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2309.02317
Yuxiang Guo
Yuxiang Guo, Xiaopeng Gao, Zhenyu Zhang, W.K.Chan and Bo Jiang
A study on the impact of pre-trained model on Just-In-Time defect prediction
Accepted by QRS2023
null
null
null
cs.SE cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Previous researchers conducting Just-In-Time (JIT) defect prediction tasks have primarily focused on the performance of individual pre-trained models, without exploring the relationship between different pre-trained models as backbones. In this study, we build six models: RoBERTaJIT, CodeBERTJIT, BARTJIT, PLBARTJIT, ...
[ { "created": "Tue, 5 Sep 2023 15:34:22 GMT", "version": "v1" }, { "created": "Thu, 23 Nov 2023 06:19:01 GMT", "version": "v2" } ]
2023-11-27
[ [ "Guo", "Yuxiang", "" ], [ "Gao", "Xiaopeng", "" ], [ "Zhang", "Zhenyu", "" ], [ "Chan", "W. K.", "" ], [ "Jiang", "Bo", "" ] ]
Previous researchers conducting Just-In-Time (JIT) defect prediction tasks have primarily focused on the performance of individual pre-trained models, without exploring the relationship between different pre-trained models as backbones. In this study, we build six models: RoBERTaJIT, CodeBERTJIT, BARTJIT, PLBARTJIT, GP...
1804.04647
Yigit Baran Can
Yigit Baran Can, Radu Timofte
An efficient CNN for spectral reconstruction from RGB images
Submitted to ICIP 2018
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, the example-based single image spectral reconstruction from RGB images task, aka, spectral super-resolution was approached by means of deep learning by Galliani et al. The proposed very deep convolutional neural network (CNN) achieved superior performance on recent large benchmarks. However, Aeschbacher et ...
[ { "created": "Thu, 12 Apr 2018 17:48:05 GMT", "version": "v1" } ]
2018-04-13
[ [ "Can", "Yigit Baran", "" ], [ "Timofte", "Radu", "" ] ]
Recently, the example-based single image spectral reconstruction from RGB images task, aka, spectral super-resolution was approached by means of deep learning by Galliani et al. The proposed very deep convolutional neural network (CNN) achieved superior performance on recent large benchmarks. However, Aeschbacher et al...
1802.09307
Konrad Hinsen
Konrad Hinsen
Digital Scientific Notations as a Human-Computer Interface in Computer-Aided Research
null
null
10.7717/peerj-cs.158
null
cs.HC cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most of today's scientific research relies on computers and software not only for administrational tasks, but also for processing scientific information. Examples of such computer-aided research are the analysis of experimental data or the simulation of phenomena based on theoretical models. With the rapid increase o...
[ { "created": "Thu, 22 Feb 2018 15:51:43 GMT", "version": "v1" } ]
2018-08-06
[ [ "Hinsen", "Konrad", "" ] ]
Most of today's scientific research relies on computers and software not only for administrational tasks, but also for processing scientific information. Examples of such computer-aided research are the analysis of experimental data or the simulation of phenomena based on theoretical models. With the rapid increase of ...
2211.13962
Rasoul Nikbakht Silab
Rasoul Nikbakht, Sarang Kahvazadeh, Josep Mangues-Bafalluy
Video on Demand Streaming Using RL-based Edge Caching in 5G Networks
3 pages, 1 figure One page version of this paper has been accepted to 2022 IEEE Conference on Standards for Communications and Networking (CSCN) - Demo submissions
null
null
null
cs.NI
http://creativecommons.org/licenses/by-nc-sa/4.0/
Edge caching can significantly improve the 5G networks' performance both in terms of delay and backhaul traffic. We use a reinforcement learning-based (RL-based) caching technique that can adapt to time-location-dependent popularity patterns for on-demand video contents. In a private 5G, we implement the proposed cac...
[ { "created": "Fri, 25 Nov 2022 09:11:01 GMT", "version": "v1" } ]
2022-11-28
[ [ "Nikbakht", "Rasoul", "" ], [ "Kahvazadeh", "Sarang", "" ], [ "Mangues-Bafalluy", "Josep", "" ] ]
Edge caching can significantly improve the 5G networks' performance both in terms of delay and backhaul traffic. We use a reinforcement learning-based (RL-based) caching technique that can adapt to time-location-dependent popularity patterns for on-demand video contents. In a private 5G, we implement the proposed cachi...
2306.07695
Evangelos Bitsikas
Evangelos Bitsikas, Theodor Schnitzler, Christina P\"opper, Aanjhan Ranganathan
Freaky Leaky SMS: Extracting User Locations by Analyzing SMS Timings
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Short Message Service (SMS) remains one of the most popular communication channels since its introduction in 2G cellular networks. In this paper, we demonstrate that merely receiving silent SMS messages regularly opens a stealthy side-channel that allows other regular network users to infer the whereabouts of the SMS...
[ { "created": "Tue, 13 Jun 2023 11:20:18 GMT", "version": "v1" }, { "created": "Wed, 14 Jun 2023 08:36:18 GMT", "version": "v2" } ]
2023-06-16
[ [ "Bitsikas", "Evangelos", "" ], [ "Schnitzler", "Theodor", "" ], [ "Pöpper", "Christina", "" ], [ "Ranganathan", "Aanjhan", "" ] ]
Short Message Service (SMS) remains one of the most popular communication channels since its introduction in 2G cellular networks. In this paper, we demonstrate that merely receiving silent SMS messages regularly opens a stealthy side-channel that allows other regular network users to infer the whereabouts of the SMS r...
1906.09108
Huiping Zhuang
Huiping Zhuang, Yi Wang, Qinglai Liu, Shuai Zhang, Zhiping Lin
Fully Decoupled Neural Network Learning Using Delayed Gradients
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Training neural networks with back-propagation (BP) requires a sequential passing of activations and gradients, which forces the network modules to work in a synchronous fashion. This has been recognized as the lockings (i.e., the forward, backward and update lockings) inherited from the BP. In this paper, we propose...
[ { "created": "Fri, 21 Jun 2019 13:02:35 GMT", "version": "v1" }, { "created": "Wed, 18 Sep 2019 11:18:32 GMT", "version": "v2" }, { "created": "Fri, 22 Nov 2019 07:01:47 GMT", "version": "v3" } ]
2019-11-25
[ [ "Zhuang", "Huiping", "" ], [ "Wang", "Yi", "" ], [ "Liu", "Qinglai", "" ], [ "Zhang", "Shuai", "" ], [ "Lin", "Zhiping", "" ] ]
Training neural networks with back-propagation (BP) requires a sequential passing of activations and gradients, which forces the network modules to work in a synchronous fashion. This has been recognized as the lockings (i.e., the forward, backward and update lockings) inherited from the BP. In this paper, we propose a...
2309.01736
Yuze Li
Yuze Li, Shunyu Yao
Understanding and Optimizing Serverless Workloads in CXL-Enabled Tiered Memory
This paper will be part of my under-going research, thus me and my advisor agreed on to withdraw this pre-print for now, until the final project is finished
null
null
null
cs.DC
http://creativecommons.org/licenses/by/4.0/
Recent Serverless workloads tend to be largescaled/CPU-memory intensive, such as DL, graph applications, that require dynamic memory-to-compute resources provisioning. Meanwhile, recent solutions seek to design page management strategies for multi-tiered memory systems, to efficiently run heavy workloads. Compute E...
[ { "created": "Mon, 4 Sep 2023 17:40:03 GMT", "version": "v1" }, { "created": "Fri, 22 Sep 2023 18:08:05 GMT", "version": "v2" } ]
2023-09-26
[ [ "Li", "Yuze", "" ], [ "Yao", "Shunyu", "" ] ]
Recent Serverless workloads tend to be largescaled/CPU-memory intensive, such as DL, graph applications, that require dynamic memory-to-compute resources provisioning. Meanwhile, recent solutions seek to design page management strategies for multi-tiered memory systems, to efficiently run heavy workloads. Compute Expre...
1308.2188
Li Zhu
Hongwei Wang, F. Richard Yu, Li Zhu, Tao Tang, and Bin Ning
Finite-State Markov Modeling of Leaky Waveguide Channels in Communication-based Train Control (CBTC) Systems
3 pages, 4 figures, letter. arXiv admin note: text overlap with arXiv:1307.7807
null
null
null
cs.DM cs.IT math.IT
http://creativecommons.org/licenses/by-nc-sa/3.0/
Leaky waveguide has been adopted in communication based train control (CBTC) systems, as it can significantly enhance railway network efficiency, safety and capacity. Since CBTC systems have high requirements for the train ground communications, modeling the leaky waveguide channels is very important to design the wi...
[ { "created": "Tue, 30 Jul 2013 04:33:07 GMT", "version": "v1" } ]
2013-08-12
[ [ "Wang", "Hongwei", "" ], [ "Yu", "F. Richard", "" ], [ "Zhu", "Li", "" ], [ "Tang", "Tao", "" ], [ "Ning", "Bin", "" ] ]
Leaky waveguide has been adopted in communication based train control (CBTC) systems, as it can significantly enhance railway network efficiency, safety and capacity. Since CBTC systems have high requirements for the train ground communications, modeling the leaky waveguide channels is very important to design the wire...
1508.02705
Ioannis Filippidis
Ioannis Filippidis and Richard M. Murray
Symbolic construction of GR(1) contracts for synchronous systems with full information
null
null
null
null
cs.LO cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work proposes a symbolic algorithm for the construction of assume-guarantee specifications that allow multiple agents to cooperate. Each agent is assigned goals expressed in a fragment of linear temporal logic known as generalized reactivity of rank 1 (GR(1)). These goals may be unrealizable, unless additional a...
[ { "created": "Tue, 11 Aug 2015 19:53:14 GMT", "version": "v1" } ]
2015-08-12
[ [ "Filippidis", "Ioannis", "" ], [ "Murray", "Richard M.", "" ] ]
This work proposes a symbolic algorithm for the construction of assume-guarantee specifications that allow multiple agents to cooperate. Each agent is assigned goals expressed in a fragment of linear temporal logic known as generalized reactivity of rank 1 (GR(1)). These goals may be unrealizable, unless additional ass...
2112.10664
Ankit Anand
Eser Ayg\"un, Laurent Orseau, Ankit Anand, Xavier Glorot, Vlad Firoiu, Lei M. Zhang, Doina Precup and Shibl Mourad
Proving Theorems using Incremental Learning and Hindsight Experience Replay
16 pages, 2 figures
null
null
null
cs.AI cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traditional automated theorem provers for first-order logic depend on speed-optimized search and many handcrafted heuristics that are designed to work best over a wide range of domains. Machine learning approaches in literature either depend on these traditional provers to bootstrap themselves or fall short on reachi...
[ { "created": "Mon, 20 Dec 2021 16:40:26 GMT", "version": "v1" } ]
2021-12-21
[ [ "Aygün", "Eser", "" ], [ "Orseau", "Laurent", "" ], [ "Anand", "Ankit", "" ], [ "Glorot", "Xavier", "" ], [ "Firoiu", "Vlad", "" ], [ "Zhang", "Lei M.", "" ], [ "Precup", "Doina", "" ], [ "Mourad", ...
Traditional automated theorem provers for first-order logic depend on speed-optimized search and many handcrafted heuristics that are designed to work best over a wide range of domains. Machine learning approaches in literature either depend on these traditional provers to bootstrap themselves or fall short on reaching...
1811.08677
Zuogong Yue
Zuogong Yue, Johan Thunberg, Lennart Ljung and Jorge Goncalves
A state-space approach to sparse dynamic network reconstruction
7 pages; preprint for CDC 2018 review
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Dynamic network reconstruction has been shown to be challenging due to the requirements on sparse network structures and network identifiability. The direct parametric method (e.g., using ARX models) requires a large amount of parameters in model selection. Amongst the parametric models, only a restricted class can e...
[ { "created": "Wed, 21 Nov 2018 10:52:57 GMT", "version": "v1" } ]
2018-11-22
[ [ "Yue", "Zuogong", "" ], [ "Thunberg", "Johan", "" ], [ "Ljung", "Lennart", "" ], [ "Goncalves", "Jorge", "" ] ]
Dynamic network reconstruction has been shown to be challenging due to the requirements on sparse network structures and network identifiability. The direct parametric method (e.g., using ARX models) requires a large amount of parameters in model selection. Amongst the parametric models, only a restricted class can eas...
2112.01741
Matan Atzmon
Matan Atzmon, Koki Nagano, Sanja Fidler, Sameh Khamis, Yaron Lipman
Frame Averaging for Equivariant Shape Space Learning
Accepted to CVPR 2022
null
null
null
cs.CV cs.GR cs.LG
http://creativecommons.org/licenses/by/4.0/
The task of shape space learning involves mapping a train set of shapes to and from a latent representation space with good generalization properties. Often, real-world collections of shapes have symmetries, which can be defined as transformations that do not change the essence of the shape. A natural way to incorpor...
[ { "created": "Fri, 3 Dec 2021 06:41:19 GMT", "version": "v1" }, { "created": "Fri, 26 Aug 2022 19:52:20 GMT", "version": "v2" } ]
2022-08-30
[ [ "Atzmon", "Matan", "" ], [ "Nagano", "Koki", "" ], [ "Fidler", "Sanja", "" ], [ "Khamis", "Sameh", "" ], [ "Lipman", "Yaron", "" ] ]
The task of shape space learning involves mapping a train set of shapes to and from a latent representation space with good generalization properties. Often, real-world collections of shapes have symmetries, which can be defined as transformations that do not change the essence of the shape. A natural way to incorporat...
2010.10039
Dingwen Tao
Jiannan Tian, Cody Rivera, Sheng Di, Jieyang Chen, Xin Liang, Dingwen Tao, Franck Cappello
Revisiting Huffman Coding: Toward Extreme Performance on Modern GPU Architectures
11 pages, 3 figures, 6 tables, published by IEEE IPDPS'21
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that data compression is becoming a critical technique to mitigate the storage burden and data movement cost. Huffman coding is arguably the most...
