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2202.06393
Christina Pan
Christina A. Pan, Sahil Yakhmi, Tara P. Iyer, Evan Strasnick, Amy X. Zhang, and Michael S. Bernstein
Comparing the Perceived Legitimacy of Content Moderation Processes: Contractors, Algorithms, Expert Panels, and Digital Juries
This paper will appear at CSCW 2022
null
10.1145/3512929
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
While research continues to investigate and improve the accuracy, fairness, and normative appropriateness of content moderation processes on large social media platforms, even the best process cannot be effective if users reject its authority as illegitimate. We present a survey experiment comparing the perceived ins...
[ { "created": "Sun, 13 Feb 2022 19:32:49 GMT", "version": "v1" }, { "created": "Thu, 6 Oct 2022 05:09:21 GMT", "version": "v2" } ]
2022-10-07
[ [ "Pan", "Christina A.", "" ], [ "Yakhmi", "Sahil", "" ], [ "Iyer", "Tara P.", "" ], [ "Strasnick", "Evan", "" ], [ "Zhang", "Amy X.", "" ], [ "Bernstein", "Michael S.", "" ] ]
While research continues to investigate and improve the accuracy, fairness, and normative appropriateness of content moderation processes on large social media platforms, even the best process cannot be effective if users reject its authority as illegitimate. We present a survey experiment comparing the perceived insti...
1502.05256
Peter Gloor
Peter Gloor, Patrick De Boer, Wei Lo, Stefan Wagner, Keiichi Nemoto, and Hauke Fuehres
Cultural Anthropology Through the Lens of Wikipedia - A Comparison of Historical Leadership Networks in the English, Chinese, Japanese and German Wikipedia
Proceedings of the 5th International Conference on Collaborative Innovation Networks COINs15, Tokyo, Japan March 12-14, 2015 (arXiv:1502.01142)
null
null
coins15/2015/04
cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper we study the differences in historical worldview between Western and Eastern cultures, represented through the English, Chinese, Japanese, and German Wikipedia. In particular, we analyze the historical networks of the World's leaders since the beginning of written history, comparing them in the four dif...
[ { "created": "Wed, 18 Feb 2015 14:45:18 GMT", "version": "v1" } ]
2015-02-19
[ [ "Gloor", "Peter", "" ], [ "De Boer", "Patrick", "" ], [ "Lo", "Wei", "" ], [ "Wagner", "Stefan", "" ], [ "Nemoto", "Keiichi", "" ], [ "Fuehres", "Hauke", "" ] ]
In this paper we study the differences in historical worldview between Western and Eastern cultures, represented through the English, Chinese, Japanese, and German Wikipedia. In particular, we analyze the historical networks of the World's leaders since the beginning of written history, comparing them in the four diffe...
2308.02213
Tianhao Qi
Tianhao Qi, Hongtao Xie, Pandeng Li, Jiannan Ge, Yongdong Zhang
Balanced Classification: A Unified Framework for Long-Tailed Object Detection
Accepted by IEEE Transactions on Multimedia, to be published; Code: https://github.com/Tianhao-Qi/BACL
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Conventional detectors suffer from performance degradation when dealing with long-tailed data due to a classification bias towards the majority head categories. In this paper, we contend that the learning bias originates from two factors: 1) the unequal competition arising from the imbalanced distribution of foregrou...
[ { "created": "Fri, 4 Aug 2023 09:11:07 GMT", "version": "v1" } ]
2023-08-07
[ [ "Qi", "Tianhao", "" ], [ "Xie", "Hongtao", "" ], [ "Li", "Pandeng", "" ], [ "Ge", "Jiannan", "" ], [ "Zhang", "Yongdong", "" ] ]
Conventional detectors suffer from performance degradation when dealing with long-tailed data due to a classification bias towards the majority head categories. In this paper, we contend that the learning bias originates from two factors: 1) the unequal competition arising from the imbalanced distribution of foreground...
1810.02684
Vahid Moosavi
Joao P. Leitao, Mohamed Zaghloul and Vahid Moosavi
Modeling overland flow from local inflows in almost no-time, using Self Organizing Maps
null
null
null
null
cs.CY cs.CC cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Physically-based overland flow models are computationally demanding, hindering their use for real-time applications. Therefore, the development of fast (and reasonably accurate) overland flow models is needed if they are to be used to support flood mitigation decision making. In this study, we investigate the potenti...
[ { "created": "Sun, 23 Sep 2018 18:54:29 GMT", "version": "v1" } ]
2018-10-08
[ [ "Leitao", "Joao P.", "" ], [ "Zaghloul", "Mohamed", "" ], [ "Moosavi", "Vahid", "" ] ]
Physically-based overland flow models are computationally demanding, hindering their use for real-time applications. Therefore, the development of fast (and reasonably accurate) overland flow models is needed if they are to be used to support flood mitigation decision making. In this study, we investigate the potential...
2110.00199
Ching-Hsun Tseng
Ching-Hsun. Tseng, Liu-Hsueh. Cheng, Shin-Jye. Lee, Xiaojun Zeng
Perturbated Gradients Updating within Unit Space for Deep Learning
null
null
10.1109/IJCNN55064.2022.9892245
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
In deep learning, optimization plays a vital role. By focusing on image classification, this work investigates the pros and cons of the widely used optimizers, and proposes a new optimizer: Perturbated Unit Gradient Descent (PUGD) algorithm with extending normalized gradient operation in tensor within perturbation to...
[ { "created": "Fri, 1 Oct 2021 04:00:51 GMT", "version": "v1" }, { "created": "Mon, 24 Jan 2022 18:25:25 GMT", "version": "v2" } ]
2022-11-10
[ [ "Tseng", "Ching-Hsun.", "" ], [ "Cheng", "Liu-Hsueh.", "" ], [ "Lee", "Shin-Jye.", "" ], [ "Zeng", "Xiaojun", "" ] ]
In deep learning, optimization plays a vital role. By focusing on image classification, this work investigates the pros and cons of the widely used optimizers, and proposes a new optimizer: Perturbated Unit Gradient Descent (PUGD) algorithm with extending normalized gradient operation in tensor within perturbation to u...
1303.5705
Jaume Agust\'i-Cullell
Jaume Agust\'i-Cullell, Francesc Esteva, Pere Garcia, Lluis Godo, Carles Sierra
Combining Multiple-Valued Logics in Modular Expert Systems
Appears in Proceedings of the Seventh Conference on Uncertainty in Artificial Intelligence (UAI1991)
null
null
UAI-P-1991-PG-17-25
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The way experts manage uncertainty usually changes depending on the task they are performing. This fact has lead us to consider the problem of communicating modules (task implementations) in a large and structured knowledge based system when modules have different uncertainty calculi. In this paper, the analysis of t...
[ { "created": "Wed, 20 Mar 2013 15:29:35 GMT", "version": "v1" } ]
2013-03-26
[ [ "Agustí-Cullell", "Jaume", "" ], [ "Esteva", "Francesc", "" ], [ "Garcia", "Pere", "" ], [ "Godo", "Lluis", "" ], [ "Sierra", "Carles", "" ] ]
The way experts manage uncertainty usually changes depending on the task they are performing. This fact has lead us to consider the problem of communicating modules (task implementations) in a large and structured knowledge based system when modules have different uncertainty calculi. In this paper, the analysis of the...
1711.05938
Yang Zhang
Zehui Xiong, Yang Zhang, Dusit Niyato, Ping Wang and Zhu Han
When Mobile Blockchain Meets Edge Computing
Accepted by IEEE Communications Magazine
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Blockchain, as the backbone technology of the current popular Bitcoin digital currency, has become a promising decentralized data management framework. Although blockchain has been widely adopted in many applications, e.g., finance, healthcare, and logistics, its application in mobile services is still limited. This ...
[ { "created": "Thu, 16 Nov 2017 05:53:57 GMT", "version": "v1" }, { "created": "Wed, 11 Apr 2018 23:14:28 GMT", "version": "v2" } ]
2018-04-13
[ [ "Xiong", "Zehui", "" ], [ "Zhang", "Yang", "" ], [ "Niyato", "Dusit", "" ], [ "Wang", "Ping", "" ], [ "Han", "Zhu", "" ] ]
Blockchain, as the backbone technology of the current popular Bitcoin digital currency, has become a promising decentralized data management framework. Although blockchain has been widely adopted in many applications, e.g., finance, healthcare, and logistics, its application in mobile services is still limited. This is...
1806.09566
Arnaud Dethise
Arnaud Dethise, Marco Chiesa, Marco Canini
Prelude: Ensuring Inter-Domain Loop-Freedom in~SDN-Enabled Networks
null
null
10.1145/3232565.3232570
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Software-Defined-eXchanges (SDXes) promise to tackle the timely quest of bringing improving the inter-domain routing ecosystem through SDN deployment. Yet, the naive deployment of SDN on the Internet raises concerns about the correctness of the inter-domain data-plane. By allowing operators to deflect traffic from th...
[ { "created": "Mon, 25 Jun 2018 17:06:10 GMT", "version": "v1" } ]
2018-06-26
[ [ "Dethise", "Arnaud", "" ], [ "Chiesa", "Marco", "" ], [ "Canini", "Marco", "" ] ]
Software-Defined-eXchanges (SDXes) promise to tackle the timely quest of bringing improving the inter-domain routing ecosystem through SDN deployment. Yet, the naive deployment of SDN on the Internet raises concerns about the correctness of the inter-domain data-plane. By allowing operators to deflect traffic from the ...
2406.00021
Arnav Goel
Medha Hira, Arnav Goel, Anubha Gupta
CrossVoice: Crosslingual Prosody Preserving Cascade-S2ST using Transfer Learning
8 pages, Accepted at ICLR 2024 - Tiny Track
null
null
null
cs.CL cs.SD eess.AS
http://creativecommons.org/licenses/by/4.0/
This paper presents CrossVoice, a novel cascade-based Speech-to-Speech Translation (S2ST) system employing advanced ASR, MT, and TTS technologies with cross-lingual prosody preservation through transfer learning. We conducted comprehensive experiments comparing CrossVoice with direct-S2ST systems, showing improved BL...
[ { "created": "Thu, 23 May 2024 20:30:54 GMT", "version": "v1" }, { "created": "Tue, 18 Jun 2024 05:26:48 GMT", "version": "v2" } ]
2024-06-19
[ [ "Hira", "Medha", "" ], [ "Goel", "Arnav", "" ], [ "Gupta", "Anubha", "" ] ]
This paper presents CrossVoice, a novel cascade-based Speech-to-Speech Translation (S2ST) system employing advanced ASR, MT, and TTS technologies with cross-lingual prosody preservation through transfer learning. We conducted comprehensive experiments comparing CrossVoice with direct-S2ST systems, showing improved BLEU...
2112.13982
KitIan Kou
Juan Han, Kit Ian Kou, Jifei Miao
Quaternion-based dynamic mode decomposition for background modeling in color videos
16 pages
null
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Scene Background Initialization (SBI) is one of the challenging problems in computer vision. Dynamic mode decomposition (DMD) is a recently proposed method to robustly decompose a video sequence into the background model and the corresponding foreground part. However, this method needs to convert the color image into...
[ { "created": "Tue, 28 Dec 2021 03:35:39 GMT", "version": "v1" } ]
2021-12-30
[ [ "Han", "Juan", "" ], [ "Kou", "Kit Ian", "" ], [ "Miao", "Jifei", "" ] ]
Scene Background Initialization (SBI) is one of the challenging problems in computer vision. Dynamic mode decomposition (DMD) is a recently proposed method to robustly decompose a video sequence into the background model and the corresponding foreground part. However, this method needs to convert the color image into t...
1507.05169
Alexander Spiegelman
Alexander Spiegelman, Yuval Cassuto, Gregory Chockler, and Idit Keidar
Space Bounds for Reliable Storage: Fundamental Limits of Coding
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the inherent space requirements of shared storage algorithms in asynchronous fault-prone systems. Previous works use codes to achieve a better storage cost than the well-known replication approach. However, a closer look reveals that they incur extra costs somewhere else: Some use unbounded storage in commun...
[ { "created": "Sat, 18 Jul 2015 10:25:18 GMT", "version": "v1" } ]
2015-07-21
[ [ "Spiegelman", "Alexander", "" ], [ "Cassuto", "Yuval", "" ], [ "Chockler", "Gregory", "" ], [ "Keidar", "Idit", "" ] ]
We study the inherent space requirements of shared storage algorithms in asynchronous fault-prone systems. Previous works use codes to achieve a better storage cost than the well-known replication approach. However, a closer look reveals that they incur extra costs somewhere else: Some use unbounded storage in communic...
1907.02678
Jingling Yuan
Yang Cao, Jingling Yuan, Song Xiao, Qing Xie
TPM: A GPS-based Trajectory Pattern Mining System
null
null
null
null
cs.OH
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With the development of big data and artificial intelligence, the technology of urban computing becomes more mature and widely used. In urban computing, using GPS-based trajectory data to discover urban dense areas, extract similar urban trajectories, predict urban traffic, and solve traffic congestion problems are a...
[ { "created": "Fri, 5 Jul 2019 04:58:10 GMT", "version": "v1" } ]
2019-07-08
[ [ "Cao", "Yang", "" ], [ "Yuan", "Jingling", "" ], [ "Xiao", "Song", "" ], [ "Xie", "Qing", "" ] ]
With the development of big data and artificial intelligence, the technology of urban computing becomes more mature and widely used. In urban computing, using GPS-based trajectory data to discover urban dense areas, extract similar urban trajectories, predict urban traffic, and solve traffic congestion problems are all...
2306.04862
Jingyue Li Prof.
