We propose a new calculus SCL(EQ) for first-order logic with equality that only learns non-redundant clauses. Following the idea of CDCL (Conflict Driven Clause Learning) and SCL (Clause Learning from Simple Models) a ground literal model assumption is used to guide inferences that are then guaranteed to be non-redunda...
cs/0008028
Mark Johnson
Mark Johnson, Stuart Geman, Stephen Canon, Zhiyi Chi and Stefan Riezler
Estimators for Stochastic ``Unification-Based'' Grammars
7 pages
Proc 37th Annual Conference of the Association for Computational Linguistics, 1999, pages 535-541
null
null
cs.CL
null
Log-linear models provide a statistically sound framework for Stochastic ``Unification-Based'' Grammars (SUBGs) and stochastic versions of other kinds of grammars. We describe two computationally-tractable ways of estimating the parameters of such grammars from a training corpus of syntactic analyses, and apply these...
[ { "created": "Fri, 25 Aug 2000 17:23:07 GMT", "version": "v1" } ]
2007-05-23
[ [ "Johnson", "Mark", "" ], [ "Geman", "Stuart", "" ], [ "Canon", "Stephen", "" ], [ "Chi", "Zhiyi", "" ], [ "Riezler", "Stefan", "" ] ]
Log-linear models provide a statistically sound framework for Stochastic ``Unification-Based'' Grammars (SUBGs) and stochastic versions of other kinds of grammars. We describe two computationally-tractable ways of estimating the parameters of such grammars from a training corpus of syntactic analyses, and apply these t...
1912.04713
Sebastian Hofst\"atter
Sebastian Hofst\"atter, Markus Zlabinger, Allan Hanbury
Neural-IR-Explorer: A Content-Focused Tool to Explore Neural Re-Ranking Results
Accepted at ECIR 2020 (demo paper)
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we look beyond metrics-based evaluation of Information Retrieval systems, to explore the reasons behind ranking results. We present the content-focused Neural-IR-Explorer, which empowers users to browse through retrieval results and inspect the inner workings and fine-grained results of neural re-rankin...
[ { "created": "Tue, 10 Dec 2019 14:41:02 GMT", "version": "v1" } ]
2019-12-11
[ [ "Hofstätter", "Sebastian", "" ], [ "Zlabinger", "Markus", "" ], [ "Hanbury", "Allan", "" ] ]
In this paper we look beyond metrics-based evaluation of Information Retrieval systems, to explore the reasons behind ranking results. We present the content-focused Neural-IR-Explorer, which empowers users to browse through retrieval results and inspect the inner workings and fine-grained results of neural re-ranking ...
1406.4277
Toni Ernvall
Toni Ernvall, Thomas Westerb\"ack, Camilla Hollanti
Constructions of Optimal and Almost Optimal Locally Repairable Codes
5 pages, conference
2014 VITAE (Aalborg), pages 1-5
10.1109/VITAE.2014.6934442
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Constructions of optimal locally repairable codes (LRCs) in the case of $(r+1) \nmid n$ and over small finite fields were stated as open problems for LRCs in [I. Tamo \emph{et al.}, "Optimal locally repairable codes and connections to matroid theory", \emph{2013 IEEE ISIT}]. In this paper, these problems are studied ...
[ { "created": "Tue, 17 Jun 2014 08:41:16 GMT", "version": "v1" } ]
2014-11-21
[ [ "Ernvall", "Toni", "" ], [ "Westerbäck", "Thomas", "" ], [ "Hollanti", "Camilla", "" ] ]
Constructions of optimal locally repairable codes (LRCs) in the case of $(r+1) \nmid n$ and over small finite fields were stated as open problems for LRCs in [I. Tamo \emph{et al.}, "Optimal locally repairable codes and connections to matroid theory", \emph{2013 IEEE ISIT}]. In this paper, these problems are studied by...
1609.04373
Aiman Soliman
Aiman Soliman, Kiumars Soltani, Anand Padmanabhan, Shaowen Wang
Consistency of Social Sensing Signatures Across Major US Cities
CyberGIS16
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Previous studies have shown that Twitter users have biases to tweet from certain locations, locational bias, and during certain hours, temporal bias. We used three years of geolocated Twitter Data to quantify these biases and test our central hypothesis that Twitter users biases are consistent across US cities. Our r...
[ { "created": "Wed, 14 Sep 2016 18:41:23 GMT", "version": "v1" } ]
2016-09-15
[ [ "Soliman", "Aiman", "" ], [ "Soltani", "Kiumars", "" ], [ "Padmanabhan", "Anand", "" ], [ "Wang", "Shaowen", "" ] ]
Previous studies have shown that Twitter users have biases to tweet from certain locations, locational bias, and during certain hours, temporal bias. We used three years of geolocated Twitter Data to quantify these biases and test our central hypothesis that Twitter users biases are consistent across US cities. Our res...
1003.1449
Rdv Ijcsis
V. S. Meenakshi, G. Padmavathi
Securing Iris Templates using Combined User and Soft Biometric based Password Hardened Fuzzy Vault
Pages IEEE format, Computer Science ISSN 19475500, International Journal of Computer Science and Information Security, IJCSIS February 2010, ISSN 1947 5500, http://sites.google.com/site/ijcsis/
International Journal of Computer Science and Information Security, IJCSIS, Vol. 7, No. 2, pp. 001-008, February 2010, USA
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-sa/3.0/
Personal identification and authentication is very crucial in the current scenario. Biometrics plays an important role in this area. Biometric based authentication has proved superior compared to traditional password based authentication. Anyhow biometrics is permanent feature of a person and cannot be reissued when ...