[ { "created": "Tue, 20 Oct 2020 05:21:55 GMT", "version": "v1" }, { "created": "Mon, 1 Mar 2021 16:11:20 GMT", "version": "v2" } ]
2021-03-02
[ [ "Tian", "Jiannan", "" ], [ "Rivera", "Cody", "" ], [ "Di", "Sheng", "" ], [ "Chen", "Jieyang", "" ], [ "Liang", "Xin", "" ], [ "Tao", "Dingwen", "" ], [ "Cappello", "Franck", "" ] ]
Today's high-performance computing (HPC) applications are producing vast volumes of data, which are challenging to store and transfer efficiently during the execution, such that data compression is becoming a critical technique to mitigate the storage burden and data movement cost. Huffman coding is arguably the most e...
2205.01959
Mingsheng Ying
Mingsheng Ying
Birkhoff-von Neumann Quantum Logic as an Assertion Language for Quantum Programs
null
null
null
null
cs.LO cs.PL quant-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A first-order logic with quantum variables is needed as an assertion language for specifying and reasoning about various properties (e.g. correctness) of quantum programs. Surprisingly, such a logic is missing in the literature, and the existing first-order Birkhoff-von Neumann quantum logic deals with only classical...
[ { "created": "Wed, 4 May 2022 08:57:44 GMT", "version": "v1" } ]
2022-05-06
[ [ "Ying", "Mingsheng", "" ] ]
A first-order logic with quantum variables is needed as an assertion language for specifying and reasoning about various properties (e.g. correctness) of quantum programs. Surprisingly, such a logic is missing in the literature, and the existing first-order Birkhoff-von Neumann quantum logic deals with only classical v...
2406.13824
Aleksandr Kazachkov
Connor Johnston, Aleksandr M. Kazachkov
Symmetrically Fair Allocations of Indivisible Goods
null
null
null
null
cs.GT math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider allocating indivisible goods with provable fairness guarantees that are satisfied regardless of which bundle of items each agent receives. Symmetrical allocations of this type are known to exist for divisible resources, such as consensus splitting of a cake into parts, each having equal value for all agen...
[ { "created": "Wed, 19 Jun 2024 20:34:08 GMT", "version": "v1" } ]
2024-06-21
[ [ "Johnston", "Connor", "" ], [ "Kazachkov", "Aleksandr M.", "" ] ]
We consider allocating indivisible goods with provable fairness guarantees that are satisfied regardless of which bundle of items each agent receives. Symmetrical allocations of this type are known to exist for divisible resources, such as consensus splitting of a cake into parts, each having equal value for all agents...
2312.08872
Jiafeng Mao
Jiafeng Mao, Xueting Wang, Kiyoharu Aizawa
The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven Initialization
ECCV 2024 Accepted
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Text-to-image diffusion models allow users control over the content of generated images. Still, text-to-image generation occasionally leads to generation failure requiring users to generate dozens of images under the same text prompt before they obtain a satisfying result. We formulate the lottery ticket hypothesis i...
[ { "created": "Wed, 13 Dec 2023 03:31:19 GMT", "version": "v1" }, { "created": "Sun, 10 Mar 2024 02:08:31 GMT", "version": "v2" }, { "created": "Sun, 14 Jul 2024 14:06:47 GMT", "version": "v3" } ]
2024-07-16
[ [ "Mao", "Jiafeng", "" ], [ "Wang", "Xueting", "" ], [ "Aizawa", "Kiyoharu", "" ] ]
Text-to-image diffusion models allow users control over the content of generated images. Still, text-to-image generation occasionally leads to generation failure requiring users to generate dozens of images under the same text prompt before they obtain a satisfying result. We formulate the lottery ticket hypothesis in ...
1407.4017
Dyonisius Dony Ariananda
Dyonisius Dony Ariananda, Daniel Romero, and Geert Leus
Compressive Periodogram Reconstruction Using Uniform Binning
Submitted to IEEE Transactions on Signal Processing
null
10.1109/TSP.2015.2430838
null
cs.OH math.SP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, two problems that show great similarities are examined. The first problem is the reconstruction of the angular-domain periodogram from spatial-domain signals received at different time indices. The second one is the reconstruction of the frequency-domain periodogram from time-domain signals received at...
[ { "created": "Wed, 9 Jul 2014 16:40:57 GMT", "version": "v1" }, { "created": "Fri, 19 Dec 2014 15:50:35 GMT", "version": "v2" } ]
2016-11-17
[ [ "Ariananda", "Dyonisius Dony", "" ], [ "Romero", "Daniel", "" ], [ "Leus", "Geert", "" ] ]
In this paper, two problems that show great similarities are examined. The first problem is the reconstruction of the angular-domain periodogram from spatial-domain signals received at different time indices. The second one is the reconstruction of the frequency-domain periodogram from time-domain signals received at d...
2306.07968
Gyungin Shin
Gyungin Shin, Weidi Xie, Samuel Albanie
arXiVeri: Automatic table verification with GPT
Tech report
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Without accurate transcription of numerical data in scientific documents, a scientist cannot draw accurate conclusions. Unfortunately, the process of copying numerical data from one paper to another is prone to human error. In this paper, we propose to meet this challenge through the novel task of automatic table ver...
[ { "created": "Tue, 13 Jun 2023 17:59:57 GMT", "version": "v1" } ]
2023-06-14
[ [ "Shin", "Gyungin", "" ], [ "Xie", "Weidi", "" ], [ "Albanie", "Samuel", "" ] ]
Without accurate transcription of numerical data in scientific documents, a scientist cannot draw accurate conclusions. Unfortunately, the process of copying numerical data from one paper to another is prone to human error. In this paper, we propose to meet this challenge through the novel task of automatic table verif...
1809.05833
Kyudong Park
Kyudong Park, Dohyeon Kim, Sung H. Han
Usability of the Size, Spacing, and Depth of Virtual Buttons on Head-Mounted Displays
null
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Virtual reality (VR) allows users to see and manipulate virtual scenes and items through input devices, like head-mounted displays. In this study, the effects of button size, spacing, and depth on the usability of virtual buttons in VR environments were investigated. Task completion time, number of errors, and subjec...
[ { "created": "Sun, 16 Sep 2018 08:01:11 GMT", "version": "v1" } ]
2018-09-18
[ [ "Park", "Kyudong", "" ], [ "Kim", "Dohyeon", "" ], [ "Han", "Sung H.", "" ] ]
Virtual reality (VR) allows users to see and manipulate virtual scenes and items through input devices, like head-mounted displays. In this study, the effects of button size, spacing, and depth on the usability of virtual buttons in VR environments were investigated. Task completion time, number of errors, and subjecti...
1402.2425
Bei Yu
Bei Yu and Jhih-Rong Gao and David Z. Pan
Triple Patterning Lithography (TPL) Layout Decomposition using End-Cutting
null
null
10.1117/12.2011355
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Triple patterning lithography (TPL) is one of the most promising techniques in the 14nm logic node and beyond. However, traditional LELELE type TPL technology suffers from native conflict and overlapping problems. Recently LELEEC process was proposed to overcome the limitations, where the third mask is used to genera...
[ { "created": "Tue, 11 Feb 2014 10:26:20 GMT", "version": "v1" } ]
2014-02-12
[ [ "Yu", "Bei", "" ], [ "Gao", "Jhih-Rong", "" ], [ "Pan", "David Z.", "" ] ]
Triple patterning lithography (TPL) is one of the most promising techniques in the 14nm logic node and beyond. However, traditional LELELE type TPL technology suffers from native conflict and overlapping problems. Recently LELEEC process was proposed to overcome the limitations, where the third mask is used to generate...
2301.12382
Maolin Yang
Maolin Yang, Pingyu Jiang, Tianshuo Zang, Yuhao Liu
Data-driven intelligent computational design for products: Method, techniques, and applications
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data-driven intelligent computational design (DICD) is a research hotspot emerged under the context of fast-developing artificial intelligence. It emphasizes on utilizing deep learning algorithms to extract and represent the design features hidden in historical or fabricated design process data, and then learn the co...
[ { "created": "Sun, 29 Jan 2023 07:17:46 GMT", "version": "v1" }, { "created": "Tue, 11 Apr 2023 07:19:31 GMT", "version": "v2" } ]
2023-04-12
[ [ "Yang", "Maolin", "" ], [ "Jiang", "Pingyu", "" ], [ "Zang", "Tianshuo", "" ], [ "Liu", "Yuhao", "" ] ]
Data-driven intelligent computational design (DICD) is a research hotspot emerged under the context of fast-developing artificial intelligence. It emphasizes on utilizing deep learning algorithms to extract and represent the design features hidden in historical or fabricated design process data, and then learn the comb...
2009.13761
EPTCS
David M. Russinoff (Arm)
Formal Verification of Arithmetic RTL: Translating Verilog to C++ to ACL2
In Proceedings ACL2 2020, arXiv:2009.12521
EPTCS 327, 2020, pp. 1-15
10.4204/EPTCS.327.1
null
cs.LO cs.SC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a methodology for formal verification of arithmetic RTL designs that combines sequential logic equivalence checking with interactive theorem proving. An intermediate model of a Verilog module is hand-coded in Restricted Algorithmic C (RAC), a primitive subset of C augmented by the integer and fixed-point r...
[ { "created": "Tue, 29 Sep 2020 04:09:53 GMT", "version": "v1" } ]
2020-09-30
[ [ "Russinoff", "David M.", "", "Arm" ] ]
We present a methodology for formal verification of arithmetic RTL designs that combines sequential logic equivalence checking with interactive theorem proving. An intermediate model of a Verilog module is hand-coded in Restricted Algorithmic C (RAC), a primitive subset of C augmented by the integer and fixed-point reg...
2202.03270
Biruk Asmare Muse
Biruk Asmare Muse and Foutse Khomh and Giuliano Antoniol
Do Developers Refactor Data Access Code? An Empirical Study
29th IEEE International Conference on Software Analysis, Evolution and Reengineering
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Developers often refactor code to improve the maintainability and comprehension of the software. There are many studies on refactoring activities in traditional software systems. However, refactoring in data-intensive systems is not well explored. Understanding the refactoring practices of developers is important to ...
[ { "created": "Mon, 7 Feb 2022 15:06:26 GMT", "version": "v1" } ]
2022-02-08
[ [ "Muse", "Biruk Asmare", "" ], [ "Khomh", "Foutse", "" ], [ "Antoniol", "Giuliano", "" ] ]
Developers often refactor code to improve the maintainability and comprehension of the software. There are many studies on refactoring activities in traditional software systems. However, refactoring in data-intensive systems is not well explored. Understanding the refactoring practices of developers is important to de...
2102.04707
Nikolas M\"ahlmann
Nikolas M\"ahlmann, Sebastian Siebertz, Alexandre Vigny
Recursive Backdoors for SAT
null
null
null
null
cs.DS cs.DM cs.LO
http://creativecommons.org/licenses/by/4.0/
A strong backdoor in a formula $\phi$ of propositional logic to a tractable class $\mathcal{C}$ of formulas is a set $B$ of variables of $\phi$ such that every assignment of the variables in $B$ results in a formula from $\mathcal{C}$. Strong backdoors of small size or with a good structure, e.g. with small backdoor ...
[ { "created": "Tue, 9 Feb 2021 08:53:57 GMT", "version": "v1" } ]
2021-02-10
[ [ "Mählmann", "Nikolas", "" ], [ "Siebertz", "Sebastian", "" ], [ "Vigny", "Alexandre", "" ] ]
A strong backdoor in a formula $\phi$ of propositional logic to a tractable class $\mathcal{C}$ of formulas is a set $B$ of variables of $\phi$ such that every assignment of the variables in $B$ results in a formula from $\mathcal{C}$. Strong backdoors of small size or with a good structure, e.g. with small backdoor tr...
1502.06577
Theodore Book
Theodore Book and Dan S. Wallach
An Empirical Study of Mobile Ad Targeting
Submitted to USENIX Security 2015
null
null
null
cs.CR cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Advertising, long the financial mainstay of the web ecosystem, has become nearly ubiquitous in the world of mobile apps. While ad targeting on the web is fairly well understood, mobile ad targeting is much less studied. In this paper, we use empirical methods to collect a database of over 225,000 ads on 32 simulated ...
[ { "created": "Mon, 23 Feb 2015 20:12:54 GMT", "version": "v1" } ]
2015-02-24
[ [ "Book", "Theodore", "" ], [ "Wallach", "Dan S.", "" ] ]
Advertising, long the financial mainstay of the web ecosystem, has become nearly ubiquitous in the world of mobile apps. While ad targeting on the web is fairly well understood, mobile ad targeting is much less studied. In this paper, we use empirical methods to collect a database of over 225,000 ads on 32 simulated de...
2010.12038
Mohammad Arani
Miguel Baritto, Md Mashum Billal, S. M. Muntasir Nasim, Rumana Afroz Sultana, Mohammad Arani, Ahmed Jawad Qureshi
Supporting Tool for The Transition of Existing Small and Medium Enterprises Towards Industry 4.0
This paper is accepted by the "International Conference on Data Analytics for Business and Industry", and it will be published by IEEE Xplore. (http://data20.uob.edu.bh/)
null
null
null
cs.CY econ.GN q-fin.EC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The rapid growth of Industry 4.0 technologies such as big data, cloud computing, smart sensors, machine learning (ML), radio-frequency identification (RFID), robotics, 3D-printing, and Internet of Things (IoT) offers Small and Medium Enterprises (SMEs) the chance to improve productivity and efficiency, reduce cost an...
[ { "created": "Thu, 15 Oct 2020 15:57:23 GMT", "version": "v1" } ]
2020-10-26
[ [ "Baritto", "Miguel", "" ], [ "Billal", "Md Mashum", "" ], [ "Nasim", "S. M. Muntasir", "" ], [ "Sultana", "Rumana Afroz", "" ], [ "Arani", "Mohammad", "" ], [ "Qureshi", "Ahmed Jawad", "" ] ]
The rapid growth of Industry 4.0 technologies such as big data, cloud computing, smart sensors, machine learning (ML), radio-frequency identification (RFID), robotics, 3D-printing, and Internet of Things (IoT) offers Small and Medium Enterprises (SMEs) the chance to improve productivity and efficiency, reduce cost and ...