Carl Smestad (1) and Jingyue Li (2) ((1) Norwegian University of Science and Technology, (2) Norwegian University of Science and Technology)
A Systematic Literature Review on Client Selection in Federated Learning
null
null
10.1145/3593434.3593438
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
With the arising concerns of privacy within machine learning, federated learning (FL) was invented in 2017, in which the clients, such as mobile devices, train a model and send the update to the centralized server. Choosing clients randomly for FL can harm learning performance due to different reasons. Many studies h...
[ { "created": "Thu, 8 Jun 2023 01:26:22 GMT", "version": "v1" } ]
2023-06-09
[ [ "Smestad", "Carl", "" ], [ "Li", "Jingyue", "" ] ]
With the arising concerns of privacy within machine learning, federated learning (FL) was invented in 2017, in which the clients, such as mobile devices, train a model and send the update to the centralized server. Choosing clients randomly for FL can harm learning performance due to different reasons. Many studies hav...
2310.09749
Yifeng Xiong
Yifeng Xiong, Fan Liu, Kai Wan, Weijie Yuan, Yuanhao Cui, and Giuseppe Caire
From Torch to Projector: Fundamental Tradeoff of Integrated Sensing and Communications
15 pages, 11 figures, submitted to IEEE BITS the Information Theory Magazine
null
null
null
cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Sensing and communications (S&C) have been historically developed in parallel. In recent decade, they have been evolving from separation to integration, giving rise to the integrated sensing and communications (ISAC) paradigm, that has been recognized as one of the six key 6G usage scenarios. Despite the plethora of ...
[ { "created": "Sun, 15 Oct 2023 06:14:49 GMT", "version": "v1" }, { "created": "Tue, 17 Oct 2023 12:30:20 GMT", "version": "v2" } ]
2023-10-18
[ [ "Xiong", "Yifeng", "" ], [ "Liu", "Fan", "" ], [ "Wan", "Kai", "" ], [ "Yuan", "Weijie", "" ], [ "Cui", "Yuanhao", "" ], [ "Caire", "Giuseppe", "" ] ]
Sensing and communications (S&C) have been historically developed in parallel. In recent decade, they have been evolving from separation to integration, giving rise to the integrated sensing and communications (ISAC) paradigm, that has been recognized as one of the six key 6G usage scenarios. Despite the plethora of re...
1610.05531
Tobias Fiebig
Tobias Fiebig, Franziska Lichtblau, Florian Streibelt, Thorben Krueger, Pieter Lexis, Randy Bush and Anja Feldmann
SoK: An Analysis of Protocol Design: Avoiding Traps for Implementation and Deployment
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Today's Internet utilizes a multitude of different protocols. While some of these protocols were first implemented and used and later documented, other were first specified and then implemented. Regardless of how protocols came to be, their definitions can contain traps that lead to insecure implementations or deploy...
[ { "created": "Tue, 18 Oct 2016 10:57:22 GMT", "version": "v1" } ]
2016-10-19
[ [ "Fiebig", "Tobias", "" ], [ "Lichtblau", "Franziska", "" ], [ "Streibelt", "Florian", "" ], [ "Krueger", "Thorben", "" ], [ "Lexis", "Pieter", "" ], [ "Bush", "Randy", "" ], [ "Feldmann", "Anja", "" ] ]
Today's Internet utilizes a multitude of different protocols. While some of these protocols were first implemented and used and later documented, other were first specified and then implemented. Regardless of how protocols came to be, their definitions can contain traps that lead to insecure implementations or deployme...
2212.01365
Hong Jun Jeon
Hong Jun Jeon, Benjamin Van Roy
An Information-Theoretic Analysis of Compute-Optimal Neural Scaling Laws
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
We study the compute-optimal trade-off between model and training data set sizes for large neural networks. Our result suggests a linear relation similar to that supported by the empirical analysis of chinchilla. While that work studies transformer-based large language models trained on the MassiveText corpus gopher,...
[ { "created": "Fri, 2 Dec 2022 18:46:41 GMT", "version": "v1" }, { "created": "Wed, 18 Oct 2023 20:53:04 GMT", "version": "v2" } ]
2023-10-20
[ [ "Jeon", "Hong Jun", "" ], [ "Van Roy", "Benjamin", "" ] ]
We study the compute-optimal trade-off between model and training data set sizes for large neural networks. Our result suggests a linear relation similar to that supported by the empirical analysis of chinchilla. While that work studies transformer-based large language models trained on the MassiveText corpus gopher, a...
2311.13168
Jianwei Feng
Jianwei Feng and Prateek Singhal
3D Face Style Transfer with a Hybrid Solution of NeRF and Mesh Rasterization
null
WACV 2024
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Style transfer for human face has been widely researched in recent years. Majority of the existing approaches work in 2D image domain and have 3D inconsistency issue when applied on different viewpoints of the same face. In this paper, we tackle the problem of 3D face style transfer which aims at generating stylized ...
[ { "created": "Wed, 22 Nov 2023 05:24:35 GMT", "version": "v1" } ]
2023-11-23
[ [ "Feng", "Jianwei", "" ], [ "Singhal", "Prateek", "" ] ]
Style transfer for human face has been widely researched in recent years. Majority of the existing approaches work in 2D image domain and have 3D inconsistency issue when applied on different viewpoints of the same face. In this paper, we tackle the problem of 3D face style transfer which aims at generating stylized no...
1805.11384
Bicheng Ying
Bicheng Ying and Kun Yuan and Ali H. Sayed
Supervised Learning Under Distributed Features
null
null
10.1109/TSP.2018.2881661
null
cs.MA cs.LG math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work studies the problem of learning under both large datasets and large-dimensional feature space scenarios. The feature information is assumed to be spread across agents in a network, where each agent observes some of the features. Through local cooperation, the agents are supposed to interact with each other ...
[ { "created": "Tue, 29 May 2018 12:25:37 GMT", "version": "v1" }, { "created": "Fri, 9 Nov 2018 08:17:47 GMT", "version": "v2" }, { "created": "Fri, 22 May 2020 18:06:47 GMT", "version": "v3" } ]
2020-05-26
[ [ "Ying", "Bicheng", "" ], [ "Yuan", "Kun", "" ], [ "Sayed", "Ali H.", "" ] ]
This work studies the problem of learning under both large datasets and large-dimensional feature space scenarios. The feature information is assumed to be spread across agents in a network, where each agent observes some of the features. Through local cooperation, the agents are supposed to interact with each other to...
1104.5059
Mitchell Bloch
Mitchell Keith Bloch
Reducing Commitment to Tasks with Off-Policy Hierarchical Reinforcement Learning
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In experimenting with off-policy temporal difference (TD) methods in hierarchical reinforcement learning (HRL) systems, we have observed unwanted on-policy learning under reproducible conditions. Here we present modifications to several TD methods that prevent unintentional on-policy learning from occurring. These mo...
[ { "created": "Wed, 27 Apr 2011 00:58:52 GMT", "version": "v1" } ]
2015-03-19
[ [ "Bloch", "Mitchell Keith", "" ] ]
In experimenting with off-policy temporal difference (TD) methods in hierarchical reinforcement learning (HRL) systems, we have observed unwanted on-policy learning under reproducible conditions. Here we present modifications to several TD methods that prevent unintentional on-policy learning from occurring. These modi...
2110.08616
Zhihao Zhang
Zhihao Zhang, Zhihao Jia
GradSign: Model Performance Inference with Theoretical Insights
null
The Tenth International Conference on Learning Representations (ICLR 2022)
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
A key challenge in neural architecture search (NAS) is quickly inferring the predictive performance of a broad spectrum of networks to discover statistically accurate and computationally efficient ones. We refer to this task as model performance inference (MPI). The current practice for efficient MPI is gradient-base...
[ { "created": "Sat, 16 Oct 2021 17:03:10 GMT", "version": "v1" }, { "created": "Sat, 18 Jun 2022 19:34:43 GMT", "version": "v2" } ]
2022-06-22
[ [ "Zhang", "Zhihao", "" ], [ "Jia", "Zhihao", "" ] ]
A key challenge in neural architecture search (NAS) is quickly inferring the predictive performance of a broad spectrum of networks to discover statistically accurate and computationally efficient ones. We refer to this task as model performance inference (MPI). The current practice for efficient MPI is gradient-based ...
1704.03225
Lukas Mosser
Lukas Mosser, Olivier Dubrule, Martin J. Blunt
Reconstruction of three-dimensional porous media using generative adversarial neural networks
21 pages, 20 figures
Phys. Rev. E 96, 043309 (2017)
10.1103/PhysRevE.96.043309
null
cs.CV cond-mat.mtrl-sci physics.flu-dyn physics.geo-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To evaluate the variability of multi-phase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the ...
[ { "created": "Tue, 11 Apr 2017 09:55:55 GMT", "version": "v1" } ]
2017-11-01
[ [ "Mosser", "Lukas", "" ], [ "Dubrule", "Olivier", "" ], [ "Blunt", "Martin J.", "" ] ]
To evaluate the variability of multi-phase flow properties of porous media at the pore scale, it is necessary to acquire a number of representative samples of the void-solid structure. While modern x-ray computer tomography has made it possible to extract three-dimensional images of the pore space, assessment of the va...
2204.04832
Nina Klobas
Thekla Hamm and Nina Klobas and George B. Mertzios and Paul G. Spirakis
The Complexity of Temporal Vertex Cover in Small-Degree Graphs
Changes to section 4.2.2
null
null
null
cs.DS cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Temporal graphs naturally model graphs whose underlying topology changes over time. Recently, the problems TEMPORAL VERTEX COVER (or TVC) and SLIDING-WINDOW TEMPORAL VERTEX COVER(or $\Delta$-TVC for time-windows of a fixed-length $\Delta$) have been established as natural extensions of the classic problem VERTEX COVE...
[ { "created": "Mon, 11 Apr 2022 02:31:00 GMT", "version": "v1" }, { "created": "Thu, 21 Mar 2024 06:21:45 GMT", "version": "v2" } ]
2024-03-22
[ [ "Hamm", "Thekla", "" ], [ "Klobas", "Nina", "" ], [ "Mertzios", "George B.", "" ], [ "Spirakis", "Paul G.", "" ] ]
Temporal graphs naturally model graphs whose underlying topology changes over time. Recently, the problems TEMPORAL VERTEX COVER (or TVC) and SLIDING-WINDOW TEMPORAL VERTEX COVER(or $\Delta$-TVC for time-windows of a fixed-length $\Delta$) have been established as natural extensions of the classic problem VERTEX COVER ...
2208.01892
Andrea Fronzetti Colladon PhD
C. Piselli, A. Fronzetti Colladon, L. Segneri, A. L. Pisello
Evaluating and improving social awareness of energy communities through semantic network analysis of online news
null
Renewable and Sustainable Energy Reviews 167, 112792 (2022)
10.1016/j.rser.2022.112792
null
cs.SI cs.CL physics.soc-ph
http://creativecommons.org/licenses/by-nc-nd/4.0/
The implementation of energy communities represents a cross-disciplinary phenomenon that has the potential to support the energy transition while fostering citizens' participation throughout the energy system and their exploitation of renewables. An important role is played by online information sources in engaging p...
[ { "created": "Wed, 3 Aug 2022 07:43:31 GMT", "version": "v1" } ]
2022-08-04
[ [ "Piselli", "C.", "" ], [ "Colladon", "A. Fronzetti", "" ], [ "Segneri", "L.", "" ], [ "Pisello", "A. L.", "" ] ]
The implementation of energy communities represents a cross-disciplinary phenomenon that has the potential to support the energy transition while fostering citizens' participation throughout the energy system and their exploitation of renewables. An important role is played by online information sources in engaging peo...
2006.10643
Nikolaos Karalias
Nikolaos Karalias, Andreas Loukas
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Combinatorial optimization problems are notoriously challenging for neural networks, especially in the absence of labeled instances. This work proposes an unsupervised learning framework for CO problems on graphs that can provide integral solutions of certified quality. Inspired by Erdos' probabilistic method, we use...
[ { "created": "Thu, 18 Jun 2020 16:13:36 GMT", "version": "v1" }, { "created": "Mon, 29 Jun 2020 15:58:55 GMT", "version": "v2" }, { "created": "Tue, 3 Nov 2020 19:42:18 GMT", "version": "v3" }, { "created": "Sun, 7 Mar 2021 20:10:53 GMT", "version": "v4" } ]
2021-03-09
[ [ "Karalias", "Nikolaos", "" ], [ "Loukas", "Andreas", "" ] ]
Combinatorial optimization problems are notoriously challenging for neural networks, especially in the absence of labeled instances. This work proposes an unsupervised learning framework for CO problems on graphs that can provide integral solutions of certified quality. Inspired by Erdos' probabilistic method, we use a...
2106.12131
Mana Ihori
Mana Ihori, Naoki Makishima, Tomohiro Tanaka, Akihiko Takashima, Shota Orihashi, Ryo Masumura
Zero-Shot Joint Modeling of Multiple Spoken-Text-Style Conversion Tasks using Switching Tokens
Accepted at INTERSPEECH 2021
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a novel spoken-text-style conversion method that can simultaneously execute multiple style conversion modules such as punctuation restoration and disfluency deletion without preparing matched datasets. In practice, transcriptions generated by automatic speech recognition systems are not high...
[ { "created": "Wed, 23 Jun 2021 02:53:14 GMT", "version": "v1" } ]
2021-06-24
[ [ "Ihori", "Mana", "" ], [ "Makishima", "Naoki", "" ], [ "Tanaka", "Tomohiro", "" ], [ "Takashima", "Akihiko", "" ], [ "Orihashi", "Shota", "" ], [ "Masumura", "Ryo", "" ] ]
In this paper, we propose a novel spoken-text-style conversion method that can simultaneously execute multiple style conversion modules such as punctuation restoration and disfluency deletion without preparing matched datasets. In practice, transcriptions generated by automatic speech recognition systems are not highly...
