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2405.14384
Marion Neumeier
Marion Neumeier, Sebastian Dorn, Michael Botsch, Wolfgang Utschick
Reliable Trajectory Prediction and Uncertainty Quantification with Conditioned Diffusion Models
Accepted at IEEE/CVF Computer Vision and Pattern Recognition Conference Workshops (CVPRW) 2024
null
null
null
cs.LG cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work introduces the conditioned Vehicle Motion Diffusion (cVMD) model, a novel network architecture for highway trajectory prediction using diffusion models. The proposed model ensures the drivability of the predicted trajectory by integrating non-holonomic motion constraints and physical constraints into the ge...
[ { "created": "Thu, 23 May 2024 10:01:39 GMT", "version": "v1" } ]
2024-05-24
[ [ "Neumeier", "Marion", "" ], [ "Dorn", "Sebastian", "" ], [ "Botsch", "Michael", "" ], [ "Utschick", "Wolfgang", "" ] ]
This work introduces the conditioned Vehicle Motion Diffusion (cVMD) model, a novel network architecture for highway trajectory prediction using diffusion models. The proposed model ensures the drivability of the predicted trajectory by integrating non-holonomic motion constraints and physical constraints into the gene...
1512.07331
Suhas Sreehari
Suhas Sreehari, S. V. Venkatakrishnan, Brendt Wohlberg, Lawrence F. Drummy, Jeffrey P. Simmons, Charles A. Bouman
Plug-and-Play Priors for Bright Field Electron Tomography and Sparse Interpolation
13 pages, 11 figures
null
10.1109/TCI.2016.2599778
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many material and biological samples in scientific imaging are characterized by non-local repeating structures. These are studied using scanning electron microscopy and electron tomography. Sparse sampling of individual pixels in a 2D image acquisition geometry, or sparse sampling of projection images with large tilt...
[ { "created": "Wed, 23 Dec 2015 02:06:29 GMT", "version": "v1" } ]
2017-11-09
[ [ "Sreehari", "Suhas", "" ], [ "Venkatakrishnan", "S. V.", "" ], [ "Wohlberg", "Brendt", "" ], [ "Drummy", "Lawrence F.", "" ], [ "Simmons", "Jeffrey P.", "" ], [ "Bouman", "Charles A.", "" ] ]
Many material and biological samples in scientific imaging are characterized by non-local repeating structures. These are studied using scanning electron microscopy and electron tomography. Sparse sampling of individual pixels in a 2D image acquisition geometry, or sparse sampling of projection images with large tilt i...
2107.07355
Stefan Marksteiner
Stefan Marksteiner, Slava Bronfman, Markus Wolf, Eddie Lazebnik
Using Cyber Digital Twins for Automated Automotive Cybersecurity Testing
6 pages, 3 figures, accepted for the joint SRCNAS/STRIVE workshop at the 6th IEEE European Symposium on Security and Privacy
2021 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW) - Safety vs Security in the Air and on the Ground
10.1109/EuroSPW54576.2021.00020
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cybersecurity testing of automotive systems has become a practical necessity, with the wide adoption of advanced driving assistance functions and vehicular communications. These functionalities require the integration of information and communication technologies that not only allow for a plethora of on-the-fly confi...
[ { "created": "Thu, 15 Jul 2021 14:32:10 GMT", "version": "v1" } ]
2021-09-07
[ [ "Marksteiner", "Stefan", "" ], [ "Bronfman", "Slava", "" ], [ "Wolf", "Markus", "" ], [ "Lazebnik", "Eddie", "" ] ]
Cybersecurity testing of automotive systems has become a practical necessity, with the wide adoption of advanced driving assistance functions and vehicular communications. These functionalities require the integration of information and communication technologies that not only allow for a plethora of on-the-fly configu...
1810.11274
Hao Chen
Hao Chen, Daniel Zelazo, Xiangke Wang, and Lincheng Shen
Convergence Analysis of Signed Nonlinear Networks
null
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This work analyzes the convergence properties of signed networks with nonlinear edge functions. We consider diffusively coupled networks comprised of maximal equilibrium-independent passive (MEIP) dynamics on the nodes, and a general class of nonlinear coupling functions on the edges. The first contribution of this w...
[ { "created": "Fri, 26 Oct 2018 11:38:58 GMT", "version": "v1" }, { "created": "Thu, 31 Jan 2019 03:07:13 GMT", "version": "v2" }, { "created": "Wed, 27 Mar 2019 05:46:44 GMT", "version": "v3" } ]
2019-03-28
[ [ "Chen", "Hao", "" ], [ "Zelazo", "Daniel", "" ], [ "Wang", "Xiangke", "" ], [ "Shen", "Lincheng", "" ] ]
This work analyzes the convergence properties of signed networks with nonlinear edge functions. We consider diffusively coupled networks comprised of maximal equilibrium-independent passive (MEIP) dynamics on the nodes, and a general class of nonlinear coupling functions on the edges. The first contribution of this wor...
2207.09869
Tam\'as Matuszka Ph.D.
Tamas Matuszka, Daniel Kozma
A Novel Neural Network Training Method for Autonomous Driving Using Semi-Pseudo-Labels and 3D Data Augmentations
null
null
10.1007/978-3-031-21967-2_18
null
cs.CV cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
Training neural networks to perform 3D object detection for autonomous driving requires a large amount of diverse annotated data. However, obtaining training data with sufficient quality and quantity is expensive and sometimes impossible due to human and sensor constraints. Therefore, a novel solution is needed for e...
[ { "created": "Wed, 20 Jul 2022 13:04:08 GMT", "version": "v1" } ]
2022-12-13
[ [ "Matuszka", "Tamas", "" ], [ "Kozma", "Daniel", "" ] ]
Training neural networks to perform 3D object detection for autonomous driving requires a large amount of diverse annotated data. However, obtaining training data with sufficient quality and quantity is expensive and sometimes impossible due to human and sensor constraints. Therefore, a novel solution is needed for ext...
1807.00948
De'Aira Bryant
Tobi Ogunyale, De'Aira Bryant and Ayanna Howard
Does Removing Stereotype Priming Remove Bias? A Pilot Human-Robot Interaction Study
5 pages, 9 figures, 1 table, to be presented at the 5th Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML 2018), Stockholm, Sweden, July 15, 2018
null
null
null
cs.RO cs.HC
http://creativecommons.org/licenses/by/4.0/
Robots capable of participating in complex social interactions have shown great potential in a variety of applications. As these robots grow more popular, it is essential to continuously evaluate the dynamics of the human-robot relationship. One factor shown to have potential impacts on this critical relationship is ...
[ { "created": "Tue, 3 Jul 2018 01:48:06 GMT", "version": "v1" } ]
2018-07-04
[ [ "Ogunyale", "Tobi", "" ], [ "Bryant", "De'Aira", "" ], [ "Howard", "Ayanna", "" ] ]
Robots capable of participating in complex social interactions have shown great potential in a variety of applications. As these robots grow more popular, it is essential to continuously evaluate the dynamics of the human-robot relationship. One factor shown to have potential impacts on this critical relationship is th...
2107.09265
Ziqi Lu
Ziqi Lu, Qiangqiang Huang, Kevin Doherty, John Leonard
Consensus-Informed Optimization Over Mixtures for Ambiguity-Aware Object SLAM
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Building object-level maps can facilitate robot-environment interactions (e.g. planning and manipulation), but objects could often have multiple probable poses when viewed from a single vantage point, due to symmetry, occlusion or perceptual failures. A robust object-level simultaneous localization and mapping (objec...
