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1906.06678
Zhi-Xiu Ye
Zhi-Xiu Ye and Zhen-Hua Ling
Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
ACL 2019
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a multi-level matching and aggregation network (MLMAN) for few-shot relation classification. Previous studies on this topic adopt prototypical networks, which calculate the embedding vector of a query instance and the prototype vector of each support set independently. In contrast, our proposed ML...
[ { "created": "Sun, 16 Jun 2019 13:10:33 GMT", "version": "v1" } ]
2019-06-18
[ [ "Ye", "Zhi-Xiu", "" ], [ "Ling", "Zhen-Hua", "" ] ]
This paper presents a multi-level matching and aggregation network (MLMAN) for few-shot relation classification. Previous studies on this topic adopt prototypical networks, which calculate the embedding vector of a query instance and the prototype vector of each support set independently. In contrast, our proposed MLMA...
2008.10238
Sunjae Yoon
Minuk Ma, Sunjae Yoon, Junyeong Kim, Youngjoon Lee, Sunghun Kang, and Chang D. Yoo
VLANet: Video-Language Alignment Network for Weakly-Supervised Video Moment Retrieval
16 pages, 6 figures, European Conference on Computer Vision, 2020
null
10.1007/978-3-030-58604-1_10
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Video Moment Retrieval (VMR) is a task to localize the temporal moment in untrimmed video specified by natural language query. For VMR, several methods that require full supervision for training have been proposed. Unfortunately, acquiring a large number of training videos with labeled temporal boundaries for each qu...
[ { "created": "Mon, 24 Aug 2020 07:54:59 GMT", "version": "v1" } ]
2023-10-10
[ [ "Ma", "Minuk", "" ], [ "Yoon", "Sunjae", "" ], [ "Kim", "Junyeong", "" ], [ "Lee", "Youngjoon", "" ], [ "Kang", "Sunghun", "" ], [ "Yoo", "Chang D.", "" ] ]
Video Moment Retrieval (VMR) is a task to localize the temporal moment in untrimmed video specified by natural language query. For VMR, several methods that require full supervision for training have been proposed. Unfortunately, acquiring a large number of training videos with labeled temporal boundaries for each quer...
2404.13874
Haoyi Qiu
Haoyi Qiu, Wenbo Hu, Zi-Yi Dou, Nanyun Peng
VALOR-EVAL: Holistic Coverage and Faithfulness Evaluation of Large Vision-Language Models
ACL 2024 Findings
null
null
null
cs.CL cs.CV
http://creativecommons.org/licenses/by/4.0/
Large Vision-Language Models (LVLMs) suffer from hallucination issues, wherein the models generate plausible-sounding but factually incorrect outputs, undermining their reliability. A comprehensive quantitative evaluation is necessary to identify and understand the extent of hallucinations in these models. However, e...
[ { "created": "Mon, 22 Apr 2024 04:49:22 GMT", "version": "v1" }, { "created": "Thu, 6 Jun 2024 02:53:37 GMT", "version": "v2" }, { "created": "Sun, 14 Jul 2024 23:11:05 GMT", "version": "v3" } ]
2024-07-16
[ [ "Qiu", "Haoyi", "" ], [ "Hu", "Wenbo", "" ], [ "Dou", "Zi-Yi", "" ], [ "Peng", "Nanyun", "" ] ]
Large Vision-Language Models (LVLMs) suffer from hallucination issues, wherein the models generate plausible-sounding but factually incorrect outputs, undermining their reliability. A comprehensive quantitative evaluation is necessary to identify and understand the extent of hallucinations in these models. However, exi...
2103.15108
Wanhua Li
Wanhua Li, Shiwei Wang, Jiwen Lu, Jianjiang Feng, Jie Zhou
Meta-Mining Discriminative Samples for Kinship Verification
Accepted by CVPR2021
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Kinship verification aims to find out whether there is a kin relation for a given pair of facial images. Kinship verification databases are born with unbalanced data. For a database with N positive kinship pairs, we naturally obtain N(N-1) negative pairs. How to fully utilize the limited positive pairs and mine discr...
[ { "created": "Sun, 28 Mar 2021 11:47:07 GMT", "version": "v1" } ]
2021-03-30
[ [ "Li", "Wanhua", "" ], [ "Wang", "Shiwei", "" ], [ "Lu", "Jiwen", "" ], [ "Feng", "Jianjiang", "" ], [ "Zhou", "Jie", "" ] ]
Kinship verification aims to find out whether there is a kin relation for a given pair of facial images. Kinship verification databases are born with unbalanced data. For a database with N positive kinship pairs, we naturally obtain N(N-1) negative pairs. How to fully utilize the limited positive pairs and mine discrim...
1101.5938
Vojt\v{e}ch P\v{r}ehnal Mgr.
Vojtech Prehnal
Dialog interface for dynamic data models
null
null
null
null
cs.SE cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, the new information system development methodology will be proposed. This methodology will enable the whole data model to be built and adjusted at the run time, without rebuilding the application. This will make the user much more powerful and independent on the manufacturer of the system. It will also...
[ { "created": "Mon, 31 Jan 2011 12:39:26 GMT", "version": "v1" } ]
2011-02-01
[ [ "Prehnal", "Vojtech", "" ] ]
In this paper, the new information system development methodology will be proposed. This methodology will enable the whole data model to be built and adjusted at the run time, without rebuilding the application. This will make the user much more powerful and independent on the manufacturer of the system. It will also c...
2402.12177
Mingtian Zhang
Mingtian Zhang, Shawn Lan, Peter Hayes, David Barber
Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning
null
null
null
null
cs.LG cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Retrieval Augmented Generation (RAG) has emerged as an effective solution for mitigating hallucinations in Large Language Models (LLMs). The retrieval stage in RAG typically involves a pre-trained embedding model, which converts queries and passages into vectors to capture their semantics. However, a standard pre-tra...
[ { "created": "Mon, 19 Feb 2024 14:33:24 GMT", "version": "v1" }, { "created": "Mon, 26 Feb 2024 11:54:12 GMT", "version": "v2" }, { "created": "Tue, 5 Mar 2024 07:08:16 GMT", "version": "v3" }, { "created": "Tue, 12 Mar 2024 16:04:23 GMT", "version": "v4" } ]
2024-03-13
[ [ "Zhang", "Mingtian", "" ], [ "Lan", "Shawn", "" ], [ "Hayes", "Peter", "" ], [ "Barber", "David", "" ] ]
Retrieval Augmented Generation (RAG) has emerged as an effective solution for mitigating hallucinations in Large Language Models (LLMs). The retrieval stage in RAG typically involves a pre-trained embedding model, which converts queries and passages into vectors to capture their semantics. However, a standard pre-train...
2405.01590
Haithem Kchaou
Manel Aloui, Hasna Chouikhi, Ghaith Chaabane, Haithem Kchaou, Chehir Dhaouadi
101 Billion Arabic Words Dataset
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In recent years, Large Language Models have revolutionized the field of natural language processing, showcasing an impressive rise predominantly in English-centric domains. These advancements have set a global benchmark, inspiring significant efforts toward developing Arabic LLMs capable of understanding and generati...
[ { "created": "Mon, 29 Apr 2024 13:15:03 GMT", "version": "v1" } ]
2024-05-06
[ [ "Aloui", "Manel", "" ], [ "Chouikhi", "Hasna", "" ], [ "Chaabane", "Ghaith", "" ], [ "Kchaou", "Haithem", "" ], [ "Dhaouadi", "Chehir", "" ] ]
In recent years, Large Language Models have revolutionized the field of natural language processing, showcasing an impressive rise predominantly in English-centric domains. These advancements have set a global benchmark, inspiring significant efforts toward developing Arabic LLMs capable of understanding and generating...
1911.10392
Mohsen Mesgar
Mohsen Mesgar, Paul Youssef, Lin Li, Dominik Bierwirth, Yihao Li, Christian M. Meyer, Iryna Gurevych
When is ACL's Deadline? A Scientific Conversational Agent
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Our conversational agent UKP-ATHENA assists NLP researchers in finding and exploring scientific literature, identifying relevant authors, planning or post-processing conference visits, and preparing paper submissions using a unified interface based on natural language inputs and responses. UKP-ATHENA enables new acce...
[ { "created": "Sat, 23 Nov 2019 17:41:02 GMT", "version": "v1" } ]
2019-11-26
[ [ "Mesgar", "Mohsen", "" ], [ "Youssef", "Paul", "" ], [ "Li", "Lin", "" ], [ "Bierwirth", "Dominik", "" ], [ "Li", "Yihao", "" ], [ "Meyer", "Christian M.", "" ], [ "Gurevych", "Iryna", "" ] ]
Our conversational agent UKP-ATHENA assists NLP researchers in finding and exploring scientific literature, identifying relevant authors, planning or post-processing conference visits, and preparing paper submissions using a unified interface based on natural language inputs and responses. UKP-ATHENA enables new access...
2405.11431
Rohitash Chandra
Jingyang Wu, Xinyi Zhang, Fangyixuan Huang, Haochen Zhou, Rohtiash Chandra
Review of deep learning models for crypto price prediction: implementation and evaluation
null
null
null
null
cs.LG q-fin.ST stat.ML
http://creativecommons.org/licenses/by-nc-nd/4.0/
There has been much interest in accurate cryptocurrency price forecast models by investors and researchers. Deep Learning models are prominent machine learning techniques that have transformed various fields and have shown potential for finance and economics. Although various deep learning models have been explored f...
[ { "created": "Sun, 19 May 2024 03:15:27 GMT", "version": "v1" }, { "created": "Sun, 2 Jun 2024 07:20:29 GMT", "version": "v2" } ]
2024-06-04
[ [ "Wu", "Jingyang", "" ], [ "Zhang", "Xinyi", "" ], [ "Huang", "Fangyixuan", "" ], [ "Zhou", "Haochen", "" ], [ "Chandra", "Rohtiash", "" ] ]
There has been much interest in accurate cryptocurrency price forecast models by investors and researchers. Deep Learning models are prominent machine learning techniques that have transformed various fields and have shown potential for finance and economics. Although various deep learning models have been explored for...
1606.05688
Aleksandar Zlateski
Aleksandar Zlateski, Kisuk Lee and H. Sebastian Seung
ZNNi - Maximizing the Inference Throughput of 3D Convolutional Networks on Multi-Core CPUs and GPUs
null
null
null
null
cs.DC cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sliding window convolutional networks (ConvNets) have become a popular approach to computer vision problems such as image segmentation, and object detection and localization. Here we consider the problem of inference, the application of a previously trained ConvNet, with emphasis on 3D images. Our goal is to maximize...
[ { "created": "Fri, 17 Jun 2016 22:16:39 GMT", "version": "v1" } ]
2016-06-21
[ [ "Zlateski", "Aleksandar", "" ], [ "Lee", "Kisuk", "" ], [ "Seung", "H. Sebastian", "" ] ]
Sliding window convolutional networks (ConvNets) have become a popular approach to computer vision problems such as image segmentation, and object detection and localization. Here we consider the problem of inference, the application of a previously trained ConvNet, with emphasis on 3D images. Our goal is to maximize t...
0810.3626
Muthiah Annamalai
Muthiah Annamalai, Darshan Shrestha, Saibun Tjuatja
Experimental Study of Application Specific Source Coding for Wireless Sensor Networks
7 pages, 7 figures, 8 tables
null
null
null
cs.NI cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The energy bottleneck in Wireless Sensor Network(WSN) can be reduced by limiting communication overhead. Application specific source coding schemes for the sensor networks provide fewer bits to represent the same amount of information exploiting the redundancy present in the source model, network architecture and the...
[ { "created": "Mon, 20 Oct 2008 18:34:22 GMT", "version": "v1" }, { "created": "Tue, 21 Oct 2008 01:16:07 GMT", "version": "v2" } ]
2008-10-21
[ [ "Annamalai", "Muthiah", "" ], [ "Shrestha", "Darshan", "" ], [ "Tjuatja", "Saibun", "" ] ]
The energy bottleneck in Wireless Sensor Network(WSN) can be reduced by limiting communication overhead. Application specific source coding schemes for the sensor networks provide fewer bits to represent the same amount of information exploiting the redundancy present in the source model, network architecture and the p...
2106.05963
Manel Baradad Jurjo
Manel Baradad, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba
Learning to See by Looking at Noise
null
null
null
null
cs.CV cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Current vision systems are trained on huge datasets, and these datasets come with costs: curation is expensive, they inherit human biases, and there are concerns over privacy and usage rights. To counter these costs, interest has surged in learning from cheaper data sources, such as unlabeled images. In this paper we...
[ { "created": "Thu, 10 Jun 2021 17:56:46 GMT", "version": "v1" }, { "created": "Wed, 8 Dec 2021 16:42:14 GMT", "version": "v2" }, { "created": "Thu, 28 Apr 2022 23:37:06 GMT", "version": "v3" } ]
2022-05-02
[ [ "Baradad", "Manel", "" ], [ "Wulff", "Jonas", "" ], [ "Wang", "Tongzhou", "" ], [ "Isola", "Phillip", "" ], [ "Torralba", "Antonio", "" ] ]
Current vision systems are trained on huge datasets, and these datasets come with costs: curation is expensive, they inherit human biases, and there are concerns over privacy and usage rights. To counter these costs, interest has surged in learning from cheaper data sources, such as unlabeled images. In this paper we g...
2304.00686
Zihao Li
Zihao Li, Aixin Sun, Chenliang Li
DiffuRec: A Diffusion Model for Sequential Recommendation
null
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Mainstream solutions to Sequential Recommendation (SR) represent items with fixed vectors. These vectors have limited capability in capturing items' latent aspects and users' diverse preferences. As a new generative paradigm, Diffusion models have achieved excellent performance in areas like computer vision and natur...