2007.13278
R Devon Hjelm
R Devon Hjelm and Philip Bachman
Representation Learning with Video Deep InfoMax
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Self-supervised learning has made unsupervised pretraining relevant again for difficult computer vision tasks. The most effective self-supervised methods involve prediction tasks based on features extracted from diverse views of the data. DeepInfoMax (DIM) is a self-supervised method which leverages the internal stru...
[ { "created": "Mon, 27 Jul 2020 02:28:47 GMT", "version": "v1" }, { "created": "Tue, 28 Jul 2020 01:27:14 GMT", "version": "v2" } ]
2020-07-29
[ [ "Hjelm", "R Devon", "" ], [ "Bachman", "Philip", "" ] ]
Self-supervised learning has made unsupervised pretraining relevant again for difficult computer vision tasks. The most effective self-supervised methods involve prediction tasks based on features extracted from diverse views of the data. DeepInfoMax (DIM) is a self-supervised method which leverages the internal struct...
1906.07930
Jia-Wei Chen
Rongfang Wang, Jia-Wei Chen, Yule Wang, Licheng Jiao, Mi Wang
SAR Image Change Detection via Spatial Metric Learning with an Improved Mahalanobis Distance
null
null
10.1109/LGRS.2019.2915251
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The log-ratio (LR) operator has been widely employed to generate the difference image for synthetic aperture radar (SAR) image change detection. However, the difference image generated by this pixel-wise operator can be subject to SAR images speckle and unavoidable registration errors between bitemporal SAR images. I...
[ { "created": "Wed, 19 Jun 2019 06:10:58 GMT", "version": "v1" } ]
2020-02-19
[ [ "Wang", "Rongfang", "" ], [ "Chen", "Jia-Wei", "" ], [ "Wang", "Yule", "" ], [ "Jiao", "Licheng", "" ], [ "Wang", "Mi", "" ] ]
The log-ratio (LR) operator has been widely employed to generate the difference image for synthetic aperture radar (SAR) image change detection. However, the difference image generated by this pixel-wise operator can be subject to SAR images speckle and unavoidable registration errors between bitemporal SAR images. In ...
1806.08337
Rena Bakhshi
Rena Bakhshi, Mary Hester, Jeroen Schot, Lode Kulik
Examining key features and platforms of IoT
11 pages, 7 figures, technical report
null
10.5281/zenodo.1296528
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
To help facilitate expertise in IoT technologies, NLeSC and SURF worked together on a project focusing on IoT applications and platforms. The information included in this case study show the results of NLeSC and SURF's investigation, examining different features offered by cloud and self-maintained IoT platforms with...
[ { "created": "Thu, 21 Jun 2018 17:25:18 GMT", "version": "v1" }, { "created": "Fri, 22 Jun 2018 21:29:42 GMT", "version": "v2" } ]
2018-06-26
[ [ "Bakhshi", "Rena", "" ], [ "Hester", "Mary", "" ], [ "Schot", "Jeroen", "" ], [ "Kulik", "Lode", "" ] ]
To help facilitate expertise in IoT technologies, NLeSC and SURF worked together on a project focusing on IoT applications and platforms. The information included in this case study show the results of NLeSC and SURF's investigation, examining different features offered by cloud and self-maintained IoT platforms with a...
2310.13328
Boqian Ma
Boqian Ma, Vir Nath Pathak, Lanping Liu, and Sushmita Ruj
One-Phase Batch Update on Sparse Merkle Trees for Rollups
21 pages, 8 figures
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A sparse Merkle tree is a Merkle tree with fixed height and indexed leaves given by a map from indices to leaf values. It allows for both efficient membership and non-membership proofs. It has been widely used as an authenticated data structure in various applications, such as layer-2 rollups for blockchains. zkSync ...
[ { "created": "Fri, 20 Oct 2023 07:43:54 GMT", "version": "v1" } ]
2023-10-23
[ [ "Ma", "Boqian", "" ], [ "Pathak", "Vir Nath", "" ], [ "Liu", "Lanping", "" ], [ "Ruj", "Sushmita", "" ] ]
A sparse Merkle tree is a Merkle tree with fixed height and indexed leaves given by a map from indices to leaf values. It allows for both efficient membership and non-membership proofs. It has been widely used as an authenticated data structure in various applications, such as layer-2 rollups for blockchains. zkSync Li...
cs/0605016
Yingbin Liang
Yingbin Liang and Venugopal V. Veeravalli
Cooperative Relay Broadcast Channels
Submitted to the IEEE Transactions on Information Theory, July 2005
null
null
null
cs.IT math.IT
null
The capacity regions are investigated for two relay broadcast channels (RBCs), where relay links are incorporated into standard two-user broadcast channels to support user cooperation. In the first channel, the Partially Cooperative Relay Broadcast Channel, only one user in the system can act as a relay and transmit ...
[ { "created": "Thu, 4 May 2006 19:13:50 GMT", "version": "v1" } ]
2007-07-13
[ [ "Liang", "Yingbin", "" ], [ "Veeravalli", "Venugopal V.", "" ] ]
The capacity regions are investigated for two relay broadcast channels (RBCs), where relay links are incorporated into standard two-user broadcast channels to support user cooperation. In the first channel, the Partially Cooperative Relay Broadcast Channel, only one user in the system can act as a relay and transmit to...
1603.02814
Chunhua Shen
Qi Wu, Chunhua Shen, Anton van den Hengel, Peng Wang, Anthony Dick
Image Captioning and Visual Question Answering Based on Attributes and External Knowledge
14 pages. arXiv admin note: text overlap with arXiv:1511.06973
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Much recent progress in Vision-to-Language problems has been achieved through a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). This approach does not explicitly represent high-level semantic concepts, but rather seeks to progress directly from image features to text. In this...
[ { "created": "Wed, 9 Mar 2016 08:56:45 GMT", "version": "v1" }, { "created": "Fri, 16 Dec 2016 11:44:34 GMT", "version": "v2" } ]
2016-12-19
[ [ "Wu", "Qi", "" ], [ "Shen", "Chunhua", "" ], [ "Hengel", "Anton van den", "" ], [ "Wang", "Peng", "" ], [ "Dick", "Anthony", "" ] ]
Much recent progress in Vision-to-Language problems has been achieved through a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). This approach does not explicitly represent high-level semantic concepts, but rather seeks to progress directly from image features to text. In this p...
2405.08852
Hao Wang
Hao Wang and Nao Li
A Click-Through Rate Prediction Method Based on Cross-Importance of Multi-Order Features
null
null
null
null
cs.LG cs.AI cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most current click-through rate prediction(CTR)models create explicit or implicit high-order feature crosses through Hadamard product or inner product, with little attention to the importance of feature crossing; only few models are either limited to the second-order explicit feature crossing, implicitly to high-orde...
[ { "created": "Tue, 14 May 2024 16:05:57 GMT", "version": "v1" } ]
2024-05-16
[ [ "Wang", "Hao", "" ], [ "Li", "Nao", "" ] ]
Most current click-through rate prediction(CTR)models create explicit or implicit high-order feature crosses through Hadamard product or inner product, with little attention to the importance of feature crossing; only few models are either limited to the second-order explicit feature crossing, implicitly to high-order ...
0905.0315
Lahatra Rakotondrainibe
Lahatra Rakotondrainibe (IETR), Yvan Kokar (IETR), Gheorghe Zaharia (IETR), Gha\"is El Zein (IETR)
Millimeter-Wave System for High Data Rate Indoor Communications
5 pages
ISSCS 2009, Iasi : Roumanie (2009)
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents the realization of a wireless Gigabit Ethernet communication system operating in the 60 GHz band. The system architecture uses a single carrier modulation. A differential encoded binary phase shift keying modulation and a differential demodulation scheme are adopted for the intermediate frequency ...
[ { "created": "Mon, 4 May 2009 07:20:31 GMT", "version": "v1" } ]
2010-11-10
[ [ "Rakotondrainibe", "Lahatra", "", "IETR" ], [ "Kokar", "Yvan", "", "IETR" ], [ "Zaharia", "Gheorghe", "", "IETR" ], [ "Zein", "Ghaïs El", "", "IETR" ] ]
This paper presents the realization of a wireless Gigabit Ethernet communication system operating in the 60 GHz band. The system architecture uses a single carrier modulation. A differential encoded binary phase shift keying modulation and a differential demodulation scheme are adopted for the intermediate frequency bl...
2205.04410
Sayan Biswas
Sayan Biswas, Kangsoo Jung, Catuscia Palamidessi
Tight Differential Privacy Blanket for Shuffle Model
Extended Abstract
null
10.1049/icp.2022.2041
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
With the recent bloom of focus on digital economy, the importance of personal data has seen a massive surge of late. Keeping pace with this trend, the model of data market is starting to emerge as a process to obtain high-quality personal information in exchange of incentives. To have a formal guarantee to protect th...
[ { "created": "Mon, 9 May 2022 16:35:54 GMT", "version": "v1" } ]
2022-11-11
[ [ "Biswas", "Sayan", "" ], [ "Jung", "Kangsoo", "" ], [ "Palamidessi", "Catuscia", "" ] ]
With the recent bloom of focus on digital economy, the importance of personal data has seen a massive surge of late. Keeping pace with this trend, the model of data market is starting to emerge as a process to obtain high-quality personal information in exchange of incentives. To have a formal guarantee to protect the ...
2206.14719
Zifeng Wang
Zifeng Wang and Jimeng Sun
Trial2Vec: Zero-Shot Clinical Trial Document Similarity Search using Self-Supervision
Findings of EMNLP 2022
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Clinical trials are essential for drug development but are extremely expensive and time-consuming to conduct. It is beneficial to study similar historical trials when designing a clinical trial. However, lengthy trial documents and lack of labeled data make trial similarity search difficult. We propose a zero-shot cl...
[ { "created": "Wed, 29 Jun 2022 15:37:11 GMT", "version": "v1" }, { "created": "Sun, 9 Oct 2022 19:43:16 GMT", "version": "v2" } ]
2022-10-11
[ [ "Wang", "Zifeng", "" ], [ "Sun", "Jimeng", "" ] ]
Clinical trials are essential for drug development but are extremely expensive and time-consuming to conduct. It is beneficial to study similar historical trials when designing a clinical trial. However, lengthy trial documents and lack of labeled data make trial similarity search difficult. We propose a zero-shot clin...
1609.06204
Alessio Palmero Aprosio
Alessio Palmero Aprosio and Giovanni Moretti
Italy goes to Stanford: a collection of CoreNLP modules for Italian
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this we paper present Tint, an easy-to-use set of fast, accurate and extendable Natural Language Processing modules for Italian. It is based on Stanford CoreNLP and is freely available as a standalone software or a library that can be integrated in an existing project.
[ { "created": "Tue, 20 Sep 2016 14:53:05 GMT", "version": "v1" }, { "created": "Thu, 13 Apr 2017 08:33:33 GMT", "version": "v2" } ]
2017-04-14
[ [ "Aprosio", "Alessio Palmero", "" ], [ "Moretti", "Giovanni", "" ] ]
In this we paper present Tint, an easy-to-use set of fast, accurate and extendable Natural Language Processing modules for Italian. It is based on Stanford CoreNLP and is freely available as a standalone software or a library that can be integrated in an existing project.
1805.02008
Xu Guo
Chang Liu, Yichao Zhu, Zhi Sun, Dingding Li, Zongliang Du, Weisheng Zhang, Xu Guo
An efficient Moving Morphable Component (MMC)-based approach for multi-resolution topology optimization
null
Structural and Multidisciplinary Optimization (2018) 58: 2455
10.1007/s00158-018-2114-0
null
cs.CE cond-mat.mtrl-sci
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the present work, a highly efficient Moving Morphable Component (MMC) based approach for multi-resolution topology optimization is proposed. In this approach, high-resolution optimization results can be obtained with much less number of degrees of freedoms (DOFs) and design variables since the finite element analy...
[ { "created": "Sat, 5 May 2018 05:38:53 GMT", "version": "v1" }, { "created": "Sun, 8 Jul 2018 04:56:17 GMT", "version": "v2" } ]
2018-12-10
[ [ "Liu", "Chang", "" ], [ "Zhu", "Yichao", "" ], [ "Sun", "Zhi", "" ], [ "Li", "Dingding", "" ], [ "Du", "Zongliang", "" ], [ "Zhang", "Weisheng", "" ], [ "Guo", "Xu", "" ] ]
In the present work, a highly efficient Moving Morphable Component (MMC) based approach for multi-resolution topology optimization is proposed. In this approach, high-resolution optimization results can be obtained with much less number of degrees of freedoms (DOFs) and design variables since the finite element analysi...
1904.02141
Yuying Zhu
Yuying Zhu, Guoxin Wang, B\"orje F. Karlsson
CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition
This paper is accepted by NAACL-HLT 2019. The code is available at https://github.com/microsoft/vert-papers/tree/master/papers/CAN-NER
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Named entity recognition (NER) in Chinese is essential but difficult because of the lack of natural delimiters. Therefore, Chinese Word Segmentation (CWS) is usually considered as the first step for Chinese NER. However, models based on word-level embeddings and lexicon features often suffer from segmentation errors ...
[ { "created": "Wed, 3 Apr 2019 17:56:38 GMT", "version": "v1" }, { "created": "Tue, 30 Apr 2019 08:10:55 GMT", "version": "v2" }, { "created": "Wed, 15 Jul 2020 14:10:33 GMT", "version": "v3" } ]
2020-07-16
[ [ "Zhu", "Yuying", "" ], [ "Wang", "Guoxin", "" ], [ "Karlsson", "Börje F.", "" ] ]
Named entity recognition (NER) in Chinese is essential but difficult because of the lack of natural delimiters. Therefore, Chinese Word Segmentation (CWS) is usually considered as the first step for Chinese NER. However, models based on word-level embeddings and lexicon features often suffer from segmentation errors an...