[ { "created": "Tue, 20 Jul 2021 05:23:20 GMT", "version": "v1" }, { "created": "Wed, 8 Sep 2021 04:32:34 GMT", "version": "v2" } ]
2021-09-09
[ [ "Lu", "Ziqi", "" ], [ "Huang", "Qiangqiang", "" ], [ "Doherty", "Kevin", "" ], [ "Leonard", "John", "" ] ]
Building object-level maps can facilitate robot-environment interactions (e.g. planning and manipulation), but objects could often have multiple probable poses when viewed from a single vantage point, due to symmetry, occlusion or perceptual failures. A robust object-level simultaneous localization and mapping (object ...
2102.00423
Reza Hadi Mogavi
Reza Hadi Mogavi, Xiaojuan Ma, Pan Hui
Characterizing Student Engagement Moods for Dropout Prediction in Question Pool Websites
Accepted in the 24th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2021)
null
10.1145/3449086
null
cs.HC cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Problem-Based Learning (PBL) is a popular approach to instruction that supports students to get hands-on training by solving problems. Question Pool websites (QPs) such as LeetCode, Code Chef, and Math Playground help PBL by supplying authentic, diverse, and contextualized questions to students. Nonetheless, empirica...
[ { "created": "Sun, 31 Jan 2021 10:30:19 GMT", "version": "v1" }, { "created": "Tue, 2 Feb 2021 19:15:09 GMT", "version": "v2" } ]
2021-02-05
[ [ "Mogavi", "Reza Hadi", "" ], [ "Ma", "Xiaojuan", "" ], [ "Hui", "Pan", "" ] ]
Problem-Based Learning (PBL) is a popular approach to instruction that supports students to get hands-on training by solving problems. Question Pool websites (QPs) such as LeetCode, Code Chef, and Math Playground help PBL by supplying authentic, diverse, and contextualized questions to students. Nonetheless, empirical ...
2104.04071
Gautam Srivastava
Farrah Huntinghawk, Candace Richard, Sarah Plosker, Gautam Srivastava
Expanding Cybersecurity Knowledge Through an Indigenous Lens: A First Look
9 pages, 0 figures
2020 IEEE CCECE, London, ON, Canada, 2020, pp. 1-4
10.1109/CCECE47787.2020.9255753.
null
cs.CY cs.CR
http://creativecommons.org/licenses/by/4.0/
Decolonization and Indigenous education are at the forefront of Canadian content currently in Academia. Over the last few decades, we have seen some major changes in the way in which we share information. In particular, we have moved into an age of electronically-shared content, and there is an increasing expectation...
[ { "created": "Tue, 30 Mar 2021 19:25:01 GMT", "version": "v1" } ]
2021-04-12
[ [ "Huntinghawk", "Farrah", "" ], [ "Richard", "Candace", "" ], [ "Plosker", "Sarah", "" ], [ "Srivastava", "Gautam", "" ] ]
Decolonization and Indigenous education are at the forefront of Canadian content currently in Academia. Over the last few decades, we have seen some major changes in the way in which we share information. In particular, we have moved into an age of electronically-shared content, and there is an increasing expectation i...
1708.02393
Chadarat Phipathananunth
Panuchart Bunyakiati and Chadarat Phipathananunth
Cherry-Picking of Code Commits in Long-Running, Multi-release Software
5 pages
null
10.1145/3106237.3122818
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents Tartarian, a tool that supports maintenance of software with long-running, multi-release branches in distributed version control systems. When new maintenance code, such as bug fixes and code improvement, is committed into a branch, it is likely that such code can be applied or reused with some ot...
[ { "created": "Tue, 8 Aug 2017 07:43:31 GMT", "version": "v1" } ]
2017-08-09
[ [ "Bunyakiati", "Panuchart", "" ], [ "Phipathananunth", "Chadarat", "" ] ]
This paper presents Tartarian, a tool that supports maintenance of software with long-running, multi-release branches in distributed version control systems. When new maintenance code, such as bug fixes and code improvement, is committed into a branch, it is likely that such code can be applied or reused with some othe...
2006.14784
Peter Vaillancourt
Peter Z. Vaillancourt, J. Eric Coulter, Richard Knepper, Brandon Barker
Self-Scaling Clusters and Reproducible Containers to Enable Scientific Computing
Accepted for publication in the IEEE conference proceedings for HPEC 2020
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Container technologies such as Docker have become a crucial component of many software industry practices especially those pertaining to reproducibility and portability. The containerization philosophy has influenced the scientific computing community, which has begun to adopt - and even develop - container technolog...
[ { "created": "Fri, 26 Jun 2020 03:57:19 GMT", "version": "v1" }, { "created": "Mon, 3 Aug 2020 23:40:15 GMT", "version": "v2" } ]
2020-08-05
[ [ "Vaillancourt", "Peter Z.", "" ], [ "Coulter", "J. Eric", "" ], [ "Knepper", "Richard", "" ], [ "Barker", "Brandon", "" ] ]
Container technologies such as Docker have become a crucial component of many software industry practices especially those pertaining to reproducibility and portability. The containerization philosophy has influenced the scientific computing community, which has begun to adopt - and even develop - container technologie...
1710.02282
Gabriele D'Angelo
Stefano Ferretti, Gabriele D'Angelo, Vittorio Ghini, Moreno Marzolla
The Quest for Scalability and Accuracy in the Simulation of the Internet of Things: an Approach based on Multi-Level Simulation
Proceedings of the IEEE/ACM International Symposium on Distributed Simulation and Real Time Applications (DS-RT 2017)
null
10.1109/DISTRA.2017.8167672
null
cs.PF cs.DC cs.MA cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents a methodology for simulating the Internet of Things (IoT) using multi-level simulation models. With respect to conventional simulators, this approach allows us to tune the level of detail of different parts of the model without compromising the scalability of the simulation. As a use case, we have...
[ { "created": "Fri, 6 Oct 2017 06:05:58 GMT", "version": "v1" }, { "created": "Tue, 7 Aug 2018 07:12:41 GMT", "version": "v2" } ]
2018-08-08
[ [ "Ferretti", "Stefano", "" ], [ "D'Angelo", "Gabriele", "" ], [ "Ghini", "Vittorio", "" ], [ "Marzolla", "Moreno", "" ] ]
This paper presents a methodology for simulating the Internet of Things (IoT) using multi-level simulation models. With respect to conventional simulators, this approach allows us to tune the level of detail of different parts of the model without compromising the scalability of the simulation. As a use case, we have d...
2002.02071
Jiangsheng You Dr.
Jason You
Finite Hilbert Transform in Weighted L2 Spaces
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Several new properties of weighted Hilbert transform are obtained. If mu is zero, two Plancherel-like equations and the isotropic properties are derived. For mu is real number, a coerciveness is derived and two iterative sequences are constructed to find the inversion. The proposed iterative sequences are applicable ...