[ { "created": "Sun, 7 Mar 2010 11:03:18 GMT", "version": "v1" } ]
2011-02-19
[ [ "Meenakshi", "V. S.", "" ], [ "Padmavathi", "G.", "" ] ]
Personal identification and authentication is very crucial in the current scenario. Biometrics plays an important role in this area. Biometric based authentication has proved superior compared to traditional password based authentication. Anyhow biometrics is permanent feature of a person and cannot be reissued when co...
cs/0009022
Gerard Escudero Bakx
Gerard Escudero, Lluis Marquez, German Rigau
A Comparison between Supervised Learning Algorithms for Word Sense Disambiguation
6 pages
Proceedings of the 4th Conference on Computational Natural Language Learning, CoNLL'2000, pp. 31-36
null
null
cs.CL cs.AI
null
This paper describes a set of comparative experiments, including cross-corpus evaluation, between five alternative algorithms for supervised Word Sense Disambiguation (WSD), namely Naive Bayes, Exemplar-based learning, SNoW, Decision Lists, and Boosting. Two main conclusions can be drawn: 1) The LazyBoosting algorith...
[ { "created": "Fri, 22 Sep 2000 15:02:26 GMT", "version": "v1" } ]
2007-05-23
[ [ "Escudero", "Gerard", "" ], [ "Marquez", "Lluis", "" ], [ "Rigau", "German", "" ] ]
This paper describes a set of comparative experiments, including cross-corpus evaluation, between five alternative algorithms for supervised Word Sense Disambiguation (WSD), namely Naive Bayes, Exemplar-based learning, SNoW, Decision Lists, and Boosting. Two main conclusions can be drawn: 1) The LazyBoosting algorithm ...
1710.04334
Allen Nie
Allen Nie, Erin D. Bennett, Noah D. Goodman
DisSent: Sentence Representation Learning from Explicit Discourse Relations
13 pages, 4 figures. ACL 2019
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning effective representations of sentences is one of the core missions of natural language understanding. Existing models either train on a vast amount of text, or require costly, manually curated sentence relation datasets. We show that with dependency parsing and rule-based rubrics, we can curate a high qualit...
[ { "created": "Thu, 12 Oct 2017 00:56:13 GMT", "version": "v1" }, { "created": "Thu, 3 May 2018 03:52:37 GMT", "version": "v2" }, { "created": "Tue, 14 May 2019 17:21:48 GMT", "version": "v3" }, { "created": "Tue, 4 Jun 2019 07:22:22 GMT", "version": "v4" } ]
2019-06-05
[ [ "Nie", "Allen", "" ], [ "Bennett", "Erin D.", "" ], [ "Goodman", "Noah D.", "" ] ]
Learning effective representations of sentences is one of the core missions of natural language understanding. Existing models either train on a vast amount of text, or require costly, manually curated sentence relation datasets. We show that with dependency parsing and rule-based rubrics, we can curate a high quality ...
2204.11667
Antoine Saporta
Antoine Saporta and Arthur Douillard and Tuan-Hung Vu and Patrick P\'erez and Matthieu Cord
Multi-Head Distillation for Continual Unsupervised Domain Adaptation in Semantic Segmentation
Published at the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2022 Workshop on Continual Learning
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Unsupervised Domain Adaptation (UDA) is a transfer learning task which aims at training on an unlabeled target domain by leveraging a labeled source domain. Beyond the traditional scope of UDA with a single source domain and a single target domain, real-world perception systems face a variety of scenarios to handle, ...
[ { "created": "Mon, 25 Apr 2022 14:03:09 GMT", "version": "v1" } ]
2022-04-26
[ [ "Saporta", "Antoine", "" ], [ "Douillard", "Arthur", "" ], [ "Vu", "Tuan-Hung", "" ], [ "Pérez", "Patrick", "" ], [ "Cord", "Matthieu", "" ] ]
Unsupervised Domain Adaptation (UDA) is a transfer learning task which aims at training on an unlabeled target domain by leveraging a labeled source domain. Beyond the traditional scope of UDA with a single source domain and a single target domain, real-world perception systems face a variety of scenarios to handle, fr...
2302.09352
Caoyun Fan
Caoyun Fan, Wenqing Chen, Jidong Tian, Yitian Li, Hao He, Yaohui Jin
MaxGNR: A Dynamic Weight Strategy via Maximizing Gradient-to-Noise Ratio for Multi-Task Learning
ACCV 2022
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
When modeling related tasks in computer vision, Multi-Task Learning (MTL) can outperform Single-Task Learning (STL) due to its ability to capture intrinsic relatedness among tasks. However, MTL may encounter the insufficient training problem, i.e., some tasks in MTL may encounter non-optimal situation compared with S...