2207.10741
Caleb Tung
Caleb Tung, Abhinav Goel, Xiao Hu, Nicholas Eliopoulos, Emmanuel Amobi, George K. Thiruvathukal, Vipin Chaudhary and Yung-Hsiang Lu
Irrelevant Pixels are Everywhere: Find and Exclude Them for More Efficient Computer Vision
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Computer vision is often performed using Convolutional Neural Networks (CNNs). CNNs are compute-intensive and challenging to deploy on power-contrained systems such as mobile and Internet-of-Things (IoT) devices. CNNs are compute-intensive because they indiscriminately compute many features on all pixels of the input...
[ { "created": "Thu, 21 Jul 2022 20:22:15 GMT", "version": "v1" } ]
2022-07-25
[ [ "Tung", "Caleb", "" ], [ "Goel", "Abhinav", "" ], [ "Hu", "Xiao", "" ], [ "Eliopoulos", "Nicholas", "" ], [ "Amobi", "Emmanuel", "" ], [ "Thiruvathukal", "George K.", "" ], [ "Chaudhary", "Vipin", "" ], ...
Computer vision is often performed using Convolutional Neural Networks (CNNs). CNNs are compute-intensive and challenging to deploy on power-contrained systems such as mobile and Internet-of-Things (IoT) devices. CNNs are compute-intensive because they indiscriminately compute many features on all pixels of the input i...
1911.09247
Zewei Chu
Zewei Chu, Mingda Chen, Jing Chen, Miaosen Wang, Kevin Gimpel, Manaal Faruqui and Xiance Si
How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions
AAAI 2020
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a large-scale dataset for the task of rewriting an ill-formed natural language question to a well-formed one. Our multi-domain question rewriting MQR dataset is constructed from human contributed Stack Exchange question edit histories. The dataset contains 427,719 question pairs which come from 303 domains...
[ { "created": "Thu, 21 Nov 2019 02:24:21 GMT", "version": "v1" } ]
2019-11-22
[ [ "Chu", "Zewei", "" ], [ "Chen", "Mingda", "" ], [ "Chen", "Jing", "" ], [ "Wang", "Miaosen", "" ], [ "Gimpel", "Kevin", "" ], [ "Faruqui", "Manaal", "" ], [ "Si", "Xiance", "" ] ]
We present a large-scale dataset for the task of rewriting an ill-formed natural language question to a well-formed one. Our multi-domain question rewriting MQR dataset is constructed from human contributed Stack Exchange question edit histories. The dataset contains 427,719 question pairs which come from 303 domains. ...
2007.05975
Benjamin Rubinstein
Tobias Edwards, Benjamin I. P. Rubinstein, Zuhe Zhang, Sanming Zhou
A Graph Symmetrisation Bound on Channel Information Leakage under Blowfish Privacy
11 pages, 5 figures; accepted to IEEE Transactions on Information Theory
null
null
null
cs.IT cs.CR cs.LG math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Blowfish privacy is a recent generalisation of differential privacy that enables improved utility while maintaining privacy policies with semantic guarantees, a factor that has driven the popularity of differential privacy in computer science. This paper relates Blowfish privacy to an important measure of privacy los...
[ { "created": "Sun, 12 Jul 2020 12:38:32 GMT", "version": "v1" }, { "created": "Mon, 7 Jun 2021 06:43:47 GMT", "version": "v2" }, { "created": "Wed, 13 Oct 2021 12:42:54 GMT", "version": "v3" } ]
2021-10-14
[ [ "Edwards", "Tobias", "" ], [ "Rubinstein", "Benjamin I. P.", "" ], [ "Zhang", "Zuhe", "" ], [ "Zhou", "Sanming", "" ] ]
Blowfish privacy is a recent generalisation of differential privacy that enables improved utility while maintaining privacy policies with semantic guarantees, a factor that has driven the popularity of differential privacy in computer science. This paper relates Blowfish privacy to an important measure of privacy loss ...
1209.5494
Nafiza Saidin
Nafiza Saidin, Harsa Amylia Mat Sakim, Umi Kalthum Ngah and Ibrahim Lutfi Shuaib
Segmentation of Breast Regions in Mammogram Based on Density: A Review
9 pages, 2 figures,IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 2, July 2012
IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 4, No 2, July 2012
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The focus of this paper is to review approaches for segmentation of breast regions in mammograms according to breast density. Studies based on density have been undertaken because of the relationship between breast cancer and density. Breast cancer usually occurs in the fibroglandular area of breast tissue, which app...
[ { "created": "Tue, 25 Sep 2012 04:58:55 GMT", "version": "v1" } ]
2012-09-26
[ [ "Saidin", "Nafiza", "" ], [ "Sakim", "Harsa Amylia Mat", "" ], [ "Ngah", "Umi Kalthum", "" ], [ "Shuaib", "Ibrahim Lutfi", "" ] ]
The focus of this paper is to review approaches for segmentation of breast regions in mammograms according to breast density. Studies based on density have been undertaken because of the relationship between breast cancer and density. Breast cancer usually occurs in the fibroglandular area of breast tissue, which appea...
2401.06391
Chong Wang
Chong Wang and Jian Zhang and Yebo Feng and Tianlin Li and Weisong Sun and Yang Liu and Xin Peng
Teaching Code LLMs to Use Autocompletion Tools in Repository-Level Code Generation
null
null
null
null
cs.SE
http://creativecommons.org/licenses/by/4.0/
Code large language models (LLMs) face limitations in repository-level code generation due to their lack of awareness of repository-level dependencies (e.g., user-defined attributes), resulting in dependency errors such as undefined-variable and no-member errors. In this work, we introduce ToolGen, an approach that i...
[ { "created": "Fri, 12 Jan 2024 06:03:56 GMT", "version": "v1" }, { "created": "Sun, 21 Jan 2024 08:41:09 GMT", "version": "v2" }, { "created": "Thu, 18 Jul 2024 07:04:38 GMT", "version": "v3" } ]
2024-07-19
[ [ "Wang", "Chong", "" ], [ "Zhang", "Jian", "" ], [ "Feng", "Yebo", "" ], [ "Li", "Tianlin", "" ], [ "Sun", "Weisong", "" ], [ "Liu", "Yang", "" ], [ "Peng", "Xin", "" ] ]
Code large language models (LLMs) face limitations in repository-level code generation due to their lack of awareness of repository-level dependencies (e.g., user-defined attributes), resulting in dependency errors such as undefined-variable and no-member errors. In this work, we introduce ToolGen, an approach that int...
2403.13268
Ningyi Liao
Ningyi Liao and Zihao Yu and Siqiang Luo
Unifews: Unified Entry-Wise Sparsification for Efficient Graph Neural Network
null
null
null
null
cs.LG cs.DB
http://creativecommons.org/licenses/by-nc-nd/4.0/
Graph Neural Networks (GNNs) have shown promising performance in various graph learning tasks, but at the cost of resource-intensive computations. The primary overhead of GNN update stems from graph propagation and weight transformation, both involving operations on graph-scale matrices. Previous studies attempt to r...
[ { "created": "Wed, 20 Mar 2024 03:07:30 GMT", "version": "v1" } ]
2024-03-21
[ [ "Liao", "Ningyi", "" ], [ "Yu", "Zihao", "" ], [ "Luo", "Siqiang", "" ] ]
Graph Neural Networks (GNNs) have shown promising performance in various graph learning tasks, but at the cost of resource-intensive computations. The primary overhead of GNN update stems from graph propagation and weight transformation, both involving operations on graph-scale matrices. Previous studies attempt to red...
1205.4776
Ilknur Icke
Ilknur Icke and Andrew Rosenberg
Visual and semantic interpretability of projections of high dimensional data for classification tasks
Longer version of the VAST 2011 poster. http://dx.doi.org/10.1109/VAST.2011.6102474
null
10.1109/VAST.2011.6102474
null
cs.HC cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A number of visual quality measures have been introduced in visual analytics literature in order to automatically select the best views of high dimensional data from a large number of candidate data projections. These methods generally concentrate on the interpretability of the visualization and pay little attention ...
[ { "created": "Tue, 22 May 2012 00:10:45 GMT", "version": "v1" } ]
2015-03-20
[ [ "Icke", "Ilknur", "" ], [ "Rosenberg", "Andrew", "" ] ]
A number of visual quality measures have been introduced in visual analytics literature in order to automatically select the best views of high dimensional data from a large number of candidate data projections. These methods generally concentrate on the interpretability of the visualization and pay little attention to...
1702.01075
Li Wang
Li Wang, Aaron D. Ames, Magnus Egerstedt
Safe Certificate-Based Maneuvers for Teams of Quadrotors Using Differential Flatness
To appear in ICRA 2017, 8 page version
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Safety Barrier Certificates that ensure collision-free maneuvers for teams of differential flatness-based quadrotors are presented in this paper. Synthesized with control barrier functions, the certificates are used to modify the nominal trajectory in a minimally invasive way to avoid collisions. The proposed collisi...
[ { "created": "Fri, 3 Feb 2017 16:42:57 GMT", "version": "v1" } ]
2017-02-06
[ [ "Wang", "Li", "" ], [ "Ames", "Aaron D.", "" ], [ "Egerstedt", "Magnus", "" ] ]
Safety Barrier Certificates that ensure collision-free maneuvers for teams of differential flatness-based quadrotors are presented in this paper. Synthesized with control barrier functions, the certificates are used to modify the nominal trajectory in a minimally invasive way to avoid collisions. The proposed collision...
2009.00261
Mohammad Keshavarzi
Mohammad Keshavarzi, Clayton Hutson, Chin-Yi Cheng, Mehdi Nourbakhsh, Michael Bergin, Mohammad Rahmani Asl
SketchOpt: Sketch-based Parametric Model Retrieval for Generative Design
null
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Developing fully parametric building models for performance-based generative design tasks often requires proficiency in many advanced 3D modeling and visual programming, limiting its use for many building designers. Moreover, iterations of such models can be time-consuming tasks and sometimes limiting, as major chang...
[ { "created": "Tue, 1 Sep 2020 06:28:09 GMT", "version": "v1" } ]
2020-09-02
[ [ "Keshavarzi", "Mohammad", "" ], [ "Hutson", "Clayton", "" ], [ "Cheng", "Chin-Yi", "" ], [ "Nourbakhsh", "Mehdi", "" ], [ "Bergin", "Michael", "" ], [ "Asl", "Mohammad Rahmani", "" ] ]
Developing fully parametric building models for performance-based generative design tasks often requires proficiency in many advanced 3D modeling and visual programming, limiting its use for many building designers. Moreover, iterations of such models can be time-consuming tasks and sometimes limiting, as major changes...
1607.06778
Saeed Manaffam
Saeed Manaffam, Alireza Seyedi, Azadeh Vosoughi, and Tara Javidi
Synchronization in Networked Systems with Parameter Mismatch: Adaptive Decentralized and Distributed Controls
9 pages, 5 figures, submitted to Trans. on Circuits ans Systems I: Regular paper 2016
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Here, we study the ultimately bounded stability of network of mismatched systems using Lyapunov direct method. We derive an upper bound on the norm of the error of network states from its average states, which it achieves in finite time. Then, we devise a decentralized compensator to asymptotically pin the network of...
[ { "created": "Fri, 22 Jul 2016 18:12:11 GMT", "version": "v1" } ]
2016-07-25
[ [ "Manaffam", "Saeed", "" ], [ "Seyedi", "Alireza", "" ], [ "Vosoughi", "Azadeh", "" ], [ "Javidi", "Tara", "" ] ]
Here, we study the ultimately bounded stability of network of mismatched systems using Lyapunov direct method. We derive an upper bound on the norm of the error of network states from its average states, which it achieves in finite time. Then, we devise a decentralized compensator to asymptotically pin the network of m...
2404.18896
Xingyuan Zhang
Xingyuan Zhang, Philip Becker-Ehmck, Patrick van der Smagt, Maximilian Karl
Overcoming Knowledge Barriers: Online Imitation Learning from Observation with Pretrained World Models
19 pages, 7 figures
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Incorporating the successful paradigm of pretraining and finetuning from Computer Vision and Natural Language Processing into decision-making has become increasingly popular in recent years. In this paper, we study Imitation Learning from Observation with pretrained models and find existing approaches such as BCO and...
[ { "created": "Mon, 29 Apr 2024 17:33:52 GMT", "version": "v1" } ]
2024-04-30
[ [ "Zhang", "Xingyuan", "" ], [ "Becker-Ehmck", "Philip", "" ], [ "van der Smagt", "Patrick", "" ], [ "Karl", "Maximilian", "" ] ]
Incorporating the successful paradigm of pretraining and finetuning from Computer Vision and Natural Language Processing into decision-making has become increasingly popular in recent years. In this paper, we study Imitation Learning from Observation with pretrained models and find existing approaches such as BCO and A...
2207.07498
Ignacio Carlucho
Ignacio Carlucho and Arrasy Rahman and William Ard and Elliot Fosong and Corina Barbalata and Stefano V. Albrecht
Cooperative Marine Operations via Ad Hoc Teams
null
null
null
null
cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
While research in ad hoc teamwork has great potential for solving real-world robotic applications, most developments so far have been focusing on environments with simple dynamics. In this article, we discuss how the problem of ad hoc teamwork can be of special interest for marine robotics and how it can aid marine o...
[ { "created": "Fri, 15 Jul 2022 14:34:57 GMT", "version": "v1" } ]
2022-07-18
[ [ "Carlucho", "Ignacio", "" ], [ "Rahman", "Arrasy", "" ], [ "Ard", "William", "" ], [ "Fosong", "Elliot", "" ], [ "Barbalata", "Corina", "" ], [ "Albrecht", "Stefano V.", "" ] ]
While research in ad hoc teamwork has great potential for solving real-world robotic applications, most developments so far have been focusing on environments with simple dynamics. In this article, we discuss how the problem of ad hoc teamwork can be of special interest for marine robotics and how it can aid marine ope...