[ { "created": "Mon, 3 Apr 2023 02:22:01 GMT", "version": "v1" }, { "created": "Tue, 4 Apr 2023 07:14:16 GMT", "version": "v2" }, { "created": "Sun, 9 Apr 2023 10:12:38 GMT", "version": "v3" }, { "created": "Mon, 30 Oct 2023 11:43:46 GMT", "version": "v4" } ]
2023-10-31
[ [ "Li", "Zihao", "" ], [ "Sun", "Aixin", "" ], [ "Li", "Chenliang", "" ] ]
Mainstream solutions to Sequential Recommendation (SR) represent items with fixed vectors. These vectors have limited capability in capturing items' latent aspects and users' diverse preferences. As a new generative paradigm, Diffusion models have achieved excellent performance in areas like computer vision and natural...
2408.01614
Jinwen Tang
Jinwen Tang and Yi Shang
Advancing Mental Health Pre-Screening: A New Custom GPT for Psychological Distress Assessment
null
null
null
null
cs.CY cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This study introduces 'Psycho Analyst', a custom GPT model based on OpenAI's GPT-4, optimized for pre-screening mental health disorders. Enhanced with DSM-5, PHQ-8, detailed data descriptions, and extensive training data, the model adeptly decodes nuanced linguistic indicators of mental health disorders. It utilizes ...
[ { "created": "Sat, 3 Aug 2024 00:38:30 GMT", "version": "v1" } ]
2024-08-06
[ [ "Tang", "Jinwen", "" ], [ "Shang", "Yi", "" ] ]
This study introduces 'Psycho Analyst', a custom GPT model based on OpenAI's GPT-4, optimized for pre-screening mental health disorders. Enhanced with DSM-5, PHQ-8, detailed data descriptions, and extensive training data, the model adeptly decodes nuanced linguistic indicators of mental health disorders. It utilizes a ...
2404.09359
Tal Hakim
Tal Hakim
Exploring Feedback Generation in Automated Skeletal Movement Assessment: A Comprehensive Overview
null
null
null
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
The application of machine-learning solutions to movement assessment from skeleton videos has attracted significant research attention in recent years. This advancement has made rehabilitation at home more accessible, utilizing movement assessment algorithms that can operate on affordable equipment for human pose det...
[ { "created": "Sun, 14 Apr 2024 21:14:47 GMT", "version": "v1" }, { "created": "Mon, 22 Apr 2024 10:52:32 GMT", "version": "v2" }, { "created": "Wed, 24 Apr 2024 15:07:04 GMT", "version": "v3" } ]
2024-04-25
[ [ "Hakim", "Tal", "" ] ]
The application of machine-learning solutions to movement assessment from skeleton videos has attracted significant research attention in recent years. This advancement has made rehabilitation at home more accessible, utilizing movement assessment algorithms that can operate on affordable equipment for human pose detec...
2306.14470
Chanjun Park
Dahyun Jung, Jaehyung Seo, Jaewook Lee, Chanjun Park, Heuiseok Lim
Knowledge Graph-Augmented Korean Generative Commonsense Reasoning
Accepted for Data-centric Machine Learning Research (DMLR) Workshop at ICML 2023
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Generative commonsense reasoning refers to the task of generating acceptable and logical assumptions about everyday situations based on commonsense understanding. By utilizing an existing dataset such as Korean CommonGen, language generation models can learn commonsense reasoning specific to the Korean language. Howe...
[ { "created": "Mon, 26 Jun 2023 07:23:47 GMT", "version": "v1" } ]
2023-06-27
[ [ "Jung", "Dahyun", "" ], [ "Seo", "Jaehyung", "" ], [ "Lee", "Jaewook", "" ], [ "Park", "Chanjun", "" ], [ "Lim", "Heuiseok", "" ] ]
Generative commonsense reasoning refers to the task of generating acceptable and logical assumptions about everyday situations based on commonsense understanding. By utilizing an existing dataset such as Korean CommonGen, language generation models can learn commonsense reasoning specific to the Korean language. Howeve...
2407.14643
Yuehua Ding
Yuehua Ding, Jean-Francois Dollinger, Vincent Vauchey, Mourad Zghal
Double-Layer Soft Data Fusion for Indoor Robot WiFi-Visual Localization
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a novel WiFi-Visual data fusion method for indoor robot (TIAGO++) localization. This method can use 10 WiFi samples and 4 low-resolution images ($58 \times 58$ in pixels) to localize a indoor robot with an average error distance about 1.32 meters. The experiment test is 3 months after the data col...
[ { "created": "Fri, 19 Jul 2024 19:40:15 GMT", "version": "v1" } ]
2024-07-23
[ [ "Ding", "Yuehua", "" ], [ "Dollinger", "Jean-Francois", "" ], [ "Vauchey", "Vincent", "" ], [ "Zghal", "Mourad", "" ] ]
This paper presents a novel WiFi-Visual data fusion method for indoor robot (TIAGO++) localization. This method can use 10 WiFi samples and 4 low-resolution images ($58 \times 58$ in pixels) to localize a indoor robot with an average error distance about 1.32 meters. The experiment test is 3 months after the data colle...
1705.07674
Ahmed Alaa
Ahmed M. Alaa, Jinsung Yoon, Scott Hu, and Mihaela van der Schaar
Individualized Risk Prognosis for Critical Care Patients: A Multi-task Gaussian Process Model
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We report the development and validation of a data-driven real-time risk score that provides timely assessments for the clinical acuity of ward patients based on their temporal lab tests and vital signs, which allows for timely intensive care unit (ICU) admissions. Unlike the existing risk scoring technologies, the p...
[ { "created": "Mon, 22 May 2017 11:27:58 GMT", "version": "v1" } ]
2017-05-23
[ [ "Alaa", "Ahmed M.", "" ], [ "Yoon", "Jinsung", "" ], [ "Hu", "Scott", "" ], [ "van der Schaar", "Mihaela", "" ] ]
We report the development and validation of a data-driven real-time risk score that provides timely assessments for the clinical acuity of ward patients based on their temporal lab tests and vital signs, which allows for timely intensive care unit (ICU) admissions. Unlike the existing risk scoring technologies, the pro...
1406.7735
Walter Lasecki
Haoqi Zhang, Andes Monroy-Hernandez, Aaron Shaw, Sean Munson, Liz Gerber, Benjamin Mako Hill, Peter Kinnaird, Shelly Farnham, and Patrick Minder
WeDo: Exploring Participatory, End-To-End Collective Action
null
null
null
ci-2014/95
cs.CY cs.HC cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many celebrate the Internet's ability to connect individuals and facilitate collective action toward a common goal. While numerous systems have been designed to support particular aspects of collective action, few systems support participatory, end-to-end collective action in which a crowd or community identifies opp...
[ { "created": "Mon, 30 Jun 2014 13:48:42 GMT", "version": "v1" } ]
2021-08-02
[ [ "Zhang", "Haoqi", "" ], [ "Monroy-Hernandez", "Andes", "" ], [ "Shaw", "Aaron", "" ], [ "Munson", "Sean", "" ], [ "Gerber", "Liz", "" ], [ "Hill", "Benjamin Mako", "" ], [ "Kinnaird", "Peter", "" ], [ ...
Many celebrate the Internet's ability to connect individuals and facilitate collective action toward a common goal. While numerous systems have been designed to support particular aspects of collective action, few systems support participatory, end-to-end collective action in which a crowd or community identifies oppor...
cs/0508075
Russell K. Standish
Russell K. Standish
Complexity of Networks
Accepted for Australian Conference on Artificial Life (ACAL05). To appear in Advances in Natural Computation (World Scientific)
in Recent Advances in Artificial Life, Abbass et al. (eds) (World Scientific: Singapore) p253 (2005).
null
null
cs.IT math.IT
null
Network or graph structures are ubiquitous in the study of complex systems. Often, we are interested in complexity trends of these system as it evolves under some dynamic. An example might be looking at the complexity of a food web as species enter an ecosystem via migration or speciation, and leave via extinction. ...
[ { "created": "Wed, 17 Aug 2005 00:51:41 GMT", "version": "v1" } ]
2007-07-16
[ [ "Standish", "Russell K.", "" ] ]
Network or graph structures are ubiquitous in the study of complex systems. Often, we are interested in complexity trends of these system as it evolves under some dynamic. An example might be looking at the complexity of a food web as species enter an ecosystem via migration or speciation, and leave via extinction. In ...
2305.12696
Ajay Patel
Ajay Patel, Delip Rao, Ansh Kothary, Kathleen McKeown, Chris Callison-Burch
Learning Interpretable Style Embeddings via Prompting LLMs
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Style representation learning builds content-independent representations of author style in text. Stylometry, the analysis of style in text, is often performed by expert forensic linguists and no large dataset of stylometric annotations exists for training. Current style representation learning uses neural methods to...
[ { "created": "Mon, 22 May 2023 04:07:54 GMT", "version": "v1" }, { "created": "Mon, 9 Oct 2023 19:20:32 GMT", "version": "v2" } ]
2023-10-11
[ [ "Patel", "Ajay", "" ], [ "Rao", "Delip", "" ], [ "Kothary", "Ansh", "" ], [ "McKeown", "Kathleen", "" ], [ "Callison-Burch", "Chris", "" ] ]
Style representation learning builds content-independent representations of author style in text. Stylometry, the analysis of style in text, is often performed by expert forensic linguists and no large dataset of stylometric annotations exists for training. Current style representation learning uses neural methods to d...
1102.0486
Sahana Bisalapur Sahana Bisalapur
Sahana S.Bisalapur
Design of an Efficient Neural Key Distribution Centre
11 pages,9 figures
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The goal of any cryptographic system is the exchange of information among the intended users without any leakage of information to others who may have unauthorized access to it. A common secret key could be created over a public channel accessible to any opponent. Neural networks can be used to generate common secret...
[ { "created": "Wed, 2 Feb 2011 16:49:01 GMT", "version": "v1" } ]
2011-02-03
[ [ "Bisalapur", "Sahana S.", "" ] ]
The goal of any cryptographic system is the exchange of information among the intended users without any leakage of information to others who may have unauthorized access to it. A common secret key could be created over a public channel accessible to any opponent. Neural networks can be used to generate common secret k...
2310.07668
S. AmirAli Gh. Ghahramani
Makan Kananian, Fatima Badiei, S. AmirAli Gh. Ghahramani
GRaMuFeN: Graph-based Multi-modal Fake News Detection in Social Media
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
The proliferation of social media platforms such as Twitter, Instagram, and Weibo has significantly enhanced the dissemination of false information. This phenomenon grants both individuals and governmental entities the ability to shape public opinions, highlighting the need for deploying effective detection methods. ...
[ { "created": "Wed, 11 Oct 2023 17:17:40 GMT", "version": "v1" } ]
2023-10-12
[ [ "Kananian", "Makan", "" ], [ "Badiei", "Fatima", "" ], [ "Ghahramani", "S. AmirAli Gh.", "" ] ]
The proliferation of social media platforms such as Twitter, Instagram, and Weibo has significantly enhanced the dissemination of false information. This phenomenon grants both individuals and governmental entities the ability to shape public opinions, highlighting the need for deploying effective detection methods. In...
1710.03702
Eike Neumann
Michal Kone\v{c}n\'y and Eike Neumann
Representations and evaluation strategies for feasibly approximable functions
33 pages, 4 figures
null
null
null
cs.CC cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A famous result due to Ko and Friedman (1982) asserts that the problems of integration and maximisation of a univariate real function are computationally hard in a well-defined sense. Yet, both functionals are routinely computed at great speed in practice. We aim to resolve this apparent paradox by studying classes o...
[ { "created": "Tue, 10 Oct 2017 16:17:52 GMT", "version": "v1" }, { "created": "Fri, 9 Nov 2018 16:17:12 GMT", "version": "v2" }, { "created": "Mon, 21 Oct 2019 21:01:19 GMT", "version": "v3" } ]
2019-10-23
[ [ "Konečný", "Michal", "" ], [ "Neumann", "Eike", "" ] ]
A famous result due to Ko and Friedman (1982) asserts that the problems of integration and maximisation of a univariate real function are computationally hard in a well-defined sense. Yet, both functionals are routinely computed at great speed in practice. We aim to resolve this apparent paradox by studying classes of ...
cs/0506039
Heechoon Lee
Weijun Zhu, Heechoon Lee, Daniel Liu and Michael P. Fitz
Antenna array geometry and coding performance
5 pages, 7 figures, ISIT 2005
null
null
null
cs.IT math.IT
null
This paper provides details about experiments in realistic, urban, and frequency flat channels with space-time coding that specifically examines the impact of the number of receive antennas and the design criteria for code selection on the performance. Also the performance characteristics are examined of the coded mo...
[ { "created": "Sat, 11 Jun 2005 02:38:26 GMT", "version": "v1" } ]
2007-07-13
[ [ "Zhu", "Weijun", "" ], [ "Lee", "Heechoon", "" ], [ "Liu", "Daniel", "" ], [ "Fitz", "Michael P.", "" ] ]
This paper provides details about experiments in realistic, urban, and frequency flat channels with space-time coding that specifically examines the impact of the number of receive antennas and the design criteria for code selection on the performance. Also the performance characteristics are examined of the coded modu...
2011.14922
Hanwen Miao
Hanwen Miao, Shengan Zhang, Carol Flannagan
Driver Behavior Extraction from Videos in Naturalistic Driving Datasets with 3D ConvNets
null
null
10.1007/s42421-022-00053-8
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Naturalistic driving data (NDD) is an important source of information to understand crash causation and human factors and to further develop crash avoidance countermeasures. Videos recorded while driving are often included in such datasets. While there is often a large amount of video data in NDD, only a small portio...
[ { "created": "Mon, 30 Nov 2020 15:53:15 GMT", "version": "v1" } ]
2022-06-30
[ [ "Miao", "Hanwen", "" ], [ "Zhang", "Shengan", "" ], [ "Flannagan", "Carol", "" ] ]
Naturalistic driving data (NDD) is an important source of information to understand crash causation and human factors and to further develop crash avoidance countermeasures. Videos recorded while driving are often included in such datasets. While there is often a large amount of video data in NDD, only a small portion ...
