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2312.11536
Litian Liu
Litian Liu and Yao Qin
Fast Decision Boundary based Out-of-Distribution Detector
ICML 2024 main conference paper
null
null
null
cs.LG eess.IV
http://creativecommons.org/licenses/by/4.0/
Efficient and effective Out-of-Distribution (OOD) detection is essential for the safe deployment of AI systems. Existing feature space methods, while effective, often incur significant computational overhead due to their reliance on auxiliary models built from training features. In this paper, we propose a computatio...
[ { "created": "Fri, 15 Dec 2023 19:50:32 GMT", "version": "v1" }, { "created": "Tue, 4 Jun 2024 16:01:27 GMT", "version": "v2" } ]
2024-06-05
[ [ "Liu", "Litian", "" ], [ "Qin", "Yao", "" ] ]
Efficient and effective Out-of-Distribution (OOD) detection is essential for the safe deployment of AI systems. Existing feature space methods, while effective, often incur significant computational overhead due to their reliance on auxiliary models built from training features. In this paper, we propose a computationa...
2210.04441
Suayb Arslan
Osman B. Guney and Suayb S. Arslan
Fault-Tolerant Strassen-Like Matrix Multiplication
6 pages, 2 figures
null
10.1109/SIU49456.2020.9302383
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this study, we propose a simple method for fault-tolerant Strassen-like matrix multiplications. The proposed method is based on using two distinct Strassen-like algorithms instead of replicating a given one. We have realized that using two different algorithms, new check relations arise resulting in more local com...
[ { "created": "Mon, 10 Oct 2022 05:18:22 GMT", "version": "v1" } ]
2022-10-11
[ [ "Guney", "Osman B.", "" ], [ "Arslan", "Suayb S.", "" ] ]
In this study, we propose a simple method for fault-tolerant Strassen-like matrix multiplications. The proposed method is based on using two distinct Strassen-like algorithms instead of replicating a given one. We have realized that using two different algorithms, new check relations arise resulting in more local compu...
0710.4828
Hossein Hajiabolhassan
Hossein Hajiabolhassan and Abbas Cheraghi
Bounds for Visual Cryptography Schemes
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we investigate the best pixel expansion of the various models of visual cryptography schemes. In this regard, we consider visual cryptography schemes introduced by Tzeng and Hu [13]. In such a model, only minimal qualified sets can recover the secret image and that the recovered secret image can be dar...
[ { "created": "Thu, 25 Oct 2007 12:17:15 GMT", "version": "v1" }, { "created": "Mon, 20 Oct 2008 01:49:21 GMT", "version": "v2" }, { "created": "Sat, 6 Jun 2009 07:08:14 GMT", "version": "v3" }, { "created": "Mon, 7 Sep 2009 03:55:32 GMT", "version": "v4" }, { "cre...
2009-12-03
[ [ "Hajiabolhassan", "Hossein", "" ], [ "Cheraghi", "Abbas", "" ] ]
In this paper, we investigate the best pixel expansion of the various models of visual cryptography schemes. In this regard, we consider visual cryptography schemes introduced by Tzeng and Hu [13]. In such a model, only minimal qualified sets can recover the secret image and that the recovered secret image can be darke...
1210.5454
Mina Guirguis
Mina Guirguis and George Atia
Stuck in Traffic (SiT) Attacks: A Framework for Identifying Stealthy Attacks that Cause Traffic Congestion
null
null
null
null
cs.NI cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in wireless technologies have enabled many new applications in Intelligent Transportation Systems (ITS) such as collision avoidance, cooperative driving, congestion avoidance, and traffic optimization. Due to the vulnerable nature of wireless communication against interference and intentional jamming,...
[ { "created": "Fri, 19 Oct 2012 15:48:54 GMT", "version": "v1" } ]
2012-10-22
[ [ "Guirguis", "Mina", "" ], [ "Atia", "George", "" ] ]
Recent advances in wireless technologies have enabled many new applications in Intelligent Transportation Systems (ITS) such as collision avoidance, cooperative driving, congestion avoidance, and traffic optimization. Due to the vulnerable nature of wireless communication against interference and intentional jamming, I...
2205.07149
Zishen Wan
Zishen Wan, Ashwin Lele, Bo Yu, Shaoshan Liu, Yu Wang, Vijay Janapa Reddi, Cong Hao, and Arijit Raychowdhury
Robotic Computing on FPGAs: Current Progress, Research Challenges, and Opportunities
2022 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), June 13-15, 2022, Incheon, Korea
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Robotic computing has reached a tipping point, with a myriad of robots (e.g., drones, self-driving cars, logistic robots) being widely applied in diverse scenarios. The continuous proliferation of robotics, however, critically depends on efficient computing substrates, driven by real-time requirements, robotic size-w...
[ { "created": "Sat, 14 May 2022 23:19:33 GMT", "version": "v1" } ]
2022-05-17
[ [ "Wan", "Zishen", "" ], [ "Lele", "Ashwin", "" ], [ "Yu", "Bo", "" ], [ "Liu", "Shaoshan", "" ], [ "Wang", "Yu", "" ], [ "Reddi", "Vijay Janapa", "" ], [ "Hao", "Cong", "" ], [ "Raychowdhury", "A...
Robotic computing has reached a tipping point, with a myriad of robots (e.g., drones, self-driving cars, logistic robots) being widely applied in diverse scenarios. The continuous proliferation of robotics, however, critically depends on efficient computing substrates, driven by real-time requirements, robotic size-wei...
1802.08562
Artsiom Sanakoyeu
Artsiom Sanakoyeu, Miguel A. Bautista, Bj\"orn Ommer
Deep Unsupervised Learning of Visual Similarities
arXiv admin note: text overlap with arXiv:1608.08792
Pattern Recognition Volume 78, June 2018, Pages 331-343
10.1016/j.patcog.2018.01.036
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Exemplar learning of visual similarities in an unsupervised manner is a problem of paramount importance to Computer Vision. In this context, however, the recent breakthrough in deep learning could not yet unfold its full potential. With only a single positive sample, a great imbalance between one positive and many ne...
[ { "created": "Thu, 22 Feb 2018 04:11:59 GMT", "version": "v1" } ]
2018-02-26
[ [ "Sanakoyeu", "Artsiom", "" ], [ "Bautista", "Miguel A.", "" ], [ "Ommer", "Björn", "" ] ]
Exemplar learning of visual similarities in an unsupervised manner is a problem of paramount importance to Computer Vision. In this context, however, the recent breakthrough in deep learning could not yet unfold its full potential. With only a single positive sample, a great imbalance between one positive and many nega...
2105.12309
Ayush Rajput
Sharan Balasubramanian, Ayush Rajput, Rodra W. Hascaryo, Chirag Rastogi, William R. Norris
Comparison of Dynamic and Kinematic Model Driven Extended Kalman Filters (EKF) for the Localization of Autonomous Underwater Vehicles
Preprint for ASME Journal for Mechanisms and Robotics, not peer reviewed yet
null
null
null
cs.RO cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs) are used for a wide variety of missions related to exploration and scientific research. Successful navigation by these systems requires a good localization system. Kalman filter based localization techniques have been prevalent since the earl...
[ { "created": "Wed, 26 May 2021 03:05:03 GMT", "version": "v1" } ]
2021-05-27
[ [ "Balasubramanian", "Sharan", "" ], [ "Rajput", "Ayush", "" ], [ "Hascaryo", "Rodra W.", "" ], [ "Rastogi", "Chirag", "" ], [ "Norris", "William R.", "" ] ]
Autonomous Underwater Vehicles (AUVs) and Remotely Operated Vehicles (ROVs) are used for a wide variety of missions related to exploration and scientific research. Successful navigation by these systems requires a good localization system. Kalman filter based localization techniques have been prevalent since the early ...
2304.01171
Qinglin Liu
Qinglin Liu, Xiaoqian Lv, Quanling Meng, Zonglin Li, Xiangyuan Lan, Shuo Yang, Shengping Zhang, Liqiang Nie
Revisiting Context Aggregation for Image Matting
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Traditional studies emphasize the significance of context information in improving matting performance. Consequently, deep learning-based matting methods delve into designing pooling or affinity-based context aggregation modules to achieve superior results. However, these modules cannot well handle the context scale ...
[ { "created": "Mon, 3 Apr 2023 17:40:30 GMT", "version": "v1" }, { "created": "Wed, 15 May 2024 02:24:58 GMT", "version": "v2" } ]
2024-05-16
[ [ "Liu", "Qinglin", "" ], [ "Lv", "Xiaoqian", "" ], [ "Meng", "Quanling", "" ], [ "Li", "Zonglin", "" ], [ "Lan", "Xiangyuan", "" ], [ "Yang", "Shuo", "" ], [ "Zhang", "Shengping", "" ], [ "Nie", ...
Traditional studies emphasize the significance of context information in improving matting performance. Consequently, deep learning-based matting methods delve into designing pooling or affinity-based context aggregation modules to achieve superior results. However, these modules cannot well handle the context scale sh...
1508.00040
Heba Aly
Heba Aly, Moustafa Youssef
An Analysis of Device-Free and Device-Based WiFi-Localization Systems
Published in International Journal of Ambient Computing and Intelligence (IJACI) - Volume 6 Issue 1, January 2014
null
10.4018/ijaci.2014010101
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
WiFi-based localization became one of the main indoor localization techniques due to the ubiquity of WiFi connectivity. However, indoor environments exhibit complex wireless propagation characteristics. Typically, these characteristics are captured by constructing a fingerprint map for the different locations in the ...
[ { "created": "Fri, 31 Jul 2015 21:42:02 GMT", "version": "v1" } ]
2015-08-04
[ [ "Aly", "Heba", "" ], [ "Youssef", "Moustafa", "" ] ]
WiFi-based localization became one of the main indoor localization techniques due to the ubiquity of WiFi connectivity. However, indoor environments exhibit complex wireless propagation characteristics. Typically, these characteristics are captured by constructing a fingerprint map for the different locations in the ar...
2306.04459
Zhen Zhang
Mengting Hu, Zhen Zhang, Shiwan Zhao, Minlie Huang and Bingzhe Wu
Uncertainty in Natural Language Processing: Sources, Quantification, and Applications
This work has been submitted to the IEEE for possible publication
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
As a main field of artificial intelligence, natural language processing (NLP) has achieved remarkable success via deep neural networks. Plenty of NLP tasks have been addressed in a unified manner, with various tasks being associated with each other through sharing the same paradigm. However, neural networks are black...
[ { "created": "Mon, 5 Jun 2023 06:46:53 GMT", "version": "v1" } ]
2023-06-08
[ [ "Hu", "Mengting", "" ], [ "Zhang", "Zhen", "" ], [ "Zhao", "Shiwan", "" ], [ "Huang", "Minlie", "" ], [ "Wu", "Bingzhe", "" ] ]
As a main field of artificial intelligence, natural language processing (NLP) has achieved remarkable success via deep neural networks. Plenty of NLP tasks have been addressed in a unified manner, with various tasks being associated with each other through sharing the same paradigm. However, neural networks are black b...
1910.10073
Maha Elbayad
Maha Elbayad and Jiatao Gu and Edouard Grave and Michael Auli
Depth-Adaptive Transformer
Published as a conference paper at ICLR 2020
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
State of the art sequence-to-sequence models for large scale tasks perform a fixed number of computations for each input sequence regardless of whether it is easy or hard to process. In this paper, we train Transformer models which can make output predictions at different stages of the network and we investigate diff...
[ { "created": "Tue, 22 Oct 2019 16:15:58 GMT", "version": "v1" }, { "created": "Mon, 16 Dec 2019 18:32:39 GMT", "version": "v2" }, { "created": "Thu, 19 Dec 2019 17:26:49 GMT", "version": "v3" }, { "created": "Fri, 14 Feb 2020 20:49:40 GMT", "version": "v4" } ]
2020-02-18
[ [ "Elbayad", "Maha", "" ], [ "Gu", "Jiatao", "" ], [ "Grave", "Edouard", "" ], [ "Auli", "Michael", "" ] ]
State of the art sequence-to-sequence models for large scale tasks perform a fixed number of computations for each input sequence regardless of whether it is easy or hard to process. In this paper, we train Transformer models which can make output predictions at different stages of the network and we investigate differ...
2302.12392
Mehala Balamurali
Mehala.Balamurali, Konstantin M. Seiler
Better Predict the Dynamic of Geometry of In-Pit Stockpiles Using Geospatial Data and Polygon Models
null
Proceedings of the 40th International Symposium on the Application of Computers and Operations Research in the Minerals Industries (APCOM, 2021), 257-267. Johannesburg: The Southern African Institute of Mining and Metallurgy, 2021
null
null
cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
Modelling stockpile is a key factor of a project economic and operation in mining, because not all the mined ores are not able to mill for many reasons. Further, the financial value of the ore in the stockpile needs to be reflected on the balance sheet. Therefore, automatically tracking the frontiers of the stockpile...
[ { "created": "Fri, 24 Feb 2023 01:46:13 GMT", "version": "v1" } ]
2023-02-27
[ [ "Balamurali", "Mehala.", "" ], [ "Seiler", "Konstantin M.", "" ] ]
Modelling stockpile is a key factor of a project economic and operation in mining, because not all the mined ores are not able to mill for many reasons. Further, the financial value of the ore in the stockpile needs to be reflected on the balance sheet. Therefore, automatically tracking the frontiers of the stockpile f...
2011.09140
Tomohide Shibata
Shogo Fujita and Tomohide Shibata and Manabu Okumura
Diverse and Non-redundant Answer Set Extraction on Community QA based on DPPs
COLING2020, 12 pages
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In community-based question answering (CQA) platforms, it takes time for a user to get useful information from among many answers. Although one solution is an answer ranking method, the user still needs to read through the top-ranked answers carefully. This paper proposes a new task of selecting a diverse and non-red...
[ { "created": "Wed, 18 Nov 2020 07:33:03 GMT", "version": "v1" } ]
2020-11-19
[ [ "Fujita", "Shogo", "" ], [ "Shibata", "Tomohide", "" ], [ "Okumura", "Manabu", "" ] ]
In community-based question answering (CQA) platforms, it takes time for a user to get useful information from among many answers. Although one solution is an answer ranking method, the user still needs to read through the top-ranked answers carefully. This paper proposes a new task of selecting a diverse and non-redun...