[ { "created": "Sat, 18 Feb 2023 14:50:45 GMT", "version": "v1" } ]
2023-02-21
[ [ "Fan", "Caoyun", "" ], [ "Chen", "Wenqing", "" ], [ "Tian", "Jidong", "" ], [ "Li", "Yitian", "" ], [ "He", "Hao", "" ], [ "Jin", "Yaohui", "" ] ]
When modeling related tasks in computer vision, Multi-Task Learning (MTL) can outperform Single-Task Learning (STL) due to its ability to capture intrinsic relatedness among tasks. However, MTL may encounter the insufficient training problem, i.e., some tasks in MTL may encounter non-optimal situation compared with STL...
2406.14283
Chaojie Wang
Chaojie Wang, Yanchen Deng, Zhiyi Lyu, Liang Zeng, Jujie He, Shuicheng Yan, Bo An
Q*: Improving Multi-step Reasoning for LLMs with Deliberative Planning
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
Large Language Models (LLMs) have demonstrated impressive capability in many natural language tasks. However, the auto-regressive generation process makes LLMs prone to produce errors, hallucinations and inconsistent statements when performing multi-step reasoning. In this paper, by casting multi-step reasoning of LL...
[ { "created": "Thu, 20 Jun 2024 13:08:09 GMT", "version": "v1" }, { "created": "Mon, 24 Jun 2024 07:50:56 GMT", "version": "v2" }, { "created": "Thu, 27 Jun 2024 09:44:45 GMT", "version": "v3" }, { "created": "Mon, 22 Jul 2024 10:01:49 GMT", "version": "v4" } ]
2024-07-23
[ [ "Wang", "Chaojie", "" ], [ "Deng", "Yanchen", "" ], [ "Lyu", "Zhiyi", "" ], [ "Zeng", "Liang", "" ], [ "He", "Jujie", "" ], [ "Yan", "Shuicheng", "" ], [ "An", "Bo", "" ] ]
Large Language Models (LLMs) have demonstrated impressive capability in many natural language tasks. However, the auto-regressive generation process makes LLMs prone to produce errors, hallucinations and inconsistent statements when performing multi-step reasoning. In this paper, by casting multi-step reasoning of LLMs...
2308.16458
Xiangru Tang
Xiangru Tang, Bill Qian, Rick Gao, Jiakang Chen, Xinyun Chen, Mark Gerstein
BioCoder: A Benchmark for Bioinformatics Code Generation with Large Language Models
null
null
null
null
cs.LG cs.AI cs.CL
http://creativecommons.org/licenses/by/4.0/
Pre-trained large language models (LLMs) have significantly improved code generation. As these models scale up, there is an increasing need for the output to handle more intricate tasks and to be appropriately specialized to particular domains. Here, we target bioinformatics due to the amount of domain knowledge, alg...
[ { "created": "Thu, 31 Aug 2023 04:52:58 GMT", "version": "v1" }, { "created": "Tue, 5 Sep 2023 17:51:16 GMT", "version": "v2" }, { "created": "Fri, 29 Sep 2023 20:27:06 GMT", "version": "v3" }, { "created": "Mon, 4 Dec 2023 11:05:29 GMT", "version": "v4" }, { "cre...
2024-05-22
[ [ "Tang", "Xiangru", "" ], [ "Qian", "Bill", "" ], [ "Gao", "Rick", "" ], [ "Chen", "Jiakang", "" ], [ "Chen", "Xinyun", "" ], [ "Gerstein", "Mark", "" ] ]
Pre-trained large language models (LLMs) have significantly improved code generation. As these models scale up, there is an increasing need for the output to handle more intricate tasks and to be appropriately specialized to particular domains. Here, we target bioinformatics due to the amount of domain knowledge, algor...
1805.01375
Tim Kuipers
Tim Kuipers, Willemijn Elkhuizen, Jouke Verlinden, Eugeni Doubrovski
Hatching for 3D prints: line-based halftoning for dual extrusion fused deposition modeling
12 pages, 14 figures
null
10.1016/j.cag.2018.04.006
null
cs.GR
http://creativecommons.org/licenses/by-nc-sa/4.0/
This work presents a halftoning technique to manufacture 3D objects with the appearance of continuous grayscale imagery for Fused Deposition Modeling (FDM) printers. While droplet-based dithering is a common halftoning technique, this is not applicable to FDM printing, since FDM builds up objects by extruding materia...
[ { "created": "Thu, 3 May 2018 15:28:50 GMT", "version": "v1" }, { "created": "Fri, 4 May 2018 08:52:05 GMT", "version": "v2" } ]
2018-05-09
[ [ "Kuipers", "Tim", "" ], [ "Elkhuizen", "Willemijn", "" ], [ "Verlinden", "Jouke", "" ], [ "Doubrovski", "Eugeni", "" ] ]
This work presents a halftoning technique to manufacture 3D objects with the appearance of continuous grayscale imagery for Fused Deposition Modeling (FDM) printers. While droplet-based dithering is a common halftoning technique, this is not applicable to FDM printing, since FDM builds up objects by extruding material ...
2202.12003
Shivani Bathla
Shivani Bathla and Vinita Vasudevan
IBIA: Bayesian Inference via Incremental Build-Infer-Approximate operations on Clique Trees
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Exact inference in Bayesian networks is intractable and has an exponential dependence on the size of the largest clique in the corresponding clique tree (CT), necessitating approximations. Factor based methods to bound clique sizes are more accurate than structure based methods, but expensive since they involve infer...