1910.14467
Mahdi Barzegar Khalilsarai
Mahdi Barzegar Khalilsarai, Tianyu Yang, Saeid Haghighatshoar, and Giuseppe Caire
Structured Channel Covariance Estimation from Limited Samples in Massive MIMO
27 pages, 9 figures
null
null
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Obtaining channel covariance knowledge is of great importance in various Multiple-Input Multiple-Output MIMO communication applications, including channel estimation and covariance-based user grouping. In a massive MIMO system, covariance estimation proves to be challenging due to the large number of antennas ($M\gg ...
[ { "created": "Thu, 31 Oct 2019 13:49:30 GMT", "version": "v1" } ]
2019-11-01
[ [ "Khalilsarai", "Mahdi Barzegar", "" ], [ "Yang", "Tianyu", "" ], [ "Haghighatshoar", "Saeid", "" ], [ "Caire", "Giuseppe", "" ] ]
Obtaining channel covariance knowledge is of great importance in various Multiple-Input Multiple-Output MIMO communication applications, including channel estimation and covariance-based user grouping. In a massive MIMO system, covariance estimation proves to be challenging due to the large number of antennas ($M\gg 1$...
1807.05761
Meredydd Williams
Meredydd Williams, Jason R. C. Nurse, Sadie Creese
"Privacy is the Boring Bit": User Perceptions and Behaviour in the Internet-of-Things
10 pages, 2 figures, Proceedings of the 15th International Conference on Privacy, Security and Trust (PST2017) (2017)
null
null
null
cs.CY cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In opinion polls, the public frequently claim to value their privacy. However, individuals often seem to overlook the principle, contributing to a disparity labelled the `Privacy Paradox'. The growth of the Internet-of-Things (IoT) is frequently claimed to place privacy at risk. However, the Paradox remains underexpl...
[ { "created": "Mon, 16 Jul 2018 09:54:15 GMT", "version": "v1" } ]
2018-07-17
[ [ "Williams", "Meredydd", "" ], [ "Nurse", "Jason R. C.", "" ], [ "Creese", "Sadie", "" ] ]
In opinion polls, the public frequently claim to value their privacy. However, individuals often seem to overlook the principle, contributing to a disparity labelled the `Privacy Paradox'. The growth of the Internet-of-Things (IoT) is frequently claimed to place privacy at risk. However, the Paradox remains underexplor...
1601.07473
Stephen Chestnut
Vladimir Braverman, Stephen R. Chestnut, David P. Woodruff, Lin F. Yang
Streaming Space Complexity of Nearly All Functions of One Variable on Frequency Vectors
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A central problem in the theory of algorithms for data streams is to determine which functions on a stream can be approximated in sublinear, and especially sub-polynomial or poly-logarithmic, space. Given a function $g$, we study the space complexity of approximating $\sum_{i=1}^n g(|f_i|)$, where $f\in\mathbb{Z}^n$ ...
[ { "created": "Wed, 27 Jan 2016 18:04:05 GMT", "version": "v1" } ]
2016-01-28
[ [ "Braverman", "Vladimir", "" ], [ "Chestnut", "Stephen R.", "" ], [ "Woodruff", "David P.", "" ], [ "Yang", "Lin F.", "" ] ]
A central problem in the theory of algorithms for data streams is to determine which functions on a stream can be approximated in sublinear, and especially sub-polynomial or poly-logarithmic, space. Given a function $g$, we study the space complexity of approximating $\sum_{i=1}^n g(|f_i|)$, where $f\in\mathbb{Z}^n$ is...
2005.10986
Jia-Wei Chen
Jia-Wei Chen, Rongfang Wang, Fan Ding, Bo Liu, Licheng Jiao, Jie Zhang
A Convolutional Neural Network with Parallel Multi-Scale Spatial Pooling to Detect Temporal Changes in SAR Images
null
Remote Sens. 2020, 12, 1619
null
null
cs.CV eess.IV
http://creativecommons.org/licenses/by/4.0/
In synthetic aperture radar (SAR) image change detection, it is quite challenging to exploit the changing information from the noisy difference image subject to the speckle. In this paper, we propose a multi-scale spatial pooling (MSSP) network to exploit the changed information from the noisy difference image. Being...
[ { "created": "Fri, 22 May 2020 03:37:30 GMT", "version": "v1" } ]
2020-05-25
[ [ "Chen", "Jia-Wei", "" ], [ "Wang", "Rongfang", "" ], [ "Ding", "Fan", "" ], [ "Liu", "Bo", "" ], [ "Jiao", "Licheng", "" ], [ "Zhang", "Jie", "" ] ]
In synthetic aperture radar (SAR) image change detection, it is quite challenging to exploit the changing information from the noisy difference image subject to the speckle. In this paper, we propose a multi-scale spatial pooling (MSSP) network to exploit the changed information from the noisy difference image. Being d...
2407.11004
Tzu-Heng Huang
Tzu-Heng Huang, Catherine Cao, Vaishnavi Bhargava, Frederic Sala
The ALCHEmist: Automated Labeling 500x CHEaper Than LLM Data Annotators
null
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Large pretrained models can be used as annotators, helping replace or augment crowdworkers and enabling distilling generalist models into smaller specialist models. Unfortunately, this comes at a cost: employing top-of-the-line models often requires paying thousands of dollars for API calls, while the resulting datas...
[ { "created": "Tue, 25 Jun 2024 17:58:26 GMT", "version": "v1" } ]
2024-07-17
[ [ "Huang", "Tzu-Heng", "" ], [ "Cao", "Catherine", "" ], [ "Bhargava", "Vaishnavi", "" ], [ "Sala", "Frederic", "" ] ]
Large pretrained models can be used as annotators, helping replace or augment crowdworkers and enabling distilling generalist models into smaller specialist models. Unfortunately, this comes at a cost: employing top-of-the-line models often requires paying thousands of dollars for API calls, while the resulting dataset...
2009.02678
Raja Appuswamy
Raja Appuswamy and Vincent Joguin
Universal Layout Emulation for Long-Term Database Archival
null
null
null
null
cs.DB cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Research on alternate media technologies, like film, synthetic DNA, and glass, for long-term data archival has received a lot of attention recently due to the media obsolescence issues faced by contemporary storage media like tape, Hard Disk Drives (HDD), and Solid State Disks (SSD). While researchers have developed ...
[ { "created": "Sun, 6 Sep 2020 09:06:13 GMT", "version": "v1" }, { "created": "Tue, 8 Sep 2020 10:09:25 GMT", "version": "v2" } ]
2020-09-09
[ [ "Appuswamy", "Raja", "" ], [ "Joguin", "Vincent", "" ] ]
Research on alternate media technologies, like film, synthetic DNA, and glass, for long-term data archival has received a lot of attention recently due to the media obsolescence issues faced by contemporary storage media like tape, Hard Disk Drives (HDD), and Solid State Disks (SSD). While researchers have developed no...
2306.17670
Ilyass Hammouamri
Ilyass Hammouamri, Ismail Khalfaoui-Hassani, Timoth\'ee Masquelier
Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings
null
ICLR 2024
null
null
cs.NE cs.AI cs.LG eess.AS
http://creativecommons.org/licenses/by/4.0/
Spiking Neural Networks (SNNs) are a promising research direction for building power-efficient information processing systems, especially for temporal tasks such as speech recognition. In SNNs, delays refer to the time needed for one spike to travel from one neuron to another. These delays matter because they influen...
[ { "created": "Fri, 30 Jun 2023 14:01:53 GMT", "version": "v1" }, { "created": "Thu, 31 Aug 2023 14:53:15 GMT", "version": "v2" }, { "created": "Fri, 1 Dec 2023 14:23:16 GMT", "version": "v3" } ]
2024-08-13
[ [ "Hammouamri", "Ilyass", "" ], [ "Khalfaoui-Hassani", "Ismail", "" ], [ "Masquelier", "Timothée", "" ] ]
Spiking Neural Networks (SNNs) are a promising research direction for building power-efficient information processing systems, especially for temporal tasks such as speech recognition. In SNNs, delays refer to the time needed for one spike to travel from one neuron to another. These delays matter because they influence...
1606.03268
Andr\'e Nichterlein
Christian Komusiewicz, Andr\'e Nichterlein, Rolf Niedermeier
Parameterized Algorithmics for Graph Modification Problems: On Interactions with Heuristics
Invited Paper at the 41st International Workshop on Graph-Theoretic Concepts in Computer Science (WG 15)
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In graph modification problems, one is given a graph G and the goal is to apply a minimum number of modification operations (such as edge deletions) to G such that the resulting graph fulfills a certain property. For example, the Cluster Deletion problem asks to delete as few edges as possible such that the resulting...
[ { "created": "Fri, 10 Jun 2016 10:50:28 GMT", "version": "v1" } ]
2016-06-13
[ [ "Komusiewicz", "Christian", "" ], [ "Nichterlein", "André", "" ], [ "Niedermeier", "Rolf", "" ] ]
In graph modification problems, one is given a graph G and the goal is to apply a minimum number of modification operations (such as edge deletions) to G such that the resulting graph fulfills a certain property. For example, the Cluster Deletion problem asks to delete as few edges as possible such that the resulting g...
2003.10026
Yan Fang
Ashwin Sanjay Lele, Yan Fang, Justin Ting, Arijit Raychowdhury
Learning to Walk: Spike Based Reinforcement Learning for Hexapod Robot Central Pattern Generation
5 pages, 7 figures, to be published in proceeding of IEEE AICAS
null
null
null
cs.NE cs.RO cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning to walk -- i.e., learning locomotion under performance and energy constraints continues to be a challenge in legged robotics. Methods such as stochastic gradient, deep reinforcement learning (RL) have been explored for bipeds, quadrupeds and hexapods. These techniques are computationally intensive and often ...
[ { "created": "Sun, 22 Mar 2020 23:45:32 GMT", "version": "v1" } ]
2020-03-24
[ [ "Lele", "Ashwin Sanjay", "" ], [ "Fang", "Yan", "" ], [ "Ting", "Justin", "" ], [ "Raychowdhury", "Arijit", "" ] ]
Learning to walk -- i.e., learning locomotion under performance and energy constraints continues to be a challenge in legged robotics. Methods such as stochastic gradient, deep reinforcement learning (RL) have been explored for bipeds, quadrupeds and hexapods. These techniques are computationally intensive and often pr...
cs/0611099
Travis Gagie
Travis Gagie
On the space complexity of one-pass compression
null
null
null
null
cs.IT math.IT
null
We study how much memory one-pass compression algorithms need to compete with the best multi-pass algorithms. We call a one-pass algorithm an (f (n, \ell))-footprint compressor if, given $n$, $\ell$ and an $n$-ary string $S$, it stores $S$ in ((\rule{0ex}{2ex} O (H_\ell (S)) + o (\log n)) |S| + O (n^{\ell + 1} \log n...
[ { "created": "Tue, 21 Nov 2006 02:06:31 GMT", "version": "v1" } ]
2007-07-16
[ [ "Gagie", "Travis", "" ] ]
We study how much memory one-pass compression algorithms need to compete with the best multi-pass algorithms. We call a one-pass algorithm an (f (n, \ell))-footprint compressor if, given $n$, $\ell$ and an $n$-ary string $S$, it stores $S$ in ((\rule{0ex}{2ex} O (H_\ell (S)) + o (\log n)) |S| + O (n^{\ell + 1} \log n))...
2208.14602
Yinhe Zheng Dr.
Yinhe Zheng
Continuous QA Learning with Structured Prompts
Duplicate of arXiv:2305.06555 (Please cite arXiv:2305.06555 since it is the camera ready version)
null
null
null
cs.CL cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
QA models with lifelong learning (LL) abilities are important for practical QA applications, and architecture-based LL methods are reported to be an effective implementation for these models. However, it is non-trivial to extend previous approaches to QA tasks since they either require access to task identities in th...
[ { "created": "Wed, 31 Aug 2022 02:38:16 GMT", "version": "v1" }, { "created": "Mon, 24 Oct 2022 08:39:02 GMT", "version": "v2" }, { "created": "Fri, 15 Mar 2024 01:53:58 GMT", "version": "v3" } ]
2024-03-18
[ [ "Zheng", "Yinhe", "" ] ]
QA models with lifelong learning (LL) abilities are important for practical QA applications, and architecture-based LL methods are reported to be an effective implementation for these models. However, it is non-trivial to extend previous approaches to QA tasks since they either require access to task identities in the ...
1906.11518
Longbin Lai
Longbin Lai, Zhu Qing, Zhengyi Yang, Xin Jin, Zhengmin Lai, Ran Wang, Kongzhang Hao, Xuemin Lin, Lu Qin, Wenjie Zhang, Ying Zhang, Zhengping Qian and Jingren Zhou
A Survey and Experimental Analysis of Distributed Subgraph Matching
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently there emerge many distributed algorithms that aim at solving subgraph matching at scale. Existing algorithm-level comparisons failed to provide a systematic view to the pros and cons of each algorithm mainly due to the intertwining of strategy and optimization. In this paper, we identify four strategies and ...
[ { "created": "Thu, 27 Jun 2019 09:38:46 GMT", "version": "v1" } ]
2019-06-28
[ [ "Lai", "Longbin", "" ], [ "Qing", "Zhu", "" ], [ "Yang", "Zhengyi", "" ], [ "Jin", "Xin", "" ], [ "Lai", "Zhengmin", "" ], [ "Wang", "Ran", "" ], [ "Hao", "Kongzhang", "" ], [ "Lin", "Xuemin", ...
Recently there emerge many distributed algorithms that aim at solving subgraph matching at scale. Existing algorithm-level comparisons failed to provide a systematic view to the pros and cons of each algorithm mainly due to the intertwining of strategy and optimization. In this paper, we identify four strategies and th...
2101.03263
Matthew Sotoudeh
Matthew Sotoudeh and Aditya V. Thakur
SyReNN: A Tool for Analyzing Deep Neural Networks
Accepted paper at TACAS 2021. Tool is available at https://github.com/95616ARG/SyReNN
null
null
null
cs.LG cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep Neural Networks (DNNs) are rapidly gaining popularity in a variety of important domains. Formally, DNNs are complicated vector-valued functions which come in a variety of sizes and applications. Unfortunately, modern DNNs have been shown to be vulnerable to a variety of attacks and buggy behavior. This has motiv...