2403.15402
Sourojit Ghosh
Sourojit Ghosh, Sarah Coppola
This Class Isn't Designed For Me: Recognizing Ableist Trends In Design Education, And Redesigning For An Inclusive And Sustainable Future
Upcoming Publication, Design Research Society 2024
null
10.21606/drs.2024.1070.
null
cs.CY
http://creativecommons.org/licenses/by/4.0/
Traditional and currently-prevalent pedagogies of design perpetuate ableist and exclusionary notions of what it means to be a designer. In this paper, we trace such historically exclusionary norms of design education, and highlight modern-day instances from our own experiences as design educators in such epistemologi...
[ { "created": "Mon, 19 Feb 2024 20:14:34 GMT", "version": "v1" } ]
2024-08-06
[ [ "Ghosh", "Sourojit", "" ], [ "Coppola", "Sarah", "" ] ]
Traditional and currently-prevalent pedagogies of design perpetuate ableist and exclusionary notions of what it means to be a designer. In this paper, we trace such historically exclusionary norms of design education, and highlight modern-day instances from our own experiences as design educators in such epistemologies...
2111.05953
Giuseppina Carannante
Giuseppina Carannante, Dimah Dera, Ghulam Rasool, Nidhal C. Bouaynaya, and Lyudmila Mihaylova
Robust Learning via Ensemble Density Propagation in Deep Neural Networks
submitted to 2020 IEEE International Workshop on Machine Learning for Signal Processing
null
null
null
cs.LG cs.AI cs.CV math.PR
http://creativecommons.org/licenses/by/4.0/
Learning in uncertain, noisy, or adversarial environments is a challenging task for deep neural networks (DNNs). We propose a new theoretically grounded and efficient approach for robust learning that builds upon Bayesian estimation and Variational Inference. We formulate the problem of density propagation through la...
[ { "created": "Wed, 10 Nov 2021 21:26:08 GMT", "version": "v1" } ]
2021-11-12
[ [ "Carannante", "Giuseppina", "" ], [ "Dera", "Dimah", "" ], [ "Rasool", "Ghulam", "" ], [ "Bouaynaya", "Nidhal C.", "" ], [ "Mihaylova", "Lyudmila", "" ] ]
Learning in uncertain, noisy, or adversarial environments is a challenging task for deep neural networks (DNNs). We propose a new theoretically grounded and efficient approach for robust learning that builds upon Bayesian estimation and Variational Inference. We formulate the problem of density propagation through laye...
1109.0775
EPTCS
Azer Bestavros (Boston University), Assaf Kfoury (Boston University)
A Domain-Specific Language for Incremental and Modular Design of Large-Scale Verifiably-Safe Flow Networks (Preliminary Report)
In Proceedings DSL 2011, arXiv:1109.0323
EPTCS 66, 2011, pp. 24-47
10.4204/EPTCS.66.2
null
cs.PL cs.DC cs.LO cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We define a domain-specific language (DSL) to inductively assemble flow networks from small networks or modules to produce arbitrarily large ones, with interchangeable functionally-equivalent parts. Our small networks or modules are "small" only as the building blocks in this inductive definition (there is no limit o...
[ { "created": "Mon, 5 Sep 2011 01:56:15 GMT", "version": "v1" } ]
2011-09-06
[ [ "Bestavros", "Azer", "", "Boston University" ], [ "Kfoury", "Assaf", "", "Boston University" ] ]
We define a domain-specific language (DSL) to inductively assemble flow networks from small networks or modules to produce arbitrarily large ones, with interchangeable functionally-equivalent parts. Our small networks or modules are "small" only as the building blocks in this inductive definition (there is no limit on ...
1910.08810
Benjamin Ramtoula
Benjamin Ramtoula, Ricardo de Azambuja, Giovanni Beltrame
CAPRICORN: Communication Aware Place Recognition using Interpretable Constellations of Objects in Robot Networks
8 pages, 6 figures, 1 table. 2020 IEEE International Conference on Robotics and Automation (ICRA)
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Using multiple robots for exploring and mapping environments can provide improved robustness and performance, but it can be difficult to implement. In particular, limited communication bandwidth is a considerable constraint when a robot needs to determine if it has visited a location that was previously explored by a...
[ { "created": "Sat, 19 Oct 2019 17:52:04 GMT", "version": "v1" }, { "created": "Thu, 26 Mar 2020 00:32:21 GMT", "version": "v2" } ]
2020-03-27
[ [ "Ramtoula", "Benjamin", "" ], [ "de Azambuja", "Ricardo", "" ], [ "Beltrame", "Giovanni", "" ] ]
Using multiple robots for exploring and mapping environments can provide improved robustness and performance, but it can be difficult to implement. In particular, limited communication bandwidth is a considerable constraint when a robot needs to determine if it has visited a location that was previously explored by ano...
0711.4792
Sriram Sridharan
Sriram Sridharan and Sriram Vishwanath
On the Capacity of a Class of MIMO Cognitive Radios
13 pages, 8 figures, Accepted for publication in Journal of Selected Topics in Signal Processing (JSTSP) - Special Issue on Dynamic Spectrum Access
null
10.1109/JSTSP.2007.914890
null
cs.IT math.IT
null
Cognitive radios have been studied recently as a means to utilize spectrum in a more efficient manner. This paper focuses on the fundamental limits of operation of a MIMO cognitive radio network with a single licensed user and a single cognitive user. The channel setting is equivalent to an interference channel with ...
[ { "created": "Thu, 29 Nov 2007 18:28:00 GMT", "version": "v1" }, { "created": "Tue, 11 Dec 2007 20:54:34 GMT", "version": "v2" } ]
2009-11-13
[ [ "Sridharan", "Sriram", "" ], [ "Vishwanath", "Sriram", "" ] ]
Cognitive radios have been studied recently as a means to utilize spectrum in a more efficient manner. This paper focuses on the fundamental limits of operation of a MIMO cognitive radio network with a single licensed user and a single cognitive user. The channel setting is equivalent to an interference channel with de...
1909.02423
Vincent Labatut
Xavier Bost (LIA), Serigne Gueye (LIA), Vincent Labatut (LIA), Martha Larson (DMIR), Georges Linar\`es (LIA), Damien Malinas (CNELIAS), Rapha\"el Roth (CNELIAS)
Remembering Winter Was Coming: Character-Oriented Video Summaries of TV Series
null
Multimedia Tools and Applications, Springer, 2019, 78(24):35373-35399
10.1007/s11042-019-07969-4
null
cs.MM cs.IR cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Today's popular TV series tend to develop continuous, complex plots spanning several seasons, but are often viewed in controlled and discontinuous conditions. Consequently, most viewers need to be re-immersed in the story before watching a new season. Although discussions with friends and family can help, we observe ...
[ { "created": "Thu, 5 Sep 2019 14:00:45 GMT", "version": "v1" }, { "created": "Wed, 11 Dec 2019 15:24:57 GMT", "version": "v2" }, { "created": "Wed, 18 Mar 2020 07:10:52 GMT", "version": "v3" } ]
2020-03-19
[ [ "Bost", "Xavier", "", "LIA" ], [ "Gueye", "Serigne", "", "LIA" ], [ "Labatut", "Vincent", "", "LIA" ], [ "Larson", "Martha", "", "DMIR" ], [ "Linarès", "Georges", "", "LIA" ], [ "Malinas", "Damien", "",...
Today's popular TV series tend to develop continuous, complex plots spanning several seasons, but are often viewed in controlled and discontinuous conditions. Consequently, most viewers need to be re-immersed in the story before watching a new season. Although discussions with friends and family can help, we observe th...
1806.09279
Amritpal Kaur
Amritpal Kaur and Harkiran Kaur
Framework for Opinion Mining Approach to Augment Education System Performance
5 pages, 2 figures
http://ijitce.co.uk/vol8n6.aspx June 2018 Issue Vol.8 No.6
null
null
cs.IR cs.CL
http://creativecommons.org/licenses/by-nc-sa/4.0/
The extensive expansion growth of social networking sites allows the people to share their views and experiences freely with their peers on internet. Due to this, huge amount of data is generated on everyday basis which can be used for the opinion mining to extract the views of people in a particular field. Opinion m...
[ { "created": "Mon, 25 Jun 2018 04:17:44 GMT", "version": "v1" } ]
2018-06-26
[ [ "Kaur", "Amritpal", "" ], [ "Kaur", "Harkiran", "" ] ]
The extensive expansion growth of social networking sites allows the people to share their views and experiences freely with their peers on internet. Due to this, huge amount of data is generated on everyday basis which can be used for the opinion mining to extract the views of people in a particular field. Opinion min...
2402.00958
Ignacio F\'abregas
Ignacio F\'abregas and Miguel Palomino and David de Frutos-Escrig
Reflection and Preservation of Properties in Coalgebraic (bi)Simulations
null
Theoretical Aspects of Computing (ICTAC) 2007. Lecture Notes in Computer Science volume 4711
10.1007/978-3-540-75292-9\_16
null
cs.LO
http://creativecommons.org/licenses/by/4.0/
Our objective is to extend the standard results of preservation and reflection of properties by bisimulations to the coalgebraic setting, as well as to study under what conditions these results hold for simulations. The notion of bisimulation is the classical one, while for simulations we use that proposed by Hughes ...
[ { "created": "Thu, 1 Feb 2024 19:26:17 GMT", "version": "v1" } ]
2024-02-05
[ [ "Fábregas", "Ignacio", "" ], [ "Palomino", "Miguel", "" ], [ "de Frutos-Escrig", "David", "" ] ]
Our objective is to extend the standard results of preservation and reflection of properties by bisimulations to the coalgebraic setting, as well as to study under what conditions these results hold for simulations. The notion of bisimulation is the classical one, while for simulations we use that proposed by Hughes an...
1909.07140
Thomas Parnell
Dimitrios Sarigiannis, Thomas Parnell, Haris Pozidis
Weighted Sampling for Combined Model Selection and Hyperparameter Tuning
Accepted for presentation at The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI 2020)
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The combined algorithm selection and hyperparameter tuning (CASH) problem is characterized by large hierarchical hyperparameter spaces. Model-free hyperparameter tuning methods can explore such large spaces efficiently since they are highly parallelizable across multiple machines. When no prior knowledge or meta-data...
[ { "created": "Mon, 16 Sep 2019 12:01:12 GMT", "version": "v1" }, { "created": "Tue, 17 Sep 2019 07:57:49 GMT", "version": "v2" }, { "created": "Thu, 21 Nov 2019 12:19:57 GMT", "version": "v3" } ]
2019-11-22
[ [ "Sarigiannis", "Dimitrios", "" ], [ "Parnell", "Thomas", "" ], [ "Pozidis", "Haris", "" ] ]
The combined algorithm selection and hyperparameter tuning (CASH) problem is characterized by large hierarchical hyperparameter spaces. Model-free hyperparameter tuning methods can explore such large spaces efficiently since they are highly parallelizable across multiple machines. When no prior knowledge or meta-data e...
2004.14164
Xiaoqing Geng
Xiaoqing Geng, Xiwen Chen, Kenny Q. Zhu, Libin Shen, Yinggong Zhao
MICK: A Meta-Learning Framework for Few-shot Relation Classification with Small Training Data
null
CIKM 2020: The 29th ACM International Conference on Information and Knowledge Management
10.1145/3340531.3411858
null
cs.CL cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Few-shot relation classification seeks to classify incoming query instances after meeting only few support instances. This ability is gained by training with large amount of in-domain annotated data. In this paper, we tackle an even harder problem by further limiting the amount of data available at training time. We ...
[ { "created": "Sun, 26 Apr 2020 06:23:38 GMT", "version": "v1" }, { "created": "Mon, 14 Dec 2020 15:54:51 GMT", "version": "v2" } ]
2020-12-15
[ [ "Geng", "Xiaoqing", "" ], [ "Chen", "Xiwen", "" ], [ "Zhu", "Kenny Q.", "" ], [ "Shen", "Libin", "" ], [ "Zhao", "Yinggong", "" ] ]
Few-shot relation classification seeks to classify incoming query instances after meeting only few support instances. This ability is gained by training with large amount of in-domain annotated data. In this paper, we tackle an even harder problem by further limiting the amount of data available at training time. We pr...
2303.13355
Son Tran
Son Quoc Tran, Phong Nguyen-Thuan Do, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
Revealing Weaknesses of Vietnamese Language Models Through Unanswerable Questions in Machine Reading Comprehension
Accepted at The 2023 EACL Student Research Workshop
null
null
null
cs.CL cs.AI
http://creativecommons.org/publicdomain/zero/1.0/
Although the curse of multilinguality significantly restricts the language abilities of multilingual models in monolingual settings, researchers now still have to rely on multilingual models to develop state-of-the-art systems in Vietnamese Machine Reading Comprehension. This difficulty in researching is because of t...
[ { "created": "Thu, 16 Mar 2023 20:32:58 GMT", "version": "v1" } ]
2023-03-24
[ [ "Tran", "Son Quoc", "" ], [ "Do", "Phong Nguyen-Thuan", "" ], [ "Van Nguyen", "Kiet", "" ], [ "Nguyen", "Ngan Luu-Thuy", "" ] ]
Although the curse of multilinguality significantly restricts the language abilities of multilingual models in monolingual settings, researchers now still have to rely on multilingual models to develop state-of-the-art systems in Vietnamese Machine Reading Comprehension. This difficulty in researching is because of the...
1905.12688
Graham Neubig
Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, Zirui Li, Yuyan Zhang, Mengzhou Xia, Shruti Rijhwani, Junxian He, Zhisong Zhang, Xuezhe Ma, Antonios Anastasopoulos, Patrick Littell, Graham Neubig
Choosing Transfer Languages for Cross-Lingual Learning
Proceedings of ACL 2019
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on low-resource languages. However, given a particular task language, it is not clear which language...
[ { "created": "Wed, 29 May 2019 19:19:47 GMT", "version": "v1" }, { "created": "Fri, 7 Jun 2019 03:37:25 GMT", "version": "v2" } ]
2019-06-10
[ [ "Lin", "Yu-Hsiang", "" ], [ "Chen", "Chian-Yu", "" ], [ "Lee", "Jean", "" ], [ "Li", "Zirui", "" ], [ "Zhang", "Yuyan", "" ], [ "Xia", "Mengzhou", "" ], [ "Rijhwani", "Shruti", "" ], [ "He", "Ju...
Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on low-resource languages. However, given a particular task language, it is not clear which language t...
1403.6167
Utkarsh R. Patel
Utkarsh R. Patel and Piero Triverio
MoM-SO: a Complete Method for Computing the Impedance of Cable Systems Including Skin, Proximity, and Ground Return Effects
This paper has now been published in the IEEE Trans. on Power Delivery in Oct. 2015, vol. 30, no. 5, pp. 2110-2118. DOI: 10.1109/TPWRD.2014.2378594
IEEE Trans. on Power Delivery in Oct. 2015, vol. 30, no. 5, pp. 2110-2118
10.1109/TPWRD.2014.2378594
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The availability of accurate and broadband models for underground and submarine cable systems is of paramount importance for the correct prediction of electromagnetic transients in power grids. Recently, we proposed the MoM-SO method for extracting the series impedance of power cables while accounting for skin and pr...
[ { "created": "Mon, 24 Mar 2014 22:03:07 GMT", "version": "v1" }, { "created": "Tue, 29 Apr 2014 18:26:42 GMT", "version": "v2" }, { "created": "Mon, 28 Sep 2015 15:51:35 GMT", "version": "v3" } ]
2016-06-29
[ [ "Patel", "Utkarsh R.", "" ], [ "Triverio", "Piero", "" ] ]
The availability of accurate and broadband models for underground and submarine cable systems is of paramount importance for the correct prediction of electromagnetic transients in power grids. Recently, we proposed the MoM-SO method for extracting the series impedance of power cables while accounting for skin and prox...
2002.01913
Augusto Luis Ballardini PhD
Augusto Luis Ballardini, Daniele Cattaneo, Rub\'en Izquierdo, Ignacio Parra Alonso, Andrea Piazzoni, Miguel \'Angel Sotelo, Domenico Giorgio Sorrenti
Vehicle Ego-Lane Estimation with Sensor Failure Modeling
preprint
null
null
null
cs.RO cs.CV cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
We present a probabilistic ego-lane estimation algorithm for highway-like scenarios that is designed to increase the accuracy of the ego-lane estimate, which can be obtained relying only on a noisy line detector and tracker. The contribution relies on a Hidden Markov Model (HMM) with a transient failure model. The pr...
[ { "created": "Wed, 5 Feb 2020 18:32:00 GMT", "version": "v1" }, { "created": "Thu, 6 Feb 2020 15:06:49 GMT", "version": "v2" } ]
2020-02-07
[ [ "Ballardini", "Augusto Luis", "" ], [ "Cattaneo", "Daniele", "" ], [ "Izquierdo", "Rubén", "" ], [ "Alonso", "Ignacio Parra", "" ], [ "Piazzoni", "Andrea", "" ], [ "Sotelo", "Miguel Ángel", "" ], [ "Sorrenti", ...
We present a probabilistic ego-lane estimation algorithm for highway-like scenarios that is designed to increase the accuracy of the ego-lane estimate, which can be obtained relying only on a noisy line detector and tracker. The contribution relies on a Hidden Markov Model (HMM) with a transient failure model. The prop...
2403.05221
Wolfgang H\"ohl
Wolfgang H\"ohl
Understanding Hybrid Spaces: Designing a Spacetime Model to Represent Dynamic Topologies of Hybrid Spaces
82 pages, 22 figures, 19 tables
null
null
null
cs.CY
http://creativecommons.org/licenses/by-nc-nd/4.0/
This paper develops a spatiotemporal model for the visualization of dynamic topologies of hybrid spaces. The visualization of spatiotemporal data is a well-known problem, for example in digital twins in urban planning. There is also a lack of a basic ontology for understanding hybrid spaces. The developed spatiotempo...
[ { "created": "Fri, 8 Mar 2024 11:18:27 GMT", "version": "v1" } ]
2024-03-11
[ [ "Höhl", "Wolfgang", "" ] ]
This paper develops a spatiotemporal model for the visualization of dynamic topologies of hybrid spaces. The visualization of spatiotemporal data is a well-known problem, for example in digital twins in urban planning. There is also a lack of a basic ontology for understanding hybrid spaces. The developed spatiotempora...
1903.12266
Maciej Zamorski
Maciej Zamorski, Adrian Zdobylak, Maciej Zi\k{e}ba, Jerzy \'Swi\k{a}tek
Generative Adversarial Networks: recent developments
10 pages
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In traditional generative modeling, good data representation is very often a base for a good machine learning model. It can be linked to good representations encoding more explanatory factors that are hidden in the original data. With the invention of Generative Adversarial Networks (GANs), a subclass of generative m...
[ { "created": "Sat, 16 Mar 2019 18:10:35 GMT", "version": "v1" } ]
2019-04-01
[ [ "Zamorski", "Maciej", "" ], [ "Zdobylak", "Adrian", "" ], [ "Zięba", "Maciej", "" ], [ "Świątek", "Jerzy", "" ] ]
In traditional generative modeling, good data representation is very often a base for a good machine learning model. It can be linked to good representations encoding more explanatory factors that are hidden in the original data. With the invention of Generative Adversarial Networks (GANs), a subclass of generative mod...
2207.02295
Benjamin Fuhrer
Benjamin Fuhrer, Yuval Shpigelman, Chen Tessler, Shie Mannor, Gal Chechik, Eitan Zahavi, Gal Dalal
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs
null
null
10.1109/CCGrid57682.2023.00039
null
cs.NI cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As communication protocols evolve, datacenter network utilization increases. As a result, congestion is more frequent, causing higher latency and packet loss. Combined with the increasing complexity of workloads, manual design of congestion control (CC) algorithms becomes extremely difficult. This calls for the devel...
[ { "created": "Tue, 5 Jul 2022 20:42:24 GMT", "version": "v1" }, { "created": "Thu, 1 Dec 2022 20:56:23 GMT", "version": "v2" }, { "created": "Tue, 3 Jan 2023 16:00:27 GMT", "version": "v3" }, { "created": "Sun, 30 Apr 2023 13:12:49 GMT", "version": "v4" }, { "crea...
2024-06-04
[ [ "Fuhrer", "Benjamin", "" ], [ "Shpigelman", "Yuval", "" ], [ "Tessler", "Chen", "" ], [ "Mannor", "Shie", "" ], [ "Chechik", "Gal", "" ], [ "Zahavi", "Eitan", "" ], [ "Dalal", "Gal", "" ] ]
As communication protocols evolve, datacenter network utilization increases. As a result, congestion is more frequent, causing higher latency and packet loss. Combined with the increasing complexity of workloads, manual design of congestion control (CC) algorithms becomes extremely difficult. This calls for the develop...
2404.08887
Jinhao Pan
Jinhao Pan, Ziwei Zhu, Jianling Wang, Allen Lin, James Caverlee
Countering Mainstream Bias via End-to-End Adaptive Local Learning
ECIR 2024
In European Conference on Information Retrieval 2024, vol 14612 (pp. 75-89)
10.1007/978-3-031-56069-9_6
null
cs.IR cs.LG
http://creativecommons.org/licenses/by/4.0/
Collaborative filtering (CF) based recommendations suffer from mainstream bias -- where mainstream users are favored over niche users, leading to poor recommendation quality for many long-tail users. In this paper, we identify two root causes of this mainstream bias: (i) discrepancy modeling, whereby CF algorithms fo...
[ { "created": "Sat, 13 Apr 2024 03:17:33 GMT", "version": "v1" } ]
2024-04-16
[ [ "Pan", "Jinhao", "" ], [ "Zhu", "Ziwei", "" ], [ "Wang", "Jianling", "" ], [ "Lin", "Allen", "" ], [ "Caverlee", "James", "" ] ]
Collaborative filtering (CF) based recommendations suffer from mainstream bias -- where mainstream users are favored over niche users, leading to poor recommendation quality for many long-tail users. In this paper, we identify two root causes of this mainstream bias: (i) discrepancy modeling, whereby CF algorithms focu...
2211.12173
Poulami Sinhamahapatra
Poulami Sinhamahapatra, Lena Heidemann, Maureen Monnet, Karsten Roscher
Towards Human-Interpretable Prototypes for Visual Assessment of Image Classification Models
null
Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 5: VISAPP, 878-887, 2023
10.5220/0011894900003417
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
Explaining black-box Artificial Intelligence (AI) models is a cornerstone for trustworthy AI and a prerequisite for its use in safety critical applications such that AI models can reliably assist humans in critical decisions. However, instead of trying to explain our models post-hoc, we need models which are interpre...
[ { "created": "Tue, 22 Nov 2022 11:01:22 GMT", "version": "v1" } ]
2023-03-10
[ [ "Sinhamahapatra", "Poulami", "" ], [ "Heidemann", "Lena", "" ], [ "Monnet", "Maureen", "" ], [ "Roscher", "Karsten", "" ] ]
Explaining black-box Artificial Intelligence (AI) models is a cornerstone for trustworthy AI and a prerequisite for its use in safety critical applications such that AI models can reliably assist humans in critical decisions. However, instead of trying to explain our models post-hoc, we need models which are interpreta...
1202.1340
Jie Xu Mr.
Yi Huang and Jie Xu and Ling Qiu
An Energy Efficient Semi-static Power Control and Link Adaptation Scheme in UMTS HSDPA
9 pages, 11 figures, accepted in EURASIP Journal on Wireless Communications and Networking, special issue on Green Radio
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
High speed downlink packet access (HSDPA) has been successfully applied in commercial systems and improves user experience significantly. However, it incurs substantial energy consumption. In this paper, we address this issue by proposing a novel energy efficient semi-static power control and link adaptation scheme i...
[ { "created": "Tue, 7 Feb 2012 03:31:30 GMT", "version": "v1" } ]
2012-02-08
[ [ "Huang", "Yi", "" ], [ "Xu", "Jie", "" ], [ "Qiu", "Ling", "" ] ]
High speed downlink packet access (HSDPA) has been successfully applied in commercial systems and improves user experience significantly. However, it incurs substantial energy consumption. In this paper, we address this issue by proposing a novel energy efficient semi-static power control and link adaptation scheme in ...
1808.06853
Seid Muhie Yimam
Seid Muhie Yimam, Chris Biemann
Demonstrating PAR4SEM - A Semantic Writing Aid with Adaptive Paraphrasing
EMNLP Demo paper
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In this paper, we present Par4Sem, a semantic writing aid tool based on adaptive paraphrasing. Unlike many annotation tools that are primarily used to collect training examples, Par4Sem is integrated into a real word application, in this case a writing aid tool, in order to collect training examples from usage data. ...
[ { "created": "Tue, 21 Aug 2018 11:37:57 GMT", "version": "v1" } ]
2018-08-22
[ [ "Yimam", "Seid Muhie", "" ], [ "Biemann", "Chris", "" ] ]
In this paper, we present Par4Sem, a semantic writing aid tool based on adaptive paraphrasing. Unlike many annotation tools that are primarily used to collect training examples, Par4Sem is integrated into a real word application, in this case a writing aid tool, in order to collect training examples from usage data. Pa...
2307.05126
Cec\'ilia Coelho
C. Coelho, M. Fernanda P. Costa, L.L. Ferr\'as
Enhancing Continuous Time Series Modelling with a Latent ODE-LSTM Approach
null
null
10.1016/j.amc.2024.128727
null
cs.LG math.OC
http://creativecommons.org/licenses/by-sa/4.0/
Due to their dynamic properties such as irregular sampling rate and high-frequency sampling, Continuous Time Series (CTS) are found in many applications. Since CTS with irregular sampling rate are difficult to model with standard Recurrent Neural Networks (RNNs), RNNs have been generalised to have continuous-time hid...
[ { "created": "Tue, 11 Jul 2023 09:01:49 GMT", "version": "v1" } ]
2024-07-02
[ [ "Coelho", "C.", "" ], [ "Costa", "M. Fernanda P.", "" ], [ "Ferrás", "L. L.", "" ] ]
Due to their dynamic properties such as irregular sampling rate and high-frequency sampling, Continuous Time Series (CTS) are found in many applications. Since CTS with irregular sampling rate are difficult to model with standard Recurrent Neural Networks (RNNs), RNNs have been generalised to have continuous-time hidde...
2407.13811
Gertjan Burghouts
Anne Kemmeren, Gertjan Burghouts, Michael van Bekkum, Wouter Meijer, Jelle van Mil
Which objects help me to act effectively? Reasoning about physically-grounded affordances
10 pages
Robotics: Science and Systems. Semantic Reasoning and Goal Understanding in Robotics 2024
null
null
cs.CV cs.RO
http://creativecommons.org/licenses/by/4.0/
For effective interactions with the open world, robots should understand how interactions with known and novel objects help them towards their goal. A key aspect of this understanding lies in detecting an object's affordances, which represent the potential effects that can be achieved by manipulating the object in va...
[ { "created": "Thu, 18 Jul 2024 11:08:57 GMT", "version": "v1" } ]
2024-07-22
[ [ "Kemmeren", "Anne", "" ], [ "Burghouts", "Gertjan", "" ], [ "van Bekkum", "Michael", "" ], [ "Meijer", "Wouter", "" ], [ "van Mil", "Jelle", "" ] ]
For effective interactions with the open world, robots should understand how interactions with known and novel objects help them towards their goal. A key aspect of this understanding lies in detecting an object's affordances, which represent the potential effects that can be achieved by manipulating the object in vari...
1804.08859
Joshua Owoyemi
Joshua Owoyemi, Koichi Hashimoto
Spatiotemporal Learning of Dynamic Gestures from 3D Point Cloud Data
Accepted to ICRA2018, 6 Pages
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we demonstrate an end-to-end spatiotemporal gesture learning approach for 3D point cloud data using a new gestures dataset of point clouds acquired from a 3D sensor. Nine classes of gestures were learned from gestures sample data. We mapped point cloud data into dense occupancy grids, then time steps o...
[ { "created": "Tue, 24 Apr 2018 06:48:56 GMT", "version": "v1" } ]
2018-04-25
[ [ "Owoyemi", "Joshua", "" ], [ "Hashimoto", "Koichi", "" ] ]
In this paper, we demonstrate an end-to-end spatiotemporal gesture learning approach for 3D point cloud data using a new gestures dataset of point clouds acquired from a 3D sensor. Nine classes of gestures were learned from gestures sample data. We mapped point cloud data into dense occupancy grids, then time steps of ...