[ { "created": "Thu, 6 Feb 2020 02:13:18 GMT", "version": "v1" }, { "created": "Tue, 11 Feb 2020 03:47:58 GMT", "version": "v2" } ]
2020-02-12
[ [ "You", "Jason", "" ] ]
Several new properties of weighted Hilbert transform are obtained. If mu is zero, two Plancherel-like equations and the isotropic properties are derived. For mu is real number, a coerciveness is derived and two iterative sequences are constructed to find the inversion. The proposed iterative sequences are applicable to...
1806.00194
Chen Huang
Chen Huang, Yining Li, Chen Change Loy, Xiaoou Tang
Deep Imbalanced Learning for Face Recognition and Attribute Prediction
14 pages, 10 figures, 8 tables. Accepted to TPAMI
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Data for face analysis often exhibit highly-skewed class distribution, i.e., most data belong to a few majority classes, while the minority classes only contain a scarce amount of instances. To mitigate this issue, contemporary deep learning methods typically follow classic strategies such as class re-sampling or cos...
[ { "created": "Fri, 1 Jun 2018 04:55:47 GMT", "version": "v1" }, { "created": "Tue, 30 Apr 2019 03:49:42 GMT", "version": "v2" } ]
2019-05-01
[ [ "Huang", "Chen", "" ], [ "Li", "Yining", "" ], [ "Loy", "Chen Change", "" ], [ "Tang", "Xiaoou", "" ] ]
Data for face analysis often exhibit highly-skewed class distribution, i.e., most data belong to a few majority classes, while the minority classes only contain a scarce amount of instances. To mitigate this issue, contemporary deep learning methods typically follow classic strategies such as class re-sampling or cost-...
2309.12578
Bokyeong Yoon
Bokyeong Yoon, Yoonsang Han, Gordon Euhyun Moon
SPION: Layer-Wise Sparse Training of Transformer via Convolutional Flood Filling
null
null
null
null
cs.LG cs.DC
http://creativecommons.org/licenses/by/4.0/
Sparsifying the Transformer has garnered considerable interest, as training the Transformer is very computationally demanding. Prior efforts to sparsify the Transformer have either used a fixed pattern or data-driven approach to reduce the number of operations involving the computation of multi-head attention, which ...
[ { "created": "Fri, 22 Sep 2023 02:14:46 GMT", "version": "v1" } ]
2023-09-25
[ [ "Yoon", "Bokyeong", "" ], [ "Han", "Yoonsang", "" ], [ "Moon", "Gordon Euhyun", "" ] ]
Sparsifying the Transformer has garnered considerable interest, as training the Transformer is very computationally demanding. Prior efforts to sparsify the Transformer have either used a fixed pattern or data-driven approach to reduce the number of operations involving the computation of multi-head attention, which is...
2312.12006
Md.Rafiul Biswas Mr.
Md. Rafiul Biswas, Ashhadul Islam, Zubair Shah, Wajdi Zaghouani, Samir Brahim Belhaouari
Can ChatGPT be Your Personal Medical Assistant?
5 pages, 7 figures, two tables, Accepted on The International Symposium on Foundation and Large Language Models (FLLM2023)
The International Symposium on Foundation and Large Language Models (FLLM2023) https://fllm-conference.org/2023/
null
null
cs.CL cs.SI
http://creativecommons.org/licenses/by/4.0/
The advanced large language model (LLM) ChatGPT has shown its potential in different domains and remains unbeaten due to its characteristics compared to other LLMs. This study aims to evaluate the potential of using a fine-tuned ChatGPT model as a personal medical assistant in the Arabic language. To do so, this stud...
[ { "created": "Tue, 19 Dec 2023 09:54:27 GMT", "version": "v1" } ]
2023-12-20
[ [ "Biswas", "Md. Rafiul", "" ], [ "Islam", "Ashhadul", "" ], [ "Shah", "Zubair", "" ], [ "Zaghouani", "Wajdi", "" ], [ "Belhaouari", "Samir Brahim", "" ] ]
The advanced large language model (LLM) ChatGPT has shown its potential in different domains and remains unbeaten due to its characteristics compared to other LLMs. This study aims to evaluate the potential of using a fine-tuned ChatGPT model as a personal medical assistant in the Arabic language. To do so, this study ...
2010.01247
Zhun Deng
Zhun Deng, Cynthia Dwork, Jialiang Wang, Linjun Zhang
Interpreting Robust Optimization via Adversarial Influence Functions
null
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Robust optimization has been widely used in nowadays data science, especially in adversarial training. However, little research has been done to quantify how robust optimization changes the optimizers and the prediction losses comparing to standard training. In this paper, inspired by the influence function in robust...
[ { "created": "Sat, 3 Oct 2020 01:19:10 GMT", "version": "v1" } ]
2020-10-06
[ [ "Deng", "Zhun", "" ], [ "Dwork", "Cynthia", "" ], [ "Wang", "Jialiang", "" ], [ "Zhang", "Linjun", "" ] ]
Robust optimization has been widely used in nowadays data science, especially in adversarial training. However, little research has been done to quantify how robust optimization changes the optimizers and the prediction losses comparing to standard training. In this paper, inspired by the influence function in robust s...
2011.08529
Zhaoyi Wan
Zhaoyi Wan, Yimin Chen, Sutao Deng, Kunpeng Chen, Cong Yao, Jiebo Luo
Slender Object Detection: Diagnoses and Improvements
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
In this paper, we are concerned with the detection of a particular type of objects with extreme aspect ratios, namely \textbf{slender objects}. In real-world scenarios, slender objects are actually very common and crucial to the objective of a detection system. However, this type of objects has been largely overlooke...
[ { "created": "Tue, 17 Nov 2020 09:39:42 GMT", "version": "v1" }, { "created": "Sat, 21 Nov 2020 05:33:07 GMT", "version": "v2" }, { "created": "Thu, 24 Dec 2020 09:14:36 GMT", "version": "v3" }, { "created": "Wed, 7 Apr 2021 02:35:15 GMT", "version": "v4" } ]
2021-04-08
[ [ "Wan", "Zhaoyi", "" ], [ "Chen", "Yimin", "" ], [ "Deng", "Sutao", "" ], [ "Chen", "Kunpeng", "" ], [ "Yao", "Cong", "" ], [ "Luo", "Jiebo", "" ] ]
In this paper, we are concerned with the detection of a particular type of objects with extreme aspect ratios, namely \textbf{slender objects}. In real-world scenarios, slender objects are actually very common and crucial to the objective of a detection system. However, this type of objects has been largely overlooked ...
1012.5041
Pablo S\'anchez-Moreno
P. S\'anchez-Moreno, A. Zarzo and J.S. Dehesa
Jensen divergence based on Fisher's information
8 pages, 8 figures
J. Phys. A: Math. Theor. 45 (2012) 125305
10.1088/1751-8113/45/12/125305
null
cs.IT math.IT physics.data-an
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The measure of Jensen-Fisher divergence between probability distributions is introduced and its theoretical grounds set up. This quantity, in contrast to the remaining Jensen divergences, is very sensitive to the fluctuations of the probability distributions because it is controlled by the (local) Fisher information,...
[ { "created": "Wed, 22 Dec 2010 17:15:17 GMT", "version": "v1" } ]
2013-01-08
[ [ "Sánchez-Moreno", "P.", "" ], [ "Zarzo", "A.", "" ], [ "Dehesa", "J. S.", "" ] ]
The measure of Jensen-Fisher divergence between probability distributions is introduced and its theoretical grounds set up. This quantity, in contrast to the remaining Jensen divergences, is very sensitive to the fluctuations of the probability distributions because it is controlled by the (local) Fisher information, w...