[ { "created": "Sat, 9 Jan 2021 00:27:23 GMT", "version": "v1" } ]
2021-01-12
[ [ "Sotoudeh", "Matthew", "" ], [ "Thakur", "Aditya V.", "" ] ]
Deep Neural Networks (DNNs) are rapidly gaining popularity in a variety of important domains. Formally, DNNs are complicated vector-valued functions which come in a variety of sizes and applications. Unfortunately, modern DNNs have been shown to be vulnerable to a variety of attacks and buggy behavior. This has motivat...
2205.09249
Hyounghun Kim
Hyounghun Kim, Aishwarya Padmakumar, Di Jin, Mohit Bansal, Dilek Hakkani-Tur
On the Limits of Evaluating Embodied Agent Model Generalization Using Validation Sets
ACL 2022 Insights Workshop (6 pages)
null
null
null
cs.CL cs.AI cs.CV cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Natural language guided embodied task completion is a challenging problem since it requires understanding natural language instructions, aligning them with egocentric visual observations, and choosing appropriate actions to execute in the environment to produce desired changes. We experiment with augmenting a transfo...
[ { "created": "Wed, 18 May 2022 23:52:21 GMT", "version": "v1" } ]
2022-05-20
[ [ "Kim", "Hyounghun", "" ], [ "Padmakumar", "Aishwarya", "" ], [ "Jin", "Di", "" ], [ "Bansal", "Mohit", "" ], [ "Hakkani-Tur", "Dilek", "" ] ]
Natural language guided embodied task completion is a challenging problem since it requires understanding natural language instructions, aligning them with egocentric visual observations, and choosing appropriate actions to execute in the environment to produce desired changes. We experiment with augmenting a transform...
2004.04077
Andrea Cossu
Andrea Cossu, Antonio Carta, Davide Bacciu
Continual Learning with Gated Incremental Memories for sequential data processing
Accepted as a conference paper at 2020 International Joint Conference on Neural Networks (IJCNN 2020). Part of 2020 IEEE World Congress on Computational Intelligence (IEEE WCCI 2020)
null
10.1109/IJCNN48605.2020.9207550
null
cs.LG cs.NE stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The ability to learn in dynamic, nonstationary environments without forgetting previous knowledge, also known as Continual Learning (CL), is a key enabler for scalable and trustworthy deployments of adaptive solutions. While the importance of continual learning is largely acknowledged in machine vision and reinforcem...
[ { "created": "Wed, 8 Apr 2020 16:00:20 GMT", "version": "v1" } ]
2021-03-25
[ [ "Cossu", "Andrea", "" ], [ "Carta", "Antonio", "" ], [ "Bacciu", "Davide", "" ] ]
The ability to learn in dynamic, nonstationary environments without forgetting previous knowledge, also known as Continual Learning (CL), is a key enabler for scalable and trustworthy deployments of adaptive solutions. While the importance of continual learning is largely acknowledged in machine vision and reinforcemen...
2109.04029
Triet Le
Xuanyu Duan, Mengmeng Ge, Triet H. M. Le, Faheem Ullah, Shang Gao, Xuequan Lu, M. Ali Babar
Automated Security Assessment for the Internet of Things
Accepted for publication at the 26th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC 2021)
null
null
null
cs.CR cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Internet of Things (IoT) based applications face an increasing number of potential security risks, which need to be systematically assessed and addressed. Expert-based manual assessment of IoT security is a predominant approach, which is usually inefficient. To address this problem, we propose an automated security a...
[ { "created": "Thu, 9 Sep 2021 04:42:24 GMT", "version": "v1" } ]
2021-09-10
[ [ "Duan", "Xuanyu", "" ], [ "Ge", "Mengmeng", "" ], [ "Le", "Triet H. M.", "" ], [ "Ullah", "Faheem", "" ], [ "Gao", "Shang", "" ], [ "Lu", "Xuequan", "" ], [ "Babar", "M. Ali", "" ] ]
Internet of Things (IoT) based applications face an increasing number of potential security risks, which need to be systematically assessed and addressed. Expert-based manual assessment of IoT security is a predominant approach, which is usually inefficient. To address this problem, we propose an automated security ass...
1807.01659
Guang-Yuan Hao
Guang-Yuan Hao, Hong-Xing Yu, Wei-Shi Zheng
MIXGAN: Learning Concepts from Different Domains for Mixture Generation
Accepted by IJCAI-ECAI 2018, the 27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we present an interesting attempt on mixture generation: absorbing different image concepts (e.g., content and style) from different domains and thus generating a new domain with learned concepts. In particular, we propose a mixture generative adversarial network (MIXGAN). MIXGAN learns concepts of cont...
[ { "created": "Wed, 4 Jul 2018 16:20:47 GMT", "version": "v1" } ]
2018-07-05
[ [ "Hao", "Guang-Yuan", "" ], [ "Yu", "Hong-Xing", "" ], [ "Zheng", "Wei-Shi", "" ] ]
In this work, we present an interesting attempt on mixture generation: absorbing different image concepts (e.g., content and style) from different domains and thus generating a new domain with learned concepts. In particular, we propose a mixture generative adversarial network (MIXGAN). MIXGAN learns concepts of conten...
2407.05216
Cheng-Han Chiang
Cheng-Han Chiang, Wei-Chih Chen, Chun-Yi Kuan, Chienchou Yang, Hung-yi Lee
Large Language Model as an Assignment Evaluator: Insights, Feedback, and Challenges in a 1000+ Student Course
An empirical report of our course: Introduction to Generative AI 2024 Spring (https://speech.ee.ntu.edu.tw/~hylee/genai/2024-spring.php)
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Using large language models (LLMs) for automatic evaluation has become an important evaluation method in NLP research. However, it is unclear whether these LLM-based evaluators can be applied in real-world classrooms to assess student assignments. This empirical report shares how we use GPT-4 as an automatic assignme...
[ { "created": "Sun, 7 Jul 2024 00:17:24 GMT", "version": "v1" } ]
2024-07-09
[ [ "Chiang", "Cheng-Han", "" ], [ "Chen", "Wei-Chih", "" ], [ "Kuan", "Chun-Yi", "" ], [ "Yang", "Chienchou", "" ], [ "Lee", "Hung-yi", "" ] ]
Using large language models (LLMs) for automatic evaluation has become an important evaluation method in NLP research. However, it is unclear whether these LLM-based evaluators can be applied in real-world classrooms to assess student assignments. This empirical report shares how we use GPT-4 as an automatic assignment...
2210.11050
Zeyu Cao
Zeyu Cao, Zhipeng Liang, Shu Zhang, Hangyu Li, Ouyang Wen, Yu Rong, Peilin Zhao, Bingzhe Wu
Vertical Federated Linear Contextual Bandits
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we investigate a novel problem of building contextual bandits in the vertical federated setting, i.e., contextual information is vertically distributed over different departments. This problem remains largely unexplored in the research community. To this end, we carefully design a customized encryption...
[ { "created": "Thu, 20 Oct 2022 06:59:42 GMT", "version": "v1" } ]
2022-10-21
[ [ "Cao", "Zeyu", "" ], [ "Liang", "Zhipeng", "" ], [ "Zhang", "Shu", "" ], [ "Li", "Hangyu", "" ], [ "Wen", "Ouyang", "" ], [ "Rong", "Yu", "" ], [ "Zhao", "Peilin", "" ], [ "Wu", "Bingzhe", "...
In this paper, we investigate a novel problem of building contextual bandits in the vertical federated setting, i.e., contextual information is vertically distributed over different departments. This problem remains largely unexplored in the research community. To this end, we carefully design a customized encryption s...
1805.00329
Michele Alberti
Michele Alberti, Vinaychandran Pondenkandath, Marcel W\"ursch, Rolf Ingold, Marcus Liwicki
DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments
Submitted at the 16th International Conference on Frontiers in Handwriting Recognition (ICFHR), 6 pages, 6 Figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce DeepDIVA: an infrastructure designed to enable quick and intuitive setup of reproducible experiments with a large range of useful analysis functionality. Reproducing scientific results can be a frustrating experience, not only in document image analysis but in machine learning in general. Using DeepDIVA ...
[ { "created": "Mon, 23 Apr 2018 20:00:42 GMT", "version": "v1" } ]
2018-05-02
[ [ "Alberti", "Michele", "" ], [ "Pondenkandath", "Vinaychandran", "" ], [ "Würsch", "Marcel", "" ], [ "Ingold", "Rolf", "" ], [ "Liwicki", "Marcus", "" ] ]
We introduce DeepDIVA: an infrastructure designed to enable quick and intuitive setup of reproducible experiments with a large range of useful analysis functionality. Reproducing scientific results can be a frustrating experience, not only in document image analysis but in machine learning in general. Using DeepDIVA a ...
1503.06680
Kieran Larkin
Kieran Gerard Larkin
Structural Similarity Index SSIMplified: Is there really a simpler concept at the heart of image quality measurement?
Updated abstract and references. 4 pages total, main analysis 2 pages, notes and minimal references 1 page
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Structural Similarity Index (SSIM) is generally considered to be a milestone in the recent history of Image Quality Assessment (IQA). Alas, SSIM's accepted development from the product of three heuristic factors continues to obscure it's real underlying simplicity. Starting instead from a symmetric-antisymmetric ...
[ { "created": "Thu, 29 Jan 2015 21:27:49 GMT", "version": "v1" }, { "created": "Mon, 25 May 2015 01:53:07 GMT", "version": "v2" } ]
2015-05-26
[ [ "Larkin", "Kieran Gerard", "" ] ]
The Structural Similarity Index (SSIM) is generally considered to be a milestone in the recent history of Image Quality Assessment (IQA). Alas, SSIM's accepted development from the product of three heuristic factors continues to obscure it's real underlying simplicity. Starting instead from a symmetric-antisymmetric re...
1907.01602
Gustavo Pinto
Wagner Felidr\'e and Leonardo Furtado and Daniel da Costa and Bruno Cartaxo and Gustavo Pinto
Continuous Integration Theater
to appear at ESEM 2019
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
Background: Continuous Integration (CI) systems are now the bedrock of several software development practices. Several tools such as TravisCI, CircleCI, and Hudson, that implement CI practices, are commonly adopted by software engineers. However, the way that software engineers use these tools could lead to what we c...
[ { "created": "Tue, 2 Jul 2019 19:47:55 GMT", "version": "v1" } ]
2019-07-04
[ [ "Felidré", "Wagner", "" ], [ "Furtado", "Leonardo", "" ], [ "da Costa", "Daniel", "" ], [ "Cartaxo", "Bruno", "" ], [ "Pinto", "Gustavo", "" ] ]
Background: Continuous Integration (CI) systems are now the bedrock of several software development practices. Several tools such as TravisCI, CircleCI, and Hudson, that implement CI practices, are commonly adopted by software engineers. However, the way that software engineers use these tools could lead to what we cal...
2202.07836
Eugene Wu
Eugene Wu
View Composition Algebra for Ad Hoc Comparison
null
null
null
null
cs.HC cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Comparison is a core task in visual analysis. Although there are numerous guidelines to help users design effective visualizations to aid known comparison tasks, there are few techniques available when users want to make ad hoc comparisons between marks, trends, or charts during data exploration and visual analysis. ...
[ { "created": "Wed, 16 Feb 2022 03:01:26 GMT", "version": "v1" } ]
2022-02-17
[ [ "Wu", "Eugene", "" ] ]
Comparison is a core task in visual analysis. Although there are numerous guidelines to help users design effective visualizations to aid known comparison tasks, there are few techniques available when users want to make ad hoc comparisons between marks, trends, or charts during data exploration and visual analysis. Fo...
1710.06831
Pooyan Fazli
Utkarsh Patel, Emre Hatay, Mike D'Arcy, Ghazal Zand, and Pooyan Fazli
Setting Up the Beam for Human-Centered Service Tasks
10 pages
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce the Beam, a collaborative autonomous mobile service robot, based on SuitableTech's Beam telepresence system. We present a set of enhancements to the telepresence system, including autonomy, human awareness, increased computation and sensing capabilities, and integration with the popular Robot Operating S...
[ { "created": "Wed, 18 Oct 2017 17:17:04 GMT", "version": "v1" } ]
2017-10-19
[ [ "Patel", "Utkarsh", "" ], [ "Hatay", "Emre", "" ], [ "D'Arcy", "Mike", "" ], [ "Zand", "Ghazal", "" ], [ "Fazli", "Pooyan", "" ] ]
We introduce the Beam, a collaborative autonomous mobile service robot, based on SuitableTech's Beam telepresence system. We present a set of enhancements to the telepresence system, including autonomy, human awareness, increased computation and sensing capabilities, and integration with the popular Robot Operating Sys...
1910.04006
Eben Holderness
Elena Alvarez-Mellado, Eben Holderness, Nicholas Miller, Fyonn Dhang, Philip Cawkwell, Kirsten Bolton, James Pustejovsky, Mei-Hua Hall
Assessing the Efficacy of Clinical Sentiment Analysis and Topic Extraction in Psychiatric Readmission Risk Prediction
LOUHI @ EMNLP 2019
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Predicting which patients are more likely to be readmitted to a hospital within 30 days after discharge is a valuable piece of information in clinical decision-making. Building a successful readmission risk classifier based on the content of Electronic Health Records (EHRs) has proved, however, to be a challenging ta...
[ { "created": "Wed, 9 Oct 2019 14:10:47 GMT", "version": "v1" } ]
2019-10-10
[ [ "Alvarez-Mellado", "Elena", "" ], [ "Holderness", "Eben", "" ], [ "Miller", "Nicholas", "" ], [ "Dhang", "Fyonn", "" ], [ "Cawkwell", "Philip", "" ], [ "Bolton", "Kirsten", "" ], [ "Pustejovsky", "James", "...
Predicting which patients are more likely to be readmitted to a hospital within 30 days after discharge is a valuable piece of information in clinical decision-making. Building a successful readmission risk classifier based on the content of Electronic Health Records (EHRs) has proved, however, to be a challenging task...