1803.10561
Matthias Walter
Dominik Ermel and Matthias Walter
Parity Polytopes and Binarization
9 pages, 1 figure, presented at 15th Cologne-Twente Workshop on Graphs and Combinatorial Optimization 2017
null
null
null
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider generalizations of parity polytopes whose variables, in addition to a parity constraint, satisfy certain ordering constraints. More precisely, the variable domain is partitioned into $k$ contiguous groups, and within each group, we require that $x_i \geq x_{i+1}$ for all relevant $i$. Such constraints are...
[ { "created": "Wed, 28 Mar 2018 12:37:47 GMT", "version": "v1" }, { "created": "Wed, 18 Apr 2018 14:35:46 GMT", "version": "v2" } ]
2018-04-19
[ [ "Ermel", "Dominik", "" ], [ "Walter", "Matthias", "" ] ]
We consider generalizations of parity polytopes whose variables, in addition to a parity constraint, satisfy certain ordering constraints. More precisely, the variable domain is partitioned into $k$ contiguous groups, and within each group, we require that $x_i \geq x_{i+1}$ for all relevant $i$. Such constraints are u...
2206.07669
Ting Chen
Ting Chen, Saurabh Saxena, Lala Li, Tsung-Yi Lin, David J. Fleet, Geoffrey Hinton
A Unified Sequence Interface for Vision Tasks
The first three authors contributed equally
null
null
null
cs.CV cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While language tasks are naturally expressed in a single, unified, modeling framework, i.e., generating sequences of tokens, this has not been the case in computer vision. As a result, there is a proliferation of distinct architectures and loss functions for different vision tasks. In this work we show that a diverse...
[ { "created": "Wed, 15 Jun 2022 17:08:53 GMT", "version": "v1" }, { "created": "Sun, 16 Oct 2022 02:41:15 GMT", "version": "v2" } ]
2022-10-18
[ [ "Chen", "Ting", "" ], [ "Saxena", "Saurabh", "" ], [ "Li", "Lala", "" ], [ "Lin", "Tsung-Yi", "" ], [ "Fleet", "David J.", "" ], [ "Hinton", "Geoffrey", "" ] ]
While language tasks are naturally expressed in a single, unified, modeling framework, i.e., generating sequences of tokens, this has not been the case in computer vision. As a result, there is a proliferation of distinct architectures and loss functions for different vision tasks. In this work we show that a diverse s...
2009.06009
Jan Novotny
Karel Ad\'amek, Jan Novotn\'y, Jeyarajan Thiyagalingam, Wesley Armour
Efficiency Near the Edge: Increasing the Energy Efficiency of FFTs on GPUs for Real-time Edge Computing
published in IEEE Access
in IEEE Access, vol. 9, pp. 18167-18182, 2021
10.1109/ACCESS.2021.3053409
null
cs.PF
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Square Kilometre Array (SKA) is an international initiative for developing the world's largest radio telescope with a total collecting area of over a million square meters. The scale of the operation, combined with the remote location of the telescope, requires the use of energy-efficient computational algorithms...
[ { "created": "Sun, 13 Sep 2020 14:48:16 GMT", "version": "v1" }, { "created": "Tue, 9 Nov 2021 21:13:56 GMT", "version": "v2" } ]
2021-11-11
[ [ "Adámek", "Karel", "" ], [ "Novotný", "Jan", "" ], [ "Thiyagalingam", "Jeyarajan", "" ], [ "Armour", "Wesley", "" ] ]
The Square Kilometre Array (SKA) is an international initiative for developing the world's largest radio telescope with a total collecting area of over a million square meters. The scale of the operation, combined with the remote location of the telescope, requires the use of energy-efficient computational algorithms. ...
1901.11173
Anusha Lalitha
Anusha Lalitha, Osman Cihan Kilinc, Tara Javidi, Farinaz Koushanfar
Peer-to-peer Federated Learning on Graphs
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of training a machine learning model over a network of nodes in a fully decentralized framework. The nodes take a Bayesian-like approach via the introduction of a belief over the model parameter space. We propose a distributed learning algorithm in which nodes update their belief by aggregate ...
[ { "created": "Thu, 31 Jan 2019 02:18:45 GMT", "version": "v1" } ]
2019-02-01
[ [ "Lalitha", "Anusha", "" ], [ "Kilinc", "Osman Cihan", "" ], [ "Javidi", "Tara", "" ], [ "Koushanfar", "Farinaz", "" ] ]
We consider the problem of training a machine learning model over a network of nodes in a fully decentralized framework. The nodes take a Bayesian-like approach via the introduction of a belief over the model parameter space. We propose a distributed learning algorithm in which nodes update their belief by aggregate in...
2402.03618
Sreejan Kumar
Sreejan Kumar, Raja Marjieh, Byron Zhang, Declan Campbell, Michael Y. Hu, Umang Bhatt, Brenden Lake, Thomas L. Griffiths
Comparing Abstraction in Humans and Large Language Models Using Multimodal Serial Reproduction
null
null
null
null
cs.AI cs.CL q-bio.NC
http://creativecommons.org/licenses/by/4.0/
Humans extract useful abstractions of the world from noisy sensory data. Serial reproduction allows us to study how people construe the world through a paradigm similar to the game of telephone, where one person observes a stimulus and reproduces it for the next to form a chain of reproductions. Past serial reproduct...
[ { "created": "Tue, 6 Feb 2024 01:07:56 GMT", "version": "v1" } ]
2024-02-07
[ [ "Kumar", "Sreejan", "" ], [ "Marjieh", "Raja", "" ], [ "Zhang", "Byron", "" ], [ "Campbell", "Declan", "" ], [ "Hu", "Michael Y.", "" ], [ "Bhatt", "Umang", "" ], [ "Lake", "Brenden", "" ], [ "Griff...
Humans extract useful abstractions of the world from noisy sensory data. Serial reproduction allows us to study how people construe the world through a paradigm similar to the game of telephone, where one person observes a stimulus and reproduces it for the next to form a chain of reproductions. Past serial reproductio...
2107.05202
Daniil Pakhomov
Sanchit Hira, Ritwik Das, Abhinav Modi, Daniil Pakhomov
Delta Sampling R-BERT for limited data and low-light action recognition
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We present an approach to perform supervised action recognition in the dark. In this work, we present our results on the ARID dataset. Most previous works only evaluate performance on large, well illuminated datasets like Kinetics and HMDB51. We demonstrate that our work is able to achieve a very low error rate while...
[ { "created": "Mon, 12 Jul 2021 05:35:51 GMT", "version": "v1" } ]
2021-07-13
[ [ "Hira", "Sanchit", "" ], [ "Das", "Ritwik", "" ], [ "Modi", "Abhinav", "" ], [ "Pakhomov", "Daniil", "" ] ]
We present an approach to perform supervised action recognition in the dark. In this work, we present our results on the ARID dataset. Most previous works only evaluate performance on large, well illuminated datasets like Kinetics and HMDB51. We demonstrate that our work is able to achieve a very low error rate while b...
1203.4367
Nasrin Jaberi
Hamidreza Barati, Nasrin Jaberi
Thesis Report: Resource Utilization Provisioning in MapReduce
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this thesis report, we have a survey on state-of-the-art methods for modelling resource utilization of MapReduce applications regard to its configuration parameters. After implementation of one of the algorithms in literature, we tried to find that if CPU usage modelling of a MapReduce application can be used to p...
[ { "created": "Tue, 20 Mar 2012 10:06:24 GMT", "version": "v1" } ]
2012-03-21
[ [ "Barati", "Hamidreza", "" ], [ "Jaberi", "Nasrin", "" ] ]
In this thesis report, we have a survey on state-of-the-art methods for modelling resource utilization of MapReduce applications regard to its configuration parameters. After implementation of one of the algorithms in literature, we tried to find that if CPU usage modelling of a MapReduce application can be used to pre...
2002.12674
Sebastian Lunz
Sebastian Lunz, Yingzhen Li, Andrew Fitzgibbon, Nate Kushman
Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data
8 pages paper, 3 pages references, 18 pages appendix
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent work has shown the ability to learn generative models for 3D shapes from only unstructured 2D images. However, training such models requires differentiating through the rasterization step of the rendering process, therefore past work has focused on developing bespoke rendering models which smooth over this non...
[ { "created": "Fri, 28 Feb 2020 12:28:12 GMT", "version": "v1" } ]
2020-03-02
[ [ "Lunz", "Sebastian", "" ], [ "Li", "Yingzhen", "" ], [ "Fitzgibbon", "Andrew", "" ], [ "Kushman", "Nate", "" ] ]
Recent work has shown the ability to learn generative models for 3D shapes from only unstructured 2D images. However, training such models requires differentiating through the rasterization step of the rendering process, therefore past work has focused on developing bespoke rendering models which smooth over this non-d...
2212.00855
Luis Alvarez
Cooper Cone, Michael Owen, Luis Alvarez, Marc Brittain
Reward Function Optimization of a Deep Reinforcement Learning Collision Avoidance System
null
null
null
null
cs.AI cs.RO
http://creativecommons.org/licenses/by-sa/4.0/
The proliferation of unmanned aircraft systems (UAS) has caused airspace regulation authorities to examine the interoperability of these aircraft with collision avoidance systems initially designed for large transport category aircraft. Limitations in the currently mandated TCAS led the Federal Aviation Administratio...
[ { "created": "Thu, 1 Dec 2022 20:20:41 GMT", "version": "v1" } ]
2022-12-05
[ [ "Cone", "Cooper", "" ], [ "Owen", "Michael", "" ], [ "Alvarez", "Luis", "" ], [ "Brittain", "Marc", "" ] ]
The proliferation of unmanned aircraft systems (UAS) has caused airspace regulation authorities to examine the interoperability of these aircraft with collision avoidance systems initially designed for large transport category aircraft. Limitations in the currently mandated TCAS led the Federal Aviation Administration ...
2308.14562
Philip Tobuschat
Philip Tobuschat, Hao Ma, Dieter B\"uchler, Bernhard Sch\"olkopf, Michael Muehlebach
Data-Efficient Online Learning of Ball Placement in Robot Table Tennis
7 pages, 6 figures, to be published in proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2023
null
null
null
cs.RO cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
We present an implementation of an online optimization algorithm for hitting a predefined target when returning ping-pong balls with a table tennis robot. The online algorithm optimizes over so-called interception policies, which define the manner in which the robot arm intercepts the ball. In our case, these are com...
[ { "created": "Mon, 28 Aug 2023 13:24:58 GMT", "version": "v1" } ]
2023-08-29
[ [ "Tobuschat", "Philip", "" ], [ "Ma", "Hao", "" ], [ "Büchler", "Dieter", "" ], [ "Schölkopf", "Bernhard", "" ], [ "Muehlebach", "Michael", "" ] ]
We present an implementation of an online optimization algorithm for hitting a predefined target when returning ping-pong balls with a table tennis robot. The online algorithm optimizes over so-called interception policies, which define the manner in which the robot arm intercepts the ball. In our case, these are compo...
2406.15265
Charlotte Pouw
Charlotte Pouw, Marianne de Heer Kloots, Afra Alishahi, Willem Zuidema
Perception of Phonological Assimilation by Neural Speech Recognition Models
Accepted for publication in Computational Linguistics (Special Issue on Language Learning, Representation, and Processing in Humans and Machines)
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Human listeners effortlessly compensate for phonological changes during speech perception, often unconsciously inferring the intended sounds. For example, listeners infer the underlying /n/ when hearing an utterance such as "clea[m] pan", where [m] arises from place assimilation to the following labial [p]. This arti...
[ { "created": "Fri, 21 Jun 2024 15:58:22 GMT", "version": "v1" } ]
2024-06-24
[ [ "Pouw", "Charlotte", "" ], [ "Kloots", "Marianne de Heer", "" ], [ "Alishahi", "Afra", "" ], [ "Zuidema", "Willem", "" ] ]
Human listeners effortlessly compensate for phonological changes during speech perception, often unconsciously inferring the intended sounds. For example, listeners infer the underlying /n/ when hearing an utterance such as "clea[m] pan", where [m] arises from place assimilation to the following labial [p]. This articl...
2003.06880
Liat Peterfreund
Liat Peterfreund
Grammars for Document Spanners
null
null
null
null
cs.DB
http://creativecommons.org/licenses/by/4.0/
We propose a new grammar-based language for defining information-extractors from documents (text) that is built upon the well-studied framework of document spanners for extracting structured data from text. While previously studied formalisms for document spanners are mainly based on regular expressions, we use an ex...
[ { "created": "Sun, 15 Mar 2020 17:50:18 GMT", "version": "v1" }, { "created": "Tue, 24 Mar 2020 11:36:38 GMT", "version": "v2" }, { "created": "Mon, 20 Apr 2020 17:00:06 GMT", "version": "v3" }, { "created": "Thu, 12 Nov 2020 11:10:52 GMT", "version": "v4" }, { "c...
2023-01-25
[ [ "Peterfreund", "Liat", "" ] ]
We propose a new grammar-based language for defining information-extractors from documents (text) that is built upon the well-studied framework of document spanners for extracting structured data from text. While previously studied formalisms for document spanners are mainly based on regular expressions, we use an exte...
2102.05346
Michael K\"olle
Michael K\"olle, Dominik Laupheimer, Stefan Schmohl, Norbert Haala, Franz Rottensteiner, Jan Dirk Wegner, Hugo Ledoux
The Hessigheim 3D (H3D) Benchmark on Semantic Segmentation of High-Resolution 3D Point Clouds and Textured Meshes from UAV LiDAR and Multi-View-Stereo
H3D can be retrieved from https://ifpwww.ifp.uni-stuttgart.de/benchmark/hessigheim/default.aspx
null
10.1016/j.ophoto.2021.100001
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Automated semantic segmentation and object detection are of great importance in geospatial data analysis. However, supervised machine learning systems such as convolutional neural networks require large corpora of annotated training data. Especially in the geospatial domain, such datasets are quite scarce. Within thi...
[ { "created": "Wed, 10 Feb 2021 09:33:48 GMT", "version": "v1" }, { "created": "Thu, 25 Feb 2021 19:25:51 GMT", "version": "v2" } ]
2021-07-20
[ [ "Kölle", "Michael", "" ], [ "Laupheimer", "Dominik", "" ], [ "Schmohl", "Stefan", "" ], [ "Haala", "Norbert", "" ], [ "Rottensteiner", "Franz", "" ], [ "Wegner", "Jan Dirk", "" ], [ "Ledoux", "Hugo", "" ]...