2203.12922
Zihan Zhang
Zihan Zhang, Xiangyang Ji, Simon S. Du
Horizon-Free Reinforcement Learning in Polynomial Time: the Power of Stationary Policies
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper gives the first polynomial-time algorithm for tabular Markov Decision Processes (MDP) that enjoys a regret bound \emph{independent on the planning horizon}. Specifically, we consider tabular MDP with $S$ states, $A$ actions, a planning horizon $H$, total reward bounded by $1$, and the agent plays for $K$ e...
[ { "created": "Thu, 24 Mar 2022 08:14:12 GMT", "version": "v1" }, { "created": "Thu, 16 Jun 2022 04:39:01 GMT", "version": "v2" } ]
2022-06-17
[ [ "Zhang", "Zihan", "" ], [ "Ji", "Xiangyang", "" ], [ "Du", "Simon S.", "" ] ]
This paper gives the first polynomial-time algorithm for tabular Markov Decision Processes (MDP) that enjoys a regret bound \emph{independent on the planning horizon}. Specifically, we consider tabular MDP with $S$ states, $A$ actions, a planning horizon $H$, total reward bounded by $1$, and the agent plays for $K$ epi...
2304.06054
Lekai Liu
Li Zhu, Lekai Liu, Changshi Yu
Landslide Susceptibility Prediction Modeling Based on Self-Screening Deep Learning Model
Some contributing authors are not signed
null
null
null
cs.LG physics.geo-ph
http://creativecommons.org/licenses/by/4.0/
Landslide susceptibility prediction has always been an important and challenging content. However, there are some uncertain problems to be solved in susceptibility modeling, such as the error of landslide samples and the complex nonlinear relationship between environmental factors. A self-screening graph convolutiona...
[ { "created": "Wed, 12 Apr 2023 10:31:03 GMT", "version": "v1" }, { "created": "Sun, 8 Oct 2023 07:05:13 GMT", "version": "v2" } ]
2023-10-10
[ [ "Zhu", "Li", "" ], [ "Liu", "Lekai", "" ], [ "Yu", "Changshi", "" ] ]
Landslide susceptibility prediction has always been an important and challenging content. However, there are some uncertain problems to be solved in susceptibility modeling, such as the error of landslide samples and the complex nonlinear relationship between environmental factors. A self-screening graph convolutional ...
2212.03759
Vaishnavi Khindkar
Vaishnavi Khindkar, Janhavi Khindkar
GAMMA: Generative Augmentation for Attentive Marine Debris Detection
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We propose an efficient and generative augmentation approach to solve the inadequacy concern of underwater debris data for visual detection. We use cycleGAN as a data augmentation technique to convert openly available, abundant data of terrestrial plastic to underwater-style images. Prior works just focus on augmenti...
[ { "created": "Wed, 7 Dec 2022 16:30:51 GMT", "version": "v1" } ]
2022-12-08
[ [ "Khindkar", "Vaishnavi", "" ], [ "Khindkar", "Janhavi", "" ] ]
We propose an efficient and generative augmentation approach to solve the inadequacy concern of underwater debris data for visual detection. We use cycleGAN as a data augmentation technique to convert openly available, abundant data of terrestrial plastic to underwater-style images. Prior works just focus on augmenting...
1605.05676
Martin Biehl
Martin Biehl, Takashi Ikegami, Daniel Polani
Towards information based spatiotemporal patterns as a foundation for agent representation in dynamical systems
8 pages, 3 figures
Proceedings of the Artificial Life Conference 2016
10.7551/978-0-262-33936-0-ch115
null
cs.AI cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present some arguments why existing methods for representing agents fall short in applications crucial to artificial life. Using a thought experiment involving a fictitious dynamical systems model of the biosphere we argue that the metabolism, motility, and the concept of counterfactual variation should be compati...
[ { "created": "Wed, 18 May 2016 18:18:38 GMT", "version": "v1" } ]
2017-04-11
[ [ "Biehl", "Martin", "" ], [ "Ikegami", "Takashi", "" ], [ "Polani", "Daniel", "" ] ]
We present some arguments why existing methods for representing agents fall short in applications crucial to artificial life. Using a thought experiment involving a fictitious dynamical systems model of the biosphere we argue that the metabolism, motility, and the concept of counterfactual variation should be compatibl...
2205.14892
Tobias Koch
Tobias Koch, Felix Liebezeit, Christian Riess, Vincent Christlein, Thomas K\"ohler
Exploring the Open World Using Incremental Extreme Value Machines
Accepted at ICPR 2022
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Dynamic environments require adaptive applications. One particular machine learning problem in dynamic environments is open world recognition. It characterizes a continuously changing domain where only some classes are seen in one batch of the training data and such batches can only be learned incrementally. Open wor...
[ { "created": "Mon, 30 May 2022 07:21:13 GMT", "version": "v1" } ]
2022-05-31
[ [ "Koch", "Tobias", "" ], [ "Liebezeit", "Felix", "" ], [ "Riess", "Christian", "" ], [ "Christlein", "Vincent", "" ], [ "Köhler", "Thomas", "" ] ]
Dynamic environments require adaptive applications. One particular machine learning problem in dynamic environments is open world recognition. It characterizes a continuously changing domain where only some classes are seen in one batch of the training data and such batches can only be learned incrementally. Open world...
1305.3333
Christos Tzamos
Dimitris Fotakis and Christos Tzamos
Strategy-Proof Facility Location for Concave Cost Functions
null
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider k-Facility Location games, where n strategic agents report their locations on the real line, and a mechanism maps them to k facilities. Each agent seeks to minimize his connection cost, given by a nonnegative increasing function of his distance to the nearest facility. Departing from previous work, that m...
[ { "created": "Wed, 15 May 2013 01:22:15 GMT", "version": "v1" } ]
2013-05-16
[ [ "Fotakis", "Dimitris", "" ], [ "Tzamos", "Christos", "" ] ]
We consider k-Facility Location games, where n strategic agents report their locations on the real line, and a mechanism maps them to k facilities. Each agent seeks to minimize his connection cost, given by a nonnegative increasing function of his distance to the nearest facility. Departing from previous work, that mos...
1810.00326
Wahyudi Wahyudi
Wahyudi, Masayu Leylia Khodra, Ary Setijadi Prihatmanto, Carmadi Machbub
Using Graph-Pattern Association Rules On Yago Knowledge Base
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose the use of Graph-Pattern Association Rules (GPARs) on the Yago knowledge base. Extending association rules for itemsets, GPARS can help to discover regularities between entities in knowledge bases. A rule-generated graph pattern (RGGP) algorithm was used for extracting rules from the Yago knowledge base an...
[ { "created": "Sun, 30 Sep 2018 06:42:18 GMT", "version": "v1" } ]
2018-10-02
[ [ "Wahyudi", "", "" ], [ "Khodra", "Masayu Leylia", "" ], [ "Prihatmanto", "Ary Setijadi", "" ], [ "Machbub", "Carmadi", "" ] ]
We propose the use of Graph-Pattern Association Rules (GPARs) on the Yago knowledge base. Extending association rules for itemsets, GPARS can help to discover regularities between entities in knowledge bases. A rule-generated graph pattern (RGGP) algorithm was used for extracting rules from the Yago knowledge base and ...
2104.14616
Adrian Moldovan
Adrian Moldovan and Angel Ca\c{t}aron and R\u{a}zvan Andonie
Learning in Feedforward Neural Networks Accelerated by Transfer Entropy
18 pages, 13 figures
null
10.3390/e22010102
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Current neural networks architectures are many times harder to train because of the increasing size and complexity of the used datasets. Our objective is to design more efficient training algorithms utilizing causal relationships inferred from neural networks. The transfer entropy (TE) was initially introduced as an ...
[ { "created": "Thu, 29 Apr 2021 19:07:07 GMT", "version": "v1" } ]
2021-05-03
[ [ "Moldovan", "Adrian", "" ], [ "Caţaron", "Angel", "" ], [ "Andonie", "Răzvan", "" ] ]
Current neural networks architectures are many times harder to train because of the increasing size and complexity of the used datasets. Our objective is to design more efficient training algorithms utilizing causal relationships inferred from neural networks. The transfer entropy (TE) was initially introduced as an in...
2102.10283
Sho Sakaino Prof.
Sho Sakaino, Kazuki Fujimoto, Yuki Saigusa, Toshiaki Tsuji
Imitation Learning for Variable Speed Contact Motion for Operation up to Control Bandwidth
Copyright 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to serve...
null
null
null
cs.RO cs.SY eess.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The generation of robot motions in the real world is difficult by using conventional controllers alone and requires highly intelligent processing. In this regard, learning-based motion generations are currently being investigated. However, the main issue has been improvements of the adaptability to spatially varying ...
[ { "created": "Sat, 20 Feb 2021 08:14:25 GMT", "version": "v1" }, { "created": "Mon, 17 May 2021 10:04:40 GMT", "version": "v2" }, { "created": "Fri, 1 Oct 2021 04:36:23 GMT", "version": "v3" }, { "created": "Mon, 25 Oct 2021 15:46:03 GMT", "version": "v4" }, { "cr...
2022-02-15
[ [ "Sakaino", "Sho", "" ], [ "Fujimoto", "Kazuki", "" ], [ "Saigusa", "Yuki", "" ], [ "Tsuji", "Toshiaki", "" ] ]
The generation of robot motions in the real world is difficult by using conventional controllers alone and requires highly intelligent processing. In this regard, learning-based motion generations are currently being investigated. However, the main issue has been improvements of the adaptability to spatially varying en...
2202.11670
Beau Coker
Beau Coker, Wessel P. Bruinsma, David R. Burt, Weiwei Pan, Finale Doshi-Velez
Wide Mean-Field Bayesian Neural Networks Ignore the Data
null
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
Bayesian neural networks (BNNs) combine the expressive power of deep learning with the advantages of Bayesian formalism. In recent years, the analysis of wide, deep BNNs has provided theoretical insight into their priors and posteriors. However, we have no analogous insight into their posteriors under approximate inf...
[ { "created": "Wed, 23 Feb 2022 18:21:50 GMT", "version": "v1" } ]
2022-02-24
[ [ "Coker", "Beau", "" ], [ "Bruinsma", "Wessel P.", "" ], [ "Burt", "David R.", "" ], [ "Pan", "Weiwei", "" ], [ "Doshi-Velez", "Finale", "" ] ]
Bayesian neural networks (BNNs) combine the expressive power of deep learning with the advantages of Bayesian formalism. In recent years, the analysis of wide, deep BNNs has provided theoretical insight into their priors and posteriors. However, we have no analogous insight into their posteriors under approximate infer...
1509.04619
Hamid Tizhoosh
Zehra Camlica, H.R. Tizhoosh, Farzad Khalvati
Medical Image Classification via SVM using LBP Features from Saliency-Based Folded Data
To appear in proceedings of The 14th International Conference on Machine Learning and Applications (IEEE ICMLA 2015), Miami, Florida, USA, 2015
null
10.1109/ICMLA.2015.131
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Good results on image classification and retrieval using support vector machines (SVM) with local binary patterns (LBPs) as features have been extensively reported in the literature where an entire image is retrieved or classified. In contrast, in medical imaging, not all parts of the image may be equally significant...
[ { "created": "Tue, 15 Sep 2015 16:08:08 GMT", "version": "v1" } ]
2016-11-17
[ [ "Camlica", "Zehra", "" ], [ "Tizhoosh", "H. R.", "" ], [ "Khalvati", "Farzad", "" ] ]
Good results on image classification and retrieval using support vector machines (SVM) with local binary patterns (LBPs) as features have been extensively reported in the literature where an entire image is retrieved or classified. In contrast, in medical imaging, not all parts of the image may be equally significant o...
2302.08642
HaiLong Liu
Hailong Liu and Shota Inoue and Takahiro Wada
Subjective Vertical Conflict Model with Visual Vertical: Predicting Motion Sickness on Autonomous Personal Mobility Vehicles
null
null
null
null
cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Passengers of level 3-5 autonomous personal mobility vehicles (APMV) can perform non-driving tasks, such as reading books and smartphones, while driving. It has been pointed out that such activities may increase motion sickness, especially when frequently avoiding pedestrians or obstacles in shared spaces. Many studi...
[ { "created": "Fri, 17 Feb 2023 01:21:32 GMT", "version": "v1" } ]
2023-02-20
[ [ "Liu", "Hailong", "" ], [ "Inoue", "Shota", "" ], [ "Wada", "Takahiro", "" ] ]
Passengers of level 3-5 autonomous personal mobility vehicles (APMV) can perform non-driving tasks, such as reading books and smartphones, while driving. It has been pointed out that such activities may increase motion sickness, especially when frequently avoiding pedestrians or obstacles in shared spaces. Many studies...
1510.01135
Eric Kerrigan
Eric C. Kerrigan
Feedback and Time are Essential for the Optimal Control of Computing Systems
null
Proc. 5th IFAC Conference on Nonlinear Model Predictive Control 2015
10.1016/j.ifacol.2015.11.309
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The performance, reliability, cost, size and energy usage of computing systems can be improved by one or more orders of magnitude by the systematic use of modern control and optimization methods. Computing systems rely on the use of feedback algorithms to schedule tasks, data and resources, but the models that are us...
[ { "created": "Mon, 5 Oct 2015 13:06:17 GMT", "version": "v1" } ]
2017-10-13
[ [ "Kerrigan", "Eric C.", "" ] ]
The performance, reliability, cost, size and energy usage of computing systems can be improved by one or more orders of magnitude by the systematic use of modern control and optimization methods. Computing systems rely on the use of feedback algorithms to schedule tasks, data and resources, but the models that are used...