1604.08625
Victor Hugo Ba\~nos Gonzalez
Victor Ba\~nos-Gonzalez, M. Shahwaiz Afaqui, Elena Lopez-Aguilera, Eduard Garcia-Villegas
Throughput and range characterization of IEEE 802.11ah
7 pages, 6 figures, 5 tables
null
null
null
cs.NI
http://creativecommons.org/licenses/by-nc-sa/4.0/
The most essential part of Internet of Things (IoT) infrastructure is the wireless communication system that acts as a bridge for the delivery of data and control messages. However, the existing wireless technologies lack the ability to support a huge amount of data exchange from many battery driven devices spread ov...
[ { "created": "Thu, 28 Apr 2016 21:42:06 GMT", "version": "v1" } ]
2016-05-02
[ [ "Baños-Gonzalez", "Victor", "" ], [ "Afaqui", "M. Shahwaiz", "" ], [ "Lopez-Aguilera", "Elena", "" ], [ "Garcia-Villegas", "Eduard", "" ] ]
The most essential part of Internet of Things (IoT) infrastructure is the wireless communication system that acts as a bridge for the delivery of data and control messages. However, the existing wireless technologies lack the ability to support a huge amount of data exchange from many battery driven devices spread over...
2208.09822
Jianyu Yao
Jianyu Yao, Boqian Shi, Chunyang Xiang, Haipeng Jia, Chendi Li, Hang Cao, Yunquan Zhang
IAAT: A Input-Aware Adaptive Tuning framework for Small GEMM
null
null
null
null
cs.DC cs.PF
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
GEMM with the small size of input matrices is becoming widely used in many fields like HPC and machine learning. Although many famous BLAS libraries already supported small GEMM, they cannot achieve near-optimal performance. This is because the costs of pack operations are high and frequent boundary processing cannot...
[ { "created": "Sun, 21 Aug 2022 06:54:59 GMT", "version": "v1" } ]
2022-08-23
[ [ "Yao", "Jianyu", "" ], [ "Shi", "Boqian", "" ], [ "Xiang", "Chunyang", "" ], [ "Jia", "Haipeng", "" ], [ "Li", "Chendi", "" ], [ "Cao", "Hang", "" ], [ "Zhang", "Yunquan", "" ] ]
GEMM with the small size of input matrices is becoming widely used in many fields like HPC and machine learning. Although many famous BLAS libraries already supported small GEMM, they cannot achieve near-optimal performance. This is because the costs of pack operations are high and frequent boundary processing cannot b...
1512.08314
Lan Wang
Olivier Brun, Lan Wang and Erol Gelenbe
Data Driven SMART Intercontinental Overlay Networks
9 pages
null
null
null
cs.NI cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper addresses the use of Big Data and machine learning based analytics to the real-time management of Internet scale Quality-of-Service Route Optimisation with the help of an overlay network. Based on the collection of large amounts of data sampled each $2$ minutes over a large number of source-destinations pa...
[ { "created": "Mon, 28 Dec 2015 03:43:04 GMT", "version": "v1" } ]
2015-12-29
[ [ "Brun", "Olivier", "" ], [ "Wang", "Lan", "" ], [ "Gelenbe", "Erol", "" ] ]
This paper addresses the use of Big Data and machine learning based analytics to the real-time management of Internet scale Quality-of-Service Route Optimisation with the help of an overlay network. Based on the collection of large amounts of data sampled each $2$ minutes over a large number of source-destinations pair...
1707.01068
Alexander Peysakhovich
Adam Lerer and Alexander Peysakhovich
Maintaining cooperation in complex social dilemmas using deep reinforcement learning
null
null
null
null
cs.AI cs.GT cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Social dilemmas are situations where individuals face a temptation to increase their payoffs at a cost to total welfare. Building artificially intelligent agents that achieve good outcomes in these situations is important because many real world interactions include a tension between selfish interests and the welfare...
[ { "created": "Tue, 4 Jul 2017 17:02:05 GMT", "version": "v1" }, { "created": "Mon, 31 Jul 2017 22:40:15 GMT", "version": "v2" }, { "created": "Sat, 28 Oct 2017 15:23:38 GMT", "version": "v3" }, { "created": "Fri, 2 Mar 2018 14:39:55 GMT", "version": "v4" } ]
2018-03-05
[ [ "Lerer", "Adam", "" ], [ "Peysakhovich", "Alexander", "" ] ]
Social dilemmas are situations where individuals face a temptation to increase their payoffs at a cost to total welfare. Building artificially intelligent agents that achieve good outcomes in these situations is important because many real world interactions include a tension between selfish interests and the welfare o...
2003.07240
Wei Wang Dr.
Shengkai Zhang, Wei Wang, Tao Jiang
WiFi-Inertial Indoor Pose Estimation for Micro Aerial Vehicles
To appear in IEEE Transactions on Industrial Electronics
null
null
null
cs.RO eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents an indoor pose estimation system for micro aerial vehicles (MAVs) with a single WiFi access point. Conventional approaches based on computer vision are limited by illumination conditions and environmental texture. Our system is free of visual limitations and instantly deployable, working upon exis...
[ { "created": "Mon, 16 Mar 2020 14:05:18 GMT", "version": "v1" } ]
2020-03-17
[ [ "Zhang", "Shengkai", "" ], [ "Wang", "Wei", "" ], [ "Jiang", "Tao", "" ] ]
This paper presents an indoor pose estimation system for micro aerial vehicles (MAVs) with a single WiFi access point. Conventional approaches based on computer vision are limited by illumination conditions and environmental texture. Our system is free of visual limitations and instantly deployable, working upon existi...
2407.08134
Amir Noorizadegan Ph.D.
A. Noorizadegan, Y.C. Hon, D.L. Young, C.S. Chen
Highway Networks for Improved Surface Reconstruction: The Role of Residuals and Weight Updates
null
null
null
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Surface reconstruction from point clouds is a fundamental challenge in computer graphics and medical imaging. In this paper, we explore the application of advanced neural network architectures for the accurate and efficient reconstruction of surfaces from data points. We introduce a novel variant of the Highway netwo...
[ { "created": "Thu, 11 Jul 2024 02:15:21 GMT", "version": "v1" } ]
2024-07-12
[ [ "Noorizadegan", "A.", "" ], [ "Hon", "Y. C.", "" ], [ "Young", "D. L.", "" ], [ "Chen", "C. S.", "" ] ]
Surface reconstruction from point clouds is a fundamental challenge in computer graphics and medical imaging. In this paper, we explore the application of advanced neural network architectures for the accurate and efficient reconstruction of surfaces from data points. We introduce a novel variant of the Highway network...
2309.00616
Zhening Huang
Zhening Huang, Xiaoyang Wu, Xi Chen, Hengshuang Zhao, Lei Zhu, Joan Lasenby
OpenIns3D: Snap and Lookup for 3D Open-vocabulary Instance Segmentation
ECCV 2024. Project page: https://zheninghuang.github.io/OpenIns3D/
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work, we introduce OpenIns3D, a new 3D-input-only framework for 3D open-vocabulary scene understanding. The OpenIns3D framework employs a "Mask-Snap-Lookup" scheme. The "Mask" module learns class-agnostic mask proposals in 3D point clouds, the "Snap" module generates synthetic scene-level images at multiple s...
[ { "created": "Fri, 1 Sep 2023 17:59:56 GMT", "version": "v1" }, { "created": "Mon, 4 Sep 2023 17:59:54 GMT", "version": "v2" }, { "created": "Thu, 5 Oct 2023 15:15:58 GMT", "version": "v3" }, { "created": "Wed, 17 Jul 2024 15:05:38 GMT", "version": "v4" }, { "crea...
2024-08-13
[ [ "Huang", "Zhening", "" ], [ "Wu", "Xiaoyang", "" ], [ "Chen", "Xi", "" ], [ "Zhao", "Hengshuang", "" ], [ "Zhu", "Lei", "" ], [ "Lasenby", "Joan", "" ] ]
In this work, we introduce OpenIns3D, a new 3D-input-only framework for 3D open-vocabulary scene understanding. The OpenIns3D framework employs a "Mask-Snap-Lookup" scheme. The "Mask" module learns class-agnostic mask proposals in 3D point clouds, the "Snap" module generates synthetic scene-level images at multiple sca...
1904.07793
Xiaosen Wang
Xiaosen Wang, Kun He, Chuanbiao Song, Liwei Wang, John E. Hopcroft
AT-GAN: An Adversarial Generator Model for Non-constrained Adversarial Examples
15 pages, 6 figures
null
null
null
cs.CV cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite the rapid development of adversarial machine learning, most adversarial attack and defense researches mainly focus on the perturbation-based adversarial examples, which is constrained by the input images. In comparison with existing works, we propose non-constrained adversarial examples, which are generated e...
[ { "created": "Tue, 16 Apr 2019 16:26:19 GMT", "version": "v1" }, { "created": "Wed, 17 Apr 2019 02:19:07 GMT", "version": "v2" }, { "created": "Tue, 21 May 2019 15:26:32 GMT", "version": "v3" }, { "created": "Fri, 7 Feb 2020 18:11:58 GMT", "version": "v4" } ]
2020-02-10
[ [ "Wang", "Xiaosen", "" ], [ "He", "Kun", "" ], [ "Song", "Chuanbiao", "" ], [ "Wang", "Liwei", "" ], [ "Hopcroft", "John E.", "" ] ]
Despite the rapid development of adversarial machine learning, most adversarial attack and defense researches mainly focus on the perturbation-based adversarial examples, which is constrained by the input images. In comparison with existing works, we propose non-constrained adversarial examples, which are generated ent...
2201.08378
Ruslan Nikolaev
Ruslan Nikolaev, Hassan Nadeem, Cathlyn Stone, Binoy Ravindran
Adelie: Continuous Address Space Layout Re-randomization for Linux Drivers
27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '22), February 28 - March 4, 2022, Lausanne, Switzerland
null
10.1145/3503222.3507779
null
cs.OS cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While address space layout randomization (ASLR) has been extensively studied for user-space programs, the corresponding OS kernel's KASLR support remains very limited, making the kernel vulnerable to just-in-time (JIT) return-oriented programming (ROP) attacks. Furthermore, commodity OSs such as Linux restrict their ...
[ { "created": "Thu, 20 Jan 2022 18:58:44 GMT", "version": "v1" } ]
2022-01-21
[ [ "Nikolaev", "Ruslan", "" ], [ "Nadeem", "Hassan", "" ], [ "Stone", "Cathlyn", "" ], [ "Ravindran", "Binoy", "" ] ]
While address space layout randomization (ASLR) has been extensively studied for user-space programs, the corresponding OS kernel's KASLR support remains very limited, making the kernel vulnerable to just-in-time (JIT) return-oriented programming (ROP) attacks. Furthermore, commodity OSs such as Linux restrict their KA...
1901.02873
Omur Ozel
Peng Zou and Omur Ozel and Suresh Subramaniam
Waiting before Serving: A Companion to Packet Management in Status Update Systems
null
null
null
null
cs.IT cs.NI math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we explore the potential of server waiting before packet transmission in improving the Age of Information (AoI) in status update systems. We consider a non-preemptive queue with Poisson arrivals and independent general service distribution and we incorporate waiting before serving in two packet managem...
[ { "created": "Wed, 9 Jan 2019 18:46:44 GMT", "version": "v1" }, { "created": "Fri, 1 Feb 2019 14:54:46 GMT", "version": "v2" }, { "created": "Tue, 5 Mar 2019 16:31:08 GMT", "version": "v3" }, { "created": "Mon, 22 Apr 2019 14:32:30 GMT", "version": "v4" } ]
2019-04-23
[ [ "Zou", "Peng", "" ], [ "Ozel", "Omur", "" ], [ "Subramaniam", "Suresh", "" ] ]
In this paper, we explore the potential of server waiting before packet transmission in improving the Age of Information (AoI) in status update systems. We consider a non-preemptive queue with Poisson arrivals and independent general service distribution and we incorporate waiting before serving in two packet managemen...
2207.10180
Feng Liu
Feng Liu, Minchul Kim, Anil Jain, and Xiaoming Liu
Controllable and Guided Face Synthesis for Unconstrained Face Recognition
to be published in ECCV 2022
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Although significant advances have been made in face recognition (FR), FR in unconstrained environments remains challenging due to the domain gap between the semi-constrained training datasets and unconstrained testing scenarios. To address this problem, we propose a controllable face synthesis model (CFSM) that can ...
[ { "created": "Wed, 20 Jul 2022 20:13:29 GMT", "version": "v1" } ]
2022-07-22
[ [ "Liu", "Feng", "" ], [ "Kim", "Minchul", "" ], [ "Jain", "Anil", "" ], [ "Liu", "Xiaoming", "" ] ]
Although significant advances have been made in face recognition (FR), FR in unconstrained environments remains challenging due to the domain gap between the semi-constrained training datasets and unconstrained testing scenarios. To address this problem, we propose a controllable face synthesis model (CFSM) that can mi...
1903.03408
Marc Maliar
Marc Maliar
How Machine (Deep) Learning Helps Us Understand Human Learning: the Value of Big Ideas
17 pages
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
I use simulation of two multilayer neural networks to gain intuition into the determinants of human learning. The first network, the teacher, is trained to achieve a high accuracy in handwritten digit recognition. The second network, the student, learns to reproduce the output of the first network. I show that learni...
[ { "created": "Sat, 16 Feb 2019 16:06:42 GMT", "version": "v1" }, { "created": "Wed, 20 Mar 2019 20:55:49 GMT", "version": "v2" } ]
2019-03-22
[ [ "Maliar", "Marc", "" ] ]
I use simulation of two multilayer neural networks to gain intuition into the determinants of human learning. The first network, the teacher, is trained to achieve a high accuracy in handwritten digit recognition. The second network, the student, learns to reproduce the output of the first network. I show that learning...