[ { "created": "Thu, 24 Feb 2022 10:30:31 GMT", "version": "v1" }, { "created": "Wed, 10 Aug 2022 04:28:07 GMT", "version": "v2" } ]
2022-08-11
[ [ "Bathla", "Shivani", "" ], [ "Vasudevan", "Vinita", "" ] ]
Exact inference in Bayesian networks is intractable and has an exponential dependence on the size of the largest clique in the corresponding clique tree (CT), necessitating approximations. Factor based methods to bound clique sizes are more accurate than structure based methods, but expensive since they involve inferen...
2205.15532
Yan Lin
Yan Lin, Tianming Liu, Wei Liu, Zhigaoyuan Wang, Li Li, Guoai Xu, Haoyu Wang
Dataset Bias in Android Malware Detection
null
null
null
null
cs.SE
http://creativecommons.org/licenses/by-nc-nd/4.0/
Researchers have proposed kinds of malware detection methods to solve the explosive mobile security threats. We argue that the experiment results are inflated due to the research bias introduced by the variability of malware dataset. We explore the impact of bias in Android malware detection in three aspects, the met...
[ { "created": "Tue, 31 May 2022 04:25:56 GMT", "version": "v1" } ]
2022-06-01
[ [ "Lin", "Yan", "" ], [ "Liu", "Tianming", "" ], [ "Liu", "Wei", "" ], [ "Wang", "Zhigaoyuan", "" ], [ "Li", "Li", "" ], [ "Xu", "Guoai", "" ], [ "Wang", "Haoyu", "" ] ]
Researchers have proposed kinds of malware detection methods to solve the explosive mobile security threats. We argue that the experiment results are inflated due to the research bias introduced by the variability of malware dataset. We explore the impact of bias in Android malware detection in three aspects, the metho...
1908.08911
Martin N\"ollenburg
Sujoy Bhore, Robert Ganian, Fabrizio Montecchiani, Martin N\"ollenburg
Parameterized Algorithms for Book Embedding Problems
Appears in the Proceedings of the 27th International Symposium on Graph Drawing and Network Visualization (GD 2019)
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A k-page book embedding of a graph G draws the vertices of G on a line and the edges on k half-planes (called pages) bounded by this line, such that no two edges on the same page cross. We study the problem of determining whether G admits a k-page book embedding both when the linear order of the vertices is fixed, ca...
[ { "created": "Fri, 23 Aug 2019 17:36:13 GMT", "version": "v1" } ]
2019-08-26
[ [ "Bhore", "Sujoy", "" ], [ "Ganian", "Robert", "" ], [ "Montecchiani", "Fabrizio", "" ], [ "Nöllenburg", "Martin", "" ] ]
A k-page book embedding of a graph G draws the vertices of G on a line and the edges on k half-planes (called pages) bounded by this line, such that no two edges on the same page cross. We study the problem of determining whether G admits a k-page book embedding both when the linear order of the vertices is fixed, call...
1911.00782
Bao Wang
Bao Wang, Difan Zou, Quanquan Gu, Stanley Osher
Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo
27 pages, 5 figures
null
null
null
cs.LG cs.NA math.NA stat.CO stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As an important Markov Chain Monte Carlo (MCMC) method, stochastic gradient Langevin dynamics (SGLD) algorithm has achieved great success in Bayesian learning and posterior sampling. However, SGLD typically suffers from slow convergence rate due to its large variance caused by the stochastic gradient. In order to all...
[ { "created": "Sat, 2 Nov 2019 20:32:11 GMT", "version": "v1" } ]
2019-11-05
[ [ "Wang", "Bao", "" ], [ "Zou", "Difan", "" ], [ "Gu", "Quanquan", "" ], [ "Osher", "Stanley", "" ] ]
As an important Markov Chain Monte Carlo (MCMC) method, stochastic gradient Langevin dynamics (SGLD) algorithm has achieved great success in Bayesian learning and posterior sampling. However, SGLD typically suffers from slow convergence rate due to its large variance caused by the stochastic gradient. In order to allev...
1407.4394
Jan St\"uckrath
Giorgio Delzanno, Jan St\"uckrath
Parameterized Verification of Graph Transformation Systems with Whole Neighbourhood Operations
Extended version of a submittion accepted at RP'14 Workshop
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a new class of graph transformation systems in which rewrite rules can be guarded by universally quantified conditions on the neighbourhood of nodes. These conditions are defined via special graph patterns which may be transformed by the rule as well. For the new class for graph rewrite rules, we provide...
[ { "created": "Wed, 16 Jul 2014 17:51:44 GMT", "version": "v1" }, { "created": "Fri, 18 Jul 2014 14:25:05 GMT", "version": "v2" } ]
2014-07-21
[ [ "Delzanno", "Giorgio", "" ], [ "Stückrath", "Jan", "" ] ]
We introduce a new class of graph transformation systems in which rewrite rules can be guarded by universally quantified conditions on the neighbourhood of nodes. These conditions are defined via special graph patterns which may be transformed by the rule as well. For the new class for graph rewrite rules, we provide a...
1902.07165
Nikolaj Tatti
Nikolaj Tatti, Jilles Vreeken
Comparing Apples and Oranges: Measuring Differences between Exploratory Data Mining Results
Journal version. The previous version is the conference version
null
10.1007/s10618-012-0275-9
null
cs.DB cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deciding whether the results of two different mining algorithms provide significantly different information is an important, yet understudied, open problem in exploratory data mining. Whether the goal is to select the most informative result for analysis, or to decide which mining approach will most likely provide th...