1505.07293
Vijay Badrinarayanan
Vijay Badrinarayanan, Ankur Handa, Roberto Cipolla
SegNet: A Deep Convolutional Encoder-Decoder Architecture for Robust Semantic Pixel-Wise Labelling
This version was first submitted to CVPR' 15 on November 14, 2014 with paper Id 1468. A similar architecture was proposed more recently on May 17, 2015, see http://arxiv.org/pdf/1505.04366.pdf
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We propose a novel deep architecture, SegNet, for semantic pixel wise image labelling. SegNet has several attractive properties; (i) it only requires forward evaluation of a fully learnt function to obtain smooth label predictions, (ii) with increasing depth, a larger context is considered for pixel labelling which i...
[ { "created": "Wed, 27 May 2015 12:54:17 GMT", "version": "v1" } ]
2015-05-28
[ [ "Badrinarayanan", "Vijay", "" ], [ "Handa", "Ankur", "" ], [ "Cipolla", "Roberto", "" ] ]
We propose a novel deep architecture, SegNet, for semantic pixel wise image labelling. SegNet has several attractive properties; (i) it only requires forward evaluation of a fully learnt function to obtain smooth label predictions, (ii) with increasing depth, a larger context is considered for pixel labelling which imp...
2308.14326
Maximilian St\"abler
Maximilian Staebler, Frank Koester, Christoph Schlueter-Langdon
Towards solving ontological dissonance using network graphs
5 pages, AMCIS 2023 proceedings
null
null
null
cs.AI cs.SI
http://creativecommons.org/licenses/by/4.0/
Data Spaces are an emerging concept for the trusted implementation of data-based applications and business models, offering a high degree of flexibility and sovereignty to all stakeholders. As Data Spaces are currently emerging in different domains such as mobility, health or food, semantic interfaces need to be iden...
[ { "created": "Mon, 28 Aug 2023 06:10:26 GMT", "version": "v1" } ]
2023-08-29
[ [ "Staebler", "Maximilian", "" ], [ "Koester", "Frank", "" ], [ "Schlueter-Langdon", "Christoph", "" ] ]
Data Spaces are an emerging concept for the trusted implementation of data-based applications and business models, offering a high degree of flexibility and sovereignty to all stakeholders. As Data Spaces are currently emerging in different domains such as mobility, health or food, semantic interfaces need to be identi...
2012.11334
Viacheslav Dubeyko
Viacheslav Dubeyko
Cognitive Computing in Data-centric Paradigm
null
null
null
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge is the most precious asset of humankind. People extract the experience from the data that provide for us the reality through the feelings. Generally speaking, it is possible to see the analogy of knowledge elaboration between humankind's way and the artificial system's way. Digital data are the "feelings" o...
[ { "created": "Mon, 14 Dec 2020 22:39:53 GMT", "version": "v1" } ]
2020-12-22
[ [ "Dubeyko", "Viacheslav", "" ] ]
Knowledge is the most precious asset of humankind. People extract the experience from the data that provide for us the reality through the feelings. Generally speaking, it is possible to see the analogy of knowledge elaboration between humankind's way and the artificial system's way. Digital data are the "feelings" of ...
1603.02381
Ragesh K Ramachandran
Ragesh K Ramachandran and Spring Berman
The Effect of Communication Topology on Scalar Field Estimation by Networked Robotic Swarms
null
null
null
null
cs.RO cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies the problem of reconstructing a two-dimensional scalar field using a swarm of networked robots with local communication capabilities. We consider the communication network of the robots to form either a chain or a grid topology. We formulate the reconstruction problem as an optimization problem tha...
[ { "created": "Tue, 8 Mar 2016 04:51:09 GMT", "version": "v1" } ]
2016-03-09
[ [ "Ramachandran", "Ragesh K", "" ], [ "Berman", "Spring", "" ] ]
This paper studies the problem of reconstructing a two-dimensional scalar field using a swarm of networked robots with local communication capabilities. We consider the communication network of the robots to form either a chain or a grid topology. We formulate the reconstruction problem as an optimization problem that ...
2304.00173
Rami Botros
Rami Botros, Rohit Prabhavalkar, Johan Schalkwyk, Ciprian Chelba, Tara N. Sainath, Fran\c{c}oise Beaufays
Lego-Features: Exporting modular encoder features for streaming and deliberation ASR
null
null
null
null
cs.CL cs.AI cs.SD eess.AS
http://creativecommons.org/licenses/by/4.0/
In end-to-end (E2E) speech recognition models, a representational tight-coupling inevitably emerges between the encoder and the decoder. We build upon recent work that has begun to explore building encoders with modular encoded representations, such that encoders and decoders from different models can be stitched tog...
[ { "created": "Fri, 31 Mar 2023 23:33:21 GMT", "version": "v1" } ]
2023-04-04
[ [ "Botros", "Rami", "" ], [ "Prabhavalkar", "Rohit", "" ], [ "Schalkwyk", "Johan", "" ], [ "Chelba", "Ciprian", "" ], [ "Sainath", "Tara N.", "" ], [ "Beaufays", "Françoise", "" ] ]
In end-to-end (E2E) speech recognition models, a representational tight-coupling inevitably emerges between the encoder and the decoder. We build upon recent work that has begun to explore building encoders with modular encoded representations, such that encoders and decoders from different models can be stitched toget...
1809.01906
Felix Leibfried
Felix Leibfried, Peter Vrancx
Model-Based Regularization for Deep Reinforcement Learning with Transcoder Networks
Presented at the NIPS Deep Reinforcement Learning Workshop, Montreal, Canada, 2018
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper proposes a new optimization objective for value-based deep reinforcement learning. We extend conventional Deep Q-Networks (DQNs) by adding a model-learning component yielding a transcoder network. The prediction errors for the model are included in the basic DQN loss as additional regularizers. This augmen...
[ { "created": "Thu, 6 Sep 2018 09:49:18 GMT", "version": "v1" }, { "created": "Tue, 20 Nov 2018 13:30:16 GMT", "version": "v2" } ]
2018-11-21
[ [ "Leibfried", "Felix", "" ], [ "Vrancx", "Peter", "" ] ]
This paper proposes a new optimization objective for value-based deep reinforcement learning. We extend conventional Deep Q-Networks (DQNs) by adding a model-learning component yielding a transcoder network. The prediction errors for the model are included in the basic DQN loss as additional regularizers. This augmente...
2202.13677
Sean Kauffman
Sean Kauffman, Martin Zimmermann
The Complexity of Evaluating nfer
null
null
null
null
cs.LO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Nfer is a rule-based language for abstracting event streams into a hierarchy of intervals with data. Nfer has multiple implementations and has been applied in the analysis of spacecraft telemetry and autonomous vehicle logs. This work provides the first complexity analysis of nfer evaluation, i.e., the problem of dec...
[ { "created": "Mon, 28 Feb 2022 10:53:09 GMT", "version": "v1" }, { "created": "Fri, 1 Jul 2022 12:37:22 GMT", "version": "v2" }, { "created": "Mon, 21 Nov 2022 12:08:18 GMT", "version": "v3" } ]
2022-11-22
[ [ "Kauffman", "Sean", "" ], [ "Zimmermann", "Martin", "" ] ]
Nfer is a rule-based language for abstracting event streams into a hierarchy of intervals with data. Nfer has multiple implementations and has been applied in the analysis of spacecraft telemetry and autonomous vehicle logs. This work provides the first complexity analysis of nfer evaluation, i.e., the problem of decid...