2201.03331
Christian Ponte-Fern\'andez
Christian Ponte-Fern\'andez (1), Jorge Gonz\'alez-Dom\'inguez (1) and Mar\'ia J. Mart\'in (1) ((1) Universidade da Coru\~na, CITIC, Computer Architecture Group, A Coru\~na, Spain)
Fiuncho: a program for any-order epistasis detection in CPU clusters
Submitted to The Journal of Supercomputing. Source code available at https://github.com/UDC-GAC/fiuncho
null
null
null
cs.DC cs.CE
http://creativecommons.org/licenses/by-nc-nd/4.0/
Epistasis can be defined as the statistical interaction of genes during the expression of a phenotype. It is believed that it plays a fundamental role in gene expression, as individual genetic variants have reported a very small increase in disease risk in previous Genome-Wide Association Studies. The most successful...
[ { "created": "Mon, 10 Jan 2022 13:19:31 GMT", "version": "v1" }, { "created": "Mon, 7 Mar 2022 16:22:12 GMT", "version": "v2" }, { "created": "Tue, 8 Mar 2022 17:07:11 GMT", "version": "v3" } ]
2022-03-09
[ [ "Ponte-Fernández", "Christian", "" ], [ "González-Domínguez", "Jorge", "" ], [ "Martín", "María J.", "" ] ]
Epistasis can be defined as the statistical interaction of genes during the expression of a phenotype. It is believed that it plays a fundamental role in gene expression, as individual genetic variants have reported a very small increase in disease risk in previous Genome-Wide Association Studies. The most successful a...
2105.11527
Qi Qian
Qi Qian, Yuanhong Xu, Juhua Hu, Hao Li, Rong Jin
Unsupervised Visual Representation Learning by Online Constrained K-Means
accepted by CVPR'22
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cluster discrimination is an effective pretext task for unsupervised representation learning, which often consists of two phases: clustering and discrimination. Clustering is to assign each instance a pseudo label that will be used to learn representations in discrimination. The main challenge resides in clustering s...
[ { "created": "Mon, 24 May 2021 20:38:32 GMT", "version": "v1" }, { "created": "Mon, 27 Dec 2021 18:37:45 GMT", "version": "v2" }, { "created": "Mon, 28 Mar 2022 20:15:05 GMT", "version": "v3" } ]
2022-03-30
[ [ "Qian", "Qi", "" ], [ "Xu", "Yuanhong", "" ], [ "Hu", "Juhua", "" ], [ "Li", "Hao", "" ], [ "Jin", "Rong", "" ] ]
Cluster discrimination is an effective pretext task for unsupervised representation learning, which often consists of two phases: clustering and discrimination. Clustering is to assign each instance a pseudo label that will be used to learn representations in discrimination. The main challenge resides in clustering sin...
1706.09297
Swapnil Dhamal
Swapnil Dhamal, Walid Ben-Ameur, Tijani Chahed, and Eitan Altman
Optimal Investment Strategies for Competing Camps in a Social Network: A Broad Framework
The original version of this paper is accepted for publication in IEEE Transactions on Network Science and Engineering. The copyright for this article belongs to IEEE
null
10.1109/TNSE.2018.2864575
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of optimally investing in nodes of a social network in a competitive setting, wherein two camps aim to drive the average opinion of the population in their own favor. Using a well-established model of opinion dynamics, we formulate the problem as a zero-sum game with its players being the two cam...
[ { "created": "Wed, 28 Jun 2017 14:02:41 GMT", "version": "v1" }, { "created": "Fri, 5 Jan 2018 14:46:20 GMT", "version": "v2" }, { "created": "Fri, 16 Feb 2018 18:19:59 GMT", "version": "v3" }, { "created": "Sun, 24 Jun 2018 09:22:12 GMT", "version": "v4" }, { "cr...
2018-08-13
[ [ "Dhamal", "Swapnil", "" ], [ "Ben-Ameur", "Walid", "" ], [ "Chahed", "Tijani", "" ], [ "Altman", "Eitan", "" ] ]
We study the problem of optimally investing in nodes of a social network in a competitive setting, wherein two camps aim to drive the average opinion of the population in their own favor. Using a well-established model of opinion dynamics, we formulate the problem as a zero-sum game with its players being the two camps...
2403.14702
Achraf Hsain Him
Achraf Hsain and Hamza El Housni
Large language model-powered chatbots for internationalizing student support in higher education
Key Words: Chatbot, Higher Education, Large Language model, Student Support, Information retrieval. Presented in the conference: The Internationalization of Higher Education and Digital Transformation: Addressing Current and Future Possibilities in Oujda, Morocco
null
null
null
cs.CY cs.IR
http://creativecommons.org/licenses/by/4.0/
This research explores the integration of chatbot technology powered by GPT-3.5 and GPT-4 Turbo into higher education to enhance internationalization and leverage digital transformation. It delves into the design, implementation, and application of Large Language Models (LLMs) for improving student engagement, inform...
[ { "created": "Sat, 16 Mar 2024 23:50:19 GMT", "version": "v1" } ]
2024-03-25
[ [ "Hsain", "Achraf", "" ], [ "Housni", "Hamza El", "" ] ]
This research explores the integration of chatbot technology powered by GPT-3.5 and GPT-4 Turbo into higher education to enhance internationalization and leverage digital transformation. It delves into the design, implementation, and application of Large Language Models (LLMs) for improving student engagement, informat...
2306.11964
Anay Mehrotra
Sruthi Gorantla, Anay Mehrotra, Amit Deshpande, Anand Louis
Sampling Individually-Fair Rankings that are Always Group Fair
Full version of a paper accepted for presentation in ACM AIES 2023
null
null
null
cs.CY cs.DS cs.IR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Rankings on online platforms help their end-users find the relevant information -- people, news, media, and products -- quickly. Fair ranking tasks, which ask to rank a set of items to maximize utility subject to satisfying group-fairness constraints, have gained significant interest in the Algorithmic Fairness, Info...
[ { "created": "Wed, 21 Jun 2023 01:26:34 GMT", "version": "v1" } ]
2023-06-22
[ [ "Gorantla", "Sruthi", "" ], [ "Mehrotra", "Anay", "" ], [ "Deshpande", "Amit", "" ], [ "Louis", "Anand", "" ] ]
Rankings on online platforms help their end-users find the relevant information -- people, news, media, and products -- quickly. Fair ranking tasks, which ask to rank a set of items to maximize utility subject to satisfying group-fairness constraints, have gained significant interest in the Algorithmic Fairness, Inform...
2211.07387
Steven Bilaj
Steven Bilaj, Sofien Dhouib, Setareh Maghsudi
Hypothesis Transfer in Bandits by Weighted Models
16 pages, 6 figures, published in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2022
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of contextual multi-armed bandits in the setting of hypothesis transfer learning. That is, we assume having access to a previously learned model on an unobserved set of contexts, and we leverage it in order to accelerate exploration on a new bandit problem. Our transfer strategy is based on a ...
[ { "created": "Mon, 14 Nov 2022 14:13:02 GMT", "version": "v1" } ]
2022-11-15
[ [ "Bilaj", "Steven", "" ], [ "Dhouib", "Sofien", "" ], [ "Maghsudi", "Setareh", "" ] ]
We consider the problem of contextual multi-armed bandits in the setting of hypothesis transfer learning. That is, we assume having access to a previously learned model on an unobserved set of contexts, and we leverage it in order to accelerate exploration on a new bandit problem. Our transfer strategy is based on a re...
2205.09573
Suryadi -
Suryadi, Yew-Soon Ong, Lock Yue Chew
Jacobian Granger Causal Neural Networks for Analysis of Stationary and Nonstationary Data
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Granger causality is a commonly used method for uncovering information flow and dependencies in a time series. Here we introduce JGC (Jacobian Granger Causality), a neural network-based approach to Granger causality using the Jacobian as a measure of variable importance, and propose a thresholding procedure for infer...
[ { "created": "Thu, 19 May 2022 14:07:54 GMT", "version": "v1" } ]
2022-05-20
[ [ "Suryadi", "", "" ], [ "Ong", "Yew-Soon", "" ], [ "Chew", "Lock Yue", "" ] ]
Granger causality is a commonly used method for uncovering information flow and dependencies in a time series. Here we introduce JGC (Jacobian Granger Causality), a neural network-based approach to Granger causality using the Jacobian as a measure of variable importance, and propose a thresholding procedure for inferri...
1509.08891
Hao Wu
Hao Wu
The Computational Principles of Learning Ability
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by/4.0/
It has been quite a long time since AI researchers in the field of computer science stop talking about simulating human intelligence or trying to explain how brain works. Recently, represented by deep learning techniques, the field of machine learning is experiencing unprecedented prosperity and some applications wit...
[ { "created": "Wed, 23 Sep 2015 04:25:44 GMT", "version": "v1" } ]
2015-09-30
[ [ "Wu", "Hao", "" ] ]
It has been quite a long time since AI researchers in the field of computer science stop talking about simulating human intelligence or trying to explain how brain works. Recently, represented by deep learning techniques, the field of machine learning is experiencing unprecedented prosperity and some applications with ...
2204.02524
Alexander H. Liu
Alexander H. Liu, Cheng-I Jeff Lai, Wei-Ning Hsu, Michael Auli, Alexei Baevski, James Glass
Simple and Effective Unsupervised Speech Synthesis
preprint, equal contribution from first two authors
null
null
null
cs.SD cs.CL eess.AS
http://creativecommons.org/licenses/by/4.0/
We introduce the first unsupervised speech synthesis system based on a simple, yet effective recipe. The framework leverages recent work in unsupervised speech recognition as well as existing neural-based speech synthesis. Using only unlabeled speech audio and unlabeled text as well as a lexicon, our method enables s...
[ { "created": "Wed, 6 Apr 2022 00:19:13 GMT", "version": "v1" }, { "created": "Thu, 7 Apr 2022 02:46:21 GMT", "version": "v2" }, { "created": "Wed, 20 Apr 2022 17:45:35 GMT", "version": "v3" } ]
2022-04-21
[ [ "Liu", "Alexander H.", "" ], [ "Lai", "Cheng-I Jeff", "" ], [ "Hsu", "Wei-Ning", "" ], [ "Auli", "Michael", "" ], [ "Baevski", "Alexei", "" ], [ "Glass", "James", "" ] ]
We introduce the first unsupervised speech synthesis system based on a simple, yet effective recipe. The framework leverages recent work in unsupervised speech recognition as well as existing neural-based speech synthesis. Using only unlabeled speech audio and unlabeled text as well as a lexicon, our method enables spe...
2103.15515
Cong-Thanh Do
Cong-Thanh Do, Rama Doddipatla, Thomas Hain
Multiple-hypothesis CTC-based semi-supervised adaptation of end-to-end speech recognition
Accepted at ICASSP 2021
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes an adaptation method for end-to-end speech recognition. In this method, multiple automatic speech recognition (ASR) 1-best hypotheses are integrated in the computation of the connectionist temporal classification (CTC) loss function. The integration of multiple ASR hypotheses helps alleviating the...
[ { "created": "Mon, 29 Mar 2021 11:38:35 GMT", "version": "v1" }, { "created": "Wed, 31 Mar 2021 09:30:35 GMT", "version": "v2" } ]
2021-04-01
[ [ "Do", "Cong-Thanh", "" ], [ "Doddipatla", "Rama", "" ], [ "Hain", "Thomas", "" ] ]
This paper proposes an adaptation method for end-to-end speech recognition. In this method, multiple automatic speech recognition (ASR) 1-best hypotheses are integrated in the computation of the connectionist temporal classification (CTC) loss function. The integration of multiple ASR hypotheses helps alleviating the i...
1910.07968
Arvind Kiwelekar
Arvind W Kiwelekar
Role of Ontology Training to Software Engineering Students
Short Position Paper
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Students of software engineering struggle to develop a systems perspective because most of the software engineering methodologies focus on developing a particular aspect of a system. Lack of unified coverage to the topic of systems modelling is identified as the root cause behind this problem. The paper explains the ...
[ { "created": "Thu, 17 Oct 2019 15:25:51 GMT", "version": "v1" } ]
2019-10-18
[ [ "Kiwelekar", "Arvind W", "" ] ]
Students of software engineering struggle to develop a systems perspective because most of the software engineering methodologies focus on developing a particular aspect of a system. Lack of unified coverage to the topic of systems modelling is identified as the root cause behind this problem. The paper explains the ro...
2012.00058
Trang Le
Joseph D. Romano, Trang T. Le, William La Cava, John T. Gregg, Daniel J. Goldberg, Natasha L. Ray, Praneel Chakraborty, Daniel Himmelstein, Weixuan Fu, and Jason H. Moore
PMLB v1.0: An open source dataset collection for benchmarking machine learning methods
4 pages, 1 figure. *: These authors contributed equally
null
null
null
cs.LG cs.DB
http://creativecommons.org/licenses/by/4.0/
Motivation: Novel machine learning and statistical modeling studies rely on standardized comparisons to existing methods using well-studied benchmark datasets. Few tools exist that provide rapid access to many of these datasets through a standardized, user-friendly interface that integrates well with popular data sci...
[ { "created": "Mon, 30 Nov 2020 19:21:44 GMT", "version": "v1" }, { "created": "Sun, 4 Apr 2021 20:31:09 GMT", "version": "v2" }, { "created": "Tue, 6 Apr 2021 12:37:35 GMT", "version": "v3" } ]
2021-04-07
[ [ "Romano", "Joseph D.", "" ], [ "Le", "Trang T.", "" ], [ "La Cava", "William", "" ], [ "Gregg", "John T.", "" ], [ "Goldberg", "Daniel J.", "" ], [ "Ray", "Natasha L.", "" ], [ "Chakraborty", "Praneel", "" ...
Motivation: Novel machine learning and statistical modeling studies rely on standardized comparisons to existing methods using well-studied benchmark datasets. Few tools exist that provide rapid access to many of these datasets through a standardized, user-friendly interface that integrates well with popular data scien...
2105.02351
Necati Cihan Camgoz Dr.
Necati Cihan Camgoz, Ben Saunders, Guillaume Rochette, Marco Giovanelli, Giacomo Inches, Robin Nachtrab-Ribback, Richard Bowden
Content4All Open Research Sign Language Translation Datasets
null
null
null
null
cs.CV cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Computational sign language research lacks the large-scale datasets that enables the creation of useful reallife applications. To date, most research has been limited to prototype systems on small domains of discourse, e.g. weather forecasts. To address this issue and to push the field forward, we release six dataset...