[ { "created": "Mon, 18 Feb 2019 16:57:43 GMT", "version": "v1" }, { "created": "Wed, 24 Apr 2019 23:41:08 GMT", "version": "v2" } ]
2019-04-26
[ [ "Tatti", "Nikolaj", "" ], [ "Vreeken", "Jilles", "" ] ]
Deciding whether the results of two different mining algorithms provide significantly different information is an important, yet understudied, open problem in exploratory data mining. Whether the goal is to select the most informative result for analysis, or to decide which mining approach will most likely provide the ...
2203.14694
Yanan Chang
Shangfei Wang, Yanan Chang, Jiahe Wang
Facial Action Unit Recognition Based on Transfer Learning
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Facial action unit recognition is an important task for facial analysis. Owing to the complex collection environment, facial action unit recognition in the wild is still challenging. The 3rd competition on affective behavior analysis in-the-wild (ABAW) has provided large amount of facial images with facial action uni...
[ { "created": "Fri, 25 Mar 2022 04:01:58 GMT", "version": "v1" } ]
2022-03-29
[ [ "Wang", "Shangfei", "" ], [ "Chang", "Yanan", "" ], [ "Wang", "Jiahe", "" ] ]
Facial action unit recognition is an important task for facial analysis. Owing to the complex collection environment, facial action unit recognition in the wild is still challenging. The 3rd competition on affective behavior analysis in-the-wild (ABAW) has provided large amount of facial images with facial action unit ...
2403.00450
Thomas Firmin
Thomas Firmin, Pierre Boulet, El-Ghazali Talbi
Parallel Hyperparameter Optimization Of Spiking Neural Network
null
null
null
null
cs.NE cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Spiking Neural Networks (SNN). SNNs are based on a more biologically inspired approach than usual artificial neural networks. Such models are characterized by complex dynamics between neurons and spikes. These are very sensitive to the hyperparameters, making their optimization challenging. To tackle hyperparameter o...
[ { "created": "Fri, 1 Mar 2024 11:11:59 GMT", "version": "v1" } ]
2024-03-04
[ [ "Firmin", "Thomas", "" ], [ "Boulet", "Pierre", "" ], [ "Talbi", "El-Ghazali", "" ] ]
Spiking Neural Networks (SNN). SNNs are based on a more biologically inspired approach than usual artificial neural networks. Such models are characterized by complex dynamics between neurons and spikes. These are very sensitive to the hyperparameters, making their optimization challenging. To tackle hyperparameter opt...
2307.16816
Xuanang Chen
Xuanang Chen, Ben He, Le Sun, Yingfei Sun
Defense of Adversarial Ranking Attack in Text Retrieval: Benchmark and Baseline via Detection
11 pages, work in progress
null
null
null
cs.IR cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural ranking models (NRMs) have undergone significant development and have become integral components of information retrieval (IR) systems. Unfortunately, recent research has unveiled the vulnerability of NRMs to adversarial document manipulations, potentially exploited by malicious search engine optimization prac...
[ { "created": "Mon, 31 Jul 2023 16:31:24 GMT", "version": "v1" } ]
2023-08-01
[ [ "Chen", "Xuanang", "" ], [ "He", "Ben", "" ], [ "Sun", "Le", "" ], [ "Sun", "Yingfei", "" ] ]
Neural ranking models (NRMs) have undergone significant development and have become integral components of information retrieval (IR) systems. Unfortunately, recent research has unveiled the vulnerability of NRMs to adversarial document manipulations, potentially exploited by malicious search engine optimization practi...
2101.10710
Mohammad Naser Sabet Jahromi
Satya M. Muddamsetty, Mohammad N. S. Jahromi, Andreea E. Ciontos, Laura M. Fenoy, Thomas B. Moeslund
Visual explanation of black-box model: Similarity Difference and Uniqueness (SIDU) method
null
Pattern Recognition 127 (2022): 108604
null
null
cs.CV cs.AI cs.HC cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Explainable Artificial Intelligence (XAI) has in recent years become a well-suited framework to generate human understandable explanations of "black-box" models. In this paper, a novel XAI visual explanation algorithm known as the Similarity Difference and Uniqueness (SIDU) method that can effectively localize entire...
[ { "created": "Tue, 26 Jan 2021 11:13:50 GMT", "version": "v1" }, { "created": "Sun, 10 Jul 2022 18:07:56 GMT", "version": "v2" } ]
2022-07-12
[ [ "Muddamsetty", "Satya M.", "" ], [ "Jahromi", "Mohammad N. S.", "" ], [ "Ciontos", "Andreea E.", "" ], [ "Fenoy", "Laura M.", "" ], [ "Moeslund", "Thomas B.", "" ] ]
Explainable Artificial Intelligence (XAI) has in recent years become a well-suited framework to generate human understandable explanations of "black-box" models. In this paper, a novel XAI visual explanation algorithm known as the Similarity Difference and Uniqueness (SIDU) method that can effectively localize entire o...