Automated semantic segmentation and object detection are of great importance in geospatial data analysis. However, supervised machine learning systems such as convolutional neural networks require large corpora of annotated training data. Especially in the geospatial domain, such datasets are quite scarce. Within this ...
2402.03907
Efe Bozkir
Efe Bozkir and S\"uleyman \"Ozdel and Ka Hei Carrie Lau and Mengdi Wang and Hong Gao and Enkelejda Kasneci
Embedding Large Language Models into Extended Reality: Opportunities and Challenges for Inclusion, Engagement, and Privacy
ACM Conversational User Interfaces 2024
null
10.1145/3640794.3665563
null
cs.HC cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Advances in artificial intelligence and human-computer interaction will likely lead to extended reality (XR) becoming pervasive. While XR can provide users with interactive, engaging, and immersive experiences, non-player characters are often utilized in pre-scripted and conventional ways. This paper argues for using...
[ { "created": "Tue, 6 Feb 2024 11:19:40 GMT", "version": "v1" }, { "created": "Thu, 20 Jun 2024 10:02:30 GMT", "version": "v2" } ]
2024-06-21
[ [ "Bozkir", "Efe", "" ], [ "Özdel", "Süleyman", "" ], [ "Lau", "Ka Hei Carrie", "" ], [ "Wang", "Mengdi", "" ], [ "Gao", "Hong", "" ], [ "Kasneci", "Enkelejda", "" ] ]
Advances in artificial intelligence and human-computer interaction will likely lead to extended reality (XR) becoming pervasive. While XR can provide users with interactive, engaging, and immersive experiences, non-player characters are often utilized in pre-scripted and conventional ways. This paper argues for using l...
2112.09196
Tong Xia
Tong Xia, Jing Han, Cecilia Mascolo
Benchmarking Uncertainty Quantification on Biosignal Classification Tasks under Dataset Shift
Accepted by The 6th International Workshop on Health Intelligence (W3PHIAI-22)
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A biosignal is a signal that can be continuously measured from human bodies, such as respiratory sounds, heart activity (ECG), brain waves (EEG), etc, based on which, machine learning models have been developed with very promising performance for automatic disease detection and health status monitoring. However, data...
[ { "created": "Thu, 16 Dec 2021 20:42:17 GMT", "version": "v1" }, { "created": "Tue, 25 Jan 2022 15:10:41 GMT", "version": "v2" } ]
2022-01-26
[ [ "Xia", "Tong", "" ], [ "Han", "Jing", "" ], [ "Mascolo", "Cecilia", "" ] ]
A biosignal is a signal that can be continuously measured from human bodies, such as respiratory sounds, heart activity (ECG), brain waves (EEG), etc, based on which, machine learning models have been developed with very promising performance for automatic disease detection and health status monitoring. However, datase...
2007.11930
Jaafar Elmirghani
Zaid H. Nasralla, Taisir E. H. Elgorashi and Jaafar M. H. Elmirghani
Blackout Resilient Optical Core Network
null
null
null
null
cs.NI eess.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A disaster may not necessarily demolish the telecommunications infrastructure, but instead it might affect the national grid and cause blackouts, consequently disrupting the network operation unless there is an alternative power source(s). In this paper, power outages are considered, and the telecommunication network...
[ { "created": "Thu, 23 Jul 2020 11:10:33 GMT", "version": "v1" } ]
2020-07-24
[ [ "Nasralla", "Zaid H.", "" ], [ "Elgorashi", "Taisir E. H.", "" ], [ "Elmirghani", "Jaafar M. H.", "" ] ]
A disaster may not necessarily demolish the telecommunications infrastructure, but instead it might affect the national grid and cause blackouts, consequently disrupting the network operation unless there is an alternative power source(s). In this paper, power outages are considered, and the telecommunication network p...
2106.10412
Devansh Jalota
Devansh Jalota, Marco Pavone, Qi Qi, Yinyu Ye
Fisher Markets with Linear Constraints: Equilibrium Properties and Efficient Distributed Algorithms
null
null
null
null
cs.GT
http://creativecommons.org/licenses/by/4.0/
The Fisher market is one of the most fundamental models for resource allocation problems in economic theory, wherein agents spend a budget of currency to buy goods that maximize their utilities, while producers sell capacity constrained goods in exchange for currency. However, the consideration of only two types of c...
[ { "created": "Sat, 19 Jun 2021 03:43:43 GMT", "version": "v1" } ]
2021-06-22
[ [ "Jalota", "Devansh", "" ], [ "Pavone", "Marco", "" ], [ "Qi", "Qi", "" ], [ "Ye", "Yinyu", "" ] ]
The Fisher market is one of the most fundamental models for resource allocation problems in economic theory, wherein agents spend a budget of currency to buy goods that maximize their utilities, while producers sell capacity constrained goods in exchange for currency. However, the consideration of only two types of con...
2205.00691
Wei Jiang
Wei Jiang and Hans D. Schotten
Initial Beamforming for Millimeter-Wave and Terahertz Communications in 6G Mobile Systems
2022 IEEE Wireless Communications and Networking Conference (WCNC), April 2022, Austin, TX, USA
null
null
null
cs.IT eess.SP math.IT
http://creativecommons.org/licenses/by-nc-nd/4.0/
To meet the demand of supreme data rates in terabits-per-second, the next-generation mobile system needs to exploit the abundant spectrum in the millimeter-wave and terahertz bands. However, high-frequency transmission heavily relies on large-scale antenna arrays to reap high beamforming gain, used to compensate for ...
[ { "created": "Mon, 2 May 2022 07:17:46 GMT", "version": "v1" } ]
2022-05-03
[ [ "Jiang", "Wei", "" ], [ "Schotten", "Hans D.", "" ] ]
To meet the demand of supreme data rates in terabits-per-second, the next-generation mobile system needs to exploit the abundant spectrum in the millimeter-wave and terahertz bands. However, high-frequency transmission heavily relies on large-scale antenna arrays to reap high beamforming gain, used to compensate for se...
2110.02597
Kerstin Bongard-Blanchy Dr
Cristiana Santos, Arianna Rossi, Lorena S\'anchez Chamorro, Kerstin Bongard-Blanchy, Ruba Abu-Salma
Cookie Banners, What's the Purpose? Analyzing Cookie Banner Text Through a Legal Lens
null
null
10.1145/3463676.3485611
null
cs.HC
http://creativecommons.org/licenses/by/4.0/
A cookie banner pops up when a user visits a website for the first time, requesting consent to the use of cookies and other trackers for a variety of purposes. Unlike prior work that has focused on evaluating the user interface (UI) design of cookie banners, this paper presents an in-depth analysis of what cookie ban...
[ { "created": "Wed, 6 Oct 2021 09:07:47 GMT", "version": "v1" }, { "created": "Thu, 7 Oct 2021 11:09:44 GMT", "version": "v2" } ]
2021-10-08
[ [ "Santos", "Cristiana", "" ], [ "Rossi", "Arianna", "" ], [ "Chamorro", "Lorena Sánchez", "" ], [ "Bongard-Blanchy", "Kerstin", "" ], [ "Abu-Salma", "Ruba", "" ] ]
A cookie banner pops up when a user visits a website for the first time, requesting consent to the use of cookies and other trackers for a variety of purposes. Unlike prior work that has focused on evaluating the user interface (UI) design of cookie banners, this paper presents an in-depth analysis of what cookie banne...
2201.08904
Jeffrey Zhao
Jeffrey Zhao, Raghav Gupta, Yuan Cao, Dian Yu, Mingqiu Wang, Harrison Lee, Abhinav Rastogi, Izhak Shafran, Yonghui Wu
Description-Driven Task-Oriented Dialog Modeling
null
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Task-oriented dialogue (TOD) systems are required to identify key information from conversations for the completion of given tasks. Such information is conventionally specified in terms of intents and slots contained in task-specific ontology or schemata. Since these schemata are designed by system developers, the na...
[ { "created": "Fri, 21 Jan 2022 22:07:41 GMT", "version": "v1" } ]
2022-01-25
[ [ "Zhao", "Jeffrey", "" ], [ "Gupta", "Raghav", "" ], [ "Cao", "Yuan", "" ], [ "Yu", "Dian", "" ], [ "Wang", "Mingqiu", "" ], [ "Lee", "Harrison", "" ], [ "Rastogi", "Abhinav", "" ], [ "Shafran", ...
Task-oriented dialogue (TOD) systems are required to identify key information from conversations for the completion of given tasks. Such information is conventionally specified in terms of intents and slots contained in task-specific ontology or schemata. Since these schemata are designed by system developers, the nami...
2309.02427
Shunyu Yao
Theodore R. Sumers, Shunyu Yao, Karthik Narasimhan, Thomas L. Griffiths
Cognitive Architectures for Language Agents
v3 is TMLR camera ready version. 19 pages of main content, 5 figures. The first two authors contributed equally, order decided by coin flip. A CoALA-based repo of recent work on language agents: https://github.com/ysymyth/awesome-language-agents
null
null
null
cs.AI cs.CL cs.LG cs.SC
http://creativecommons.org/licenses/by/4.0/
Recent efforts have augmented large language models (LLMs) with external resources (e.g., the Internet) or internal control flows (e.g., prompt chaining) for tasks requiring grounding or reasoning, leading to a new class of language agents. While these agents have achieved substantial empirical success, we lack a sys...
[ { "created": "Tue, 5 Sep 2023 17:56:20 GMT", "version": "v1" }, { "created": "Wed, 27 Sep 2023 15:27:25 GMT", "version": "v2" }, { "created": "Fri, 15 Mar 2024 15:44:11 GMT", "version": "v3" } ]
2024-03-18
[ [ "Sumers", "Theodore R.", "" ], [ "Yao", "Shunyu", "" ], [ "Narasimhan", "Karthik", "" ], [ "Griffiths", "Thomas L.", "" ] ]
Recent efforts have augmented large language models (LLMs) with external resources (e.g., the Internet) or internal control flows (e.g., prompt chaining) for tasks requiring grounding or reasoning, leading to a new class of language agents. While these agents have achieved substantial empirical success, we lack a syste...
2001.07607
Timothy LaRock
Timothy LaRock, Timothy Sakharov, Sahely Bhadra, Tina Eliassi-Rad
Understanding the Limitations of Network Online Learning
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Studies of networked phenomena, such as interactions in online social media, often rely on incomplete data, either because these phenomena are partially observed, or because the data is too large or expensive to acquire all at once. Analysis of incomplete data leads to skewed or misleading results. In this paper, we ...
[ { "created": "Thu, 9 Jan 2020 13:59:20 GMT", "version": "v1" } ]
2020-01-22
[ [ "LaRock", "Timothy", "" ], [ "Sakharov", "Timothy", "" ], [ "Bhadra", "Sahely", "" ], [ "Eliassi-Rad", "Tina", "" ] ]
Studies of networked phenomena, such as interactions in online social media, often rely on incomplete data, either because these phenomena are partially observed, or because the data is too large or expensive to acquire all at once. Analysis of incomplete data leads to skewed or misleading results. In this paper, we in...
2002.04741
Hao Chen
Hao Chen, Yali Wang, Guoyou Wang, Xiang Bai, and Yu Qiao
Progressive Object Transfer Detection
TIP 2019
null
10.1109/TIP.2019.2938680
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent development of object detection mainly depends on deep learning with large-scale benchmarks. However, collecting such fully-annotated data is often difficult or expensive for real-world applications, which restricts the power of deep neural networks in practice. Alternatively, humans can detect new objects wit...
[ { "created": "Wed, 12 Feb 2020 00:16:24 GMT", "version": "v1" }, { "created": "Thu, 13 Feb 2020 05:06:51 GMT", "version": "v2" } ]
2020-02-19
[ [ "Chen", "Hao", "" ], [ "Wang", "Yali", "" ], [ "Wang", "Guoyou", "" ], [ "Bai", "Xiang", "" ], [ "Qiao", "Yu", "" ] ]
Recent development of object detection mainly depends on deep learning with large-scale benchmarks. However, collecting such fully-annotated data is often difficult or expensive for real-world applications, which restricts the power of deep neural networks in practice. Alternatively, humans can detect new objects with ...
2108.08977
Zecheng He
Zecheng He, Ruby B. Lee
CloudShield: Real-time Anomaly Detection in the Cloud
null
null
null
null
cs.CR cs.LG
http://creativecommons.org/licenses/by/4.0/
In cloud computing, it is desirable if suspicious activities can be detected by automatic anomaly detection systems. Although anomaly detection has been investigated in the past, it remains unsolved in cloud computing. Challenges are: characterizing the normal behavior of a cloud server, distinguishing between benign...
[ { "created": "Fri, 20 Aug 2021 03:14:18 GMT", "version": "v1" }, { "created": "Wed, 25 Aug 2021 05:08:12 GMT", "version": "v2" } ]
2021-08-26
[ [ "He", "Zecheng", "" ], [ "Lee", "Ruby B.", "" ] ]
In cloud computing, it is desirable if suspicious activities can be detected by automatic anomaly detection systems. Although anomaly detection has been investigated in the past, it remains unsolved in cloud computing. Challenges are: characterizing the normal behavior of a cloud server, distinguishing between benign a...
2408.02313
Benjamin Marais
Tony Quertier, Benjamin Marais, Gr\'egoire Barru\'e, St\'ephane Morucci, S\'evan Az\'e, S\'ebastien Salladin
A Lean Transformer Model for Dynamic Malware Analysis and Detection
null
null
null
null
cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Malware is a fast-growing threat to the modern computing world and existing lines of defense are not efficient enough to address this issue. This is mainly due to the fact that many prevention solutions rely on signature-based detection methods that can easily be circumvented by hackers. Therefore, there is a recurre...
[ { "created": "Mon, 5 Aug 2024 08:46:46 GMT", "version": "v1" } ]
2024-08-06
[ [ "Quertier", "Tony", "" ], [ "Marais", "Benjamin", "" ], [ "Barrué", "Grégoire", "" ], [ "Morucci", "Stéphane", "" ], [ "Azé", "Sévan", "" ], [ "Salladin", "Sébastien", "" ] ]
Malware is a fast-growing threat to the modern computing world and existing lines of defense are not efficient enough to address this issue. This is mainly due to the fact that many prevention solutions rely on signature-based detection methods that can easily be circumvented by hackers. Therefore, there is a recurrent...