[ { "created": "Wed, 5 May 2021 22:14:53 GMT", "version": "v1" } ]
2021-05-07
[ [ "Camgoz", "Necati Cihan", "" ], [ "Saunders", "Ben", "" ], [ "Rochette", "Guillaume", "" ], [ "Giovanelli", "Marco", "" ], [ "Inches", "Giacomo", "" ], [ "Nachtrab-Ribback", "Robin", "" ], [ "Bowden", "Richard"...
Computational sign language research lacks the large-scale datasets that enables the creation of useful reallife applications. To date, most research has been limited to prototype systems on small domains of discourse, e.g. weather forecasts. To address this issue and to push the field forward, we release six datasets ...
2301.00418
Duc-Vu Nguyen
Duc-Vu Nguyen, Ngan Luu-Thuy Nguyen
Is word segmentation necessary for Vietnamese sentiment classification?
In Proceedings of the 16th International Conference on Computing and Communication Technologies (RIVF 2022)
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To the best of our knowledge, this paper made the first attempt to answer whether word segmentation is necessary for Vietnamese sentiment classification. To do this, we presented five pre-trained monolingual S4- based language models for Vietnamese, including one model without word segmentation, and four models using...
[ { "created": "Sun, 1 Jan 2023 15:04:47 GMT", "version": "v1" } ]
2023-01-03
[ [ "Nguyen", "Duc-Vu", "" ], [ "Nguyen", "Ngan Luu-Thuy", "" ] ]
To the best of our knowledge, this paper made the first attempt to answer whether word segmentation is necessary for Vietnamese sentiment classification. To do this, we presented five pre-trained monolingual S4- based language models for Vietnamese, including one model without word segmentation, and four models using R...
2309.17339
Maximilian Schambach
Maximilian Schambach, Dominique Paul, Johannes S. Otterbach
Scaling Experiments in Self-Supervised Cross-Table Representation Learning
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
To analyze the scaling potential of deep tabular representation learning models, we introduce a novel Transformer-based architecture specifically tailored to tabular data and cross-table representation learning by utilizing table-specific tokenizers and a shared Transformer backbone. Our training approach encompasses...
[ { "created": "Fri, 29 Sep 2023 15:48:38 GMT", "version": "v1" } ]
2023-10-02
[ [ "Schambach", "Maximilian", "" ], [ "Paul", "Dominique", "" ], [ "Otterbach", "Johannes S.", "" ] ]
To analyze the scaling potential of deep tabular representation learning models, we introduce a novel Transformer-based architecture specifically tailored to tabular data and cross-table representation learning by utilizing table-specific tokenizers and a shared Transformer backbone. Our training approach encompasses b...
2202.10587
Yin Fang
Yin Fang, Zhuo Chen, Xiaohui Fan and Ningyu Zhang
Knowledge-informed Molecular Learning: A Survey on Paradigm Transfer
8 pages, 3 figures
null
null
null
cs.LG cs.AI physics.chem-ph q-bio.QM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine learning, notably deep learning, has significantly propelled molecular investigations within the biochemical sphere. Traditionally, modeling for such research has centered around a handful of paradigms. For instance, the prediction paradigm is frequently deployed for tasks such as molecular property predictio...
[ { "created": "Thu, 17 Feb 2022 06:18:02 GMT", "version": "v1" }, { "created": "Tue, 5 Sep 2023 10:46:44 GMT", "version": "v2" } ]
2023-09-06
[ [ "Fang", "Yin", "" ], [ "Chen", "Zhuo", "" ], [ "Fan", "Xiaohui", "" ], [ "Zhang", "Ningyu", "" ] ]
Machine learning, notably deep learning, has significantly propelled molecular investigations within the biochemical sphere. Traditionally, modeling for such research has centered around a handful of paradigms. For instance, the prediction paradigm is frequently deployed for tasks such as molecular property prediction....
2304.00483
Mathieu Ravaut
Iva Bojic, Josef Halim, Verena Suharman, Sreeja Tar, Qi Chwen Ong, Duy Phung, Mathieu Ravaut, Shafiq Joty, Josip Car
A Data-centric Framework for Improving Domain-specific Machine Reading Comprehension Datasets
null
2023.In The Fourth Workshop on Insights from Negative Results in NLP, pages 19-32, Dubrovnik, Croatia. Association for Computational Linguistics
10.18653/v1/2023.insights-1.3
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Low-quality data can cause downstream problems in high-stakes applications. Data-centric approach emphasizes on improving dataset quality to enhance model performance. High-quality datasets are needed for general-purpose Large Language Models (LLMs) training, as well as for domain-specific models, which are usually s...
[ { "created": "Sun, 2 Apr 2023 08:26:38 GMT", "version": "v1" }, { "created": "Fri, 26 May 2023 05:43:19 GMT", "version": "v2" } ]
2023-10-13
[ [ "Bojic", "Iva", "" ], [ "Halim", "Josef", "" ], [ "Suharman", "Verena", "" ], [ "Tar", "Sreeja", "" ], [ "Ong", "Qi Chwen", "" ], [ "Phung", "Duy", "" ], [ "Ravaut", "Mathieu", "" ], [ "Joty", "...
Low-quality data can cause downstream problems in high-stakes applications. Data-centric approach emphasizes on improving dataset quality to enhance model performance. High-quality datasets are needed for general-purpose Large Language Models (LLMs) training, as well as for domain-specific models, which are usually sma...
1902.09197
Manoel Horta Ribeiro
Manoel Horta Ribeiro, Kristina Gligori\'c, Robert West
Message Distortion in Information Cascades
Presented at TheWebConf 2019
null
10.1145/3308558.3313531
null
cs.SI
http://creativecommons.org/licenses/by/4.0/
Information diffusion is usually modeled as a process in which immutable pieces of information propagate over a network. In reality, however, messages are not immutable, but may be morphed with every step, potentially entailing large cumulative distortions. This process may lead to misinformation even in the absence ...
[ { "created": "Mon, 25 Feb 2019 11:20:23 GMT", "version": "v1" }, { "created": "Fri, 7 Jun 2019 23:36:43 GMT", "version": "v2" } ]
2019-06-11
[ [ "Ribeiro", "Manoel Horta", "" ], [ "Gligorić", "Kristina", "" ], [ "West", "Robert", "" ] ]
Information diffusion is usually modeled as a process in which immutable pieces of information propagate over a network. In reality, however, messages are not immutable, but may be morphed with every step, potentially entailing large cumulative distortions. This process may lead to misinformation even in the absence of...
2205.07611
Haochen Han
Haochen Han, Qinghua Zheng, Minnan Luo, Kaiyao Miao, Feng Tian and Yan Chen
Noise-Tolerant Learning for Audio-Visual Action Recognition
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.MM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, video recognition is emerging with the help of multi-modal learning, which focuses on integrating distinct modalities to improve the performance or robustness of the model. Although various multi-modal learning methods have been proposed and offer remarkable recognition results, almost all of these methods ...
[ { "created": "Mon, 16 May 2022 12:14:03 GMT", "version": "v1" }, { "created": "Fri, 20 May 2022 10:10:55 GMT", "version": "v2" }, { "created": "Mon, 11 Sep 2023 04:23:25 GMT", "version": "v3" } ]
2023-09-12
[ [ "Han", "Haochen", "" ], [ "Zheng", "Qinghua", "" ], [ "Luo", "Minnan", "" ], [ "Miao", "Kaiyao", "" ], [ "Tian", "Feng", "" ], [ "Chen", "Yan", "" ] ]
Recently, video recognition is emerging with the help of multi-modal learning, which focuses on integrating distinct modalities to improve the performance or robustness of the model. Although various multi-modal learning methods have been proposed and offer remarkable recognition results, almost all of these methods re...
1908.02284
Zachary Ren
Zongze Ren, Guofu Yang, Shugong Xu
Two-stage Training for Chinese Dialect Recognition
Accepted to Interspeech 2019
null
null
null
cs.CL cs.LG eess.AS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we present a two-stage language identification (LID) system based on a shallow ResNet14 followed by a simple 2-layer recurrent neural network (RNN) architecture, which was used for Xunfei (iFlyTek) Chinese Dialect Recognition Challenge and won the first place among 110 teams. The system trains an acous...
[ { "created": "Tue, 6 Aug 2019 04:28:56 GMT", "version": "v1" }, { "created": "Sat, 10 Aug 2019 09:28:00 GMT", "version": "v2" } ]
2019-08-13
[ [ "Ren", "Zongze", "" ], [ "Yang", "Guofu", "" ], [ "Xu", "Shugong", "" ] ]
In this paper, we present a two-stage language identification (LID) system based on a shallow ResNet14 followed by a simple 2-layer recurrent neural network (RNN) architecture, which was used for Xunfei (iFlyTek) Chinese Dialect Recognition Challenge and won the first place among 110 teams. The system trains an acousti...
2309.16158
Jindong Li
Jindong Li, Guobin Shen, Dongcheng Zhao, Qian Zhang, Yi Zeng
FireFly v2: Advancing Hardware Support for High-Performance Spiking Neural Network with a Spatiotemporal FPGA Accelerator
null
null
null
null
cs.NE cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Spiking Neural Networks (SNNs) are expected to be a promising alternative to Artificial Neural Networks (ANNs) due to their strong biological interpretability and high energy efficiency. Specialized SNN hardware offers clear advantages over general-purpose devices in terms of power and performance. However, there's s...
[ { "created": "Thu, 28 Sep 2023 04:17:02 GMT", "version": "v1" } ]
2023-09-29
[ [ "Li", "Jindong", "" ], [ "Shen", "Guobin", "" ], [ "Zhao", "Dongcheng", "" ], [ "Zhang", "Qian", "" ], [ "Zeng", "Yi", "" ] ]
Spiking Neural Networks (SNNs) are expected to be a promising alternative to Artificial Neural Networks (ANNs) due to their strong biological interpretability and high energy efficiency. Specialized SNN hardware offers clear advantages over general-purpose devices in terms of power and performance. However, there's sti...
2305.20055
Songning Lai
Haoxuan Xu, Songning Lai, Xianyang Li, Yang Yang
Cross-Domain Car Detection Model with Integrated Convolutional Block Attention Mechanism
It needs to be returned for major modifications
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Car detection, particularly through camera vision, has become a major focus in the field of computer vision and has gained widespread adoption. While current car detection systems are capable of good detection, reliable detection can still be challenging due to factors such as proximity between the car, light intensi...
[ { "created": "Wed, 31 May 2023 17:28:13 GMT", "version": "v1" }, { "created": "Sun, 11 Jun 2023 12:10:08 GMT", "version": "v2" }, { "created": "Wed, 21 Jun 2023 11:34:33 GMT", "version": "v3" }, { "created": "Thu, 29 Jun 2023 18:08:22 GMT", "version": "v4" } ]
2023-07-03
[ [ "Xu", "Haoxuan", "" ], [ "Lai", "Songning", "" ], [ "Li", "Xianyang", "" ], [ "Yang", "Yang", "" ] ]
Car detection, particularly through camera vision, has become a major focus in the field of computer vision and has gained widespread adoption. While current car detection systems are capable of good detection, reliable detection can still be challenging due to factors such as proximity between the car, light intensity...
2111.14998
Jack Ziegler
Jack Ziegler and Ryan M. Mcgranaghan
Harnessing expressive capacity of Machine Learning modeling to represent complex coupling of Earth's auroral space weather regimes
Lower resolution
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
We develop multiple Deep Learning (DL) models that advance the state-of-the-art predictions of the global auroral particle precipitation. We use observations from low Earth orbiting spacecraft of the electron energy flux to develop a model that improves global nowcasts (predictions at the time of observation) of the ...
[ { "created": "Mon, 29 Nov 2021 22:35:09 GMT", "version": "v1" } ]
2021-12-01
[ [ "Ziegler", "Jack", "" ], [ "Mcgranaghan", "Ryan M.", "" ] ]
We develop multiple Deep Learning (DL) models that advance the state-of-the-art predictions of the global auroral particle precipitation. We use observations from low Earth orbiting spacecraft of the electron energy flux to develop a model that improves global nowcasts (predictions at the time of observation) of the ac...
2208.01548
Sunjay Cauligi
Sunjay Cauligi, Marco Guarnieri, Daniel Moghimi, Deian Stefan, Marco Vassena
A Turning Point for Verified Spectre Sandboxing
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Spectre attacks enable an attacker to access restricted data in an application's memory. Both the academic community and industry veterans have developed several mitigations to block Spectre attacks, but to date, very few have been formally vetted; most are "best effort" strategies. Formal guarantees are particularly...
[ { "created": "Tue, 2 Aug 2022 15:56:17 GMT", "version": "v1" } ]
2022-08-03
[ [ "Cauligi", "Sunjay", "" ], [ "Guarnieri", "Marco", "" ], [ "Moghimi", "Daniel", "" ], [ "Stefan", "Deian", "" ], [ "Vassena", "Marco", "" ] ]
Spectre attacks enable an attacker to access restricted data in an application's memory. Both the academic community and industry veterans have developed several mitigations to block Spectre attacks, but to date, very few have been formally vetted; most are "best effort" strategies. Formal guarantees are particularly c...
1912.00778
Itay Lieder
Itay Lieder, Meirav Segal, Eran Avidan, Asaf Cohen, Tom Hope
Learning a faceted customer segmentation for discovering new business opportunities at Intel
3 pages, 4 figures, Published in proceedings of IEEE BigData 2019
null
null
null
cs.IR cs.CL cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
For sales and marketing organizations within large enterprises, identifying and understanding new markets, customers and partners is a key challenge. Intel's Sales and Marketing Group (SMG) faces similar challenges while growing in new markets and domains and evolving its existing business. In today's complex technol...