2406.10714
Neehar Peri
Arun Balajee Vasudevan, Neehar Peri, Jeff Schneider, Deva Ramanan
Planning with Adaptive World Models for Autonomous Driving
Project Page: https://arunbalajeev.github.io/world_models_planning/world_model_paper.html
null
null
null
cs.RO cs.LG
http://creativecommons.org/licenses/by/4.0/
Motion planning is crucial for safe navigation in complex urban environments. Historically, motion planners (MPs) have been evaluated with procedurally-generated simulators like CARLA. However, such synthetic benchmarks do not capture real-world multi-agent interactions. nuPlan, a recently released MP benchmark, addr...
[ { "created": "Sat, 15 Jun 2024 18:53:45 GMT", "version": "v1" } ]
2024-06-18
[ [ "Vasudevan", "Arun Balajee", "" ], [ "Peri", "Neehar", "" ], [ "Schneider", "Jeff", "" ], [ "Ramanan", "Deva", "" ] ]
Motion planning is crucial for safe navigation in complex urban environments. Historically, motion planners (MPs) have been evaluated with procedurally-generated simulators like CARLA. However, such synthetic benchmarks do not capture real-world multi-agent interactions. nuPlan, a recently released MP benchmark, addres...
2201.13402
Alex Berke
Alex Berke and Dan Calacci
Privacy Limitations Of Interest-based Advertising On The Web: A Post-mortem Empirical Analysis Of Google's FLoC
Author version of paper In Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security (CCS '22)
null
null
null
cs.CY
http://creativecommons.org/licenses/by/4.0/
In 2020, Google announced it would disable third-party cookies in the Chrome browser to improve user privacy. In order to continue to enable interest-based advertising while mitigating risks of individualized user tracking, Google proposed FLoC. The FLoC algorithm assigns users to "cohorts" that represent groups of u...
[ { "created": "Mon, 31 Jan 2022 18:07:33 GMT", "version": "v1" }, { "created": "Wed, 2 Feb 2022 16:01:55 GMT", "version": "v2" }, { "created": "Thu, 3 Feb 2022 04:44:27 GMT", "version": "v3" }, { "created": "Tue, 3 May 2022 02:27:37 GMT", "version": "v4" }, { "crea...
2022-10-17
[ [ "Berke", "Alex", "" ], [ "Calacci", "Dan", "" ] ]
In 2020, Google announced it would disable third-party cookies in the Chrome browser to improve user privacy. In order to continue to enable interest-based advertising while mitigating risks of individualized user tracking, Google proposed FLoC. The FLoC algorithm assigns users to "cohorts" that represent groups of use...
2004.02186
Edoardo Remelli
Edoardo Remelli, Shangchen Han, Sina Honari, Pascal Fua, Robert Wang
Lightweight Multi-View 3D Pose Estimation through Camera-Disentangled Representation
null
The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 6040-6049
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a lightweight solution to recover 3D pose from multi-view images captured with spatially calibrated cameras. Building upon recent advances in interpretable representation learning, we exploit 3D geometry to fuse input images into a unified latent representation of pose, which is disentangled from camera vi...
[ { "created": "Sun, 5 Apr 2020 12:52:29 GMT", "version": "v1" }, { "created": "Sat, 20 Jun 2020 08:35:57 GMT", "version": "v2" } ]
2020-06-23
[ [ "Remelli", "Edoardo", "" ], [ "Han", "Shangchen", "" ], [ "Honari", "Sina", "" ], [ "Fua", "Pascal", "" ], [ "Wang", "Robert", "" ] ]
We present a lightweight solution to recover 3D pose from multi-view images captured with spatially calibrated cameras. Building upon recent advances in interpretable representation learning, we exploit 3D geometry to fuse input images into a unified latent representation of pose, which is disentangled from camera view...
2104.04998
Ayush Maheshwari
Atul Sahay, Ayush Maheshwari, Ritesh Kumar, Ganesh Ramakrishnan, Manjesh Kumar Hanawal, Kavi Arya
Unsupervised Learning of Explainable Parse Trees for Improved Generalisation
8 Pages, 5 Tables, 4 Figures. To appear at IJCNN 2021
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recursive neural networks (RvNN) have been shown useful for learning sentence representations and helped achieve competitive performance on several natural language inference tasks. However, recent RvNN-based models fail to learn simple grammar and meaningful semantics in their intermediate tree representation. In th...
[ { "created": "Sun, 11 Apr 2021 12:10:03 GMT", "version": "v1" } ]
2021-04-13
[ [ "Sahay", "Atul", "" ], [ "Maheshwari", "Ayush", "" ], [ "Kumar", "Ritesh", "" ], [ "Ramakrishnan", "Ganesh", "" ], [ "Hanawal", "Manjesh Kumar", "" ], [ "Arya", "Kavi", "" ] ]
Recursive neural networks (RvNN) have been shown useful for learning sentence representations and helped achieve competitive performance on several natural language inference tasks. However, recent RvNN-based models fail to learn simple grammar and meaningful semantics in their intermediate tree representation. In this...
2404.01990
Shuaiyi Huang
Shuaiyi Huang, De-An Huang, Zhiding Yu, Shiyi Lan, Subhashree Radhakrishnan, Jose M. Alvarez, Abhinav Shrivastava, Anima Anandkumar
What is Point Supervision Worth in Video Instance Segmentation?