1309.5316
Brigitte Charnomordic
Aur\'elie Th\'ebaut (MISTEA), Thibault Scholash, Brigitte Charnomordic (MISTEA), Nadine Hilgert (MISTEA)
A modeling approach to design a software sensor and analyze agronomical features - Application to sap flow and grape quality relationship
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work proposes a framework using temporal data and domain knowledge in order to analyze complex agronomical features. The expertise is first formalized in an ontology, under the form of concepts and relationships between them, and then used in conjunction with raw data and mathematical models to design a software...
[ { "created": "Fri, 20 Sep 2013 16:41:43 GMT", "version": "v1" } ]
2013-09-23
[ [ "Thébaut", "Aurélie", "", "MISTEA" ], [ "Scholash", "Thibault", "", "MISTEA" ], [ "Charnomordic", "Brigitte", "", "MISTEA" ], [ "Hilgert", "Nadine", "", "MISTEA" ] ]
This work proposes a framework using temporal data and domain knowledge in order to analyze complex agronomical features. The expertise is first formalized in an ontology, under the form of concepts and relationships between them, and then used in conjunction with raw data and mathematical models to design a software s...
1909.13708
Rog\'erio De Lemos
Lionel Montrieux, Rogerio de Lemos, Chris Bailey
Engineering Self-adaptive Authorisation Infrastructures
A shorter version of the this paper appeared in: Montrieux L., de Lemos R., Bailey C. (2019) Challenges in Engineering Self-Adaptive Authorisation Infrastructures. In: Yu Y. et al. (eds) Engineering Adaptive Software Systems. Springer, Singapore
null
10.1007/978-981-13-2185-6_3
null
cs.CR cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As organisations expand and interconnect, authorisation infrastructures become increasingly difficult to manage. Several solutions have been proposed, including self-adaptive authorisation, where the access control policies are dynamically adapted at run-time to respond to misuse and malicious behaviour. The ultimate...
[ { "created": "Mon, 30 Sep 2019 13:59:09 GMT", "version": "v1" } ]
2019-10-01
[ [ "Montrieux", "Lionel", "" ], [ "de Lemos", "Rogerio", "" ], [ "Bailey", "Chris", "" ] ]
As organisations expand and interconnect, authorisation infrastructures become increasingly difficult to manage. Several solutions have been proposed, including self-adaptive authorisation, where the access control policies are dynamically adapted at run-time to respond to misuse and malicious behaviour. The ultimate g...
2304.04005
Seyed Mohammad Hosien Abedy Nejad
Seyed Mohammad Hossein Abedy Nejad, Mohammad Amin Behzadi, Abdolrahim Taheri
A new transformation for embedded convolutional neural network approach toward real-time servo motor overload fault-detection
null
null
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Overloading in DC servo motors is a major concern in industries, as many companies face the problem of finding expert operators, and also human monitoring may not be an effective solution. Therefore, this paper proposed an embedded Artificial intelligence (AI) approach using a Convolutional Neural Network (CNN) using...
[ { "created": "Sat, 8 Apr 2023 13:36:33 GMT", "version": "v1" } ]
2023-04-11
[ [ "Nejad", "Seyed Mohammad Hossein Abedy", "" ], [ "Behzadi", "Mohammad Amin", "" ], [ "Taheri", "Abdolrahim", "" ] ]
Overloading in DC servo motors is a major concern in industries, as many companies face the problem of finding expert operators, and also human monitoring may not be an effective solution. Therefore, this paper proposed an embedded Artificial intelligence (AI) approach using a Convolutional Neural Network (CNN) using a...
2005.07959
Benedek Rozemberczki
Benedek Rozemberczki and Rik Sarkar
Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models
Source code is available at: https://github.com/benedekrozemberczki/FEATHER
CIKM 2020
null
null
cs.LG cs.DM cs.SI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we propose a flexible notion of characteristic functions defined on graph vertices to describe the distribution of vertex features at multiple scales. We introduce FEATHER, a computationally efficient algorithm to calculate a specific variant of these characteristic functions where the probability weig...
[ { "created": "Sat, 16 May 2020 11:47:05 GMT", "version": "v1" }, { "created": "Sun, 16 Aug 2020 16:21:09 GMT", "version": "v2" } ]
2020-08-18
[ [ "Rozemberczki", "Benedek", "" ], [ "Sarkar", "Rik", "" ] ]
In this paper, we propose a flexible notion of characteristic functions defined on graph vertices to describe the distribution of vertex features at multiple scales. We introduce FEATHER, a computationally efficient algorithm to calculate a specific variant of these characteristic functions where the probability weight...
1809.10636
Anoop Toffy
Chae Young Lee, Anoop Toffy, Gue Jun Jung, Woo-Jin Han
Conditional WaveGAN
Preprint
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Generative models are successfully used for image synthesis in the recent years. But when it comes to other modalities like audio, text etc little progress has been made. Recent works focus on generating audio from a generative model in an unsupervised setting. We explore the possibility of using generative models co...
[ { "created": "Thu, 27 Sep 2018 16:56:23 GMT", "version": "v1" } ]
2018-09-30
[ [ "Lee", "Chae Young", "" ], [ "Toffy", "Anoop", "" ], [ "Jung", "Gue Jun", "" ], [ "Han", "Woo-Jin", "" ] ]
Generative models are successfully used for image synthesis in the recent years. But when it comes to other modalities like audio, text etc little progress has been made. Recent works focus on generating audio from a generative model in an unsupervised setting. We explore the possibility of using generative models cond...
1501.01829
Or Ordentlich
Or Ordentlich and Uri Erez
Performance Analysis and Optimal Filter Design for Sigma-Delta Modulation via Duality with DPCM
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sampling above the Nyquist rate is at the heart of sigma-delta modulation, where the increase in sampling rate is translated to a reduction in the overall (mean-squared-error) reconstruction distortion. This is attained by using a feedback filter at the encoder, in conjunction with a low-pass filter at the decoder. T...
[ { "created": "Thu, 8 Jan 2015 13:14:40 GMT", "version": "v1" }, { "created": "Tue, 9 Jun 2015 17:10:44 GMT", "version": "v2" } ]
2015-06-10
[ [ "Ordentlich", "Or", "" ], [ "Erez", "Uri", "" ] ]
Sampling above the Nyquist rate is at the heart of sigma-delta modulation, where the increase in sampling rate is translated to a reduction in the overall (mean-squared-error) reconstruction distortion. This is attained by using a feedback filter at the encoder, in conjunction with a low-pass filter at the decoder. The...
2009.14737
Keyu Tian
Keyu Tian, Chen Lin, Ming Sun, Luping Zhou, Junjie Yan, Wanli Ouyang
Improving Auto-Augment via Augmentation-Wise Weight Sharing
Accepted to NeurIPS 2020 (Poster)
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The recent progress on automatically searching augmentation policies has boosted the performance substantially for various tasks. A key component of automatic augmentation search is the evaluation process for a particular augmentation policy, which is utilized to return reward and usually runs thousands of times. A p...
[ { "created": "Wed, 30 Sep 2020 15:23:12 GMT", "version": "v1" }, { "created": "Thu, 22 Oct 2020 15:12:47 GMT", "version": "v2" } ]
2020-10-23
[ [ "Tian", "Keyu", "" ], [ "Lin", "Chen", "" ], [ "Sun", "Ming", "" ], [ "Zhou", "Luping", "" ], [ "Yan", "Junjie", "" ], [ "Ouyang", "Wanli", "" ] ]
The recent progress on automatically searching augmentation policies has boosted the performance substantially for various tasks. A key component of automatic augmentation search is the evaluation process for a particular augmentation policy, which is utilized to return reward and usually runs thousands of times. A pla...
2104.03071
Vijit Malik
Aditya Jindal, Ankur Gupta, Jaya Srivastava, Preeti Menghwani, Vijit Malik, Vishesh Kaushik, Ashutosh Modi
BreakingBERT@IITK at SemEval-2021 Task 9 : Statement Verification and Evidence Finding with Tables
Accepted at SemEval 2021 Task 9, 11 Pages (8 Pages main content+ 1 pages for references + 2 Pages Appendix)
null
null
null
cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
Recently, there has been an interest in factual verification and prediction over structured data like tables and graphs. To circumvent any false news incident, it is necessary to not only model and predict over structured data efficiently but also to explain those predictions. In this paper, as part of the SemEval-20...
[ { "created": "Wed, 7 Apr 2021 11:41:07 GMT", "version": "v1" }, { "created": "Sat, 10 Apr 2021 10:08:47 GMT", "version": "v2" } ]
2021-04-13
[ [ "Jindal", "Aditya", "" ], [ "Gupta", "Ankur", "" ], [ "Srivastava", "Jaya", "" ], [ "Menghwani", "Preeti", "" ], [ "Malik", "Vijit", "" ], [ "Kaushik", "Vishesh", "" ], [ "Modi", "Ashutosh", "" ] ]
Recently, there has been an interest in factual verification and prediction over structured data like tables and graphs. To circumvent any false news incident, it is necessary to not only model and predict over structured data efficiently but also to explain those predictions. In this paper, as part of the SemEval-2021...
2408.07614
Sergei Vassilvitskii
Kareem Amin, Alex Kulesza, Sergei Vassilvitskii
Practical Considerations for Differential Privacy
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Differential privacy is the gold standard for statistical data release. Used by governments, companies, and academics, its mathematically rigorous guarantees and worst-case assumptions on the strength and knowledge of attackers make it a robust and compelling framework for reasoning about privacy. However, even with ...
[ { "created": "Wed, 14 Aug 2024 15:28:28 GMT", "version": "v1" } ]
2024-08-15
[ [ "Amin", "Kareem", "" ], [ "Kulesza", "Alex", "" ], [ "Vassilvitskii", "Sergei", "" ] ]
Differential privacy is the gold standard for statistical data release. Used by governments, companies, and academics, its mathematically rigorous guarantees and worst-case assumptions on the strength and knowledge of attackers make it a robust and compelling framework for reasoning about privacy. However, even with la...
2311.18402
Xinwei Fu
Dan Song, Xinwei Fu, Weizhi Nie, Wenhui Li, Lanjun Wang, You Yang, Anan Liu
MV-CLIP: Multi-View CLIP for Zero-shot 3D Shape Recognition
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large-scale pre-trained models have demonstrated impressive performance in vision and language tasks within open-world scenarios. Due to the lack of comparable pre-trained models for 3D shapes, recent methods utilize language-image pre-training to realize zero-shot 3D shape recognition. However, due to the modality g...
[ { "created": "Thu, 30 Nov 2023 09:51:53 GMT", "version": "v1" }, { "created": "Wed, 17 Apr 2024 08:57:35 GMT", "version": "v2" } ]
2024-04-18
[ [ "Song", "Dan", "" ], [ "Fu", "Xinwei", "" ], [ "Nie", "Weizhi", "" ], [ "Li", "Wenhui", "" ], [ "Wang", "Lanjun", "" ], [ "Yang", "You", "" ], [ "Liu", "Anan", "" ] ]
Large-scale pre-trained models have demonstrated impressive performance in vision and language tasks within open-world scenarios. Due to the lack of comparable pre-trained models for 3D shapes, recent methods utilize language-image pre-training to realize zero-shot 3D shape recognition. However, due to the modality gap...
1902.08915
Yiwei Zhang
Yiwei Zhang, Chunbiao Zhu, Ge Li, Yuan Zhao, Haifeng Shen
Bi-Skip: A Motion Deblurring Network Using Self-paced Learning
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A fast and effective motion deblurring method has great application values in real life. This work presents an innovative approach in which a self-paced learning is combined with GAN to deblur image. First, We explain that a proper generator can be used as deep priors and point out that the solution for pixel-based l...
[ { "created": "Sun, 24 Feb 2019 10:28:04 GMT", "version": "v1" } ]
2019-02-26
[ [ "Zhang", "Yiwei", "" ], [ "Zhu", "Chunbiao", "" ], [ "Li", "Ge", "" ], [ "Zhao", "Yuan", "" ], [ "Shen", "Haifeng", "" ] ]
A fast and effective motion deblurring method has great application values in real life. This work presents an innovative approach in which a self-paced learning is combined with GAN to deblur image. First, We explain that a proper generator can be used as deep priors and point out that the solution for pixel-based los...
1801.04510
Jia Wu
Chenglong Dai, Jia Wu, Dechang Pi, Lin Cui
Brain EEG Time Series Selection: A Novel Graph-Based Approach for Classification
9 pages, 5 figures, Accepted by SDM-2018
null
null
null
cs.LG q-bio.NC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Brain Electroencephalography (EEG) classification is widely applied to analyze cerebral diseases in recent years. Unfortunately, invalid/noisy EEGs degrade the diagnosis performance and most previously developed methods ignore the necessity of EEG selection for classification. To this end, this paper proposes a novel...
[ { "created": "Sun, 14 Jan 2018 04:51:22 GMT", "version": "v1" }, { "created": "Fri, 9 Feb 2018 06:19:21 GMT", "version": "v2" } ]
2018-02-12
[ [ "Dai", "Chenglong", "" ], [ "Wu", "Jia", "" ], [ "Pi", "Dechang", "" ], [ "Cui", "Lin", "" ] ]
Brain Electroencephalography (EEG) classification is widely applied to analyze cerebral diseases in recent years. Unfortunately, invalid/noisy EEGs degrade the diagnosis performance and most previously developed methods ignore the necessity of EEG selection for classification. To this end, this paper proposes a novel m...
1203.0439
Pierre de Leusse
Pierre de Leusse, Panos Periorellis, Theo Dimitrakos and Srijith K. Nair
Self Managed Security Cell, a security model for the Internet of Things and Services
null
The First International Conference on Advances in Future Internet, AFIN 2009, IEEE Computer Society, June 18-23, 2009, Athens/Vouliagmeni, Greece, Best paper award
10.1109/AFIN.2009.15
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Internet of Things and Services is a rapidly growing concept that illustrates that the ever increasing amount of physical items of our daily life which become addressable through a network could be made more easily manageable and usable through the use of Services. This surge of exposed resources along with the l...