2209.10767
Srikanth Malla
Srikanth Malla, Chiho Choi, Isht Dwivedi, Joon Hee Choi, Jiachen Li
DRAMA: Joint Risk Localization and Captioning in Driving
WACV 2023 (Winter Conference on Applications of Computer Vision)
null
null
null
cs.CV cs.AI cs.LG cs.RO
http://creativecommons.org/licenses/by-nc-sa/4.0/
Considering the functionality of situational awareness in safety-critical automation systems, the perception of risk in driving scenes and its explainability is of particular importance for autonomous and cooperative driving. Toward this goal, this paper proposes a new research direction of joint risk localization in...
[ { "created": "Thu, 22 Sep 2022 03:53:56 GMT", "version": "v1" }, { "created": "Wed, 5 Oct 2022 21:09:10 GMT", "version": "v2" } ]
2022-10-07
[ [ "Malla", "Srikanth", "" ], [ "Choi", "Chiho", "" ], [ "Dwivedi", "Isht", "" ], [ "Choi", "Joon Hee", "" ], [ "Li", "Jiachen", "" ] ]
Considering the functionality of situational awareness in safety-critical automation systems, the perception of risk in driving scenes and its explainability is of particular importance for autonomous and cooperative driving. Toward this goal, this paper proposes a new research direction of joint risk localization in d...
2211.06223
Linqi Ye Dr.
Linqi Ye, Xueqian Wang, Houde Liu, Bin Liang
The Simplest Balance Controller for Dynamic Walking
null
null
null
null
cs.RO cs.SY eess.SY
http://creativecommons.org/licenses/by/4.0/
Humans can balance very well during walking, even when perturbed. But it seems difficult to achieve robust walking for bipedal robots. Here we describe the simplest balance controller that leads to robust walking for a linear inverted pendulum (LIP) model. The main idea is to use a linear function of the body velocit...
[ { "created": "Fri, 11 Nov 2022 14:19:40 GMT", "version": "v1" } ]
2022-11-14
[ [ "Ye", "Linqi", "" ], [ "Wang", "Xueqian", "" ], [ "Liu", "Houde", "" ], [ "Liang", "Bin", "" ] ]
Humans can balance very well during walking, even when perturbed. But it seems difficult to achieve robust walking for bipedal robots. Here we describe the simplest balance controller that leads to robust walking for a linear inverted pendulum (LIP) model. The main idea is to use a linear function of the body velocity ...
2309.16783
David Widemann
Lakshmi Nair, David Widemann, Brad Turcott, Nick Moore, Alexandra Wleklinski, Darius Bunandar, Ioannis Papavasileiou, Shihu Wang, Eric Logan
Photonic Accelerators for Image Segmentation in Autonomous Driving and Defect Detection
null
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by/4.0/
Photonic computing promises faster and more energy-efficient deep neural network (DNN) inference than traditional digital hardware. Advances in photonic computing can have profound impacts on applications such as autonomous driving and defect detection that depend on fast, accurate and energy efficient execution of i...
[ { "created": "Thu, 28 Sep 2023 18:22:41 GMT", "version": "v1" }, { "created": "Tue, 3 Oct 2023 16:34:13 GMT", "version": "v2" } ]
2023-10-04
[ [ "Nair", "Lakshmi", "" ], [ "Widemann", "David", "" ], [ "Turcott", "Brad", "" ], [ "Moore", "Nick", "" ], [ "Wleklinski", "Alexandra", "" ], [ "Bunandar", "Darius", "" ], [ "Papavasileiou", "Ioannis", "" ...
Photonic computing promises faster and more energy-efficient deep neural network (DNN) inference than traditional digital hardware. Advances in photonic computing can have profound impacts on applications such as autonomous driving and defect detection that depend on fast, accurate and energy efficient execution of ima...
2102.08085
Fouzia Altaf Ms
Fouzia Altaf, Syed M.S. Islam, Naeem K. Janjua, Naveed Akhtar
Boosting Deep Transfer Learning for COVID-19 Classification
5 pages
null
null
null
cs.CV cs.AI cs.LG
http://creativecommons.org/licenses/by-nc-nd/4.0/
COVID-19 classification using chest Computed Tomography (CT) has been found pragmatically useful by several studies. Due to the lack of annotated samples, these studies recommend transfer learning and explore the choices of pre-trained models and data augmentation. However, it is still unknown if there are better str...
[ { "created": "Tue, 16 Feb 2021 11:15:23 GMT", "version": "v1" } ]
2021-02-17
[ [ "Altaf", "Fouzia", "" ], [ "Islam", "Syed M. S.", "" ], [ "Janjua", "Naeem K.", "" ], [ "Akhtar", "Naveed", "" ] ]
COVID-19 classification using chest Computed Tomography (CT) has been found pragmatically useful by several studies. Due to the lack of annotated samples, these studies recommend transfer learning and explore the choices of pre-trained models and data augmentation. However, it is still unknown if there are better strat...
2011.01671
Christian Berger
Christian Berger, Hans P. Reiser, Jo\~ao Sousa, Alysson Bessani
AWARE: Adaptive Wide-Area Replication for Fast and Resilient Byzantine Consensus
This paper consists of 16 pages in total. This paper is the accepted version to be published in IEEE Transactions on Dependable and Secure Computing (2020). For the published version refer to DOI https://doi.org/10.1109/TDSC.2020.3030605
null
10.1109/TDSC.2020.3030605
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
With upcoming blockchain infrastructures, world-spanning Byzantine consensus is getting practical and necessary. In geographically distributed systems, the pace at which consensus is achieved is limited by the heterogenous latencies of connections between replicas. If deployed on a wide-area network, consensus-based ...
[ { "created": "Tue, 3 Nov 2020 12:58:39 GMT", "version": "v1" } ]
2020-11-04
[ [ "Berger", "Christian", "" ], [ "Reiser", "Hans P.", "" ], [ "Sousa", "João", "" ], [ "Bessani", "Alysson", "" ] ]
With upcoming blockchain infrastructures, world-spanning Byzantine consensus is getting practical and necessary. In geographically distributed systems, the pace at which consensus is achieved is limited by the heterogenous latencies of connections between replicas. If deployed on a wide-area network, consensus-based sy...
2403.18133
Erkan Karabulut
Erkan Karabulut, Victoria Degeler, Paul Groth
AE SemRL: Learning Semantic Association Rules with Autoencoders
null
null
null
null
cs.LG cs.AI
http://creativecommons.org/licenses/by/4.0/
Association Rule Mining (ARM) is the task of learning associations among data features in the form of logical rules. Mining association rules from high-dimensional numerical data, for example, time series data from a large number of sensors in a smart environment, is a computationally intensive task. In this study, w...
[ { "created": "Tue, 26 Mar 2024 22:28:43 GMT", "version": "v1" } ]
2024-03-28
[ [ "Karabulut", "Erkan", "" ], [ "Degeler", "Victoria", "" ], [ "Groth", "Paul", "" ] ]
Association Rule Mining (ARM) is the task of learning associations among data features in the form of logical rules. Mining association rules from high-dimensional numerical data, for example, time series data from a large number of sensors in a smart environment, is a computationally intensive task. In this study, we ...