1208.5195
Muhammad Javed
Muhammad Javed, Bashir Ahmad, Zaffar Abbas, Allah Nawaz, Muhammad Ali Abid and Ihsan Ullah
Decreasing defect rate of test cases by designing and analysis for recursive modules of a program structure: Improvement in test cases
4 pages
IJCSIS August 2012, Vol. 10 No. 8
null
null
cs.SE
http://creativecommons.org/licenses/by/3.0/
Designing and analysis of test cases is a challenging tasks for tester roles especially those who are related to test the structure of program. Recently, Programmers are showing valuable trend towards the implementation of recursive modules in a program structure. In testing phase of software development life cycle, ...
[ { "created": "Sun, 26 Aug 2012 06:55:07 GMT", "version": "v1" } ]
2012-08-28
[ [ "Javed", "Muhammad", "" ], [ "Ahmad", "Bashir", "" ], [ "Abbas", "Zaffar", "" ], [ "Nawaz", "Allah", "" ], [ "Abid", "Muhammad Ali", "" ], [ "Ullah", "Ihsan", "" ] ]
Designing and analysis of test cases is a challenging tasks for tester roles especially those who are related to test the structure of program. Recently, Programmers are showing valuable trend towards the implementation of recursive modules in a program structure. In testing phase of software development life cycle, te...
2002.10306
Indro Spinelli
Indro Spinelli, Simone Scardapane, Aurelio Uncini
Adaptive Propagation Graph Convolutional Network
Published in IEEE Transaction on Neural Networks and Learning Systems
IEEE Transactions on Neural Networks and Learning Systems, 2020
10.1109/TNNLS.2020.3025110
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph convolutional networks (GCNs) are a family of neural network models that perform inference on graph data by interleaving vertex-wise operations and message-passing exchanges across nodes. Concerning the latter, two key questions arise: (i) how to design a differentiable exchange protocol (e.g., a 1-hop Laplacia...
[ { "created": "Mon, 24 Feb 2020 15:31:16 GMT", "version": "v1" }, { "created": "Mon, 15 Jun 2020 18:28:25 GMT", "version": "v2" }, { "created": "Mon, 28 Sep 2020 09:28:34 GMT", "version": "v3" } ]
2020-09-29
[ [ "Spinelli", "Indro", "" ], [ "Scardapane", "Simone", "" ], [ "Uncini", "Aurelio", "" ] ]
Graph convolutional networks (GCNs) are a family of neural network models that perform inference on graph data by interleaving vertex-wise operations and message-passing exchanges across nodes. Concerning the latter, two key questions arise: (i) how to design a differentiable exchange protocol (e.g., a 1-hop Laplacian ...
2007.13156
Anthony Bagnall Dr
Alejandro Pasos Ruiz, Michael Flynn and Anthony Bagnall
Benchmarking Multivariate Time Series Classification Algorithms
Data Min Knowl Disc (2020)
The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances, Data Mining and Knowledge Discovery volume 35, pages 401 to 449 (2021)
10.1007/s10618-020-00727-3
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Time Series Classification (TSC) involved building predictive models for a discrete target variable from ordered, real valued, attributes. Over recent years, a new set of TSC algorithms have been developed which have made significant improvement over the previous state of the art. The main focus has been on univariat...
[ { "created": "Sun, 26 Jul 2020 15:56:40 GMT", "version": "v1" }, { "created": "Wed, 26 Apr 2023 08:49:30 GMT", "version": "v2" } ]
2023-04-27
[ [ "Ruiz", "Alejandro Pasos", "" ], [ "Flynn", "Michael", "" ], [ "Bagnall", "Anthony", "" ] ]
Time Series Classification (TSC) involved building predictive models for a discrete target variable from ordered, real valued, attributes. Over recent years, a new set of TSC algorithms have been developed which have made significant improvement over the previous state of the art. The main focus has been on univariate ...
2310.09343
Hyungjoo Chae
Hyungjoo Chae, Yongho Song, Kai Tzu-iunn Ong, Taeyoon Kwon, Minjin Kim, Youngjae Yu, Dongha Lee, Dongyeop Kang, Jinyoung Yeo
Dialogue Chain-of-Thought Distillation for Commonsense-aware Conversational Agents
25 pages, 8 figures, Accepted to EMNLP 2023
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by-nc-nd/4.0/
Human-like chatbots necessitate the use of commonsense reasoning in order to effectively comprehend and respond to implicit information present within conversations. Achieving such coherence and informativeness in responses, however, is a non-trivial task. Even for large language models (LLMs), the task of identifyin...
[ { "created": "Fri, 13 Oct 2023 18:17:23 GMT", "version": "v1" }, { "created": "Sun, 22 Oct 2023 09:16:52 GMT", "version": "v2" } ]
2023-10-24
[ [ "Chae", "Hyungjoo", "" ], [ "Song", "Yongho", "" ], [ "Ong", "Kai Tzu-iunn", "" ], [ "Kwon", "Taeyoon", "" ], [ "Kim", "Minjin", "" ], [ "Yu", "Youngjae", "" ], [ "Lee", "Dongha", "" ], [ "Kang", ...
Human-like chatbots necessitate the use of commonsense reasoning in order to effectively comprehend and respond to implicit information present within conversations. Achieving such coherence and informativeness in responses, however, is a non-trivial task. Even for large language models (LLMs), the task of identifying ...
2108.09879
Tanmay Ghai
Yixiang Yao, Tanmay Ghai, Srivatsan Ravi, Pedro Szekely
AMPPERE: A Universal Abstract Machine for Privacy-Preserving Entity Resolution Evaluation
10 pages, 6 figures, Published in CIKM '21; corrected title & fixed abstract formatting
null
10.1145/3459637.3482318
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Entity resolution is the task of identifying records in different datasets that refer to the same entity in the real world. In sensitive domains (e.g. financial accounts, hospital health records), entity resolution must meet privacy requirements to avoid revealing sensitive information such as personal identifiable i...
[ { "created": "Mon, 23 Aug 2021 00:57:39 GMT", "version": "v1" }, { "created": "Tue, 24 Aug 2021 01:37:36 GMT", "version": "v2" }, { "created": "Thu, 4 Nov 2021 20:54:47 GMT", "version": "v3" } ]
2021-11-08
[ [ "Yao", "Yixiang", "" ], [ "Ghai", "Tanmay", "" ], [ "Ravi", "Srivatsan", "" ], [ "Szekely", "Pedro", "" ] ]
Entity resolution is the task of identifying records in different datasets that refer to the same entity in the real world. In sensitive domains (e.g. financial accounts, hospital health records), entity resolution must meet privacy requirements to avoid revealing sensitive information such as personal identifiable inf...
2308.08930
Runmin Cong
Runmin Cong, Hongyu Liu, Chen Zhang, Wei Zhang, Feng Zheng, Ran Song, and Sam Kwong
Point-aware Interaction and CNN-induced Refinement Network for RGB-D Salient Object Detection
Accepted by ACM MM 2023
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
By integrating complementary information from RGB image and depth map, the ability of salient object detection (SOD) for complex and challenging scenes can be improved. In recent years, the important role of Convolutional Neural Networks (CNNs) in feature extraction and cross-modality interaction has been fully explo...
[ { "created": "Thu, 17 Aug 2023 11:57:49 GMT", "version": "v1" } ]
2023-08-21
[ [ "Cong", "Runmin", "" ], [ "Liu", "Hongyu", "" ], [ "Zhang", "Chen", "" ], [ "Zhang", "Wei", "" ], [ "Zheng", "Feng", "" ], [ "Song", "Ran", "" ], [ "Kwong", "Sam", "" ] ]
By integrating complementary information from RGB image and depth map, the ability of salient object detection (SOD) for complex and challenging scenes can be improved. In recent years, the important role of Convolutional Neural Networks (CNNs) in feature extraction and cross-modality interaction has been fully explore...
2301.01482
Yunfeng Li
Yunfeng Li, Bo Wang, Ye Li, Zhuoyan Liu, Wei Huo, Yueming Li, Jian Cao
Underwater Object Tracker: UOSTrack for Marine Organism Grasping of Underwater Vehicles
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A visual single-object tracker is an indispensable component of underwater vehicles (UVs) in marine organism grasping tasks. Its accuracy and stability are imperative to guide the UVs to perform grasping behavior. Although single-object trackers show competitive performance in the challenge of underwater image degrad...
[ { "created": "Wed, 4 Jan 2023 08:22:34 GMT", "version": "v1" }, { "created": "Tue, 17 Jan 2023 02:04:17 GMT", "version": "v2" }, { "created": "Thu, 23 Mar 2023 05:34:15 GMT", "version": "v3" }, { "created": "Mon, 27 Mar 2023 06:23:07 GMT", "version": "v4" }, { "cr...
2023-07-25
[ [ "Li", "Yunfeng", "" ], [ "Wang", "Bo", "" ], [ "Li", "Ye", "" ], [ "Liu", "Zhuoyan", "" ], [ "Huo", "Wei", "" ], [ "Li", "Yueming", "" ], [ "Cao", "Jian", "" ] ]
A visual single-object tracker is an indispensable component of underwater vehicles (UVs) in marine organism grasping tasks. Its accuracy and stability are imperative to guide the UVs to perform grasping behavior. Although single-object trackers show competitive performance in the challenge of underwater image degradat...
2312.03243
Jian Cheng Wong
Jian Cheng Wong, Chin Chun Ooi, Abhishek Gupta, Pao-Hsiung Chiu, Joshua Shao Zheng Low, My Ha Dao, Yew-Soon Ong
Generalizable Neural Physics Solvers by Baldwinian Evolution
null
null
null
null
cs.NE cs.CE cs.LG
http://creativecommons.org/licenses/by/4.0/
Physics-informed neural networks (PINNs) are at the forefront of scientific machine learning, making possible the creation of machine intelligence that is cognizant of physical laws and able to accurately simulate them. In this paper, the potential of discovering PINNs that generalize over an entire family of physics...
[ { "created": "Wed, 6 Dec 2023 02:31:12 GMT", "version": "v1" } ]
2023-12-07
[ [ "Wong", "Jian Cheng", "" ], [ "Ooi", "Chin Chun", "" ], [ "Gupta", "Abhishek", "" ], [ "Chiu", "Pao-Hsiung", "" ], [ "Low", "Joshua Shao Zheng", "" ], [ "Dao", "My Ha", "" ], [ "Ong", "Yew-Soon", "" ] ]
Physics-informed neural networks (PINNs) are at the forefront of scientific machine learning, making possible the creation of machine intelligence that is cognizant of physical laws and able to accurately simulate them. In this paper, the potential of discovering PINNs that generalize over an entire family of physics t...
1302.5348
Ben London
Ben London and Bert Huang and Lise Getoor
Graph-based Generalization Bounds for Learning Binary Relations
null
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We investigate the generalizability of learned binary relations: functions that map pairs of instances to a logical indicator. This problem has application in numerous areas of machine learning, such as ranking, entity resolution and link prediction. Our learning framework incorporates an example labeler that, given ...
[ { "created": "Thu, 21 Feb 2013 17:30:42 GMT", "version": "v1" }, { "created": "Wed, 27 Feb 2013 03:33:47 GMT", "version": "v2" }, { "created": "Fri, 31 May 2013 21:12:47 GMT", "version": "v3" } ]
2013-06-04
[ [ "London", "Ben", "" ], [ "Huang", "Bert", "" ], [ "Getoor", "Lise", "" ] ]
We investigate the generalizability of learned binary relations: functions that map pairs of instances to a logical indicator. This problem has application in numerous areas of machine learning, such as ranking, entity resolution and link prediction. Our learning framework incorporates an example labeler that, given a ...
1711.04467
Lior Kamma
Diptarka Chakraborty, Lior Kamma, Kasper Green Larsen
Tight Cell Probe Bounds for Succinct Boolean Matrix-Vector Multiplication
null
null
null
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The conjectured hardness of Boolean matrix-vector multiplication has been used with great success to prove conditional lower bounds for numerous important data structure problems, see Henzinger et al. [STOC'15]. In recent work, Larsen and Williams [SODA'17] attacked the problem from the upper bound side and gave a su...
[ { "created": "Mon, 13 Nov 2017 08:29:45 GMT", "version": "v1" } ]
2017-11-15
[ [ "Chakraborty", "Diptarka", "" ], [ "Kamma", "Lior", "" ], [ "Larsen", "Kasper Green", "" ] ]
The conjectured hardness of Boolean matrix-vector multiplication has been used with great success to prove conditional lower bounds for numerous important data structure problems, see Henzinger et al. [STOC'15]. In recent work, Larsen and Williams [SODA'17] attacked the problem from the upper bound side and gave a surp...
1901.06824
Kyrill Winkler
Matthias F\"ugger, Thomas Nowak, Kyrill Winkler
On the Radius of Nonsplit Graphs and Information Dissemination in Dynamic Networks
12 pages, 1 figure
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A nonsplit graph is a directed graph where each pair of nodes has a common incoming neighbor. We show that the radius of such graphs is in $O(\log \log n)$, where $n$ is the number of nodes. We then generalize the result to products of nonsplit graphs. The analysis of nonsplit graph products has direct implications...
[ { "created": "Mon, 21 Jan 2019 08:45:38 GMT", "version": "v1" } ]
2019-01-23
[ [ "Függer", "Matthias", "" ], [ "Nowak", "Thomas", "" ], [ "Winkler", "Kyrill", "" ] ]
A nonsplit graph is a directed graph where each pair of nodes has a common incoming neighbor. We show that the radius of such graphs is in $O(\log \log n)$, where $n$ is the number of nodes. We then generalize the result to products of nonsplit graphs. The analysis of nonsplit graph products has direct implications in ...
2406.09044
Hanqing Wang
Hanqing Wang, Zeguan Xiao, Yixia Li, Shuo Wang, Guanhua Chen, Yun Chen
MiLoRA: Harnessing Minor Singular Components for Parameter-Efficient LLM Finetuning
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Efficient finetuning of large language models (LLMs) aims to adapt the LLMs with reduced computation and memory cost. Previous LoRA-based approaches initialize the low-rank matrices with gaussian distribution and zero values, while keeping the original weight matrices frozen. However, the trainable model parameters o...