[ { "created": "Fri, 2 Mar 2012 12:17:20 GMT", "version": "v1" } ]
2012-03-05
[ [ "de Leusse", "Pierre", "" ], [ "Periorellis", "Panos", "" ], [ "Dimitrakos", "Theo", "" ], [ "Nair", "Srijith K.", "" ] ]
The Internet of Things and Services is a rapidly growing concept that illustrates that the ever increasing amount of physical items of our daily life which become addressable through a network could be made more easily manageable and usable through the use of Services. This surge of exposed resources along with the lev...
1912.03673
Matthias Rottmann
Matthias Rottmann, Kira Maag, Robin Chan, Fabian H\"uger, Peter Schlicht, Hanno Gottschalk
Detection of False Positive and False Negative Samples in Semantic Segmentation
null
null
null
null
cs.CV cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In recent years, deep learning methods have outperformed other methods in image recognition. This has fostered imagination of potential application of deep learning technology including safety relevant applications like the interpretation of medical images or autonomous driving. The passage from assistance of a human...
[ { "created": "Sun, 8 Dec 2019 13:04:06 GMT", "version": "v1" } ]
2019-12-10
[ [ "Rottmann", "Matthias", "" ], [ "Maag", "Kira", "" ], [ "Chan", "Robin", "" ], [ "Hüger", "Fabian", "" ], [ "Schlicht", "Peter", "" ], [ "Gottschalk", "Hanno", "" ] ]
In recent years, deep learning methods have outperformed other methods in image recognition. This has fostered imagination of potential application of deep learning technology including safety relevant applications like the interpretation of medical images or autonomous driving. The passage from assistance of a human d...
2103.17252
Giulia Dominijanni
Giulia Dominijanni, Solaiman Shokur, Gionata Salvietti, Sarah Buehler, Erica Palmerini, Simone Rossi, Frederique De Vignemont, Andrea D'Avella, Tamar R. Makin, Domenico Prattichizzo, Silvestro Micera
Enhancing human bodies with extra robotic arms and fingers: The Neural Resource Allocation Problem
null
null
null
null
cs.RO cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
The emergence of robot-based body augmentation promises exciting innovations that will inform robotics, human-machine interaction, and wearable electronics. Even though augmentative devices like extra robotic arms and fingers in many ways build on restorative technologies, they introduce unique challenges for bidirec...
[ { "created": "Wed, 31 Mar 2021 17:54:13 GMT", "version": "v1" } ]
2021-04-01
[ [ "Dominijanni", "Giulia", "" ], [ "Shokur", "Solaiman", "" ], [ "Salvietti", "Gionata", "" ], [ "Buehler", "Sarah", "" ], [ "Palmerini", "Erica", "" ], [ "Rossi", "Simone", "" ], [ "De Vignemont", "Frederique", ...
The emergence of robot-based body augmentation promises exciting innovations that will inform robotics, human-machine interaction, and wearable electronics. Even though augmentative devices like extra robotic arms and fingers in many ways build on restorative technologies, they introduce unique challenges for bidirecti...
2307.11654
H\'ector Carri\'on
H\'ector Carri\'on, Narges Norouzi
FEDD -- Fair, Efficient, and Diverse Diffusion-based Lesion Segmentation and Malignancy Classification
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-sa/4.0/
Skin diseases affect millions of people worldwide, across all ethnicities. Increasing diagnosis accessibility requires fair and accurate segmentation and classification of dermatology images. However, the scarcity of annotated medical images, especially for rare diseases and underrepresented skin tones, poses a chall...
[ { "created": "Fri, 21 Jul 2023 15:42:01 GMT", "version": "v1" } ]
2023-07-24
[ [ "Carrión", "Héctor", "" ], [ "Norouzi", "Narges", "" ] ]
Skin diseases affect millions of people worldwide, across all ethnicities. Increasing diagnosis accessibility requires fair and accurate segmentation and classification of dermatology images. However, the scarcity of annotated medical images, especially for rare diseases and underrepresented skin tones, poses a challen...
1808.00923
Valeria Vignudelli
Filippo Bonchi, Ana Sokolova, Valeria Vignudelli
The Theory of Traces for Systems with Nondeterminism, Probability, and Termination
null
Logical Methods in Computer Science, Volume 18, Issue 2 (June 17, 2022) lmcs:6261
10.46298/lmcs-18(2:21)2022
null
cs.LO
http://creativecommons.org/licenses/by/4.0/
This paper studies trace-based equivalences for systems combining nondeterministic and probabilistic choices. We show how trace semantics for such processes can be recovered by instantiating a coalgebraic construction known as the generalised powerset construction. We characterise and compare the resulting semantics ...
[ { "created": "Thu, 2 Aug 2018 17:19:29 GMT", "version": "v1" }, { "created": "Sat, 11 Aug 2018 14:01:53 GMT", "version": "v2" }, { "created": "Tue, 15 Jan 2019 11:44:53 GMT", "version": "v3" }, { "created": "Wed, 1 Apr 2020 11:07:38 GMT", "version": "v4" }, { "cre...
2023-06-22
[ [ "Bonchi", "Filippo", "" ], [ "Sokolova", "Ana", "" ], [ "Vignudelli", "Valeria", "" ] ]
This paper studies trace-based equivalences for systems combining nondeterministic and probabilistic choices. We show how trace semantics for such processes can be recovered by instantiating a coalgebraic construction known as the generalised powerset construction. We characterise and compare the resulting semantics to...
2107.01428
Konrad Dabrowski
Konrad K. Dabrowski and Peter Jonsson and Sebastian Ordyniak and George Osipov
Solving Infinite-Domain CSPs Using the Patchwork Property
34 pages, 2 figures. Parts of this article appeared in the proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI 2021)
null
null
null
cs.AI cs.CC cs.DS cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The constraint satisfaction problem (CSP) has important applications in computer science and AI. In particular, infinite-domain CSPs have been intensively used in subareas of AI such as spatio-temporal reasoning. Since constraint satisfaction is a computationally hard problem, much work has been devoted to identifyin...
[ { "created": "Sat, 3 Jul 2021 13:04:41 GMT", "version": "v1" } ]
2021-07-06
[ [ "Dabrowski", "Konrad K.", "" ], [ "Jonsson", "Peter", "" ], [ "Ordyniak", "Sebastian", "" ], [ "Osipov", "George", "" ] ]
The constraint satisfaction problem (CSP) has important applications in computer science and AI. In particular, infinite-domain CSPs have been intensively used in subareas of AI such as spatio-temporal reasoning. Since constraint satisfaction is a computationally hard problem, much work has been devoted to identifying ...
2208.14586
Yasunori Ishii Mr
Yuzuru Nakamura, Yasunori Ishii, Yuki Maruyama, Takayoshi Yamashita
Few-shot Adaptive Object Detection with Cross-Domain CutMix
Yuzuru Nakamura and Yasunori Ishii are equal contribution
null
null
null
cs.CV stat.ML
http://creativecommons.org/licenses/by/4.0/
In object detection, data amount and cost are a trade-off, and collecting a large amount of data in a specific domain is labor intensive. Therefore, existing large-scale datasets are used for pre-training. However, conventional transfer learning and domain adaptation cannot bridge the domain gap when the target domai...
[ { "created": "Wed, 31 Aug 2022 01:26:10 GMT", "version": "v1" } ]
2022-09-01
[ [ "Nakamura", "Yuzuru", "" ], [ "Ishii", "Yasunori", "" ], [ "Maruyama", "Yuki", "" ], [ "Yamashita", "Takayoshi", "" ] ]
In object detection, data amount and cost are a trade-off, and collecting a large amount of data in a specific domain is labor intensive. Therefore, existing large-scale datasets are used for pre-training. However, conventional transfer learning and domain adaptation cannot bridge the domain gap when the target domain ...
2001.06626
Hengyi Cai
Hengyi Cai, Hongshen Chen, Cheng Zhang, Yonghao Song, Xiaofang Zhao, Dawei Yin
Adaptive Parameterization for Neural Dialogue Generation
Published as a long paper in EMNLP 2019
null
10.18653/v1/D19-1188
null
cs.CL cs.IR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural conversation systems generate responses based on the sequence-to-sequence (SEQ2SEQ) paradigm. Typically, the model is equipped with a single set of learned parameters to generate responses for given input contexts. When confronting diverse conversations, its adaptability is rather limited and the model is henc...
[ { "created": "Sat, 18 Jan 2020 08:18:19 GMT", "version": "v1" } ]
2020-01-22
[ [ "Cai", "Hengyi", "" ], [ "Chen", "Hongshen", "" ], [ "Zhang", "Cheng", "" ], [ "Song", "Yonghao", "" ], [ "Zhao", "Xiaofang", "" ], [ "Yin", "Dawei", "" ] ]
Neural conversation systems generate responses based on the sequence-to-sequence (SEQ2SEQ) paradigm. Typically, the model is equipped with a single set of learned parameters to generate responses for given input contexts. When confronting diverse conversations, its adaptability is rather limited and the model is hence ...
1612.05794
Zeeshan Malik Khawar
Zeeshan Khawar Malik, Zain U. Hussain, Ziad Kobti, Charlie W. Lees, Newton Howard and Amir Hussain
A new recurrent neural network based predictive model for Faecal Calprotectin analysis: A retrospective study
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Faecal Calprotectin (FC) is a surrogate marker for intestinal inflammation, termed Inflammatory Bowel Disease (IBD), but not for cancer. In this retrospective study of 804 patients, an enhanced benchmark predictive model for analyzing FC is developed, based on a novel state-of-the-art Echo State Network (ESN), an adv...
[ { "created": "Sat, 17 Dec 2016 17:01:08 GMT", "version": "v1" } ]
2016-12-20
[ [ "Malik", "Zeeshan Khawar", "" ], [ "Hussain", "Zain U.", "" ], [ "Kobti", "Ziad", "" ], [ "Lees", "Charlie W.", "" ], [ "Howard", "Newton", "" ], [ "Hussain", "Amir", "" ] ]
Faecal Calprotectin (FC) is a surrogate marker for intestinal inflammation, termed Inflammatory Bowel Disease (IBD), but not for cancer. In this retrospective study of 804 patients, an enhanced benchmark predictive model for analyzing FC is developed, based on a novel state-of-the-art Echo State Network (ESN), an advan...
2105.06575
Daniel Larraz
Daniel Larraz, Micka\"el Laurent, Cesare Tinelli
Merit and Blame Assignment with Kind 2
null
null
null
null
cs.LO
http://creativecommons.org/licenses/by-nc-nd/4.0/
We introduce two new major features of the open-source model checker Kind 2 which provide traceability information between specification and design elements such as assumptions, guarantees, or other behavioral constraints in synchronous reactive system models. This new version of Kind 2 can identify minimal sets of d...
[ { "created": "Thu, 13 May 2021 22:40:09 GMT", "version": "v1" } ]
2021-05-17
[ [ "Larraz", "Daniel", "" ], [ "Laurent", "Mickaël", "" ], [ "Tinelli", "Cesare", "" ] ]
We introduce two new major features of the open-source model checker Kind 2 which provide traceability information between specification and design elements such as assumptions, guarantees, or other behavioral constraints in synchronous reactive system models. This new version of Kind 2 can identify minimal sets of des...
2405.14078
Han-Dong Lim
Han-Dong Lim, Donghwan Lee
A finite time analysis of distributed Q-learning
null
null
null
null
cs.AI cs.LG cs.MA
http://creativecommons.org/licenses/by/4.0/
Multi-agent reinforcement learning (MARL) has witnessed a remarkable surge in interest, fueled by the empirical success achieved in applications of single-agent reinforcement learning (RL). In this study, we consider a distributed Q-learning scenario, wherein a number of agents cooperatively solve a sequential decisi...
[ { "created": "Thu, 23 May 2024 00:52:38 GMT", "version": "v1" } ]
2024-05-24
[ [ "Lim", "Han-Dong", "" ], [ "Lee", "Donghwan", "" ] ]
Multi-agent reinforcement learning (MARL) has witnessed a remarkable surge in interest, fueled by the empirical success achieved in applications of single-agent reinforcement learning (RL). In this study, we consider a distributed Q-learning scenario, wherein a number of agents cooperatively solve a sequential decision...
2207.12939
Kai H\"appeler
Senay Cakir, Marcel Gau{\ss}, Kai H\"appeler, Yassine Ounajjar, Fabian Heinle and Reiner Marchthaler
Semantic Segmentation for Autonomous Driving: Model Evaluation, Dataset Generation, Perspective Comparison, and Real-Time Capability
8 pages, 7 figures, 9 tables
null
null
null
cs.CV cs.AI cs.RO
http://creativecommons.org/licenses/by-sa/4.0/
Environmental perception is an important aspect within the field of autonomous vehicles that provides crucial information about the driving domain, including but not limited to identifying clear driving areas and surrounding obstacles. Semantic segmentation is a widely used perception method for self-driving cars tha...
[ { "created": "Tue, 26 Jul 2022 14:45:44 GMT", "version": "v1" } ]
2022-07-27
[ [ "Cakir", "Senay", "" ], [ "Gauß", "Marcel", "" ], [ "Häppeler", "Kai", "" ], [ "Ounajjar", "Yassine", "" ], [ "Heinle", "Fabian", "" ], [ "Marchthaler", "Reiner", "" ] ]
Environmental perception is an important aspect within the field of autonomous vehicles that provides crucial information about the driving domain, including but not limited to identifying clear driving areas and surrounding obstacles. Semantic segmentation is a widely used perception method for self-driving cars that ...