1704.03928
Noah Stephens-Davidowitz
Huck Bennett, Alexander Golovnev, Noah Stephens-Davidowitz
On the Quantitative Hardness of CVP
null
FOCS 2017
null
null
cs.CC cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
$ \newcommand{\eps}{\varepsilon} \newcommand{\problem}[1]{\ensuremath{\mathrm{#1}} } \newcommand{\CVP}{\problem{CVP}} \newcommand{\SVP}{\problem{SVP}} \newcommand{\CVPP}{\problem{CVPP}} \newcommand{\ensuremath}[1]{#1} $For odd integers $p \geq 1$ (and $p = \infty$), we show that the Closest Vector Problem in the $\el...
[ { "created": "Wed, 12 Apr 2017 20:55:59 GMT", "version": "v1" }, { "created": "Thu, 5 Oct 2017 19:05:01 GMT", "version": "v2" } ]
2019-01-28
[ [ "Bennett", "Huck", "" ], [ "Golovnev", "Alexander", "" ], [ "Stephens-Davidowitz", "Noah", "" ] ]
$ \newcommand{\eps}{\varepsilon} \newcommand{\problem}[1]{\ensuremath{\mathrm{#1}} } \newcommand{\CVP}{\problem{CVP}} \newcommand{\SVP}{\problem{SVP}} \newcommand{\CVPP}{\problem{CVPP}} \newcommand{\ensuremath}[1]{#1} $For odd integers $p \geq 1$ (and $p = \infty$), we show that the Closest Vector Problem in the $\ell_...
2310.00922
Hong Huy Nguyen
Huy H. Nguyen, Junichi Yamagishi, Isao Echizen
How Close are Other Computer Vision Tasks to Deepfake Detection?
Accepted to be Published in Proceedings of the IEEE International Joint Conference on Biometrics (IJCB 2023)
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we challenge the conventional belief that supervised ImageNet-trained models have strong generalizability and are suitable for use as feature extractors in deepfake detection. We present a new measurement, "model separability," for visually and quantitatively assessing a model's raw capacity to separat...
[ { "created": "Mon, 2 Oct 2023 06:32:35 GMT", "version": "v1" } ]
2023-10-03
[ [ "Nguyen", "Huy H.", "" ], [ "Yamagishi", "Junichi", "" ], [ "Echizen", "Isao", "" ] ]
In this paper, we challenge the conventional belief that supervised ImageNet-trained models have strong generalizability and are suitable for use as feature extractors in deepfake detection. We present a new measurement, "model separability," for visually and quantitatively assessing a model's raw capacity to separate ...
2107.07983
Zhi-Gang Liu
Zhi-Gang Liu, Paul N. Whatmough, Yuhao Zhu, Matthew Mattina
S2TA: Exploiting Structured Sparsity for Energy-Efficient Mobile CNN Acceleration
Accepted by the HPCA 20222, the 28th IEEE International Symposium on High-Performance Computer Architecture (HPCA-28)
null
null
null
cs.AR cs.LG
http://creativecommons.org/licenses/by/4.0/
Exploiting sparsity is a key technique in accelerating quantized convolutional neural network (CNN) inference on mobile devices. Prior sparse CNN accelerators largely exploit un-structured sparsity and achieve significant speedups. Due to the unbounded, largely unpredictable sparsity patterns, however, exploiting uns...
[ { "created": "Fri, 16 Jul 2021 15:57:06 GMT", "version": "v1" }, { "created": "Thu, 6 Jan 2022 16:23:55 GMT", "version": "v2" } ]
2022-01-07
[ [ "Liu", "Zhi-Gang", "" ], [ "Whatmough", "Paul N.", "" ], [ "Zhu", "Yuhao", "" ], [ "Mattina", "Matthew", "" ] ]
Exploiting sparsity is a key technique in accelerating quantized convolutional neural network (CNN) inference on mobile devices. Prior sparse CNN accelerators largely exploit un-structured sparsity and achieve significant speedups. Due to the unbounded, largely unpredictable sparsity patterns, however, exploiting unstr...
1804.06682
Mostafa Wahby
Mostafa Wahby, Mary Katherine Heinrich, Daniel Nicolas Hofstadler, Payam Zahadat, Sebastian Risi, Phil Ayres, Thomas Schmickl and Heiko Hamann
A Robot to Shape your Natural Plant: The Machine Learning Approach to Model and Control Bio-Hybrid Systems
null
null
10.1145/3205455.3205516
null
cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Bio-hybrid systems---close couplings of natural organisms with technology---are high potential and still underexplored. In existing work, robots have mostly influenced group behaviors of animals. We explore the possibilities of mixing robots with natural plants, merging useful attributes. Significant synergies arise ...
[ { "created": "Wed, 18 Apr 2018 12:30:18 GMT", "version": "v1" }, { "created": "Thu, 19 Apr 2018 09:26:34 GMT", "version": "v2" } ]
2018-04-20
[ [ "Wahby", "Mostafa", "" ], [ "Heinrich", "Mary Katherine", "" ], [ "Hofstadler", "Daniel Nicolas", "" ], [ "Zahadat", "Payam", "" ], [ "Risi", "Sebastian", "" ], [ "Ayres", "Phil", "" ], [ "Schmickl", "Thomas", ...
Bio-hybrid systems---close couplings of natural organisms with technology---are high potential and still underexplored. In existing work, robots have mostly influenced group behaviors of animals. We explore the possibilities of mixing robots with natural plants, merging useful attributes. Significant synergies arise by...
2008.10715
Binghui Wang
Binghui Wang, Jinyuan Jia, Xiaoyu Cao, Neil Zhenqiang Gong
Certified Robustness of Graph Neural Networks against Adversarial Structural Perturbation
Accepted by ACM SIGKDD'21
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Graph neural networks (GNNs) have recently gained much attention for node and graph classification tasks on graph-structured data. However, multiple recent works showed that an attacker can easily make GNNs predict incorrectly via perturbing the graph structure, i.e., adding or deleting edges in the graph. We aim to ...
[ { "created": "Mon, 24 Aug 2020 21:39:10 GMT", "version": "v1" }, { "created": "Fri, 4 Jun 2021 02:34:29 GMT", "version": "v2" }, { "created": "Fri, 16 Jul 2021 01:54:43 GMT", "version": "v3" } ]
2021-07-19
[ [ "Wang", "Binghui", "" ], [ "Jia", "Jinyuan", "" ], [ "Cao", "Xiaoyu", "" ], [ "Gong", "Neil Zhenqiang", "" ] ]
Graph neural networks (GNNs) have recently gained much attention for node and graph classification tasks on graph-structured data. However, multiple recent works showed that an attacker can easily make GNNs predict incorrectly via perturbing the graph structure, i.e., adding or deleting edges in the graph. We aim to de...
2307.16651
Yu Wu
Yu Wu, Dimitris Spathis, Hong Jia, Ignacio Perez-Pozuelo, Tomas Gonzales, Soren Brage, Nicholas Wareham, Cecilia Mascolo
UDAMA: Unsupervised Domain Adaptation through Multi-discriminator Adversarial Training with Noisy Labels Improves Cardio-fitness Prediction
Accepted at Machine Learning for Healthcare (MLHC) 2023
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep learning models have shown great promise in various healthcare monitoring applications. However, most healthcare datasets with high-quality (gold-standard) labels are small-scale, as directly collecting ground truth is often costly and time-consuming. As a result, models developed and validated on small-scale da...