[ { "created": "Thu, 13 Jun 2024 12:30:02 GMT", "version": "v1" } ]
2024-06-14
[ [ "Wang", "Hanqing", "" ], [ "Xiao", "Zeguan", "" ], [ "Li", "Yixia", "" ], [ "Wang", "Shuo", "" ], [ "Chen", "Guanhua", "" ], [ "Chen", "Yun", "" ] ]
Efficient finetuning of large language models (LLMs) aims to adapt the LLMs with reduced computation and memory cost. Previous LoRA-based approaches initialize the low-rank matrices with gaussian distribution and zero values, while keeping the original weight matrices frozen. However, the trainable model parameters opt...
1806.04422
Kele Xu
Dawei Feng, Kele Xu, Haibo Mi, Feifan Liao and Yan Zhou
Sample Dropout for Audio Scene Classification Using Multi-Scale Dense Connected Convolutional Neural Network
Accepted to 2018 Pacific Rim Knowledge Acquisition Workshop (PKAW)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Acoustic scene classification is an intricate problem for a machine. As an emerging field of research, deep Convolutional Neural Networks (CNN) achieve convincing results. In this paper, we explore the use of multi-scale Dense connected convolutional neural network (DenseNet) for the classification task, with the goa...
[ { "created": "Tue, 12 Jun 2018 09:59:11 GMT", "version": "v1" } ]
2018-06-13
[ [ "Feng", "Dawei", "" ], [ "Xu", "Kele", "" ], [ "Mi", "Haibo", "" ], [ "Liao", "Feifan", "" ], [ "Zhou", "Yan", "" ] ]
Acoustic scene classification is an intricate problem for a machine. As an emerging field of research, deep Convolutional Neural Networks (CNN) achieve convincing results. In this paper, we explore the use of multi-scale Dense connected convolutional neural network (DenseNet) for the classification task, with the goal ...
1410.4421
Sergio Grammatico
Sergio Grammatico, Francesca Parise, Marcello Colombino, John Lygeros
Decentralized Convergence to Nash Equilibria in Constrained Deterministic Mean Field Control
IEEE Trans. on Automatic Control (cond. accepted)
null
10.1109/TAC.2015.2513368
null
cs.SY cs.GT math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper considers decentralized control and optimization methodologies for large populations of systems, consisting of several agents with different individual behaviors, constraints and interests, and affected by the aggregate behavior of the overall population. For such large-scale systems, the theory of aggrega...
[ { "created": "Thu, 16 Oct 2014 13:48:14 GMT", "version": "v1" }, { "created": "Sun, 17 May 2015 20:59:36 GMT", "version": "v2" } ]
2016-11-15
[ [ "Grammatico", "Sergio", "" ], [ "Parise", "Francesca", "" ], [ "Colombino", "Marcello", "" ], [ "Lygeros", "John", "" ] ]
This paper considers decentralized control and optimization methodologies for large populations of systems, consisting of several agents with different individual behaviors, constraints and interests, and affected by the aggregate behavior of the overall population. For such large-scale systems, the theory of aggregati...
1208.3530
Haimonti Dutta
Haimonti Dutta, William Chan, Deepak Shankargouda, Manoj Pooleery, Axinia Radeva, Kyle Rego, Boyi Xie, Rebecca Passonneau, Austin Lee and Barbara Taranto
Leveraging Subjective Human Annotation for Clustering Historic Newspaper Articles
null
null
null
null
cs.IR cs.CL cs.DL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The New York Public Library is participating in the Chronicling America initiative to develop an online searchable database of historically significant newspaper articles. Microfilm copies of the newspapers are scanned and high resolution Optical Character Recognition (OCR) software is run on them. The text from the ...
[ { "created": "Fri, 17 Aug 2012 04:48:58 GMT", "version": "v1" } ]
2012-08-20
[ [ "Dutta", "Haimonti", "" ], [ "Chan", "William", "" ], [ "Shankargouda", "Deepak", "" ], [ "Pooleery", "Manoj", "" ], [ "Radeva", "Axinia", "" ], [ "Rego", "Kyle", "" ], [ "Xie", "Boyi", "" ], [ "Pas...
The New York Public Library is participating in the Chronicling America initiative to develop an online searchable database of historically significant newspaper articles. Microfilm copies of the newspapers are scanned and high resolution Optical Character Recognition (OCR) software is run on them. The text from the OC...
2208.06722
Efstratios Chatzoglou
Efstratios Chatzoglou, Vasileios Kouliaridis, Georgios Kambourakis, Georgios Karopoulos and Stefanos Gritzalis
A hands-on gaze on HTTP/3 security through the lens of HTTP/2 and a public dataset
null
null
10.1016/j.cose.2022.103051
null
cs.CR
http://creativecommons.org/licenses/by/4.0/
Following QUIC protocol ratification on May 2021, the third major version of the Hypertext Transfer Protocol, namely HTTP/3, was published around one year later in RFC 9114. In light of these consequential advancements, the current work aspires to provide a full-blown coverage of the following issues, which to our kn...
[ { "created": "Sat, 13 Aug 2022 20:10:49 GMT", "version": "v1" }, { "created": "Fri, 9 Dec 2022 23:40:41 GMT", "version": "v2" } ]
2022-12-13
[ [ "Chatzoglou", "Efstratios", "" ], [ "Kouliaridis", "Vasileios", "" ], [ "Kambourakis", "Georgios", "" ], [ "Karopoulos", "Georgios", "" ], [ "Gritzalis", "Stefanos", "" ] ]
Following QUIC protocol ratification on May 2021, the third major version of the Hypertext Transfer Protocol, namely HTTP/3, was published around one year later in RFC 9114. In light of these consequential advancements, the current work aspires to provide a full-blown coverage of the following issues, which to our know...
1804.01675
Andrew Paplinski
Yanan Li, Haixiang Guo, Andrew P Paplinski
Semi-Supervised Classification for oil reservoir
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper addresses the general problem of accurate identification of oil reservoirs. Recent improvements in well or borehole logging technology have resulted in an explosive amount of data available for processing. The traditional methods of analysis of the logs characteristics by experts require significant amount...
[ { "created": "Thu, 5 Apr 2018 05:41:39 GMT", "version": "v1" } ]
2018-04-06
[ [ "Li", "Yanan", "" ], [ "Guo", "Haixiang", "" ], [ "Paplinski", "Andrew P", "" ] ]
This paper addresses the general problem of accurate identification of oil reservoirs. Recent improvements in well or borehole logging technology have resulted in an explosive amount of data available for processing. The traditional methods of analysis of the logs characteristics by experts require significant amount o...
1906.06003
Hongyu Lin
Hongyu Lin, Yaojie Lu, Xianpei Han, Le Sun
Cost-sensitive Regularization for Label Confusion-aware Event Detection
Accepted to ACL2019
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In supervised event detection, most of the mislabeling occurs between a small number of confusing type pairs, including trigger-NIL pairs and sibling sub-types of the same coarse type. To address this label confusion problem, this paper proposes cost-sensitive regularization, which can force the training procedure to...
[ { "created": "Fri, 14 Jun 2019 03:27:11 GMT", "version": "v1" } ]
2019-06-17
[ [ "Lin", "Hongyu", "" ], [ "Lu", "Yaojie", "" ], [ "Han", "Xianpei", "" ], [ "Sun", "Le", "" ] ]
In supervised event detection, most of the mislabeling occurs between a small number of confusing type pairs, including trigger-NIL pairs and sibling sub-types of the same coarse type. To address this label confusion problem, this paper proposes cost-sensitive regularization, which can force the training procedure to c...
1509.03564
Brian Ruttenberg
Avi Pfeffer, Brian Ruttenberg, Amy Sliva, Michael Howard, Glenn Takata
Lazy Factored Inference for Functional Probabilistic Programming
null
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Probabilistic programming provides the means to represent and reason about complex probabilistic models using programming language constructs. Even simple probabilistic programs can produce models with infinitely many variables. Factored inference algorithms are widely used for probabilistic graphical models, but can...
[ { "created": "Fri, 11 Sep 2015 15:45:39 GMT", "version": "v1" } ]
2015-09-14
[ [ "Pfeffer", "Avi", "" ], [ "Ruttenberg", "Brian", "" ], [ "Sliva", "Amy", "" ], [ "Howard", "Michael", "" ], [ "Takata", "Glenn", "" ] ]
Probabilistic programming provides the means to represent and reason about complex probabilistic models using programming language constructs. Even simple probabilistic programs can produce models with infinitely many variables. Factored inference algorithms are widely used for probabilistic graphical models, but canno...
1503.00306
Xin Luna Dong
Ravali Pochampally and Anish Das Sarma and Xin Luna Dong and Alexandra Meliou and Divesh Srivastava
Fusing Data with Correlations
Sigmod'2014
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many applications rely on Web data and extraction systems to accomplish knowledge-driven tasks. Web information is not curated, so many sources provide inaccurate, or conflicting information. Moreover, extraction systems introduce additional noise to the data. We wish to automatically distinguish correct data and err...
[ { "created": "Sun, 1 Mar 2015 16:52:55 GMT", "version": "v1" } ]
2015-03-03
[ [ "Pochampally", "Ravali", "" ], [ "Sarma", "Anish Das", "" ], [ "Dong", "Xin Luna", "" ], [ "Meliou", "Alexandra", "" ], [ "Srivastava", "Divesh", "" ] ]
Many applications rely on Web data and extraction systems to accomplish knowledge-driven tasks. Web information is not curated, so many sources provide inaccurate, or conflicting information. Moreover, extraction systems introduce additional noise to the data. We wish to automatically distinguish correct data and erron...
2301.04003
Qichen Wang
Qichen Wang, Xiao Hu, Binyang Dai and Ke Yi
Change Propagation Without Joins
Full version of the VLDB paper, correcting some errors from the original paper
null
10.14778/3579075.3579080
null
cs.DB cs.DS
http://creativecommons.org/licenses/by-nc-nd/4.0/
We revisit the classical change propagation framework for query evaluation under updates. The standard framework takes a query plan and materializes the intermediate views, which incurs high polynomial costs in both space and time, with the join operator being the culprit. In this paper, we propose a new change propa...
[ { "created": "Tue, 10 Jan 2023 14:50:31 GMT", "version": "v1" }, { "created": "Sat, 2 Dec 2023 07:56:18 GMT", "version": "v2" } ]
2023-12-05
[ [ "Wang", "Qichen", "" ], [ "Hu", "Xiao", "" ], [ "Dai", "Binyang", "" ], [ "Yi", "Ke", "" ] ]
We revisit the classical change propagation framework for query evaluation under updates. The standard framework takes a query plan and materializes the intermediate views, which incurs high polynomial costs in both space and time, with the join operator being the culprit. In this paper, we propose a new change propaga...
2309.03974
Alec Flowers
Pau Mulet Arabi, Alec Flowers, Lukas Mauch, Fabien Cardinaux
DBsurf: A Discrepancy Based Method for Discrete Stochastic Gradient Estimation
22 pages, 7 figures
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Computing gradients of an expectation with respect to the distributional parameters of a discrete distribution is a problem arising in many fields of science and engineering. Typically, this problem is tackled using Reinforce, which frames the problem of gradient estimation as a Monte Carlo simulation. Unfortunately,...
[ { "created": "Thu, 7 Sep 2023 19:15:40 GMT", "version": "v1" } ]
2023-09-11
[ [ "Arabi", "Pau Mulet", "" ], [ "Flowers", "Alec", "" ], [ "Mauch", "Lukas", "" ], [ "Cardinaux", "Fabien", "" ] ]
Computing gradients of an expectation with respect to the distributional parameters of a discrete distribution is a problem arising in many fields of science and engineering. Typically, this problem is tackled using Reinforce, which frames the problem of gradient estimation as a Monte Carlo simulation. Unfortunately, t...
1602.00955
Dengxin Dai
Dengxin Dai, Luc Van Gool
Unsupervised High-level Feature Learning by Ensemble Projection for Semi-supervised Image Classification and Image Clustering
22 pages, 8 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper investigates the problem of image classification with limited or no annotations, but abundant unlabeled data. The setting exists in many tasks such as semi-supervised image classification, image clustering, and image retrieval. Unlike previous methods, which develop or learn sophisticated regularizers for ...
[ { "created": "Tue, 2 Feb 2016 14:53:36 GMT", "version": "v1" }, { "created": "Thu, 4 Feb 2016 13:58:00 GMT", "version": "v2" } ]
2016-02-05
[ [ "Dai", "Dengxin", "" ], [ "Van Gool", "Luc", "" ] ]
This paper investigates the problem of image classification with limited or no annotations, but abundant unlabeled data. The setting exists in many tasks such as semi-supervised image classification, image clustering, and image retrieval. Unlike previous methods, which develop or learn sophisticated regularizers for cl...
2004.04069
Peter Hancock
P. J. B. Hancock, R. S. Somai and V. R. Mileva
Convolutional neural net face recognition works in non-human-like ways
8 pages, 2 figures. Submitted to Royal Society Open Science
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Convolutional neural networks (CNNs) give state of the art performance in many pattern recognition problems but can be fooled by carefully crafted patterns of noise. We report that CNN face recognition systems also make surprising "errors". We tested six commercial face recognition CNNs and found that they outperform...
[ { "created": "Wed, 8 Apr 2020 15:42:14 GMT", "version": "v1" }, { "created": "Tue, 23 Jun 2020 11:59:06 GMT", "version": "v2" } ]
2020-06-24
[ [ "Hancock", "P. J. B.", "" ], [ "Somai", "R. S.", "" ], [ "Mileva", "V. R.", "" ] ]
Convolutional neural networks (CNNs) give state of the art performance in many pattern recognition problems but can be fooled by carefully crafted patterns of noise. We report that CNN face recognition systems also make surprising "errors". We tested six commercial face recognition CNNs and found that they outperform t...