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Video instance segmentation (VIS) is a challenging vision task that aims to detect, segment, and track objects in videos. Conventional VIS methods rely on densely-annotated object masks which are expensive. We reduce the human annotations to only one point for each object in a video frame during training, and obtain ...
[ { "created": "Mon, 1 Apr 2024 17:38:25 GMT", "version": "v1" } ]
2024-04-03
[ [ "Huang", "Shuaiyi", "" ], [ "Huang", "De-An", "" ], [ "Yu", "Zhiding", "" ], [ "Lan", "Shiyi", "" ], [ "Radhakrishnan", "Subhashree", "" ], [ "Alvarez", "Jose M.", "" ], [ "Shrivastava", "Abhinav", "" ], ...
Video instance segmentation (VIS) is a challenging vision task that aims to detect, segment, and track objects in videos. Conventional VIS methods rely on densely-annotated object masks which are expensive. We reduce the human annotations to only one point for each object in a video frame during training, and obtain hi...
2008.09246
Jie Xu
Jie Xu, Wei Zhang, Fei Wang
A(DP)$^2$SGD: Asynchronous Decentralized Parallel Stochastic Gradient Descent with Differential Privacy
null
null
null
null
cs.LG cs.DC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As deep learning models are usually massive and complex, distributed learning is essential for increasing training efficiency. Moreover, in many real-world application scenarios like healthcare, distributed learning can also keep the data local and protect privacy. A popular distributed learning strategy is federated...
[ { "created": "Fri, 21 Aug 2020 00:56:22 GMT", "version": "v1" } ]
2020-08-24
[ [ "Xu", "Jie", "" ], [ "Zhang", "Wei", "" ], [ "Wang", "Fei", "" ] ]
As deep learning models are usually massive and complex, distributed learning is essential for increasing training efficiency. Moreover, in many real-world application scenarios like healthcare, distributed learning can also keep the data local and protect privacy. A popular distributed learning strategy is federated l...
2201.06880
Xu Liu
Xu Liu, Wei Peng, Zhiqiang Gong, Weien Zhou, Wen Yao
Temperature Field Inversion of Heat-Source Systems via Physics-Informed Neural Networks
null
Engineering Applications of Artificial Intelligence(2022)
10.1016/j.engappai.2022.104902
2022.08.01
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Temperature field inversion of heat-source systems (TFI-HSS) with limited observations is essential to monitor the system health. Although some methods such as interpolation have been proposed to solve TFI-HSS, those existing methods ignore correlations between data constraints and physics constraints, causing the lo...
[ { "created": "Tue, 18 Jan 2022 11:21:35 GMT", "version": "v1" } ]
2022-06-14
[ [ "Liu", "Xu", "" ], [ "Peng", "Wei", "" ], [ "Gong", "Zhiqiang", "" ], [ "Zhou", "Weien", "" ], [ "Yao", "Wen", "" ] ]
Temperature field inversion of heat-source systems (TFI-HSS) with limited observations is essential to monitor the system health. Although some methods such as interpolation have been proposed to solve TFI-HSS, those existing methods ignore correlations between data constraints and physics constraints, causing the low ...
2102.03958
Tsuyoshi Yoshida
Tsuyoshi Yoshida, Koji Igarashi, Magnus Karlsson, and Erik Agrell
Compressed Shaping: Concept and FPGA Demonstration
10 pages, 12 figures
IEEE/OSA Journal of Lightwave Technology, vol. 39, no. 17, pp. 5412-5422, Sept. 2021
10.1109/JLT.2021.3085974
null
cs.IT eess.SP math.IT
http://creativecommons.org/licenses/by-sa/4.0/
Probabilistic shaping (PS) has been widely studied and applied to optical fiber communications. The encoder of PS expends the number of bit slots and controls the probability distribution of channel input symbols. Not only studies focused on PS but also most works on optical fiber communications have assumed source u...
[ { "created": "Mon, 8 Feb 2021 01:37:22 GMT", "version": "v1" }, { "created": "Wed, 28 Apr 2021 05:23:01 GMT", "version": "v2" } ]
2024-01-25
[ [ "Yoshida", "Tsuyoshi", "" ], [ "Igarashi", "Koji", "" ], [ "Karlsson", "Magnus", "" ], [ "Agrell", "Erik", "" ] ]
Probabilistic shaping (PS) has been widely studied and applied to optical fiber communications. The encoder of PS expends the number of bit slots and controls the probability distribution of channel input symbols. Not only studies focused on PS but also most works on optical fiber communications have assumed source uni...
2311.10505
Carmine Dodaro
Simone Caruso, Carmine Dodaro, Marco Maratea, Marco Mochi, Francesco Riccio
CNL2ASP: converting controlled natural language sentences into ASP
Under consideration in Theory and Practice of Logic Programming (TPLP)
null
null
null
cs.AI cs.CL cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Answer Set Programming (ASP) is a popular declarative programming language for solving hard combinatorial problems. Although ASP has gained widespread acceptance in academic and industrial contexts, there are certain user groups who may find it more advantageous to employ a higher-level language that closely resemble...
[ { "created": "Fri, 17 Nov 2023 13:10:58 GMT", "version": "v1" } ]
2023-11-20
[ [ "Caruso", "Simone", "" ], [ "Dodaro", "Carmine", "" ], [ "Maratea", "Marco", "" ], [ "Mochi", "Marco", "" ], [ "Riccio", "Francesco", "" ] ]
Answer Set Programming (ASP) is a popular declarative programming language for solving hard combinatorial problems. Although ASP has gained widespread acceptance in academic and industrial contexts, there are certain user groups who may find it more advantageous to employ a higher-level language that closely resembles ...