1109.2112
Andrew King
Maria Chudnovsky, Andrew D. King, Matthieu Plumettaz and Paul Seymour
A local strengthening of Reed's {\omega}, \Delta, {\chi} conjecture for quasi-line graphs
18 pages, 1 figure
null
null
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Reed's $\omega$, $\Delta$, $\chi$ conjecture proposes that every graph satisfies $\chi\leq \lceil\frac 12(\Delta+1+\omega)\rceil$; it is known to hold for all claw-free graphs. In this paper we consider a local strengthening of this conjecture. We prove the local strengthening for line graphs, then note that previous...
[ { "created": "Fri, 9 Sep 2011 19:58:34 GMT", "version": "v1" }, { "created": "Tue, 29 Nov 2011 01:00:08 GMT", "version": "v2" } ]
2011-11-30
[ [ "Chudnovsky", "Maria", "" ], [ "King", "Andrew D.", "" ], [ "Plumettaz", "Matthieu", "" ], [ "Seymour", "Paul", "" ] ]
Reed's $\omega$, $\Delta$, $\chi$ conjecture proposes that every graph satisfies $\chi\leq \lceil\frac 12(\Delta+1+\omega)\rceil$; it is known to hold for all claw-free graphs. In this paper we consider a local strengthening of this conjecture. We prove the local strengthening for line graphs, then note that previous r...
2009.10444
Manuel Aiple
Manuel Aiple, Andre Schiele and Frans C.T. van der Helm
Self-Adapting Variable Impedance Actuator Control for Precision and Dynamic Tasks
12 pages, 13 figures, submitted to IEEE Transactions on Haptics
null
null
null
cs.RO cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Variable impedance actuators (VIAs) as tool devices for teleoperation could extend the range of tasks that humans can perform through a teleoperated robot by mimicking the change of upper limb stiffness that humans perform for different tasks, increasing the dynamic range of the robot. This requires appropriate imped...
[ { "created": "Tue, 22 Sep 2020 10:51:59 GMT", "version": "v1" } ]
2020-09-23
[ [ "Aiple", "Manuel", "" ], [ "Schiele", "Andre", "" ], [ "van der Helm", "Frans C. T.", "" ] ]
Variable impedance actuators (VIAs) as tool devices for teleoperation could extend the range of tasks that humans can perform through a teleoperated robot by mimicking the change of upper limb stiffness that humans perform for different tasks, increasing the dynamic range of the robot. This requires appropriate impedan...
1803.00047
Myle Ott
Myle Ott and Michael Auli and David Grangier and Marc'Aurelio Ranzato
Analyzing Uncertainty in Neural Machine Translation
ICML 2018
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine translation is a popular test bed for research in neural sequence-to-sequence models but despite much recent research, there is still a lack of understanding of these models. Practitioners report performance degradation with large beams, the under-estimation of rare words and a lack of diversity in the final ...
[ { "created": "Wed, 28 Feb 2018 19:33:24 GMT", "version": "v1" }, { "created": "Wed, 28 Mar 2018 15:10:32 GMT", "version": "v2" }, { "created": "Tue, 12 Jun 2018 11:12:43 GMT", "version": "v3" }, { "created": "Mon, 13 Aug 2018 17:13:23 GMT", "version": "v4" } ]
2018-08-14
[ [ "Ott", "Myle", "" ], [ "Auli", "Michael", "" ], [ "Grangier", "David", "" ], [ "Ranzato", "Marc'Aurelio", "" ] ]
Machine translation is a popular test bed for research in neural sequence-to-sequence models but despite much recent research, there is still a lack of understanding of these models. Practitioners report performance degradation with large beams, the under-estimation of rare words and a lack of diversity in the final tr...
2010.07990
Adrian de Wynter
Adrian de Wynter
An Algorithm for Learning Smaller Representations of Models With Scarce Data
Preprint. Under review
null
null
null
cs.LG cs.AI cs.DS
http://creativecommons.org/licenses/by/4.0/
We present a greedy algorithm for solving binary classification problems in situations where the dataset is either too small or not fully representative of the problem being solved, and obtaining more data is not possible. This algorithm is of particular interest when training small models that have trouble generaliz...
[ { "created": "Thu, 15 Oct 2020 19:17:51 GMT", "version": "v1" } ]
2020-10-19
[ [ "de Wynter", "Adrian", "" ] ]
We present a greedy algorithm for solving binary classification problems in situations where the dataset is either too small or not fully representative of the problem being solved, and obtaining more data is not possible. This algorithm is of particular interest when training small models that have trouble generalizin...
2111.11983
Michael Raskin
Michael Raskin
Modular population protocols
null
null
null
null
cs.DC
http://creativecommons.org/licenses/by-nc-sa/4.0/
Population protocols are a model of distributed computation intended for the study of networks of independent computing agents with dynamic communication structure. Each agent has a finite number of states, and communication opportunities occur nondeterministically, allowing the agents involved to change their states...
[ { "created": "Tue, 23 Nov 2021 16:24:45 GMT", "version": "v1" }, { "created": "Tue, 18 Jun 2024 16:50:03 GMT", "version": "v2" } ]
2024-06-19
[ [ "Raskin", "Michael", "" ] ]
Population protocols are a model of distributed computation intended for the study of networks of independent computing agents with dynamic communication structure. Each agent has a finite number of states, and communication opportunities occur nondeterministically, allowing the agents involved to change their states b...
1512.00242
Haibing Wu
Haibing Wu and Xiaodong Gu
Towards Dropout Training for Convolutional Neural Networks
This paper has been published in Neural Networks, http://www.sciencedirect.com/science/article/pii/S0893608015001446
Neural Networks 71: 1-10 (2015)
10.1016/j.neunet.2015.07.007
null
cs.LG cs.CV cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking ac...
[ { "created": "Tue, 1 Dec 2015 12:46:11 GMT", "version": "v1" } ]
2015-12-02
[ [ "Wu", "Haibing", "" ], [ "Gu", "Xiaodong", "" ] ]
Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking acti...
2404.08213
Jaewook Lee
Jaewook Lee, Jun Wang, Elizabeth Brown, Liam Chu, Sebastian S. Rodriguez, Jon E. Froehlich
GazePointAR: A Context-Aware Multimodal Voice Assistant for Pronoun Disambiguation in Wearable Augmented Reality
null
null
null
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
Voice assistants (VAs) like Siri and Alexa are transforming human-computer interaction; however, they lack awareness of users' spatiotemporal context, resulting in limited performance and unnatural dialogue. We introduce GazePointAR, a fully-functional context-aware VA for wearable augmented reality that leverages ey...
[ { "created": "Fri, 12 Apr 2024 02:50:43 GMT", "version": "v1" } ]
2024-04-15
[ [ "Lee", "Jaewook", "" ], [ "Wang", "Jun", "" ], [ "Brown", "Elizabeth", "" ], [ "Chu", "Liam", "" ], [ "Rodriguez", "Sebastian S.", "" ], [ "Froehlich", "Jon E.", "" ] ]
Voice assistants (VAs) like Siri and Alexa are transforming human-computer interaction; however, they lack awareness of users' spatiotemporal context, resulting in limited performance and unnatural dialogue. We introduce GazePointAR, a fully-functional context-aware VA for wearable augmented reality that leverages eye ...
2203.05085
Aloni Cohen
Aloni Cohen, Moon Duchin, JN Matthews, Bhushan Suwal
Census TopDown: The Impacts of Differential Privacy on Redistricting
2nd Symposium on Foundations of Responsible Computing (FORC 2021)
null
10.4230/LIPIcs.FORC.2021.5
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The 2020 Decennial Census will be released with a new disclosure avoidance system in place, putting differential privacy in the spotlight for a wide range of data users. We consider several key applications of Census data in redistricting, developing tools and demonstrations for practitioners who are concerned about ...
[ { "created": "Wed, 9 Mar 2022 23:28:53 GMT", "version": "v1" } ]
2022-03-11
[ [ "Cohen", "Aloni", "" ], [ "Duchin", "Moon", "" ], [ "Matthews", "JN", "" ], [ "Suwal", "Bhushan", "" ] ]
The 2020 Decennial Census will be released with a new disclosure avoidance system in place, putting differential privacy in the spotlight for a wide range of data users. We consider several key applications of Census data in redistricting, developing tools and demonstrations for practitioners who are concerned about th...
2012.03910
Sebastian Biewer
Sebastian Biewer, Rayna Dimitrova, Michael Fries, Maciej Gazda, Thomas Heinze, Holger Hermanns and Mohammad Reza Mousavi
Conformance Relations and Hyperproperties for Doping Detection in Time and Space
null
Logical Methods in Computer Science, Volume 18, Issue 1 (January 19, 2022) lmcs:6963
10.46298/lmcs-18(1:14)2022
null
cs.LO
http://creativecommons.org/licenses/by/4.0/
We present a novel and generalised notion of doping cleanness for cyber-physical systems that allows for perturbing the inputs and observing the perturbed outputs both in the time- and value-domains. We instantiate our definition using existing notions of conformance for cyber-physical systems. As a formal basis for ...
[ { "created": "Mon, 7 Dec 2020 18:41:17 GMT", "version": "v1" }, { "created": "Mon, 5 Jul 2021 15:40:23 GMT", "version": "v2" }, { "created": "Mon, 17 Jan 2022 09:01:15 GMT", "version": "v3" } ]
2023-06-22
[ [ "Biewer", "Sebastian", "" ], [ "Dimitrova", "Rayna", "" ], [ "Fries", "Michael", "" ], [ "Gazda", "Maciej", "" ], [ "Heinze", "Thomas", "" ], [ "Hermanns", "Holger", "" ], [ "Mousavi", "Mohammad Reza", "" ...
We present a novel and generalised notion of doping cleanness for cyber-physical systems that allows for perturbing the inputs and observing the perturbed outputs both in the time- and value-domains. We instantiate our definition using existing notions of conformance for cyber-physical systems. As a formal basis for mo...
2203.14825
Richard Shaw
Richard Shaw, Sibi Catley-Chandar, Ales Leonardis, Eduardo Perez-Pellitero
HDR Reconstruction from Bracketed Exposures and Events
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Reconstruction of high-quality HDR images is at the core of modern computational photography. Significant progress has been made with multi-frame HDR reconstruction methods, producing high-resolution, rich and accurate color reconstructions with high-frequency details. However, they are still prone to fail in dynamic...
[ { "created": "Mon, 28 Mar 2022 15:04:41 GMT", "version": "v1" } ]
2022-03-29
[ [ "Shaw", "Richard", "" ], [ "Catley-Chandar", "Sibi", "" ], [ "Leonardis", "Ales", "" ], [ "Perez-Pellitero", "Eduardo", "" ] ]
Reconstruction of high-quality HDR images is at the core of modern computational photography. Significant progress has been made with multi-frame HDR reconstruction methods, producing high-resolution, rich and accurate color reconstructions with high-frequency details. However, they are still prone to fail in dynamic o...
2303.01181
Maximilian Muschalik
Maximilian Muschalik, Fabian Fumagalli, Barbara Hammer, Eyke H\"ullermeier
iSAGE: An Incremental Version of SAGE for Online Explanation on Data Streams
null
null
10.1007/978-3-031-43418-1_26
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Existing methods for explainable artificial intelligence (XAI), including popular feature importance measures such as SAGE, are mostly restricted to the batch learning scenario. However, machine learning is often applied in dynamic environments, where data arrives continuously and learning must be done in an online m...
[ { "created": "Thu, 2 Mar 2023 11:51:54 GMT", "version": "v1" }, { "created": "Wed, 14 Jun 2023 18:10:04 GMT", "version": "v2" } ]
2023-10-31
[ [ "Muschalik", "Maximilian", "" ], [ "Fumagalli", "Fabian", "" ], [ "Hammer", "Barbara", "" ], [ "Hüllermeier", "Eyke", "" ] ]
Existing methods for explainable artificial intelligence (XAI), including popular feature importance measures such as SAGE, are mostly restricted to the batch learning scenario. However, machine learning is often applied in dynamic environments, where data arrives continuously and learning must be done in an online man...
1812.01393
Yongchao Xu
Yongchao Xu, Yukang Wang, Wei Zhou, Yongpan Wang, Zhibo Yang, Xiang Bai
TextField: Learning A Deep Direction Field for Irregular Scene Text Detection
To appear in IEEE TIP
null
10.1109/TIP.2019.2900589
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Scene text detection is an important step of scene text reading system. The main challenges lie on significantly varied sizes and aspect ratios, arbitrary orientations and shapes. Driven by recent progress in deep learning, impressive performances have been achieved for multi-oriented text detection. Yet, the perform...
[ { "created": "Tue, 4 Dec 2018 13:12:58 GMT", "version": "v1" }, { "created": "Mon, 29 Jul 2019 06:18:33 GMT", "version": "v2" } ]
2019-10-02
[ [ "Xu", "Yongchao", "" ], [ "Wang", "Yukang", "" ], [ "Zhou", "Wei", "" ], [ "Wang", "Yongpan", "" ], [ "Yang", "Zhibo", "" ], [ "Bai", "Xiang", "" ] ]
Scene text detection is an important step of scene text reading system. The main challenges lie on significantly varied sizes and aspect ratios, arbitrary orientations and shapes. Driven by recent progress in deep learning, impressive performances have been achieved for multi-oriented text detection. Yet, the performan...
1912.03696
Ziyang Fan
Xiao Han, Ziyang Fan, Chao Li, Zeyang Liu, L.Jay Guo
High-Freedom Inverse Design with Deep Neural Network for Metasurface Filter in the Visible
null
null
null
null
cs.OH eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In order to obtain a metasurface structure capable of filtering the light of a specific wavelength in the visible band, traditional method usually traverses the space consisting of possible designs, searching for a potentially satisfying device by performing iterative calculations to solve Maxwell's equations. In thi...