1702.02805
Qi Guo
Qi Guo, Ce Zhu, Zhiqiang Xia, Zhengtao Wang, Yipeng Liu
Attribute-controlled face photo synthesis from simple line drawing
5 pages, 5 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Face photo synthesis from simple line drawing is a one-to-many task as simple line drawing merely contains the contour of human face. Previous exemplar-based methods are over-dependent on the datasets and are hard to generalize to complicated natural scenes. Recently, several works utilize deep neural networks to inc...
[ { "created": "Thu, 9 Feb 2017 12:21:36 GMT", "version": "v1" } ]
2017-02-10
[ [ "Guo", "Qi", "" ], [ "Zhu", "Ce", "" ], [ "Xia", "Zhiqiang", "" ], [ "Wang", "Zhengtao", "" ], [ "Liu", "Yipeng", "" ] ]
Face photo synthesis from simple line drawing is a one-to-many task as simple line drawing merely contains the contour of human face. Previous exemplar-based methods are over-dependent on the datasets and are hard to generalize to complicated natural scenes. Recently, several works utilize deep neural networks to incre...
2310.00405
Chengming Feng
Chengming Feng, Jing Hu, Xin Wang, Shu Hu, Bin Zhu, Xi Wu, Hongtu Zhu and Siwei Lyu
Controlling Neural Style Transfer with Deep Reinforcement Learning
Accepted by IJCAI 2023. The contributions of Chengming Feng and Jing Hu to this paper were equal. arXiv admin note: substantial text overlap with arXiv:2309.13672
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-nd/4.0/
Controlling the degree of stylization in the Neural Style Transfer (NST) is a little tricky since it usually needs hand-engineering on hyper-parameters. In this paper, we propose the first deep Reinforcement Learning (RL) based architecture that splits one-step style transfer into a step-wise process for the NST task...
[ { "created": "Sat, 30 Sep 2023 15:01:02 GMT", "version": "v1" } ]
2024-08-15
[ [ "Feng", "Chengming", "" ], [ "Hu", "Jing", "" ], [ "Wang", "Xin", "" ], [ "Hu", "Shu", "" ], [ "Zhu", "Bin", "" ], [ "Wu", "Xi", "" ], [ "Zhu", "Hongtu", "" ], [ "Lyu", "Siwei", "" ] ]
Controlling the degree of stylization in the Neural Style Transfer (NST) is a little tricky since it usually needs hand-engineering on hyper-parameters. In this paper, we propose the first deep Reinforcement Learning (RL) based architecture that splits one-step style transfer into a step-wise process for the NST task. ...
2203.07983
Evan Crothers
Evan Crothers, Nathalie Japkowicz, Herna Viktor, Paula Branco
Adversarial Robustness of Neural-Statistical Features in Detection of Generative Transformers
null
null
10.1109/IJCNN55064.2022.9892269
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by-nc-sa/4.0/
The detection of computer-generated text is an area of rapidly increasing significance as nascent generative models allow for efficient creation of compelling human-like text, which may be abused for the purposes of spam, disinformation, phishing, or online influence campaigns. Past work has studied detection of curr...
[ { "created": "Wed, 2 Mar 2022 16:46:39 GMT", "version": "v1" } ]
2022-10-05
[ [ "Crothers", "Evan", "" ], [ "Japkowicz", "Nathalie", "" ], [ "Viktor", "Herna", "" ], [ "Branco", "Paula", "" ] ]
The detection of computer-generated text is an area of rapidly increasing significance as nascent generative models allow for efficient creation of compelling human-like text, which may be abused for the purposes of spam, disinformation, phishing, or online influence campaigns. Past work has studied detection of curren...
2011.11716
Pingakshya Goswami
Pingakshya Goswami and Dinesh Bhatia
Automated Floorplanning for Partially Reconfigurable Designs on Heterogenrous FPGAs
This paper was accepted as a poster in ACM SIGDA International Symposium on FPGA, 2016
null
10.1145/2847263.2847323
null
cs.AR
http://creativecommons.org/licenses/by-sa/4.0/
Floorplanning problem has been extensively explored for homogeneous FPGAs. Most modern FPGAs consist of heterogeneous resources in the form of configurable logic blocks, DSP blocks, BRAMs and more. Very little work has been done for heterogeneous FPGAs. In addition, features like partial reconfigurability allow on-th...
[ { "created": "Mon, 23 Nov 2020 20:41:03 GMT", "version": "v1" } ]
2020-11-25
[ [ "Goswami", "Pingakshya", "" ], [ "Bhatia", "Dinesh", "" ] ]
Floorplanning problem has been extensively explored for homogeneous FPGAs. Most modern FPGAs consist of heterogeneous resources in the form of configurable logic blocks, DSP blocks, BRAMs and more. Very little work has been done for heterogeneous FPGAs. In addition, features like partial reconfigurability allow on-the-...
2305.01074
Kien Thanh Nguyen
Kien Nguyen, Tharindu Fernando, Clinton Fookes, Sridha Sridharan
Physical Adversarial Attacks for Surveillance: A Survey
This paper has been accepted for publication in T-NNLS
null
10.1109/TNNLS.2023.3321432
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Modern automated surveillance techniques are heavily reliant on deep learning methods. Despite the superior performance, these learning systems are inherently vulnerable to adversarial attacks - maliciously crafted inputs that are designed to mislead, or trick, models into making incorrect predictions. An adversary c...
[ { "created": "Mon, 1 May 2023 20:19:59 GMT", "version": "v1" }, { "created": "Fri, 29 Sep 2023 13:43:21 GMT", "version": "v2" }, { "created": "Sat, 14 Oct 2023 06:56:54 GMT", "version": "v3" } ]
2023-10-17
[ [ "Nguyen", "Kien", "" ], [ "Fernando", "Tharindu", "" ], [ "Fookes", "Clinton", "" ], [ "Sridharan", "Sridha", "" ] ]
Modern automated surveillance techniques are heavily reliant on deep learning methods. Despite the superior performance, these learning systems are inherently vulnerable to adversarial attacks - maliciously crafted inputs that are designed to mislead, or trick, models into making incorrect predictions. An adversary can...
1706.10260
Jie Wang
Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet and Jie Wang
How biased is your model? Concentration Inequalities, Information and Model Bias
null
null
null
null
cs.IT math.IT math.PR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We derive tight and computable bounds on the bias of statistical estimators, or more generally of quantities of interest, when evaluated on a baseline model P rather than on the typically unknown true model Q. Our proposed method combines the scalable information inequality derived by P. Dupuis, K.Chowdhary, the auth...
[ { "created": "Fri, 30 Jun 2017 16:19:42 GMT", "version": "v1" } ]
2017-07-04
[ [ "Gourgoulias", "Konstantinos", "" ], [ "Katsoulakis", "Markos A.", "" ], [ "Rey-Bellet", "Luc", "" ], [ "Wang", "Jie", "" ] ]
We derive tight and computable bounds on the bias of statistical estimators, or more generally of quantities of interest, when evaluated on a baseline model P rather than on the typically unknown true model Q. Our proposed method combines the scalable information inequality derived by P. Dupuis, K.Chowdhary, the author...
2112.10070
Jingye Li
Jingye Li, Hao Fei, Jiang Liu, Shengqiong Wu, Meishan Zhang, Chong Teng, Donghong Ji, Fei Li
Unified Named Entity Recognition as Word-Word Relation Classification
Accepted by AAAI'22
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
So far, named entity recognition (NER) has been involved with three major types, including flat, overlapped (aka. nested), and discontinuous NER, which have mostly been studied individually. Recently, a growing interest has been built for unified NER, tackling the above three jobs concurrently with one single model. ...
[ { "created": "Sun, 19 Dec 2021 06:11:07 GMT", "version": "v1" } ]
2021-12-21
[ [ "Li", "Jingye", "" ], [ "Fei", "Hao", "" ], [ "Liu", "Jiang", "" ], [ "Wu", "Shengqiong", "" ], [ "Zhang", "Meishan", "" ], [ "Teng", "Chong", "" ], [ "Ji", "Donghong", "" ], [ "Li", "Fei", ...
So far, named entity recognition (NER) has been involved with three major types, including flat, overlapped (aka. nested), and discontinuous NER, which have mostly been studied individually. Recently, a growing interest has been built for unified NER, tackling the above three jobs concurrently with one single model. Cu...
2302.11051
Tiansheng Huang
Tiansheng Huang, Li Shen, Yan Sun, Weiwei Lin, Dacheng Tao
Fusion of Global and Local Knowledge for Personalized Federated Learning
Accepted by TMLR
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Personalized federated learning, as a variant of federated learning, trains customized models for clients using their heterogeneously distributed data. However, it is still inconclusive about how to design personalized models with better representation of shared global knowledge and personalized pattern. To bridge th...
[ { "created": "Tue, 21 Feb 2023 23:09:45 GMT", "version": "v1" } ]
2023-02-23
[ [ "Huang", "Tiansheng", "" ], [ "Shen", "Li", "" ], [ "Sun", "Yan", "" ], [ "Lin", "Weiwei", "" ], [ "Tao", "Dacheng", "" ] ]
Personalized federated learning, as a variant of federated learning, trains customized models for clients using their heterogeneously distributed data. However, it is still inconclusive about how to design personalized models with better representation of shared global knowledge and personalized pattern. To bridge the ...
2403.16161
Hao Tang
Guillaume Thiry, Hao Tang, Radu Timofte, Luc Van Gool
Towards Online Real-Time Memory-based Video Inpainting Transformers
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Video inpainting tasks have seen significant improvements in recent years with the rise of deep neural networks and, in particular, vision transformers. Although these models show promising reconstruction quality and temporal consistency, they are still unsuitable for live videos, one of the last steps to make them c...
[ { "created": "Sun, 24 Mar 2024 14:02:25 GMT", "version": "v1" } ]
2024-03-26
[ [ "Thiry", "Guillaume", "" ], [ "Tang", "Hao", "" ], [ "Timofte", "Radu", "" ], [ "Van Gool", "Luc", "" ] ]
Video inpainting tasks have seen significant improvements in recent years with the rise of deep neural networks and, in particular, vision transformers. Although these models show promising reconstruction quality and temporal consistency, they are still unsuitable for live videos, one of the last steps to make them com...
2306.08173
Peihan Liu
Alyssa Huang, Peihan Liu, Ryumei Nakada, Linjun Zhang, Wanrong Zhang
Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
null
null
null
null
cs.LG cs.CR cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The surge in multimodal AI's success has sparked concerns over data privacy in vision-and-language tasks. While CLIP has revolutionized multimodal learning through joint training on images and text, its potential to unintentionally disclose sensitive information necessitates the integration of privacy-preserving mech...
[ { "created": "Tue, 13 Jun 2023 23:32:09 GMT", "version": "v1" }, { "created": "Fri, 1 Mar 2024 04:24:04 GMT", "version": "v2" } ]
2024-03-04
[ [ "Huang", "Alyssa", "" ], [ "Liu", "Peihan", "" ], [ "Nakada", "Ryumei", "" ], [ "Zhang", "Linjun", "" ], [ "Zhang", "Wanrong", "" ] ]
The surge in multimodal AI's success has sparked concerns over data privacy in vision-and-language tasks. While CLIP has revolutionized multimodal learning through joint training on images and text, its potential to unintentionally disclose sensitive information necessitates the integration of privacy-preserving mechan...
2212.05505
Xiaohui Jiang
Shihao Wang, Xiaohui Jiang, Ying Li
Focal-PETR: Embracing Foreground for Efficient Multi-Camera 3D Object Detection
Tech Report
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The dominant multi-camera 3D detection paradigm is based on explicit 3D feature construction, which requires complicated indexing of local image-view features via 3D-to-2D projection. Other methods implicitly introduce geometric positional encoding and perform global attention (e.g., PETR) to build the relationship b...
[ { "created": "Sun, 11 Dec 2022 13:38:54 GMT", "version": "v1" }, { "created": "Tue, 13 Dec 2022 09:28:01 GMT", "version": "v2" } ]
2022-12-14
[ [ "Wang", "Shihao", "" ], [ "Jiang", "Xiaohui", "" ], [ "Li", "Ying", "" ] ]
The dominant multi-camera 3D detection paradigm is based on explicit 3D feature construction, which requires complicated indexing of local image-view features via 3D-to-2D projection. Other methods implicitly introduce geometric positional encoding and perform global attention (e.g., PETR) to build the relationship bet...
2205.02129
Jinlan Fu
Yang Xiao, Jinlan Fu, See-Kiong Ng, Pengfei Liu
Are All the Datasets in Benchmark Necessary? A Pilot Study of Dataset Evaluation for Text Classification
9 pages, 9 figures
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In this paper, we ask the research question of whether all the datasets in the benchmark are necessary. We approach this by first characterizing the distinguishability of datasets when comparing different systems. Experiments on 9 datasets and 36 systems show that several existing benchmark datasets contribute little...
[ { "created": "Wed, 4 May 2022 15:33:00 GMT", "version": "v1" } ]
2022-05-05
[ [ "Xiao", "Yang", "" ], [ "Fu", "Jinlan", "" ], [ "Ng", "See-Kiong", "" ], [ "Liu", "Pengfei", "" ] ]
In this paper, we ask the research question of whether all the datasets in the benchmark are necessary. We approach this by first characterizing the distinguishability of datasets when comparing different systems. Experiments on 9 datasets and 36 systems show that several existing benchmark datasets contribute little t...
2011.04000
Ashutosh Modi
Ishika Singh and Ahsan Barkati and Tushar Goswamy and Ashutosh Modi
Adapting a Language Model for Controlled Affective Text Generation
15 Pages (9 + 2 (references) + 4 (appendix)), accepted at COLING 2020
null
null
null
cs.CL cs.AI cs.LG
http://creativecommons.org/licenses/by/4.0/
Human use language not just to convey information but also to express their inner feelings and mental states. In this work, we adapt the state-of-the-art language generation models to generate affective (emotional) text. We posit a model capable of generating affect-driven and topic-focused sentences without losing g...