2309.11582
Yilun Zhu
Yilun Zhu, Siyao Peng, Sameer Pradhan, Amir Zeldes
Incorporating Singletons and Mention-based Features in Coreference Resolution via Multi-task Learning for Better Generalization
IJCNLP-AACL 2023
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Previous attempts to incorporate a mention detection step into end-to-end neural coreference resolution for English have been hampered by the lack of singleton mention span data as well as other entity information. This paper presents a coreference model that learns singletons as well as features such as entity type ...
[ { "created": "Wed, 20 Sep 2023 18:44:24 GMT", "version": "v1" } ]
2023-09-22
[ [ "Zhu", "Yilun", "" ], [ "Peng", "Siyao", "" ], [ "Pradhan", "Sameer", "" ], [ "Zeldes", "Amir", "" ] ]
Previous attempts to incorporate a mention detection step into end-to-end neural coreference resolution for English have been hampered by the lack of singleton mention span data as well as other entity information. This paper presents a coreference model that learns singletons as well as features such as entity type an...
1901.02918
Barry Smith
Jobst Landgrebe and Barry Smith
Making AI meaningful again
23 pages, 1 Table
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the s...
[ { "created": "Wed, 9 Jan 2019 20:16:44 GMT", "version": "v1" }, { "created": "Sun, 17 Feb 2019 11:07:26 GMT", "version": "v2" }, { "created": "Sat, 23 Mar 2019 06:17:08 GMT", "version": "v3" } ]
2019-03-26
[ [ "Landgrebe", "Jobst", "" ], [ "Smith", "Barry", "" ] ]
Artificial intelligence (AI) research enjoyed an initial period of enthusiasm in the 1970s and 80s. But this enthusiasm was tempered by a long interlude of frustration when genuinely useful AI applications failed to be forthcoming. Today, we are experiencing once again a period of enthusiasm, fired above all by the suc...
1002.0123
Sang Joon Kim
Sang Joon Kim, Besma Smida, Natasha Devroye
Achievable rate regions and outer bounds for a multi-pair bi-directional relay network
61 pages, 12 figures, will be submitted to IEEE info theory
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In a bi-directional relay channel, a pair of nodes wish to exchange independent messages over a shared wireless half-duplex channel with the help of relays. Recent work has mostly considered information theoretic limits of the bi-directional relay channel with two terminal nodes (or end users) and one relay. In this ...
[ { "created": "Sun, 31 Jan 2010 13:34:29 GMT", "version": "v1" } ]
2010-02-02
[ [ "Kim", "Sang Joon", "" ], [ "Smida", "Besma", "" ], [ "Devroye", "Natasha", "" ] ]
In a bi-directional relay channel, a pair of nodes wish to exchange independent messages over a shared wireless half-duplex channel with the help of relays. Recent work has mostly considered information theoretic limits of the bi-directional relay channel with two terminal nodes (or end users) and one relay. In this wo...
1701.07731
Jonathan Detchart
Jonathan Detchart, J\'er\^ome Lacan
Fast Xor-based Erasure Coding based on Polynomial Ring Transforms
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The complexity of software implementations of MDS erasure codes mainly depends on the efficiency of the finite field operations implementation. In this paper, we propose a method to reduce the complexity of the finite field multiplication by using fast transforms between a field and a ring to perform the multiplicati...
[ { "created": "Thu, 26 Jan 2017 14:58:11 GMT", "version": "v1" }, { "created": "Tue, 13 Jun 2017 09:14:15 GMT", "version": "v2" } ]
2017-06-14
[ [ "Detchart", "Jonathan", "" ], [ "Lacan", "Jérôme", "" ] ]
The complexity of software implementations of MDS erasure codes mainly depends on the efficiency of the finite field operations implementation. In this paper, we propose a method to reduce the complexity of the finite field multiplication by using fast transforms between a field and a ring to perform the multiplication...
2202.06367
Susanna Rumsey
Susanna E. Rumsey (1) and Stark C. Draper (1) and Frank R. Kschischang (1) ((1) Department of Electrical and Computer Engineering, University of Toronto)
Information Density in Multi-Layer Resistive Memories
null
in IEEE Transactions on Information Theory, vol. 67, no. 3, pp. 1446-1460, March 2021
10.1109/TIT.2020.3040255
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Resistive memories store information in a crossbar arrangement of two-terminal devices that can be programmed to patterns of high or low resistance. While extremely compact, this technology suffers from the "sneak-path" problem: certain information patterns cannot be recovered, as multiple low resistances in parallel...
[ { "created": "Sun, 13 Feb 2022 17:31:32 GMT", "version": "v1" } ]
2022-02-15
[ [ "Rumsey", "Susanna E.", "" ], [ "Draper", "Stark C.", "" ], [ "Kschischang", "Frank R.", "" ] ]
Resistive memories store information in a crossbar arrangement of two-terminal devices that can be programmed to patterns of high or low resistance. While extremely compact, this technology suffers from the "sneak-path" problem: certain information patterns cannot be recovered, as multiple low resistances in parallel m...