[ { "created": "Sun, 8 Dec 2019 15:28:36 GMT", "version": "v1" } ]
2019-12-10
[ [ "Han", "Xiao", "" ], [ "Fan", "Ziyang", "" ], [ "Li", "Chao", "" ], [ "Liu", "Zeyang", "" ], [ "Guo", "L. Jay", "" ] ]
In order to obtain a metasurface structure capable of filtering the light of a specific wavelength in the visible band, traditional method usually traverses the space consisting of possible designs, searching for a potentially satisfying device by performing iterative calculations to solve Maxwell's equations. In this ...
1205.2476
Benoit Otjacques
Beno\^it Otjacques, Micka\"el Stefas, Ma\"el Cornil, Fernand Feltz
Open Data Visualization: Keeping Traces of the Exploration Process
Presented at the First International Workshop On Open Data, WOD-2012 (http://arxiv.org/abs/1204.3726)
null
null
WOD/2012/NANTES/1
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper describes a system to support the visual exploration of Open Data. During his/her interactive experience with the graphics, the user can easily store the current complete state of the visualization application (called a viewpoint). Next, he/she can compose sequences of these viewpoints (called scenarios) t...
[ { "created": "Fri, 11 May 2012 10:46:50 GMT", "version": "v1" } ]
2012-05-14
[ [ "Otjacques", "Benoît", "" ], [ "Stefas", "Mickaël", "" ], [ "Cornil", "Maël", "" ], [ "Feltz", "Fernand", "" ] ]
This paper describes a system to support the visual exploration of Open Data. During his/her interactive experience with the graphics, the user can easily store the current complete state of the visualization application (called a viewpoint). Next, he/she can compose sequences of these viewpoints (called scenarios) tha...
1401.6333
Yang Yu
Yang Yu and Hong Qian
The Sampling-and-Learning Framework: A Statistical View of Evolutionary Algorithms
null
null
null
null
cs.NE cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Evolutionary algorithms (EAs), a large class of general purpose optimization algorithms inspired from the natural phenomena, are widely used in various industrial optimizations and often show excellent performance. This paper presents an attempt towards revealing their general power from a statistical view of EAs. By...
[ { "created": "Fri, 24 Jan 2014 13:10:11 GMT", "version": "v1" }, { "created": "Fri, 11 Apr 2014 14:29:27 GMT", "version": "v2" } ]
2014-04-14
[ [ "Yu", "Yang", "" ], [ "Qian", "Hong", "" ] ]
Evolutionary algorithms (EAs), a large class of general purpose optimization algorithms inspired from the natural phenomena, are widely used in various industrial optimizations and often show excellent performance. This paper presents an attempt towards revealing their general power from a statistical view of EAs. By s...
2408.00374
Xi Chen
Xi Chen, Rahul Bhadani, Larry Head
Conformal Trajectory Prediction with Multi-View Data Integration in Cooperative Driving
null
null
null
null
cs.AI cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Current research on trajectory prediction primarily relies on data collected by onboard sensors of an ego vehicle. With the rapid advancement in connected technologies, such as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, valuable information from alternate views becomes accessible via ...
[ { "created": "Thu, 1 Aug 2024 08:32:03 GMT", "version": "v1" }, { "created": "Fri, 2 Aug 2024 13:00:46 GMT", "version": "v2" } ]
2024-08-05
[ [ "Chen", "Xi", "" ], [ "Bhadani", "Rahul", "" ], [ "Head", "Larry", "" ] ]
Current research on trajectory prediction primarily relies on data collected by onboard sensors of an ego vehicle. With the rapid advancement in connected technologies, such as vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, valuable information from alternate views becomes accessible via wi...
1807.06414
Mehdi Ben Lazreg
Mehdi Ben Lazreg, Morten Goodwin
Combining a Context Aware Neural Network with a Denoising Autoencoder for Measuring String Similarities
null
null
null
null
cs.IR cs.AI cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Measuring similarities between strings is central for many established and fast growing research areas including information retrieval, biology, and natural language processing. The traditional approach for string similarity measurements is to define a metric over a word space that quantifies and sums up the differen...
[ { "created": "Mon, 16 Jul 2018 12:29:23 GMT", "version": "v1" } ]
2018-08-20
[ [ "Lazreg", "Mehdi Ben", "" ], [ "Goodwin", "Morten", "" ] ]
Measuring similarities between strings is central for many established and fast growing research areas including information retrieval, biology, and natural language processing. The traditional approach for string similarity measurements is to define a metric over a word space that quantifies and sums up the difference...
1402.5045
Lucas Paletta
Nicolas Sabouret, Haza\"el Jones, Magalie Ochs, Mathieu Chollet, Catherine Pelachaud
Expressing social attitudes in virtual agents for social training games
null
null
null
IDGEI/2014/11
cs.HC cs.AI cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The use of virtual agents in social coaching has increased rapidly in the last decade. In order to train the user in different situations than can occur in real life, the virtual agent should be able to express different social attitudes. In this paper, we propose a model of social attitudes that enables a virtual ag...
[ { "created": "Thu, 20 Feb 2014 15:41:26 GMT", "version": "v1" } ]
2014-02-21
[ [ "Sabouret", "Nicolas", "" ], [ "Jones", "Hazaël", "" ], [ "Ochs", "Magalie", "" ], [ "Chollet", "Mathieu", "" ], [ "Pelachaud", "Catherine", "" ] ]
The use of virtual agents in social coaching has increased rapidly in the last decade. In order to train the user in different situations than can occur in real life, the virtual agent should be able to express different social attitudes. In this paper, we propose a model of social attitudes that enables a virtual agen...
1611.01769
Dmitry Kosolobov
Dominik Kempa and Dmitry Kosolobov
LZ-End Parsing in Compressed Space
12 pages, 4 figure
null
10.1109/DCC.2017.73
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present an algorithm that constructs the LZ-End parsing (a variation of LZ77) of a given string of length $n$ in $O(n\log\ell)$ expected time and $O(z + \ell)$ space, where $z$ is the number of phrases in the parsing and $\ell$ is the length of the longest phrase. As an option, we can fix $\ell$ (e.g., to the size...
[ { "created": "Sun, 6 Nov 2016 12:47:25 GMT", "version": "v1" }, { "created": "Thu, 15 Jun 2017 21:38:21 GMT", "version": "v2" } ]
2020-12-15
[ [ "Kempa", "Dominik", "" ], [ "Kosolobov", "Dmitry", "" ] ]
We present an algorithm that constructs the LZ-End parsing (a variation of LZ77) of a given string of length $n$ in $O(n\log\ell)$ expected time and $O(z + \ell)$ space, where $z$ is the number of phrases in the parsing and $\ell$ is the length of the longest phrase. As an option, we can fix $\ell$ (e.g., to the size o...
2403.11495
Yile Chen
Yile Chen, Xiucheng Li, Gao Cong, Zhifeng Bao, Cheng Long
Semantic-Enhanced Representation Learning for Road Networks with Temporal Dynamics
null
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this study, we introduce a novel framework called Toast for learning general-purpose representations of road networks, along with its advanced counterpart DyToast, designed to enhance the integration of temporal dynamics to boost the performance of various time-sensitive downstream tasks. Specifically, we propose ...
[ { "created": "Mon, 18 Mar 2024 05:59:56 GMT", "version": "v1" } ]
2024-03-19
[ [ "Chen", "Yile", "" ], [ "Li", "Xiucheng", "" ], [ "Cong", "Gao", "" ], [ "Bao", "Zhifeng", "" ], [ "Long", "Cheng", "" ] ]
In this study, we introduce a novel framework called Toast for learning general-purpose representations of road networks, along with its advanced counterpart DyToast, designed to enhance the integration of temporal dynamics to boost the performance of various time-sensitive downstream tasks. Specifically, we propose to...
2106.12807
Vijay Lingam
Vijay Lingam, Rahul Ragesh, Arun Iyer, Sundararajan Sellamanickam
Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs
Accepted at Deep Learning on Graphs: Method and Applications (DLG-KDD 2021)
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph Neural Networks (GNNs) have shown excellent performance on graphs that exhibit strong homophily with respect to the node labels i.e. connected nodes have same labels. However, they perform poorly on heterophilic graphs. Recent approaches have typically modified aggregation schemes, designed adaptive graph filte...
[ { "created": "Thu, 24 Jun 2021 07:48:18 GMT", "version": "v1" } ]
2021-06-25
[ [ "Lingam", "Vijay", "" ], [ "Ragesh", "Rahul", "" ], [ "Iyer", "Arun", "" ], [ "Sellamanickam", "Sundararajan", "" ] ]
Graph Neural Networks (GNNs) have shown excellent performance on graphs that exhibit strong homophily with respect to the node labels i.e. connected nodes have same labels. However, they perform poorly on heterophilic graphs. Recent approaches have typically modified aggregation schemes, designed adaptive graph filters...
2211.11154
Wei Wei
Wei Wei, Daheng Li, Peng Wang, Yiming Li, Wanyi Li, Yongkang Luo, Jun Zhong
DVGG: Deep Variational Grasp Generation for Dextrous Manipulation
Accepted by Robotics and Automation Letters (RA-L, 2021)
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Grasping with anthropomorphic robotic hands involves much more hand-object interactions compared to parallel-jaw grippers. Modeling hand-object interactions is essential to the study of multi-finger hand dextrous manipulation. This work presents DVGG, an efficient grasp generation network that takes single-view obser...
[ { "created": "Mon, 21 Nov 2022 02:34:52 GMT", "version": "v1" } ]
2022-11-22
[ [ "Wei", "Wei", "" ], [ "Li", "Daheng", "" ], [ "Wang", "Peng", "" ], [ "Li", "Yiming", "" ], [ "Li", "Wanyi", "" ], [ "Luo", "Yongkang", "" ], [ "Zhong", "Jun", "" ] ]
Grasping with anthropomorphic robotic hands involves much more hand-object interactions compared to parallel-jaw grippers. Modeling hand-object interactions is essential to the study of multi-finger hand dextrous manipulation. This work presents DVGG, an efficient grasp generation network that takes single-view observa...
2402.04453
Tobias Vente
Tobias Vente, Joeran Beel
The Potential of AutoML for Recommender Systems
null
null
null
null
cs.IR cs.LG
http://creativecommons.org/licenses/by/4.0/
Automated Machine Learning (AutoML) has greatly advanced applications of Machine Learning (ML) including model compression, machine translation, and computer vision. Recommender Systems (RecSys) can be seen as an application of ML. Yet, AutoML has found little attention in the RecSys community; nor has RecSys found n...
[ { "created": "Tue, 6 Feb 2024 22:42:28 GMT", "version": "v1" } ]
2024-02-08
[ [ "Vente", "Tobias", "" ], [ "Beel", "Joeran", "" ] ]
Automated Machine Learning (AutoML) has greatly advanced applications of Machine Learning (ML) including model compression, machine translation, and computer vision. Recommender Systems (RecSys) can be seen as an application of ML. Yet, AutoML has found little attention in the RecSys community; nor has RecSys found not...
2403.07573
Masoud Shokrnezhad
Masoud Shokrnezhad, Hao Yu, Tarik Taleb, Richard Li, Kyunghan Lee, Jaeseung Song, and Cedric Westphal
Towards a Dynamic Future with Adaptable Computing and Network Convergence (ACNC)
null
null
null
null
cs.NI cs.AI cs.DC cs.ET cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the context of advancing 6G, a substantial paradigm shift is anticipated, highlighting comprehensive everything-to-everything interactions characterized by numerous connections and stringent adherence to Quality of Service/Experience (QoS/E) prerequisites. The imminent challenge stems from resource scarcity, promp...
[ { "created": "Tue, 12 Mar 2024 12:03:16 GMT", "version": "v1" } ]
2024-03-13
[ [ "Shokrnezhad", "Masoud", "" ], [ "Yu", "Hao", "" ], [ "Taleb", "Tarik", "" ], [ "Li", "Richard", "" ], [ "Lee", "Kyunghan", "" ], [ "Song", "Jaeseung", "" ], [ "Westphal", "Cedric", "" ] ]
In the context of advancing 6G, a substantial paradigm shift is anticipated, highlighting comprehensive everything-to-everything interactions characterized by numerous connections and stringent adherence to Quality of Service/Experience (QoS/E) prerequisites. The imminent challenge stems from resource scarcity, prompti...
2106.06519
Pakhi Bamdev
Karthik Ganesan, Pakhi Bamdev, Jaivarsan B, Amresh Venugopal, Abhinav Tushar
N-Best ASR Transformer: Enhancing SLU Performance using Multiple ASR Hypotheses
6 pages, 3 figures, Accepted at ACL 2021 as a main conference paper
null
null
null
cs.CL cs.LG cs.SD eess.AS
http://creativecommons.org/licenses/by-sa/4.0/
Spoken Language Understanding (SLU) systems parse speech into semantic structures like dialog acts and slots. This involves the use of an Automatic Speech Recognizer (ASR) to transcribe speech into multiple text alternatives (hypotheses). Transcription errors, common in ASRs, impact downstream SLU performance negativ...
[ { "created": "Fri, 11 Jun 2021 17:29:00 GMT", "version": "v1" } ]
2021-06-14
[ [ "Ganesan", "Karthik", "" ], [ "Bamdev", "Pakhi", "" ], [ "B", "Jaivarsan", "" ], [ "Venugopal", "Amresh", "" ], [ "Tushar", "Abhinav", "" ] ]
Spoken Language Understanding (SLU) systems parse speech into semantic structures like dialog acts and slots. This involves the use of an Automatic Speech Recognizer (ASR) to transcribe speech into multiple text alternatives (hypotheses). Transcription errors, common in ASRs, impact downstream SLU performance negativel...
1504.01358
Logan Washbourne
Logan Washbourne
A Survey of P2P Network Security
12 pages, 6 figures
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a review of peer-to-peer network security. Popular for sharing of multimedia files, these networks carry risks and vulnerabilities relating to data integrity, spyware, adware, and unwanted files. Further attacks include those of forgery, pollution, repudiation, membership and Eclipse attacks, neig...