[ { "created": "Sun, 8 Nov 2020 15:24:39 GMT", "version": "v1" } ]
2020-11-10
[ [ "Singh", "Ishika", "" ], [ "Barkati", "Ahsan", "" ], [ "Goswamy", "Tushar", "" ], [ "Modi", "Ashutosh", "" ] ]
Human use language not just to convey information but also to express their inner feelings and mental states. In this work, we adapt the state-of-the-art language generation models to generate affective (emotional) text. We posit a model capable of generating affect-driven and topic-focused sentences without losing gra...
2101.06570
Iyiola E. Olatunji
Iyiola E. Olatunji, Wolfgang Nejdl and Megha Khosla
Membership Inference Attack on Graph Neural Networks
Best student paper award, IEEE TPS 21
null
null
null
cs.LG cs.CR
http://creativecommons.org/licenses/by/4.0/
Graph Neural Networks (GNNs), which generalize traditional deep neural networks on graph data, have achieved state-of-the-art performance on several graph analytical tasks. We focus on how trained GNN models could leak information about the \emph{member} nodes that they were trained on. We introduce two realistic set...
[ { "created": "Sun, 17 Jan 2021 02:12:35 GMT", "version": "v1" }, { "created": "Mon, 22 Mar 2021 21:12:16 GMT", "version": "v2" }, { "created": "Sat, 18 Dec 2021 06:42:38 GMT", "version": "v3" } ]
2021-12-21
[ [ "Olatunji", "Iyiola E.", "" ], [ "Nejdl", "Wolfgang", "" ], [ "Khosla", "Megha", "" ] ]
Graph Neural Networks (GNNs), which generalize traditional deep neural networks on graph data, have achieved state-of-the-art performance on several graph analytical tasks. We focus on how trained GNN models could leak information about the \emph{member} nodes that they were trained on. We introduce two realistic setti...
1912.10170
Joeran Beel
Dominika Tkaczyk, Andrew Collins, Joeran Beel
Na\"iveRole: Author-Contribution Extraction and Parsing from Biomedical Manuscripts
arXiv admin note: substantial text overlap with arXiv:1802.01174
27th AIAI Irish Conference on Artificial Intelligence and Cognitive Science, 2019
null
null
cs.CL cs.DL cs.IR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Information about the contributions of individual authors to scientific publications is important for assessing authors' achievements. Some biomedical publications have a short section that describes authors' roles and contributions. It is usually written in natural language and hence author contributions cannot be t...
[ { "created": "Sun, 15 Dec 2019 14:37:06 GMT", "version": "v1" } ]
2019-12-24
[ [ "Tkaczyk", "Dominika", "" ], [ "Collins", "Andrew", "" ], [ "Beel", "Joeran", "" ] ]
Information about the contributions of individual authors to scientific publications is important for assessing authors' achievements. Some biomedical publications have a short section that describes authors' roles and contributions. It is usually written in natural language and hence author contributions cannot be tri...
1808.02517
Jelena Diakonikolas
Jelena Diakonikolas, Maryam Fazel, Lorenzo Orecchia
Fair Packing and Covering on a Relative Scale
To appear in SIAM Journal on Optimization
null
null
null
cs.DS cs.NI math.OC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Fair resource allocation is a fundamental optimization problem with applications in operations research, networking, and economic and game theory. Research in these areas has led to the general acceptance of a class of $\alpha$-fair utility functions parameterized by $\alpha \in [0, \infty]$. We consider $\alpha$-fai...
[ { "created": "Tue, 7 Aug 2018 18:55:04 GMT", "version": "v1" }, { "created": "Mon, 5 Nov 2018 18:02:14 GMT", "version": "v2" }, { "created": "Sun, 15 Nov 2020 20:18:18 GMT", "version": "v3" } ]
2020-11-17
[ [ "Diakonikolas", "Jelena", "" ], [ "Fazel", "Maryam", "" ], [ "Orecchia", "Lorenzo", "" ] ]
Fair resource allocation is a fundamental optimization problem with applications in operations research, networking, and economic and game theory. Research in these areas has led to the general acceptance of a class of $\alpha$-fair utility functions parameterized by $\alpha \in [0, \infty]$. We consider $\alpha$-fair ...
1010.2000
Julien Langou
Henricus Bouwmeester and Julien Langou
A Critical Path Approach to Analyzing Parallelism of Algorithmic Variants. Application to Cholesky Inversion
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Algorithms come with multiple variants which are obtained by changing the mathematical approach from which the algorithm is derived. These variants offer a wide spectrum of performance when implemented on a multicore platform and we seek to understand these differences in performances from a theoretical point of view...
[ { "created": "Mon, 11 Oct 2010 05:34:40 GMT", "version": "v1" } ]
2010-10-12
[ [ "Bouwmeester", "Henricus", "" ], [ "Langou", "Julien", "" ] ]
Algorithms come with multiple variants which are obtained by changing the mathematical approach from which the algorithm is derived. These variants offer a wide spectrum of performance when implemented on a multicore platform and we seek to understand these differences in performances from a theoretical point of view. ...
2211.02006
Yang Liu
Yang Liu, Yao Zhang, Yixin Wang, Yang Zhang, Jiang Tian, Zhongchao Shi, Jianping Fan, Zhiqiang He
SAP-DETR: Bridging the Gap Between Salient Points and Queries-Based Transformer Detector for Fast Model Convergency
CVPR 2023
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, the dominant DETR-based approaches apply central-concept spatial prior to accelerate Transformer detector convergency. These methods gradually refine the reference points to the center of target objects and imbue object queries with the updated central reference information for spatially conditional attenti...
[ { "created": "Thu, 3 Nov 2022 17:20:55 GMT", "version": "v1" }, { "created": "Wed, 15 Mar 2023 18:19:12 GMT", "version": "v2" } ]
2023-03-17
[ [ "Liu", "Yang", "" ], [ "Zhang", "Yao", "" ], [ "Wang", "Yixin", "" ], [ "Zhang", "Yang", "" ], [ "Tian", "Jiang", "" ], [ "Shi", "Zhongchao", "" ], [ "Fan", "Jianping", "" ], [ "He", "Zhiqiang",...
Recently, the dominant DETR-based approaches apply central-concept spatial prior to accelerate Transformer detector convergency. These methods gradually refine the reference points to the center of target objects and imbue object queries with the updated central reference information for spatially conditional attention...
2406.18625
Liming Wang
Liming Wang, Yuan Gong, Nauman Dawalatabad, Marco Vilela, Katerina Placek, Brian Tracey, Yishu Gong, Alan Premasiri, Fernando Vieira, James Glass
Automatic Prediction of Amyotrophic Lateral Sclerosis Progression using Longitudinal Speech Transformer
null
null
null
null
cs.SD cs.AI eess.AS
http://creativecommons.org/licenses/by/4.0/
Automatic prediction of amyotrophic lateral sclerosis (ALS) disease progression provides a more efficient and objective alternative than manual approaches. We propose ALS longitudinal speech transformer (ALST), a neural network-based automatic predictor of ALS disease progression from longitudinal speech recordings o...
[ { "created": "Wed, 26 Jun 2024 13:28:24 GMT", "version": "v1" } ]
2024-06-28
[ [ "Wang", "Liming", "" ], [ "Gong", "Yuan", "" ], [ "Dawalatabad", "Nauman", "" ], [ "Vilela", "Marco", "" ], [ "Placek", "Katerina", "" ], [ "Tracey", "Brian", "" ], [ "Gong", "Yishu", "" ], [ "Prema...
Automatic prediction of amyotrophic lateral sclerosis (ALS) disease progression provides a more efficient and objective alternative than manual approaches. We propose ALS longitudinal speech transformer (ALST), a neural network-based automatic predictor of ALS disease progression from longitudinal speech recordings of ...
2401.10778
Lars Van Den Haak MSc
Lars B. van den Haak, Anton Wijs, Marieke Huisman, Mark van den Brand
HaliVer: Deductive Verification and Scheduling Languages Join Forces
null
null
null
null
cs.LO cs.PL
http://creativecommons.org/licenses/by/4.0/
The HaliVer tool integrates deductive verification into the popular scheduling language Halide, used for image processing pipelines and array computations. HaliVer uses Vercors, a separation logic-based verifier, to verify the correctness of (1) the Halide algorithms and (2) the optimised parallel code produced by \h...
[ { "created": "Fri, 19 Jan 2024 15:53:27 GMT", "version": "v1" } ]
2024-01-22
[ [ "Haak", "Lars B. van den", "" ], [ "Wijs", "Anton", "" ], [ "Huisman", "Marieke", "" ], [ "Brand", "Mark van den", "" ] ]
The HaliVer tool integrates deductive verification into the popular scheduling language Halide, used for image processing pipelines and array computations. HaliVer uses Vercors, a separation logic-based verifier, to verify the correctness of (1) the Halide algorithms and (2) the optimised parallel code produced by \hal...
1512.03623
Aysegul Yayimli
Aysegul Yayimli
A Practical Layered Model for Flexible-grid Optical Networks to Reduce the Routing Complexity
3 pages, 2 figures
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This article proposes a new layered model to represent the spectrum assignment on flexible-grid optical networks. This model can reduce the time-complexity of existing routing and spectrum assignment methods by providing a data structure that captures the current spectrum usage of the network links.
[ { "created": "Fri, 11 Dec 2015 12:38:07 GMT", "version": "v1" } ]
2015-12-14
[ [ "Yayimli", "Aysegul", "" ] ]
This article proposes a new layered model to represent the spectrum assignment on flexible-grid optical networks. This model can reduce the time-complexity of existing routing and spectrum assignment methods by providing a data structure that captures the current spectrum usage of the network links.
1407.4879
Wayes Tushar
Wayes Tushar, Shisheng Huang, Chau Yuen, Jian (Andrew) Zhang and David B. Smith
Synthetic Generation of Solar States for Smart Grid: A Multiple Segment Markov Chain Apptoach
6 pages, 4 figures, conference paper
null
null
null
cs.PF
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The use of photovoltaic (PV) sources is becoming very popular in smart grid for their ecological benefits, with higher scalability and utilization for local generation and delivery. PV can also potentially avoid the energy losses that are normally associated with long-range grid distribution. The increased penetratio...
[ { "created": "Fri, 18 Jul 2014 03:09:59 GMT", "version": "v1" } ]
2014-07-21
[ [ "Tushar", "Wayes", "", "Andrew" ], [ "Huang", "Shisheng", "", "Andrew" ], [ "Yuen", "Chau", "", "Andrew" ], [ "Jian", "", "", "Andrew" ], [ "Zhang", "", "" ], [ "Smith", "David B.", "" ] ]
The use of photovoltaic (PV) sources is becoming very popular in smart grid for their ecological benefits, with higher scalability and utilization for local generation and delivery. PV can also potentially avoid the energy losses that are normally associated with long-range grid distribution. The increased penetration ...
2205.10031
Boxuan Chen
Boxuan Chen, Ruifeng Zhang, Shaochu Wang, Liqiang Zhang, Yu Liu
Deep Learning-based Inertial Odometry for Pedestrian Tracking using Attention Mechanism and Res2Net Module
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pedestrian dead reckoning is a challenging task due to the low-cost inertial sensor error accumulation. Recent research has shown that deep learning methods can achieve impressive performance in handling this issue. In this letter, we propose inertial odometry using a deep learning-based velocity estimation method. T...
[ { "created": "Fri, 20 May 2022 09:00:25 GMT", "version": "v1" }, { "created": "Wed, 8 Jun 2022 05:22:00 GMT", "version": "v2" } ]
2022-06-09
[ [ "Chen", "Boxuan", "" ], [ "Zhang", "Ruifeng", "" ], [ "Wang", "Shaochu", "" ], [ "Zhang", "Liqiang", "" ], [ "Liu", "Yu", "" ] ]
Pedestrian dead reckoning is a challenging task due to the low-cost inertial sensor error accumulation. Recent research has shown that deep learning methods can achieve impressive performance in handling this issue. In this letter, we propose inertial odometry using a deep learning-based velocity estimation method. The...
2002.03049
Yuliang Li
Zhengjie Miao, Yuliang Li, Xiaolan Wang, Wang-Chiew Tan
Snippext: Semi-supervised Opinion Mining with Augmented Data
Accepted to WWW 2020
null
10.1145/3366423.3380144
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Online services are interested in solutions to opinion mining, which is the problem of extracting aspects, opinions, and sentiments from text. One method to mine opinions is to leverage the recent success of pre-trained language models which can be fine-tuned to obtain high-quality extractions from reviews. However, ...
[ { "created": "Fri, 7 Feb 2020 23:54:23 GMT", "version": "v1" } ]
2020-02-11
[ [ "Miao", "Zhengjie", "" ], [ "Li", "Yuliang", "" ], [ "Wang", "Xiaolan", "" ], [ "Tan", "Wang-Chiew", "" ] ]
Online services are interested in solutions to opinion mining, which is the problem of extracting aspects, opinions, and sentiments from text. One method to mine opinions is to leverage the recent success of pre-trained language models which can be fine-tuned to obtain high-quality extractions from reviews. However, fi...
2303.01668
Chuheng Zhang
Yuanying Cai, Chuheng Zhang, Wei Shen, Xuyun Zhang, Wenjie Ruan, Longbo Huang
RePreM: Representation Pre-training with Masked Model for Reinforcement Learning
Accepted by AAAI-23
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Inspired by the recent success of sequence modeling in RL and the use of masked language model for pre-training, we propose a masked model for pre-training in RL, RePreM (Representation Pre-training with Masked Model), which trains the encoder combined with transformer blocks to predict the masked states or actions i...
[ { "created": "Fri, 3 Mar 2023 02:04:14 GMT", "version": "v1" } ]
2023-03-06
[ [ "Cai", "Yuanying", "" ], [ "Zhang", "Chuheng", "" ], [ "Shen", "Wei", "" ], [ "Zhang", "Xuyun", "" ], [ "Ruan", "Wenjie", "" ], [ "Huang", "Longbo", "" ] ]
Inspired by the recent success of sequence modeling in RL and the use of masked language model for pre-training, we propose a masked model for pre-training in RL, RePreM (Representation Pre-training with Masked Model), which trains the encoder combined with transformer blocks to predict the masked states or actions in ...