2101.06067
Jean-Pierre Sleiman
Jean-Pierre Sleiman, Farbod Farshidian, Marco Hutter
Constraint Handling in Continuous-Time DDP-Based Model Predictive Control
null
null
null
null
cs.RO cs.SY eess.SY math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Sequential Linear Quadratic (SLQ) algorithm is a continuous-time variant of the well-known Differential Dynamic Programming (DDP) technique with a Gauss-Newton Hessian approximation. This family of methods has gained popularity in the robotics community due to its efficiency in solving complex trajectory optimiza...
[ { "created": "Fri, 15 Jan 2021 11:29:11 GMT", "version": "v1" }, { "created": "Fri, 26 Mar 2021 11:33:11 GMT", "version": "v2" } ]
2021-03-29
[ [ "Sleiman", "Jean-Pierre", "" ], [ "Farshidian", "Farbod", "" ], [ "Hutter", "Marco", "" ] ]
The Sequential Linear Quadratic (SLQ) algorithm is a continuous-time variant of the well-known Differential Dynamic Programming (DDP) technique with a Gauss-Newton Hessian approximation. This family of methods has gained popularity in the robotics community due to its efficiency in solving complex trajectory optimizati...
2106.03614
Mo Zhou
Mo Zhou, Le Wang, Zhenxing Niu, Qilin Zhang, Nanning Zheng, Gang Hua
Adversarial Attack and Defense in Deep Ranking
null
null
null
null
cs.CV cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep Neural Network classifiers are vulnerable to adversarial attack, where an imperceptible perturbation could result in misclassification. However, the vulnerability of DNN-based image ranking systems remains under-explored. In this paper, we propose two attacks against deep ranking systems, i.e., Candidate Attack ...
[ { "created": "Mon, 7 Jun 2021 13:41:45 GMT", "version": "v1" } ]
2021-06-08
[ [ "Zhou", "Mo", "" ], [ "Wang", "Le", "" ], [ "Niu", "Zhenxing", "" ], [ "Zhang", "Qilin", "" ], [ "Zheng", "Nanning", "" ], [ "Hua", "Gang", "" ] ]
Deep Neural Network classifiers are vulnerable to adversarial attack, where an imperceptible perturbation could result in misclassification. However, the vulnerability of DNN-based image ranking systems remains under-explored. In this paper, we propose two attacks against deep ranking systems, i.e., Candidate Attack an...
1904.05530
Xiang Ren
Woojeong Jin, Meng Qu, Xisen Jin, Xiang Ren
Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs
15 pages, 8 figures, accepted at as full paper in EMNLP 2020
null
null
null
cs.LG cs.AI cs.CL stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge graph reasoning is a critical task in natural language processing. The task becomes more challenging on temporal knowledge graphs, where each fact is associated with a timestamp. Most existing methods focus on reasoning at past timestamps and they are not able to predict facts happening in the future. This ...
[ { "created": "Thu, 11 Apr 2019 04:45:42 GMT", "version": "v1" }, { "created": "Tue, 4 Jun 2019 19:06:37 GMT", "version": "v2" }, { "created": "Tue, 8 Oct 2019 03:32:40 GMT", "version": "v3" }, { "created": "Tue, 6 Oct 2020 18:40:59 GMT", "version": "v4" } ]
2020-10-08
[ [ "Jin", "Woojeong", "" ], [ "Qu", "Meng", "" ], [ "Jin", "Xisen", "" ], [ "Ren", "Xiang", "" ] ]
Knowledge graph reasoning is a critical task in natural language processing. The task becomes more challenging on temporal knowledge graphs, where each fact is associated with a timestamp. Most existing methods focus on reasoning at past timestamps and they are not able to predict facts happening in the future. This pa...
2005.10296
Ajith Suresh
Nishat Koti, Mahak Pancholi, Arpita Patra, Ajith Suresh
SWIFT: Super-fast and Robust Privacy-Preserving Machine Learning
This article is the full and extended version of an article to appear in USENIX Security 2021
null
null
null
cs.CR cs.LG
http://creativecommons.org/licenses/by/4.0/
Performing machine learning (ML) computation on private data while maintaining data privacy, aka Privacy-preserving Machine Learning~(PPML), is an emergent field of research. Recently, PPML has seen a visible shift towards the adoption of the Secure Outsourced Computation~(SOC) paradigm due to the heavy computation t...
[ { "created": "Wed, 20 May 2020 18:20:23 GMT", "version": "v1" }, { "created": "Fri, 30 Oct 2020 08:26:09 GMT", "version": "v2" }, { "created": "Wed, 17 Feb 2021 08:47:28 GMT", "version": "v3" } ]
2021-02-18
[ [ "Koti", "Nishat", "" ], [ "Pancholi", "Mahak", "" ], [ "Patra", "Arpita", "" ], [ "Suresh", "Ajith", "" ] ]
Performing machine learning (ML) computation on private data while maintaining data privacy, aka Privacy-preserving Machine Learning~(PPML), is an emergent field of research. Recently, PPML has seen a visible shift towards the adoption of the Secure Outsourced Computation~(SOC) paradigm due to the heavy computation tha...
2102.11749
Ewan Dunbar
Louis Fournier and Ewan Dunbar
Paraphrases do not explain word analogies
To appear in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Many types of distributional word embeddings (weakly) encode linguistic regularities as directions (the difference between "jump" and "jumped" will be in a similar direction to that of "walk" and "walked," and so on). Several attempts have been made to explain this fact. We respond to Allen and Hospedales' recent (IC...
[ { "created": "Tue, 23 Feb 2021 15:25:10 GMT", "version": "v1" } ]
2021-02-24
[ [ "Fournier", "Louis", "" ], [ "Dunbar", "Ewan", "" ] ]
Many types of distributional word embeddings (weakly) encode linguistic regularities as directions (the difference between "jump" and "jumped" will be in a similar direction to that of "walk" and "walked," and so on). Several attempts have been made to explain this fact. We respond to Allen and Hospedales' recent (ICML...
2009.10333
Aanchal Mongia
Aanchal Mongia, Stuti Jain, Emilie Chouzenoux and Angshul Majumda
DeepVir -- Graphical Deep Matrix Factorization for "In Silico" Antiviral Repositioning: Application to COVID-19
null
null
null
null
cs.LG stat.ML
http://creativecommons.org/publicdomain/zero/1.0/
This work formulates antiviral repositioning as a matrix completion problem where the antiviral drugs are along the rows and the viruses along the columns. The input matrix is partially filled, with ones in positions where the antiviral has been known to be effective against a virus. The curated metadata for antivira...
[ { "created": "Tue, 22 Sep 2020 05:57:03 GMT", "version": "v1" } ]
2020-09-23
[ [ "Mongia", "Aanchal", "" ], [ "Jain", "Stuti", "" ], [ "Chouzenoux", "Emilie", "" ], [ "Majumda", "Angshul", "" ] ]
This work formulates antiviral repositioning as a matrix completion problem where the antiviral drugs are along the rows and the viruses along the columns. The input matrix is partially filled, with ones in positions where the antiviral has been known to be effective against a virus. The curated metadata for antivirals...
2401.01353
Ralph Ankele
Ralph Ankele, Hamed Haddadi
The Boomerang protocol: A Decentralised Privacy-Preserving Verifiable Incentive Protocol
fix formatting issue in abstract
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-nd/4.0/
In the era of data-driven economies, incentive systems and loyalty programs, have become ubiquitous in various sectors, including advertising, retail, travel, and financial services. While these systems offer advantages for both users and companies, they necessitate the transfer and analysis of substantial amounts of...
[ { "created": "Wed, 6 Dec 2023 09:37:45 GMT", "version": "v1" }, { "created": "Tue, 9 Jan 2024 17:27:33 GMT", "version": "v2" } ]
2024-01-11
[ [ "Ankele", "Ralph", "" ], [ "Haddadi", "Hamed", "" ] ]
In the era of data-driven economies, incentive systems and loyalty programs, have become ubiquitous in various sectors, including advertising, retail, travel, and financial services. While these systems offer advantages for both users and companies, they necessitate the transfer and analysis of substantial amounts of s...
2310.16361
Zhiyu Chen
Besnik Fetahu, Zhiyu Chen, Oleg Rokhlenko, Shervin Malmasi
InstructPTS: Instruction-Tuning LLMs for Product Title Summarization
Accepted by EMNLP 2023 (Industry Track)
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
E-commerce product catalogs contain billions of items. Most products have lengthy titles, as sellers pack them with product attributes to improve retrieval, and highlight key product aspects. This results in a gap between such unnatural products titles, and how customers refer to them. It also limits how e-commerce s...
[ { "created": "Wed, 25 Oct 2023 04:56:07 GMT", "version": "v1" } ]
2023-10-26
[ [ "Fetahu", "Besnik", "" ], [ "Chen", "Zhiyu", "" ], [ "Rokhlenko", "Oleg", "" ], [ "Malmasi", "Shervin", "" ] ]
E-commerce product catalogs contain billions of items. Most products have lengthy titles, as sellers pack them with product attributes to improve retrieval, and highlight key product aspects. This results in a gap between such unnatural products titles, and how customers refer to them. It also limits how e-commerce sto...
2005.00820
Clara Meister
Clara Meister, Elizabeth Salesky, Ryan Cotterell
Generalized Entropy Regularization or: There's Nothing Special about Label Smoothing
Published as long paper at ACL 2020
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Prior work has explored directly regularizing the output distributions of probabilistic models to alleviate peaky (i.e. over-confident) predictions, a common sign of overfitting. This class of techniques, of which label smoothing is one, has a connection to entropy regularization. Despite the consistent success of la...
[ { "created": "Sat, 2 May 2020 12:46:28 GMT", "version": "v1" }, { "created": "Tue, 12 May 2020 06:22:06 GMT", "version": "v2" } ]
2020-05-13
[ [ "Meister", "Clara", "" ], [ "Salesky", "Elizabeth", "" ], [ "Cotterell", "Ryan", "" ] ]
Prior work has explored directly regularizing the output distributions of probabilistic models to alleviate peaky (i.e. over-confident) predictions, a common sign of overfitting. This class of techniques, of which label smoothing is one, has a connection to entropy regularization. Despite the consistent success of labe...
2301.11608
Lecheng Kong
Lecheng Kong, Christopher King, Bradley Fritz, Yixin Chen
A Multi-View Joint Learning Framework for Embedding Clinical Codes and Text Using Graph Neural Networks
null
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Learning to represent free text is a core task in many clinical machine learning (ML) applications, as clinical text contains observations and plans not otherwise available for inference. State-of-the-art methods use large language models developed with immense computational resources and training data; however, appl...
[ { "created": "Fri, 27 Jan 2023 09:19:03 GMT", "version": "v1" } ]
2023-01-30
[ [ "Kong", "Lecheng", "" ], [ "King", "Christopher", "" ], [ "Fritz", "Bradley", "" ], [ "Chen", "Yixin", "" ] ]
Learning to represent free text is a core task in many clinical machine learning (ML) applications, as clinical text contains observations and plans not otherwise available for inference. State-of-the-art methods use large language models developed with immense computational resources and training data; however, applyi...
2010.02035
Aksel Wilhelm Wold Eide
Aksel Wilhelm Wold Eide, Eilif Solberg, Ingebj{\o}rg K{\aa}sen
Sample weighting as an explanation for mode collapse in generative adversarial networks
41 pages, 21 figures, preprint
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative adversarial networks were introduced with a logistic MiniMax cost formulation, which normally fails to train due to saturation, and a Non-Saturating reformulation. While addressing the saturation problem, NS-GAN also inverts the generator's sample weighting, implicitly shifting emphasis from higher-scoring...
[ { "created": "Mon, 5 Oct 2020 14:13:45 GMT", "version": "v1" } ]
2020-10-06
[ [ "Eide", "Aksel Wilhelm Wold", "" ], [ "Solberg", "Eilif", "" ], [ "Kåsen", "Ingebjørg", "" ] ]
Generative adversarial networks were introduced with a logistic MiniMax cost formulation, which normally fails to train due to saturation, and a Non-Saturating reformulation. While addressing the saturation problem, NS-GAN also inverts the generator's sample weighting, implicitly shifting emphasis from higher-scoring t...
2103.02907
Qibin Hou
Qibin Hou, Daquan Zhou, Jiashi Feng
Coordinate Attention for Efficient Mobile Network Design
CVPR2021
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Recent studies on mobile network design have demonstrated the remarkable effectiveness of channel attention (e.g., the Squeeze-and-Excitation attention) for lifting model performance, but they generally neglect the positional information, which is important for generating spatially selective attention maps. In this p...
[ { "created": "Thu, 4 Mar 2021 09:18:02 GMT", "version": "v1" } ]
2021-03-05
[ [ "Hou", "Qibin", "" ], [ "Zhou", "Daquan", "" ], [ "Feng", "Jiashi", "" ] ]
Recent studies on mobile network design have demonstrated the remarkable effectiveness of channel attention (e.g., the Squeeze-and-Excitation attention) for lifting model performance, but they generally neglect the positional information, which is important for generating spatially selective attention maps. In this pap...
2308.16584
Zhongtao Jiang
Zhongtao Jiang, Yuanzhe Zhang, Yiming Ju, and Kang Liu
Unsupervised Text Style Transfer with Deep Generative Models
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a general framework for unsupervised text style transfer with deep generative models. The framework models each sentence-label pair in the non-parallel corpus as partially observed from a complete quadruplet which additionally contains two latent codes representing the content and style, respectively. Thes...
[ { "created": "Thu, 31 Aug 2023 09:29:35 GMT", "version": "v1" } ]
2023-09-01
[ [ "Jiang", "Zhongtao", "" ], [ "Zhang", "Yuanzhe", "" ], [ "Ju", "Yiming", "" ], [ "Liu", "Kang", "" ] ]
We present a general framework for unsupervised text style transfer with deep generative models. The framework models each sentence-label pair in the non-parallel corpus as partially observed from a complete quadruplet which additionally contains two latent codes representing the content and style, respectively. These ...
2201.09081
Steve Huntsman
Steve Huntsman
Physical geometry of channel degradation
null
null
10.1109/CISS56502.2023.10089672
null
cs.IT cond-mat.stat-mech math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We outline a geometrical correspondence between capacity and effective free energy minima of discrete memoryless channels. This correspondence informs the behavior of a timescale that is important in effective statistical physics.