[ { "created": "Mon, 31 Jul 2023 13:31:53 GMT", "version": "v1" } ]
2023-08-01
[ [ "Wu", "Yu", "" ], [ "Spathis", "Dimitris", "" ], [ "Jia", "Hong", "" ], [ "Perez-Pozuelo", "Ignacio", "" ], [ "Gonzales", "Tomas", "" ], [ "Brage", "Soren", "" ], [ "Wareham", "Nicholas", "" ], [ "M...
Deep learning models have shown great promise in various healthcare monitoring applications. However, most healthcare datasets with high-quality (gold-standard) labels are small-scale, as directly collecting ground truth is often costly and time-consuming. As a result, models developed and validated on small-scale data...
2403.14614
Yuning Cui
Yuning Cui and Syed Waqas Zamir and Salman Khan and Alois Knoll and Mubarak Shah and Fahad Shahbaz Khan
AdaIR: Adaptive All-in-One Image Restoration via Frequency Mining and Modulation
28 pages,15 figures
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the image acquisition process, various forms of degradation, including noise, haze, and rain, are frequently introduced. These degradations typically arise from the inherent limitations of cameras or unfavorable ambient conditions. To recover clean images from degraded versions, numerous specialized restoration me...
[ { "created": "Thu, 21 Mar 2024 17:58:14 GMT", "version": "v1" } ]
2024-03-22
[ [ "Cui", "Yuning", "" ], [ "Zamir", "Syed Waqas", "" ], [ "Khan", "Salman", "" ], [ "Knoll", "Alois", "" ], [ "Shah", "Mubarak", "" ], [ "Khan", "Fahad Shahbaz", "" ] ]
In the image acquisition process, various forms of degradation, including noise, haze, and rain, are frequently introduced. These degradations typically arise from the inherent limitations of cameras or unfavorable ambient conditions. To recover clean images from degraded versions, numerous specialized restoration meth...
2202.02524
Harichandana B S S
Harichandana B S S, Vibhav Agarwal, Sourav Ghosh, Gopi Ramena, Sumit Kumar and Barath Raj Kandur Raja
PrivPAS: A real time Privacy-Preserving AI System and applied ethics
Accepted at 16th IEEE International Conference on Semantic Computing (ICSC), January 26-28, 2022 [update: Best Paper candidate at ICSC 2022]
2022 IEEE 16th International Conference on Semantic Computing (ICSC), Laguna Hills, CA, USA, 2022, pp. 9-16
10.1109/ICSC52841.2022.00010
null
cs.CV cs.CR
http://creativecommons.org/licenses/by-nc-nd/4.0/
With 3.78 billion social media users worldwide in 2021 (48% of the human population), almost 3 billion images are shared daily. At the same time, a consistent evolution of smartphone cameras has led to a photography explosion with 85% of all new pictures being captured using smartphones. However, lately, there has be...
[ { "created": "Sat, 5 Feb 2022 09:52:54 GMT", "version": "v1" }, { "created": "Tue, 8 Feb 2022 14:23:15 GMT", "version": "v2" } ]
2022-04-05
[ [ "S", "Harichandana B S", "" ], [ "Agarwal", "Vibhav", "" ], [ "Ghosh", "Sourav", "" ], [ "Ramena", "Gopi", "" ], [ "Kumar", "Sumit", "" ], [ "Raja", "Barath Raj Kandur", "" ] ]
With 3.78 billion social media users worldwide in 2021 (48% of the human population), almost 3 billion images are shared daily. At the same time, a consistent evolution of smartphone cameras has led to a photography explosion with 85% of all new pictures being captured using smartphones. However, lately, there has been...
1510.05860
Ya-Feng Liu
Ya-Feng Liu
Dynamic Spectrum Management: A Complete Complexity Characterization
The paper has been accepted for publication in IEEE Transactions on Information Theory
null
null
null
cs.IT cs.CC math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Consider a multi-user multi-carrier communication system where multiple users share multiple discrete subcarriers. To achieve high spectrum efficiency, the users in the system must choose their transmit power dynamically in response to fast channel fluctuations. Assuming perfect channel state information, two formula...
[ { "created": "Tue, 20 Oct 2015 12:24:35 GMT", "version": "v1" }, { "created": "Sat, 29 Oct 2016 00:26:26 GMT", "version": "v2" } ]
2016-11-01
[ [ "Liu", "Ya-Feng", "" ] ]
Consider a multi-user multi-carrier communication system where multiple users share multiple discrete subcarriers. To achieve high spectrum efficiency, the users in the system must choose their transmit power dynamically in response to fast channel fluctuations. Assuming perfect channel state information, two formulati...
2408.07191
Jonas Linkerh\"agner
Jonas Linkerh\"agner, Cheng Shi, Ivan Dokmani\'c
Joint Graph Rewiring and Feature Denoising via Spectral Resonance
null
null
null
null
cs.LG cs.SI stat.ML
http://creativecommons.org/licenses/by/4.0/
Graph neural networks (GNNs) take as input the graph structure and the feature vectors associated with the nodes. Both contain noisy information about the labels. Here we propose joint denoising and rewiring (JDR)--an algorithm to jointly denoise the graph structure and features, which can improve the performance of ...
[ { "created": "Tue, 13 Aug 2024 20:16:11 GMT", "version": "v1" } ]
2024-08-15
[ [ "Linkerhägner", "Jonas", "" ], [ "Shi", "Cheng", "" ], [ "Dokmanić", "Ivan", "" ] ]
Graph neural networks (GNNs) take as input the graph structure and the feature vectors associated with the nodes. Both contain noisy information about the labels. Here we propose joint denoising and rewiring (JDR)--an algorithm to jointly denoise the graph structure and features, which can improve the performance of an...
2201.04402
Ekrem \c{C}etinkaya
Ekrem \c{C}etinkaya and Minh Nguyen and Christian Timmerer
MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural Networks
8 pages, 3 figures
MMM 2022: MultiMedia Modeling pp 465-472
10.1007/978-3-030-98355-0_40
null
cs.CV cs.MM
http://creativecommons.org/licenses/by-nc-nd/4.0/
Deep neural network (DNN) based approaches have been intensively studied to improve video quality thanks to their fast advancement in recent years. These approaches are designed mainly for desktop devices due to their high computational cost. However, with the increasing performance of mobile devices in recent years,...
[ { "created": "Wed, 12 Jan 2022 10:38:04 GMT", "version": "v1" } ]
2022-03-22
[ [ "Çetinkaya", "Ekrem", "" ], [ "Nguyen", "Minh", "" ], [ "Timmerer", "Christian", "" ] ]
Deep neural network (DNN) based approaches have been intensively studied to improve video quality thanks to their fast advancement in recent years. These approaches are designed mainly for desktop devices due to their high computational cost. However, with the increasing performance of mobile devices in recent years, i...
1908.08332
Luis Cruz
Luis Cruz, Rui Abreu, John Grundy, Li Li, Xin Xia
Do Energy-oriented Changes Hinder Maintainability?