[ { "created": "Mon, 6 Apr 2015 19:10:03 GMT", "version": "v1" } ]
2015-04-07
[ [ "Washbourne", "Logan", "" ] ]
This paper presents a review of peer-to-peer network security. Popular for sharing of multimedia files, these networks carry risks and vulnerabilities relating to data integrity, spyware, adware, and unwanted files. Further attacks include those of forgery, pollution, repudiation, membership and Eclipse attacks, neighb...
1912.02919
Stephanie L. Hyland
Stephanie L. Hyland and Shruti Tople
An Empirical Study on the Intrinsic Privacy of SGD
21 pages, 11 figures, 8 tables
null
null
null
cs.LG cs.CR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Introducing noise in the training of machine learning systems is a powerful way to protect individual privacy via differential privacy guarantees, but comes at a cost to utility. This work looks at whether the inherent randomness of stochastic gradient descent (SGD) could contribute to privacy, effectively reducing t...
[ { "created": "Thu, 5 Dec 2019 23:28:05 GMT", "version": "v1" }, { "created": "Thu, 5 Mar 2020 16:08:31 GMT", "version": "v2" }, { "created": "Thu, 25 Jun 2020 11:46:04 GMT", "version": "v3" }, { "created": "Mon, 28 Feb 2022 10:28:07 GMT", "version": "v4" } ]
2022-03-01
[ [ "Hyland", "Stephanie L.", "" ], [ "Tople", "Shruti", "" ] ]
Introducing noise in the training of machine learning systems is a powerful way to protect individual privacy via differential privacy guarantees, but comes at a cost to utility. This work looks at whether the inherent randomness of stochastic gradient descent (SGD) could contribute to privacy, effectively reducing the...
1801.02442
Ali Bereyhi
Ali Bereyhi, Mohammad Ali Sedaghat, Ralf R. M\"uller
Precoding via Approximate Message Passing with Instantaneous Signal Constraints
2018 International Zurich Seminar on Information and Communication (IZS) 5 pages and 2 figures
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a low complexity precoding algorithm based on the recently proposed Generalized Least Square Error (GLSE) scheme with generic penalty and support. The algorithm iteratively constructs the transmit vector via Approximate Message Passing (AMP). Using the asymptotic decoupling property of GLSE precod...
[ { "created": "Mon, 8 Jan 2018 14:33:23 GMT", "version": "v1" } ]
2018-01-09
[ [ "Bereyhi", "Ali", "" ], [ "Sedaghat", "Mohammad Ali", "" ], [ "Müller", "Ralf R.", "" ] ]
This paper proposes a low complexity precoding algorithm based on the recently proposed Generalized Least Square Error (GLSE) scheme with generic penalty and support. The algorithm iteratively constructs the transmit vector via Approximate Message Passing (AMP). Using the asymptotic decoupling property of GLSE precoder...
2407.01717
Ahmad AlMughrabi
Ahmad AlMughrabi, Umair Haroon, Ricardo Marques, Petia Radeva
VolETA: One- and Few-shot Food Volume Estimation
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Accurate food volume estimation is essential for dietary assessment, nutritional tracking, and portion control applications. We present VolETA, a sophisticated methodology for estimating food volume using 3D generative techniques. Our approach creates a scaled 3D mesh of food objects using one- or few-RGBD images. We...
[ { "created": "Mon, 1 Jul 2024 18:47:15 GMT", "version": "v1" } ]
2024-07-03
[ [ "AlMughrabi", "Ahmad", "" ], [ "Haroon", "Umair", "" ], [ "Marques", "Ricardo", "" ], [ "Radeva", "Petia", "" ] ]
Accurate food volume estimation is essential for dietary assessment, nutritional tracking, and portion control applications. We present VolETA, a sophisticated methodology for estimating food volume using 3D generative techniques. Our approach creates a scaled 3D mesh of food objects using one- or few-RGBD images. We s...
2212.11167
Yunlong Lin
Yunlong Lin, Zirui Li, Cheng Gong, Chao Lu, Xinwei Wang, Jianwei Gong
Continual Interactive Behavior Learning With Traffic Divergence Measurement: A Dynamic Gradient Scenario Memory Approach
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Developing autonomous vehicles (AVs) helps improve the road safety and traffic efficiency of intelligent transportation systems (ITS). Accurately predicting the trajectories of traffic participants is essential to the decision-making and motion planning of AVs in interactive scenarios. Recently, learning-based trajec...
[ { "created": "Wed, 21 Dec 2022 16:28:50 GMT", "version": "v1" } ]
2022-12-22
[ [ "Lin", "Yunlong", "" ], [ "Li", "Zirui", "" ], [ "Gong", "Cheng", "" ], [ "Lu", "Chao", "" ], [ "Wang", "Xinwei", "" ], [ "Gong", "Jianwei", "" ] ]
Developing autonomous vehicles (AVs) helps improve the road safety and traffic efficiency of intelligent transportation systems (ITS). Accurately predicting the trajectories of traffic participants is essential to the decision-making and motion planning of AVs in interactive scenarios. Recently, learning-based trajecto...
2107.10552
Konstantinos Makantasis
Konstantinos Makantasis, David Melhart, Antonios Liapis, Georgios N. Yannakakis
Privileged Information for Modeling Affect In The Wild
8 pages, 4 figures, 2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII)
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A key challenge of affective computing research is discovering ways to reliably transfer affect models that are built in the laboratory to real world settings, namely in the wild. The existing gap between in vitro and in vivo affect applications is mainly caused by limitations related to affect sensing including intr...
[ { "created": "Thu, 22 Jul 2021 10:09:16 GMT", "version": "v1" } ]
2021-07-23
[ [ "Makantasis", "Konstantinos", "" ], [ "Melhart", "David", "" ], [ "Liapis", "Antonios", "" ], [ "Yannakakis", "Georgios N.", "" ] ]
A key challenge of affective computing research is discovering ways to reliably transfer affect models that are built in the laboratory to real world settings, namely in the wild. The existing gap between in vitro and in vivo affect applications is mainly caused by limitations related to affect sensing including intrus...
2206.04381
Zheng Chang
Zheng Chang, Xinfeng Zhang, Shanshe Wang, Siwei Ma, and Wen Gao
STIP: A SpatioTemporal Information-Preserving and Perception-Augmented Model for High-Resolution Video Prediction
This journal paper is extended from our previous work accepted in CVPR2022 and has been submitted to IEEE Transactions on Multimedia
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Although significant achievements have been achieved by recurrent neural network (RNN) based video prediction methods, their performance in datasets with high resolutions is still far from satisfactory because of the information loss problem and the perception-insensitive mean square error (MSE) based loss functions....
[ { "created": "Thu, 9 Jun 2022 09:49:04 GMT", "version": "v1" } ]
2022-06-10
[ [ "Chang", "Zheng", "" ], [ "Zhang", "Xinfeng", "" ], [ "Wang", "Shanshe", "" ], [ "Ma", "Siwei", "" ], [ "Gao", "Wen", "" ] ]
Although significant achievements have been achieved by recurrent neural network (RNN) based video prediction methods, their performance in datasets with high resolutions is still far from satisfactory because of the information loss problem and the perception-insensitive mean square error (MSE) based loss functions. I...
2310.14450
Hans Hanley
Hans W. A. Hanley, Zakir Durumeric
TATA: Stance Detection via Topic-Agnostic and Topic-Aware Embeddings
Accepted to EMNLP 2023; Updated citations
null
null
null
cs.CL cs.CY cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Stance detection is important for understanding different attitudes and beliefs on the Internet. However, given that a passage's stance toward a given topic is often highly dependent on that topic, building a stance detection model that generalizes to unseen topics is difficult. In this work, we propose using contras...
[ { "created": "Sun, 22 Oct 2023 23:23:44 GMT", "version": "v1" }, { "created": "Mon, 13 Nov 2023 03:22:32 GMT", "version": "v2" }, { "created": "Thu, 8 Feb 2024 15:17:15 GMT", "version": "v3" } ]
2024-02-09
[ [ "Hanley", "Hans W. A.", "" ], [ "Durumeric", "Zakir", "" ] ]
Stance detection is important for understanding different attitudes and beliefs on the Internet. However, given that a passage's stance toward a given topic is often highly dependent on that topic, building a stance detection model that generalizes to unseen topics is difficult. In this work, we propose using contrasti...
1404.1518
Aske Plaat
Aske Plaat, Jonathan Schaeffer, Wim Pijls, Arie de Bruin
Nearly Optimal Minimax Tree Search?
null
null
null
null
cs.AI
http://creativecommons.org/licenses/by-nc-sa/3.0/
Knuth and Moore presented a theoretical lower bound on the number of leaves that any fixed-depth minimax tree-search algorithm traversing a uniform tree must explore, the so-called minimal tree. Since real-life minimax trees are not uniform, the exact size of this tree is not known for most applications. Further, mos...
[ { "created": "Sat, 5 Apr 2014 20:13:58 GMT", "version": "v1" } ]
2014-04-08
[ [ "Plaat", "Aske", "" ], [ "Schaeffer", "Jonathan", "" ], [ "Pijls", "Wim", "" ], [ "de Bruin", "Arie", "" ] ]
Knuth and Moore presented a theoretical lower bound on the number of leaves that any fixed-depth minimax tree-search algorithm traversing a uniform tree must explore, the so-called minimal tree. Since real-life minimax trees are not uniform, the exact size of this tree is not known for most applications. Further, most ...
2310.12755
Yuanduo Hong
Yuanduo Hong, Jue Wang, Weichao Sun, and Huihui Pan
Minimalist and High-Performance Semantic Segmentation with Plain Vision Transformers
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the wake of Masked Image Modeling (MIM), a diverse range of plain, non-hierarchical Vision Transformer (ViT) models have been pre-trained with extensive datasets, offering new paradigms and significant potential for semantic segmentation. Current state-of-the-art systems incorporate numerous inductive biases and e...
[ { "created": "Thu, 19 Oct 2023 14:01:40 GMT", "version": "v1" } ]
2023-10-20
[ [ "Hong", "Yuanduo", "" ], [ "Wang", "Jue", "" ], [ "Sun", "Weichao", "" ], [ "Pan", "Huihui", "" ] ]
In the wake of Masked Image Modeling (MIM), a diverse range of plain, non-hierarchical Vision Transformer (ViT) models have been pre-trained with extensive datasets, offering new paradigms and significant potential for semantic segmentation. Current state-of-the-art systems incorporate numerous inductive biases and emp...
2106.11483
Tong Guo
Tong Guo
A Comprehensive Comparison of Pre-training Language Models
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Recently, the development of pre-trained language models has brought natural language processing (NLP) tasks to the new state-of-the-art. In this paper we explore the efficiency of various pre-trained language models. We pre-train a list of transformer-based models with the same amount of text and the same training s...
[ { "created": "Tue, 22 Jun 2021 02:12:29 GMT", "version": "v1" }, { "created": "Fri, 30 Jul 2021 01:45:28 GMT", "version": "v2" }, { "created": "Wed, 20 Oct 2021 06:33:06 GMT", "version": "v3" }, { "created": "Fri, 12 Aug 2022 12:39:05 GMT", "version": "v4" }, { "c...
2023-07-27
[ [ "Guo", "Tong", "" ] ]
Recently, the development of pre-trained language models has brought natural language processing (NLP) tasks to the new state-of-the-art. In this paper we explore the efficiency of various pre-trained language models. We pre-train a list of transformer-based models with the same amount of text and the same training ste...
2305.09933
Steven Macenski
Steve Macenski, Alberto Soragna, Michael Carroll, Zhenpeng Ge
Impact of ROS 2 Node Composition in Robotic Systems
IEEE Robotics and Automation Letters, 2023
null
null
null
cs.RO
http://creativecommons.org/licenses/by/4.0/
The Robot Operating System 2 (ROS 2) is the second generation of ROS representing a step forward in the robotic framework. Several new types of nodes and executor models are integral to control where, how, and when information is processed in the computational graph. This paper explores and benchmarks one of these ne...
[ { "created": "Wed, 17 May 2023 03:39:32 GMT", "version": "v1" } ]
2023-05-18
[ [ "Macenski", "Steve", "" ], [ "Soragna", "Alberto", "" ], [ "Carroll", "Michael", "" ], [ "Ge", "Zhenpeng", "" ] ]
The Robot Operating System 2 (ROS 2) is the second generation of ROS representing a step forward in the robotic framework. Several new types of nodes and executor models are integral to control where, how, and when information is processed in the computational graph. This paper explores and benchmarks one of these new ...
2401.08179
Christodoulos Peltekis
Christodoulos Peltekis, Vasileios Titopoulos, Chrysostomos Nicopoulos, Giorgos Dimitrakopoulos
DeMM: A Decoupled Matrix Multiplication Engine Supporting Relaxed Structured Sparsity
Accepted on the IEEE Computer Architecture Letters
null
10.1109/LCA.2024.3355178
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep Learning (DL) has achieved unprecedented success in various application domains. Meanwhile, model pruning has emerged as a viable solution to reduce the footprint of DL models in mobile applications, without compromising their accuracy. To enable the matrix engines built for dense DL models to also handle their ...
[ { "created": "Tue, 16 Jan 2024 07:51:15 GMT", "version": "v1" } ]
2024-01-17
[ [ "Peltekis", "Christodoulos", "" ], [ "Titopoulos", "Vasileios", "" ], [ "Nicopoulos", "Chrysostomos", "" ], [ "Dimitrakopoulos", "Giorgos", "" ] ]
Deep Learning (DL) has achieved unprecedented success in various application domains. Meanwhile, model pruning has emerged as a viable solution to reduce the footprint of DL models in mobile applications, without compromising their accuracy. To enable the matrix engines built for dense DL models to also handle their pr...