[ { "created": "Sat, 22 Jan 2022 15:36:59 GMT", "version": "v1" } ]
2023-04-18
[ [ "Huntsman", "Steve", "" ] ]
We outline a geometrical correspondence between capacity and effective free energy minima of discrete memoryless channels. This correspondence informs the behavior of a timescale that is important in effective statistical physics.
1609.08531
Anirban Bhattacharyya
Anirban Bhattacharyya and Andrey Mokhov and Ken Pierce
An Empirical Comparison of Formalisms for Modelling and Analysis of Dynamic Reconfiguration of Dependable Systems
84 pages including 4 appendices, journal paper
null
null
null
cs.SE cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper uses a case study to evaluate empirically three formalisms of different kinds for their suitability for the modelling and analysis of dynamic reconfiguration of dependable systems. The requirements on an ideal formalism for dynamic software reconfiguration are defined. The reconfiguration of an office work...
[ { "created": "Tue, 27 Sep 2016 16:59:50 GMT", "version": "v1" } ]
2016-09-28
[ [ "Bhattacharyya", "Anirban", "" ], [ "Mokhov", "Andrey", "" ], [ "Pierce", "Ken", "" ] ]
This paper uses a case study to evaluate empirically three formalisms of different kinds for their suitability for the modelling and analysis of dynamic reconfiguration of dependable systems. The requirements on an ideal formalism for dynamic software reconfiguration are defined. The reconfiguration of an office workfl...
2405.11537
Mikhail Konenkov
Mikhail Konenkov, Artem Lykov, Daria Trinitatova, Dzmitry Tsetserukou
VR-GPT: Visual Language Model for Intelligent Virtual Reality Applications
Updated version
null
null
null
cs.RO cs.AI cs.ET
http://creativecommons.org/licenses/by-nc-nd/4.0/
The advent of immersive Virtual Reality applications has transformed various domains, yet their integration with advanced artificial intelligence technologies like Visual Language Models remains underexplored. This study introduces a pioneering approach utilizing VLMs within VR environments to enhance user interactio...
[ { "created": "Sun, 19 May 2024 12:56:00 GMT", "version": "v1" }, { "created": "Thu, 11 Jul 2024 07:46:14 GMT", "version": "v2" }, { "created": "Sat, 3 Aug 2024 10:19:54 GMT", "version": "v3" } ]
2024-08-06
[ [ "Konenkov", "Mikhail", "" ], [ "Lykov", "Artem", "" ], [ "Trinitatova", "Daria", "" ], [ "Tsetserukou", "Dzmitry", "" ] ]
The advent of immersive Virtual Reality applications has transformed various domains, yet their integration with advanced artificial intelligence technologies like Visual Language Models remains underexplored. This study introduces a pioneering approach utilizing VLMs within VR environments to enhance user interaction ...
2303.11011
Xinglong Luo
Xinglong Luo, Kunming Luo, Ao Luo, Zhengning Wang, Ping Tan, Shuaicheng Liu
Learning Optical Flow from Event Camera with Rendered Dataset
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study the problem of estimating optical flow from event cameras. One important issue is how to build a high-quality event-flow dataset with accurate event values and flow labels. Previous datasets are created by either capturing real scenes by event cameras or synthesizing from images with pasted foreground object...
[ { "created": "Mon, 20 Mar 2023 10:44:32 GMT", "version": "v1" } ]
2023-03-21
[ [ "Luo", "Xinglong", "" ], [ "Luo", "Kunming", "" ], [ "Luo", "Ao", "" ], [ "Wang", "Zhengning", "" ], [ "Tan", "Ping", "" ], [ "Liu", "Shuaicheng", "" ] ]
We study the problem of estimating optical flow from event cameras. One important issue is how to build a high-quality event-flow dataset with accurate event values and flow labels. Previous datasets are created by either capturing real scenes by event cameras or synthesizing from images with pasted foreground objects....
1908.06724
Shreyas Kolala Venkataramanaiah
Shreyas Kolala Venkataramanaiah, Yufei Ma, Shihui Yin, Eriko Nurvithadhi, Aravind Dasu, Yu Cao, Jae-sun Seo
Automatic Compiler Based FPGA Accelerator for CNN Training
6 pages, 9 figures, paper accepted at FPL2019 conference
null
null
null
cs.LG cs.NE eess.SP
http://creativecommons.org/licenses/by/4.0/
Training of convolutional neural networks (CNNs)on embedded platforms to support on-device learning is earning vital importance in recent days. Designing flexible training hard-ware is much more challenging than inference hardware, due to design complexity and large computation/memory requirement. In this work, we pr...
[ { "created": "Thu, 15 Aug 2019 18:49:38 GMT", "version": "v1" } ]
2019-08-20
[ [ "Venkataramanaiah", "Shreyas Kolala", "" ], [ "Ma", "Yufei", "" ], [ "Yin", "Shihui", "" ], [ "Nurvithadhi", "Eriko", "" ], [ "Dasu", "Aravind", "" ], [ "Cao", "Yu", "" ], [ "Seo", "Jae-sun", "" ] ]
Training of convolutional neural networks (CNNs)on embedded platforms to support on-device learning is earning vital importance in recent days. Designing flexible training hard-ware is much more challenging than inference hardware, due to design complexity and large computation/memory requirement. In this work, we pres...
2012.13190
Yves Rychener
Yves Rychener, Xavier Renard, Djam\'e Seddah, Pascal Frossard, Marcin Detyniecki
QUACKIE: A NLP Classification Task With Ground Truth Explanations
null
null
null
null
cs.CL stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
NLP Interpretability aims to increase trust in model predictions. This makes evaluating interpretability approaches a pressing issue. There are multiple datasets for evaluating NLP Interpretability, but their dependence on human provided ground truths raises questions about their unbiasedness. In this work, we take a...
[ { "created": "Thu, 24 Dec 2020 10:43:20 GMT", "version": "v1" }, { "created": "Sun, 27 Dec 2020 18:04:17 GMT", "version": "v2" } ]
2020-12-29
[ [ "Rychener", "Yves", "" ], [ "Renard", "Xavier", "" ], [ "Seddah", "Djamé", "" ], [ "Frossard", "Pascal", "" ], [ "Detyniecki", "Marcin", "" ] ]
NLP Interpretability aims to increase trust in model predictions. This makes evaluating interpretability approaches a pressing issue. There are multiple datasets for evaluating NLP Interpretability, but their dependence on human provided ground truths raises questions about their unbiasedness. In this work, we take a d...
2307.06013
Li Cai
Li Cai, Xin Mao, Youshao Xiao, Changxu Wu, Man Lan
An Effective and Efficient Time-aware Entity Alignment Framework via Two-aspect Three-view Label Propagation
Accepted by IJCAI 2023
null
null
null
cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Entity alignment (EA) aims to find the equivalent entity pairs between different knowledge graphs (KGs), which is crucial to promote knowledge fusion. With the wide use of temporal knowledge graphs (TKGs), time-aware EA (TEA) methods appear to enhance EA. Existing TEA models are based on Graph Neural Networks (GNN) a...
[ { "created": "Wed, 12 Jul 2023 08:51:20 GMT", "version": "v1" } ]
2023-07-13
[ [ "Cai", "Li", "" ], [ "Mao", "Xin", "" ], [ "Xiao", "Youshao", "" ], [ "Wu", "Changxu", "" ], [ "Lan", "Man", "" ] ]
Entity alignment (EA) aims to find the equivalent entity pairs between different knowledge graphs (KGs), which is crucial to promote knowledge fusion. With the wide use of temporal knowledge graphs (TKGs), time-aware EA (TEA) methods appear to enhance EA. Existing TEA models are based on Graph Neural Networks (GNN) and...
2311.16406
Arman Roohi
Sepehr Tabrizchi, Shaahin Angizi, Arman Roohi
DIAC: Design Exploration of Intermittent-Aware Computing Realizing Batteryless Systems
6 pages, will be appeared in Design, Automation and Test in Europe Conference 2024
null
null
null
cs.AR cs.ET
http://creativecommons.org/licenses/by-nc-sa/4.0/
Battery-powered IoT devices face challenges like cost, maintenance, and environmental sustainability, prompting the emergence of batteryless energy-harvesting systems that harness ambient sources. However, their intermittent behavior can disrupt program execution and cause data loss, leading to unpredictable outcomes...
[ { "created": "Tue, 28 Nov 2023 01:18:30 GMT", "version": "v1" } ]
2023-11-29
[ [ "Tabrizchi", "Sepehr", "" ], [ "Angizi", "Shaahin", "" ], [ "Roohi", "Arman", "" ] ]
Battery-powered IoT devices face challenges like cost, maintenance, and environmental sustainability, prompting the emergence of batteryless energy-harvesting systems that harness ambient sources. However, their intermittent behavior can disrupt program execution and cause data loss, leading to unpredictable outcomes. ...
2201.00180
Mohammadhossein Ghahramani
Mohammadhossein Ghahramani, Mengchu Zhou, Anna Molter, Francesco Pilla
IoT-based Route Recommendation for an Intelligent Waste Management System
11
null
10.1109/JIOT.2021.3132126
null
cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
The Internet of Things (IoT) is a paradigm characterized by a network of embedded sensors and services. These sensors are incorporated to collect various information, track physical conditions, e.g., waste bins' status, and exchange data with different centralized platforms. The need for such sensors is increasing; h...
[ { "created": "Sat, 1 Jan 2022 12:36:22 GMT", "version": "v1" } ]
2022-01-04
[ [ "Ghahramani", "Mohammadhossein", "" ], [ "Zhou", "Mengchu", "" ], [ "Molter", "Anna", "" ], [ "Pilla", "Francesco", "" ] ]
The Internet of Things (IoT) is a paradigm characterized by a network of embedded sensors and services. These sensors are incorporated to collect various information, track physical conditions, e.g., waste bins' status, and exchange data with different centralized platforms. The need for such sensors is increasing; how...
1107.0919
Markus Lohrey
Stefan G\"oller (University of Bremen), Markus Lohrey (University of Leipzig)
The First-Order Theory of Ground Tree Rewrite Graphs
accepted for Logical Methods in Computer Science
Logical Methods in Computer Science, Volume 10, Issue 1 (February 12, 2014) lmcs:1223
10.2168/LMCS-10(1:7)2014
null
cs.LO cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We prove that the complexity of the uniform first-order theory of ground tree rewrite graphs is in ATIME(2^{2^{poly(n)}},O(n)). Providing a matching lower bound, we show that there is some fixed ground tree rewrite graph whose first-order theory is hard for ATIME(2^{2^{poly(n)}},poly(n)) with respect to logspace redu...
[ { "created": "Tue, 5 Jul 2011 16:32:12 GMT", "version": "v1" }, { "created": "Wed, 6 Jul 2011 22:30:54 GMT", "version": "v2" }, { "created": "Wed, 8 Jan 2014 09:22:16 GMT", "version": "v3" }, { "created": "Mon, 10 Feb 2014 10:39:12 GMT", "version": "v4" } ]
2015-07-01
[ [ "Göller", "Stefan", "", "University of Bremen" ], [ "Lohrey", "Markus", "", "University of\n Leipzig" ] ]
We prove that the complexity of the uniform first-order theory of ground tree rewrite graphs is in ATIME(2^{2^{poly(n)}},O(n)). Providing a matching lower bound, we show that there is some fixed ground tree rewrite graph whose first-order theory is hard for ATIME(2^{2^{poly(n)}},poly(n)) with respect to logspace reduct...
2006.09108
Jinghua Yu
Jinghua Yu, Stefan Wagner, Feng Luo
An STPA-based Approach for Systematic Security Analysis of In-vehicle Diagnostic and Software Update Systems
6 pages, 7 figures, submitted to FISITA 2020 World Congress
null
null
F2020-VES-020, FISITA Web Congress 2020
cs.CR cs.SE cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The in-vehicle diagnostic and software update system, which supports remote diagnostic and Over-The-Air (OTA) software updates, is a critical attack goal in automobiles. Adversaries can inject malicious software into vehicles or steal sensitive information through communication channels. Therefore, security analysis,...
[ { "created": "Tue, 16 Jun 2020 12:34:17 GMT", "version": "v1" } ]
2020-12-01
[ [ "Yu", "Jinghua", "" ], [ "Wagner", "Stefan", "" ], [ "Luo", "Feng", "" ] ]
The in-vehicle diagnostic and software update system, which supports remote diagnostic and Over-The-Air (OTA) software updates, is a critical attack goal in automobiles. Adversaries can inject malicious software into vehicles or steal sensitive information through communication channels. Therefore, security analysis, w...
2306.07084
Karin Festl
Karin Festl, Patrick Promitzer, Daniel Watzenig, Huilin Yin
Performance of Graph Database Management Systems as route planning solutions for different data and usage characteristics
Submitted to IEEE IAVVC 2023
null
null
null
cs.DB cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph databases have grown in popularity in recent years as they are able to efficiently store and query complex relationships between data. Incidentally, navigation data and road networks can be processed, sampled or modified efficiently when stored as a graph. As a result, graph databases are a solution for solving...
[ { "created": "Mon, 12 Jun 2023 12:55:09 GMT", "version": "v1" } ]
2023-06-13
[ [ "Festl", "Karin", "" ], [ "Promitzer", "Patrick", "" ], [ "Watzenig", "Daniel", "" ], [ "Yin", "Huilin", "" ] ]
Graph databases have grown in popularity in recent years as they are able to efficiently store and query complex relationships between data. Incidentally, navigation data and road networks can be processed, sampled or modified efficiently when stored as a graph. As a result, graph databases are a solution for solving r...
1901.08618
Shantanu Sharma
Nisha Panwar, Shantanu Sharma, Guoxi Wang, Sharad Mehrotra, Nalini Venkatasubramanian
Verifiable Round-Robin Scheme for Smart Homes
Accepted in ACM Conference on Data and Application Security and Privacy (CODASPY), 2019. 12 pages
null
10.1145/3292006.3300043
null
cs.CR cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Advances in sensing, networking, and actuation technologies have resulted in the IoT wave that is expected to revolutionize all aspects of modern society. This paper focuses on the new challenges of privacy that arise in IoT in the context of smart homes. Specifically, the paper focuses on preventing the user's priva...