[ { "created": "Wed, 27 Nov 2019 15:48:26 GMT", "version": "v1" } ]
2019-12-03
[ [ "Lieder", "Itay", "" ], [ "Segal", "Meirav", "" ], [ "Avidan", "Eran", "" ], [ "Cohen", "Asaf", "" ], [ "Hope", "Tom", "" ] ]
For sales and marketing organizations within large enterprises, identifying and understanding new markets, customers and partners is a key challenge. Intel's Sales and Marketing Group (SMG) faces similar challenges while growing in new markets and domains and evolving its existing business. In today's complex technolog...
2309.16686
Luisa Schuhmacher
Luisa Schuhmacher, Sofie Pollin, Hazem Sallouha
ecoBLE: A Low-Computation Energy Consumption Prediction Framework for Bluetooth Low Energy
To be published in proceedings of the 2023 International Conference on Embedded Wireless Systems and Networks (EWSN)
null
null
null
cs.NI cs.LG
http://creativecommons.org/licenses/by/4.0/
Bluetooth Low Energy (BLE) is a de-facto technology for Internet of Things (IoT) applications, promising very low energy consumption. However, this low energy consumption accounts only for the radio part, and it overlooks the energy consumption of other hardware and software components. Monitoring and predicting the ...
[ { "created": "Wed, 2 Aug 2023 13:04:23 GMT", "version": "v1" } ]
2023-10-02
[ [ "Schuhmacher", "Luisa", "" ], [ "Pollin", "Sofie", "" ], [ "Sallouha", "Hazem", "" ] ]
Bluetooth Low Energy (BLE) is a de-facto technology for Internet of Things (IoT) applications, promising very low energy consumption. However, this low energy consumption accounts only for the radio part, and it overlooks the energy consumption of other hardware and software components. Monitoring and predicting the en...
2103.06624
Huan Zhang
Shiqi Wang, Huan Zhang, Kaidi Xu, Xue Lin, Suman Jana, Cho-Jui Hsieh, J. Zico Kolter
Beta-CROWN: Efficient Bound Propagation with Per-neuron Split Constraints for Complete and Incomplete Neural Network Robustness Verification
Shiqi Wang, Huan Zhang and Kaidi Xu contributed equally. Accepted by NeurIPS 2021
null
null
null
cs.LG cs.AI cs.CR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bound propagation based incomplete neural network verifiers such as CROWN are very efficient and can significantly accelerate branch-and-bound (BaB) based complete verification of neural networks. However, bound propagation cannot fully handle the neuron split constraints introduced by BaB commonly handled by expensi...
[ { "created": "Thu, 11 Mar 2021 11:56:54 GMT", "version": "v1" }, { "created": "Sun, 31 Oct 2021 22:51:18 GMT", "version": "v2" } ]
2021-11-02
[ [ "Wang", "Shiqi", "" ], [ "Zhang", "Huan", "" ], [ "Xu", "Kaidi", "" ], [ "Lin", "Xue", "" ], [ "Jana", "Suman", "" ], [ "Hsieh", "Cho-Jui", "" ], [ "Kolter", "J. Zico", "" ] ]
Bound propagation based incomplete neural network verifiers such as CROWN are very efficient and can significantly accelerate branch-and-bound (BaB) based complete verification of neural networks. However, bound propagation cannot fully handle the neuron split constraints introduced by BaB commonly handled by expensive...
2407.20608
Otso Haavisto
Otso Haavisto and Robin Welsch
Questionnaires for Everyone: Streamlining Cross-Cultural Questionnaire Adaptation with GPT-Based Translation Quality Evaluation
19 pages, 13 figures
null
null
null
cs.HC cs.CL
http://creativecommons.org/licenses/by/4.0/
Adapting questionnaires to new languages is a resource-intensive process often requiring the hiring of multiple independent translators, which limits the ability of researchers to conduct cross-cultural research and effectively creates inequalities in research and society. This work presents a prototype tool that can...
[ { "created": "Tue, 30 Jul 2024 07:34:40 GMT", "version": "v1" } ]
2024-07-31
[ [ "Haavisto", "Otso", "" ], [ "Welsch", "Robin", "" ] ]
Adapting questionnaires to new languages is a resource-intensive process often requiring the hiring of multiple independent translators, which limits the ability of researchers to conduct cross-cultural research and effectively creates inequalities in research and society. This work presents a prototype tool that can e...
2001.04129
Jorge Calvo-Zaragoza
Antonio-Javier Gallego, Jorge Calvo-Zaragoza, Robert B. Fisher
Incremental Unsupervised Domain-Adversarial Training of Neural Networks
26 pages, 7 figures
IEEE Trans. Neural Networks Learn. Syst. 32(11): 4864-4878 (2021)
10.1109/TNNLS.2020.3025954
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the context of supervised statistical learning, it is typically assumed that the training set comes from the same distribution that draws the test samples. When this is not the case, the behavior of the learned model is unpredictable and becomes dependent upon the degree of similarity between the distribution of t...
[ { "created": "Mon, 13 Jan 2020 09:54:35 GMT", "version": "v1" } ]
2022-05-12
[ [ "Gallego", "Antonio-Javier", "" ], [ "Calvo-Zaragoza", "Jorge", "" ], [ "Fisher", "Robert B.", "" ] ]
In the context of supervised statistical learning, it is typically assumed that the training set comes from the same distribution that draws the test samples. When this is not the case, the behavior of the learned model is unpredictable and becomes dependent upon the degree of similarity between the distribution of the...
1903.03214
Stewart Jamieson
Yogesh Girdhar, Levi Cai, Stewart Jamieson, Nathan McGuire, Genevieve Flaspohler, Stefano Suman, Brian Claus
Streaming Scene Maps for Co-Robotic Exploration in Bandwidth Limited Environments
8 pages, 6 figures, accepted for presentation in IEEE Int. Conf. on Robotics and Automation, ICRA '19, Montreal, Canada, May 2019
2019 IEEE International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 7940-7946
10.1109/ICRA.2019.8794132
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a bandwidth tunable technique for real-time probabilistic scene modeling and mapping to enable co-robotic exploration in communication constrained environments such as the deep sea. The parameters of the system enable the user to characterize the scene complexity represented by the map, which in t...
[ { "created": "Thu, 7 Mar 2019 23:05:23 GMT", "version": "v1" } ]
2020-03-09
[ [ "Girdhar", "Yogesh", "" ], [ "Cai", "Levi", "" ], [ "Jamieson", "Stewart", "" ], [ "McGuire", "Nathan", "" ], [ "Flaspohler", "Genevieve", "" ], [ "Suman", "Stefano", "" ], [ "Claus", "Brian", "" ] ]
This paper proposes a bandwidth tunable technique for real-time probabilistic scene modeling and mapping to enable co-robotic exploration in communication constrained environments such as the deep sea. The parameters of the system enable the user to characterize the scene complexity represented by the map, which in tur...
2104.08742
Rik Koncel-Kedziorski
Rik Koncel-Kedziorski and Noah A. Smith
Go Forth and Prosper: Language Modeling with Ancient Textual History
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce a technique for improving document-level language models (LM) by leveraging "ancient history": text that is outside the LM's current context window. We learn an auxiliary function to select spans from the ancient history which can help the LM to predict future text. The selected text spans are then copie...
[ { "created": "Sun, 18 Apr 2021 06:57:30 GMT", "version": "v1" } ]
2021-04-20
[ [ "Koncel-Kedziorski", "Rik", "" ], [ "Smith", "Noah A.", "" ] ]
We introduce a technique for improving document-level language models (LM) by leveraging "ancient history": text that is outside the LM's current context window. We learn an auxiliary function to select spans from the ancient history which can help the LM to predict future text. The selected text spans are then copied ...
1810.07088
Shaofeng Yuan
Yunan Wu, Feng Yang, Ying Liu, Xuefan Zha, Shaofeng Yuan
A Comparison of 1-D and 2-D Deep Convolutional Neural Networks in ECG Classification
4 pages, 5 figures, 3 tables
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Effective detection of arrhythmia is an important task in the remote monitoring of electrocardiogram (ECG). The traditional ECG recognition depends on the judgment of the clinicians' experience, but the results suffer from the probability of human error due to the fatigue. To solve this problem, an ECG signal classif...
[ { "created": "Tue, 16 Oct 2018 15:40:33 GMT", "version": "v1" } ]
2018-10-17
[ [ "Wu", "Yunan", "" ], [ "Yang", "Feng", "" ], [ "Liu", "Ying", "" ], [ "Zha", "Xuefan", "" ], [ "Yuan", "Shaofeng", "" ] ]
Effective detection of arrhythmia is an important task in the remote monitoring of electrocardiogram (ECG). The traditional ECG recognition depends on the judgment of the clinicians' experience, but the results suffer from the probability of human error due to the fatigue. To solve this problem, an ECG signal classific...
2209.03826
Felix Engelmann
Pascal Oser, Felix Engelmann, Stefan L\"uders, Frank Kargl
Evaluating the Future Device Security Risk Indicator for Hundreds of IoT Devices
accepted at ESORICS STM22 workshop
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
IoT devices are present in many, especially corporate and sensitive, networks and regularly introduce security risks due to slow vendor responses to vulnerabilities and high difficulty of patching. In this paper, we want to evaluate to what extent the development of future risk of IoT devices due to new and unpatched...
[ { "created": "Thu, 8 Sep 2022 14:00:48 GMT", "version": "v1" }, { "created": "Fri, 16 Sep 2022 12:19:16 GMT", "version": "v2" } ]
2022-09-19
[ [ "Oser", "Pascal", "" ], [ "Engelmann", "Felix", "" ], [ "Lüders", "Stefan", "" ], [ "Kargl", "Frank", "" ] ]
IoT devices are present in many, especially corporate and sensitive, networks and regularly introduce security risks due to slow vendor responses to vulnerabilities and high difficulty of patching. In this paper, we want to evaluate to what extent the development of future risk of IoT devices due to new and unpatched v...
2304.10348
Bata Vasic Dr
Bata Vasc, Nithin Raveendran and Bane Vasic
Neuro-OSVETA: A Robust Watermarking of 3D Meshes
10 pages, 5 figures
Proceedings of the International Telemetering Conference (ITC 2019), ISSN 1546-2188, vol. 55, pp. 387 - 396, Las Vegas, NV, USA, Octobar 21 - 24, 2019
null
null
cs.MM
http://creativecommons.org/licenses/by-nc-sa/4.0/
Best and practical watermarking schemes for copyright protection of 3D meshes are required to be blind and robust to attacks and errors. In this paper, we present the latest developments in 3D blind watermarking with a special emphasis on our Ordered Statistics Vertex Extraction and Tracing Algorithm (OSVETA) algorit...
[ { "created": "Thu, 20 Apr 2023 14:39:24 GMT", "version": "v1" } ]
2023-04-21
[ [ "Vasc", "Bata", "" ], [ "Raveendran", "Nithin", "" ], [ "Vasic", "Bane", "" ] ]
Best and practical watermarking schemes for copyright protection of 3D meshes are required to be blind and robust to attacks and errors. In this paper, we present the latest developments in 3D blind watermarking with a special emphasis on our Ordered Statistics Vertex Extraction and Tracing Algorithm (OSVETA) algorithm...
1811.10396
Arash Ardakani
Arash Ardakani, Zhengyun Ji, Warren J. Gross
Learning to Skip Ineffectual Recurrent Computations in LSTMs
Accepted as a conference paper for presentation at DATE 2019
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Long Short-Term Memory (LSTM) is a special class of recurrent neural network, which has shown remarkable successes in processing sequential data. The typical architecture of an LSTM involves a set of states and gates: the states retain information over arbitrary time intervals and the gates regulate the flow of infor...
[ { "created": "Fri, 9 Nov 2018 15:51:40 GMT", "version": "v1" }, { "created": "Thu, 29 Nov 2018 22:44:01 GMT", "version": "v2" } ]
2018-12-03
[ [ "Ardakani", "Arash", "" ], [ "Ji", "Zhengyun", "" ], [ "Gross", "Warren J.", "" ] ]
Long Short-Term Memory (LSTM) is a special class of recurrent neural network, which has shown remarkable successes in processing sequential data. The typical architecture of an LSTM involves a set of states and gates: the states retain information over arbitrary time intervals and the gates regulate the flow of informa...
2003.02518
V\'aclav Rozho\v{n}
V\'aclav Rozho\v{n}
Simple and sharp analysis of k-means||
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a simple analysis of k-means|| (Bahmani et al., PVLDB 2012) -- a distributed variant of the k-means++ algorithm (Arthur and Vassilvitskii, SODA 2007). Moreover, the bound on the number of rounds is improved from $O(\log n)$ to $O(\log n / \log\log n)$, which we show to be tight.
[ { "created": "Thu, 5 Mar 2020 10:18:48 GMT", "version": "v1" }, { "created": "Thu, 2 Jul 2020 13:34:45 GMT", "version": "v2" } ]
2020-07-03
[ [ "Rozhoň", "Václav", "" ] ]
We present a simple analysis of k-means|| (Bahmani et al., PVLDB 2012) -- a distributed variant of the k-means++ algorithm (Arthur and Vassilvitskii, SODA 2007). Moreover, the bound on the number of rounds is improved from $O(\log n)$ to $O(\log n / \log\log n)$, which we show to be tight.
1405.4041
Ethan Jackson
Ethan K. Jackson
A Module System for Domain-Specific Languages
Appearing in International Conference on Logic Programming (ICLP) 2014
Theory and Practice of Logic Programming 14 (2014) 771-785
10.1017/S1471068414000337
null
cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Domain-specific languages (DSLs) are routinely created to simplify difficult or specialized programming tasks. They expose useful abstractions and design patterns in the form of language constructs, provide static semantics to eagerly detect misuse of these constructs, and dynamic semantics to completely define how l...
[ { "created": "Fri, 16 May 2014 00:47:10 GMT", "version": "v1" } ]
2020-02-19
[ [ "Jackson", "Ethan K.", "" ] ]
Domain-specific languages (DSLs) are routinely created to simplify difficult or specialized programming tasks. They expose useful abstractions and design patterns in the form of language constructs, provide static semantics to eagerly detect misuse of these constructs, and dynamic semantics to completely define how lan...