[ { "created": "Thu, 24 Jan 2019 19:20:22 GMT", "version": "v1" } ]
2019-01-28
[ [ "Panwar", "Nisha", "" ], [ "Sharma", "Shantanu", "" ], [ "Wang", "Guoxi", "" ], [ "Mehrotra", "Sharad", "" ], [ "Venkatasubramanian", "Nalini", "" ] ]
Advances in sensing, networking, and actuation technologies have resulted in the IoT wave that is expected to revolutionize all aspects of modern society. This paper focuses on the new challenges of privacy that arise in IoT in the context of smart homes. Specifically, the paper focuses on preventing the user's privacy...
2205.00385
Jichao Yin
Jichao Yin and Hu Wang and Shuhao Li and Daozhen Guo
An efficient topology optimization method based on adaptive reanalysis with projection reduction
42 pages, 32 figures
null
null
null
cs.CE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Efficient topology optimization based on the adaptive auxiliary reduced model reanalysis (AARMR) is proposed to improve computational efficiency and scale. In this method, a projection auxiliary reduced model (PARM) is integrated into the combined approximation reduced model (CARM) to reduce the dimension of the mode...
[ { "created": "Sun, 1 May 2022 02:55:02 GMT", "version": "v1" }, { "created": "Tue, 3 Jan 2023 07:29:47 GMT", "version": "v2" } ]
2023-01-04
[ [ "Yin", "Jichao", "" ], [ "Wang", "Hu", "" ], [ "Li", "Shuhao", "" ], [ "Guo", "Daozhen", "" ] ]
Efficient topology optimization based on the adaptive auxiliary reduced model reanalysis (AARMR) is proposed to improve computational efficiency and scale. In this method, a projection auxiliary reduced model (PARM) is integrated into the combined approximation reduced model (CARM) to reduce the dimension of the model ...
1403.7022
Hengjun Zhao
Jiang Liu and Naijun Zhan and Hengjun Zhao and Liang Zou
Abstraction of Elementary Hybrid Systems by Variable Transformation
null
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Elementary hybrid systems (EHSs) are those hybrid systems (HSs) containing elementary functions such as exp, ln, sin, cos, etc. EHSs are very common in practice, especially in safety-critical domains. Due to the non-polynomial expressions which lead to undecidable arithmetic, verification of EHSs is very hard. Existi...
[ { "created": "Thu, 27 Mar 2014 13:38:12 GMT", "version": "v1" }, { "created": "Mon, 20 Oct 2014 11:43:22 GMT", "version": "v2" }, { "created": "Tue, 13 Jan 2015 09:09:07 GMT", "version": "v3" }, { "created": "Wed, 14 Jan 2015 06:33:56 GMT", "version": "v4" } ]
2015-01-15
[ [ "Liu", "Jiang", "" ], [ "Zhan", "Naijun", "" ], [ "Zhao", "Hengjun", "" ], [ "Zou", "Liang", "" ] ]
Elementary hybrid systems (EHSs) are those hybrid systems (HSs) containing elementary functions such as exp, ln, sin, cos, etc. EHSs are very common in practice, especially in safety-critical domains. Due to the non-polynomial expressions which lead to undecidable arithmetic, verification of EHSs is very hard. Existing...
2406.16449
Mingrui Wu
Mingrui Wu, Jiayi Ji, Oucheng Huang, Jiale Li, Yuhang Wu, Xiaoshuai Sun, Rongrong Ji
Evaluating and Analyzing Relationship Hallucinations in Large Vision-Language Models
ICML2024; Project Page:https://github.com/mrwu-mac/R-Bench
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
The issue of hallucinations is a prevalent concern in existing Large Vision-Language Models (LVLMs). Previous efforts have primarily focused on investigating object hallucinations, which can be easily alleviated by introducing object detectors. However, these efforts neglect hallucinations in inter-object relationshi...
[ { "created": "Mon, 24 Jun 2024 08:42:42 GMT", "version": "v1" }, { "created": "Wed, 3 Jul 2024 03:02:35 GMT", "version": "v2" }, { "created": "Thu, 11 Jul 2024 06:48:39 GMT", "version": "v3" }, { "created": "Thu, 18 Jul 2024 04:39:29 GMT", "version": "v4" } ]
2024-07-19
[ [ "Wu", "Mingrui", "" ], [ "Ji", "Jiayi", "" ], [ "Huang", "Oucheng", "" ], [ "Li", "Jiale", "" ], [ "Wu", "Yuhang", "" ], [ "Sun", "Xiaoshuai", "" ], [ "Ji", "Rongrong", "" ] ]
The issue of hallucinations is a prevalent concern in existing Large Vision-Language Models (LVLMs). Previous efforts have primarily focused on investigating object hallucinations, which can be easily alleviated by introducing object detectors. However, these efforts neglect hallucinations in inter-object relationships...
1909.13516
Yao Wan
Yao Wan, Jingdong Shu, Yulei Sui, Guandong Xu, Zhou Zhao, Jian Wu and Philip S. Yu
Multi-Modal Attention Network Learning for Semantic Source Code Retrieval
null
null
null
null
cs.SE cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Code retrieval techniques and tools have been playing a key role in facilitating software developers to retrieve existing code fragments from available open-source repositories given a user query. Despite the existing efforts in improving the effectiveness of code retrieval, there are still two main issues hindering ...
[ { "created": "Mon, 30 Sep 2019 08:35:04 GMT", "version": "v1" } ]
2019-10-01
[ [ "Wan", "Yao", "" ], [ "Shu", "Jingdong", "" ], [ "Sui", "Yulei", "" ], [ "Xu", "Guandong", "" ], [ "Zhao", "Zhou", "" ], [ "Wu", "Jian", "" ], [ "Yu", "Philip S.", "" ] ]
Code retrieval techniques and tools have been playing a key role in facilitating software developers to retrieve existing code fragments from available open-source repositories given a user query. Despite the existing efforts in improving the effectiveness of code retrieval, there are still two main issues hindering th...
2406.18330
Matan Halfon
Matan Halfon, Eyal Rozenberg, Ehud Rivlin, Daniel Freedman
Molecular Diffusion Models with Virtual Receptors
null
https://neurips.cc/virtual/2023/77389
null
null
cs.LG q-bio.BM
http://creativecommons.org/licenses/by/4.0/
Machine learning approaches to Structure-Based Drug Design (SBDD) have proven quite fertile over the last few years. In particular, diffusion-based approaches to SBDD have shown great promise. We present a technique which expands on this diffusion approach in two crucial ways. First, we address the size disparity bet...
[ { "created": "Wed, 26 Jun 2024 13:18:42 GMT", "version": "v1" } ]
2024-07-01
[ [ "Halfon", "Matan", "" ], [ "Rozenberg", "Eyal", "" ], [ "Rivlin", "Ehud", "" ], [ "Freedman", "Daniel", "" ] ]
Machine learning approaches to Structure-Based Drug Design (SBDD) have proven quite fertile over the last few years. In particular, diffusion-based approaches to SBDD have shown great promise. We present a technique which expands on this diffusion approach in two crucial ways. First, we address the size disparity betwe...
2102.05638
Zach Wood-Doughty
Zach Wood-Doughty, Ilya Shpitser, Mark Dredze
Generating Synthetic Text Data to Evaluate Causal Inference Methods
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Drawing causal conclusions from observational data requires making assumptions about the true data-generating process. Causal inference research typically considers low-dimensional data, such as categorical or numerical fields in structured medical records. High-dimensional and unstructured data such as natural langu...
[ { "created": "Wed, 10 Feb 2021 18:53:11 GMT", "version": "v1" } ]
2021-02-11
[ [ "Wood-Doughty", "Zach", "" ], [ "Shpitser", "Ilya", "" ], [ "Dredze", "Mark", "" ] ]
Drawing causal conclusions from observational data requires making assumptions about the true data-generating process. Causal inference research typically considers low-dimensional data, such as categorical or numerical fields in structured medical records. High-dimensional and unstructured data such as natural languag...
2103.09583
Stefan Ohrhallinger
Stefan Ohrhallinger and Jiju Peethambaran and Amal D. Parakkat and Tamal K. Dey and Ramanathan Muthuganapathy
2D Points Curve Reconstruction Survey and Benchmark
24 pages, 22 figures, 5 tables
null
null
null
cs.GR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Curve reconstruction from unstructured points in a plane is a fundamental problem with many applications that has generated research interest for decades. Involved aspects like handling open, sharp, multiple and non-manifold outlines, run-time and provability as well as potential extension to 3D for surface reconstru...
[ { "created": "Wed, 17 Mar 2021 11:55:43 GMT", "version": "v1" } ]
2021-03-18
[ [ "Ohrhallinger", "Stefan", "" ], [ "Peethambaran", "Jiju", "" ], [ "Parakkat", "Amal D.", "" ], [ "Dey", "Tamal K.", "" ], [ "Muthuganapathy", "Ramanathan", "" ] ]
Curve reconstruction from unstructured points in a plane is a fundamental problem with many applications that has generated research interest for decades. Involved aspects like handling open, sharp, multiple and non-manifold outlines, run-time and provability as well as potential extension to 3D for surface reconstruct...
2210.07547
Songyang Gao
Songyang Gao, Shihan Dou, Qi Zhang, Xuanjing Huang
Kernel-Whitening: Overcome Dataset Bias with Isotropic Sentence Embedding
Accepted by EMNLP2022
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by-sa/4.0/
Dataset bias has attracted increasing attention recently for its detrimental effect on the generalization ability of fine-tuned models. The current mainstream solution is designing an additional shallow model to pre-identify biased instances. However, such two-stage methods scale up the computational complexity of tr...
[ { "created": "Fri, 14 Oct 2022 05:56:38 GMT", "version": "v1" } ]
2022-10-17
[ [ "Gao", "Songyang", "" ], [ "Dou", "Shihan", "" ], [ "Zhang", "Qi", "" ], [ "Huang", "Xuanjing", "" ] ]
Dataset bias has attracted increasing attention recently for its detrimental effect on the generalization ability of fine-tuned models. The current mainstream solution is designing an additional shallow model to pre-identify biased instances. However, such two-stage methods scale up the computational complexity of trai...
1903.12221
Alex Glikson
Ping-Min Lin, Alex Glikson
Mitigating Cold Starts in Serverless Platforms: A Pool-Based Approach
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Rapid adoption of the serverless (or Function-as-a-Service, FaaS) paradigm, pioneered by Amazon with AWS Lambda and followed by numerous commercial offerings and open source projects, introduces new challenges in designing the cloud infrastructure, balancing between performance and cost. While instant per-request ela...
[ { "created": "Thu, 28 Mar 2019 18:55:30 GMT", "version": "v1" } ]
2019-04-01
[ [ "Lin", "Ping-Min", "" ], [ "Glikson", "Alex", "" ] ]
Rapid adoption of the serverless (or Function-as-a-Service, FaaS) paradigm, pioneered by Amazon with AWS Lambda and followed by numerous commercial offerings and open source projects, introduces new challenges in designing the cloud infrastructure, balancing between performance and cost. While instant per-request elast...
2201.12011
Bendaoud Fayssal
Bendaoud Fayssal and Abdennebi Marwen and Didi Fedoua
A MADM method for network selection in heterogeneous wireless networks
null
null
null
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
The coexistence of different Radio Access Technologies (RATs) in the same area has enabled the researchers to get profit from the available networks by the selection of the best RAT at each moment to satisfy the user requirements. The challenge is to achieve the Always Best Connected (ABC) concept; the main issue is ...
[ { "created": "Fri, 28 Jan 2022 09:47:29 GMT", "version": "v1" } ]
2022-01-31
[ [ "Fayssal", "Bendaoud", "" ], [ "Marwen", "Abdennebi", "" ], [ "Fedoua", "Didi", "" ] ]
The coexistence of different Radio Access Technologies (RATs) in the same area has enabled the researchers to get profit from the available networks by the selection of the best RAT at each moment to satisfy the user requirements. The challenge is to achieve the Always Best Connected (ABC) concept; the main issue is th...
1309.6849
Joris Mooij
Joris Mooij, Tom Heskes
Cyclic Causal Discovery from Continuous Equilibrium Data
Appears in Proceedings of the Twenty-Ninth Conference on Uncertainty in Artificial Intelligence (UAI2013)
null
null
UAI-P-2013-PG-431-439
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a method for learning cyclic causal models from a combination of observational and interventional equilibrium data. Novel aspects of the proposed method are its ability to work with continuous data (without assuming linearity) and to deal with feedback loops. Within the context of biochemical reactions, we...
[ { "created": "Thu, 26 Sep 2013 12:45:43 GMT", "version": "v1" } ]
2013-09-27
[ [ "Mooij", "Joris", "" ], [ "Heskes", "Tom", "" ] ]
We propose a method for learning cyclic causal models from a combination of observational and interventional equilibrium data. Novel aspects of the proposed method are its ability to work with continuous data (without assuming linearity) and to deal with feedback loops. Within the context of biochemical reactions, we a...
2405.20680
Mingda Li
Mingda Li, Xinyu Li, Yifan Chen, Wenfeng Xuan, Weinan Zhang
Unraveling and Mitigating Retriever Inconsistencies in Retrieval-Augmented Large Language Models
ACL 2024 (findings)
null
null
null
cs.AI cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Although Retrieval-Augmented Large Language Models (RALMs) demonstrate their superiority in terms of factuality, they do not consistently outperform the original retrieval-free Language Models (LMs). Our experiments reveal that this example-level performance inconsistency exists not only between retrieval-augmented a...
[ { "created": "Fri, 31 May 2024 08:22:49 GMT", "version": "v1" }, { "created": "Mon, 3 Jun 2024 06:20:18 GMT", "version": "v2" }, { "created": "Tue, 4 Jun 2024 11:51:53 GMT", "version": "v3" } ]
2024-06-05
[ [ "Li", "Mingda", "" ], [ "Li", "Xinyu", "" ], [ "Chen", "Yifan", "" ], [ "Xuan", "Wenfeng", "" ], [ "Zhang", "Weinan", "" ] ]
Although Retrieval-Augmented Large Language Models (RALMs) demonstrate their superiority in terms of factuality, they do not consistently outperform the original retrieval-free Language Models (LMs). Our experiments reveal that this example-level performance inconsistency exists not only between retrieval-augmented and...