International Conference on Software Maintenance and Evolution - ICSME 2019
null
null
null
cs.SE cs.PF
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Energy efficiency is a crucial quality requirement for mobile applications. However, improving energy efficiency is far from trivial as developers lack the knowledge and tools to aid in this activity. In this paper we study the impact of changes to improve energy efficiency on the maintainability of Android applicati...
[ { "created": "Thu, 22 Aug 2019 12:21:08 GMT", "version": "v1" } ]
2019-08-29
[ [ "Cruz", "Luis", "" ], [ "Abreu", "Rui", "" ], [ "Grundy", "John", "" ], [ "Li", "Li", "" ], [ "Xia", "Xin", "" ] ]
Energy efficiency is a crucial quality requirement for mobile applications. However, improving energy efficiency is far from trivial as developers lack the knowledge and tools to aid in this activity. In this paper we study the impact of changes to improve energy efficiency on the maintainability of Android application...
1403.2508
Rajib Das
Sunirmal Khatua, Preetam K. Sur, Rajib K. Das and Nandini Mukherjee
Heuristic-based Optimal Resource Provisioning in Application-centric Cloud
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Cloud Service Providers (CSPs) adapt different pricing models for their offered services. Some of the models are suitable for short term requirement while others may be suitable for the Cloud Service User's (CSU) long term requirement. In this paper, we look at the problem of finding the amount of resources to be res...
[ { "created": "Tue, 11 Mar 2014 09:07:16 GMT", "version": "v1" } ]
2014-03-12
[ [ "Khatua", "Sunirmal", "" ], [ "Sur", "Preetam K.", "" ], [ "Das", "Rajib K.", "" ], [ "Mukherjee", "Nandini", "" ] ]
Cloud Service Providers (CSPs) adapt different pricing models for their offered services. Some of the models are suitable for short term requirement while others may be suitable for the Cloud Service User's (CSU) long term requirement. In this paper, we look at the problem of finding the amount of resources to be reser...
1211.3719
Athanasios Lioumpas S.
Athanasios S. Lioumpas, Petros S. Bithas, Angeliki Alexiou
Partitioning of Distributed MIMO Systems based on Overhead Considerations
IEEE Wireless Communications Letters
null
10.1109/WCL.2013.072913.130449
null
cs.NI cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Distributed-Multiple Input Multiple Output (DMIMO) networks is a promising enabler to address the challenges of high traffic demand in future wireless networks. A limiting factor that is directly related to the performance of these systems is the overhead signaling required for distributing data and control informati...
[ { "created": "Thu, 15 Nov 2012 20:21:29 GMT", "version": "v1" }, { "created": "Fri, 16 Nov 2012 17:18:49 GMT", "version": "v2" }, { "created": "Sun, 21 Jul 2013 19:49:23 GMT", "version": "v3" } ]
2016-11-18
[ [ "Lioumpas", "Athanasios S.", "" ], [ "Bithas", "Petros S.", "" ], [ "Alexiou", "Angeliki", "" ] ]
Distributed-Multiple Input Multiple Output (DMIMO) networks is a promising enabler to address the challenges of high traffic demand in future wireless networks. A limiting factor that is directly related to the performance of these systems is the overhead signaling required for distributing data and control information...
2006.12779
Francesco Cicala
Francesco Cicala, Luca Bortolussi
Density-embedding layers: a general framework for adaptive receptive fields
13 pages, 2 figures, submitted to NeurIPS 2020
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The effectiveness and performance of artificial neural networks, particularly for visual tasks, depends in crucial ways on the receptive field of neurons. The receptive field itself depends on the interplay between several architectural aspects, including sparsity, pooling, and activation functions. In recent literat...
[ { "created": "Tue, 23 Jun 2020 06:09:16 GMT", "version": "v1" }, { "created": "Mon, 6 Jul 2020 07:36:24 GMT", "version": "v2" } ]
2020-07-07
[ [ "Cicala", "Francesco", "" ], [ "Bortolussi", "Luca", "" ] ]
The effectiveness and performance of artificial neural networks, particularly for visual tasks, depends in crucial ways on the receptive field of neurons. The receptive field itself depends on the interplay between several architectural aspects, including sparsity, pooling, and activation functions. In recent literatur...
2303.14828
Dina Bashkirova
Dina Bashkirova, Samarth Mishra, Diala Lteif, Piotr Teterwak, Donghyun Kim, Fadi Alladkani, James Akl, Berk Calli, Sarah Adel Bargal, Kate Saenko, Daehan Kim, Minseok Seo, YoungJin Jeon, Dong-Geol Choi, Shahaf Ettedgui, Raja Giryes, Shady Abu-Hussein, Binhui Xie, Shuang Li
VisDA 2022 Challenge: Domain Adaptation for Industrial Waste Sorting
Proceedings of Machine Learning Research
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Label-efficient and reliable semantic segmentation is essential for many real-life applications, especially for industrial settings with high visual diversity, such as waste sorting. In industrial waste sorting, one of the biggest challenges is the extreme diversity of the input stream depending on factors like the l...
[ { "created": "Sun, 26 Mar 2023 21:38:38 GMT", "version": "v1" } ]
2023-03-28
[ [ "Bashkirova", "Dina", "" ], [ "Mishra", "Samarth", "" ], [ "Lteif", "Diala", "" ], [ "Teterwak", "Piotr", "" ], [ "Kim", "Donghyun", "" ], [ "Alladkani", "Fadi", "" ], [ "Akl", "James", "" ], [ "Cal...
Label-efficient and reliable semantic segmentation is essential for many real-life applications, especially for industrial settings with high visual diversity, such as waste sorting. In industrial waste sorting, one of the biggest challenges is the extreme diversity of the input stream depending on factors like the loc...
1405.2199
Madhumangal Pal Dr.
Madhumangal Pal and Anita Pal
Scheduling algorithm to select $k$ optimal programme slots in television channels: A graph theoretic approach
25 pages
null
null
null
cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, it is shown that all programmes of all television channels can be modelled as an interval graph. The programme slots are taken as the vertices of the graph and if the time duration of two {programme slots} have non-empty intersection, the corresponding vertices are considered to be connected by an edge...
[ { "created": "Fri, 9 May 2014 10:29:10 GMT", "version": "v1" } ]
2014-05-12
[ [ "Pal", "Madhumangal", "" ], [ "Pal", "Anita", "" ] ]
In this paper, it is shown that all programmes of all television channels can be modelled as an interval graph. The programme slots are taken as the vertices of the graph and if the time duration of two {programme slots} have non-empty intersection, the corresponding vertices are considered to be connected by an edge. ...
2103.10107
Luk\'a\v{s} Picek
Luk\'a\v{s} Picek, Milan \v{S}ulc, Ji\v{r}\'i Matas, Jacob Heilmann-Clausen, Thomas S. Jeppesen, Thomas L{\ae}ss{\o}e, Tobias Fr{\o}slev
Danish Fungi 2020 -- Not Just Another Image Recognition Dataset
null
null
10.1109/WACV51458.2022.00334
null
cs.CV eess.IV
http://creativecommons.org/licenses/by/4.0/
We introduce a novel fine-grained dataset and benchmark, the Danish Fungi 2020 (DF20). The dataset, constructed from observations submitted to the Atlas of Danish Fungi, is unique in its taxonomy-accurate class labels, small number of errors, highly unbalanced long-tailed class distribution, rich observation metadata...
[ { "created": "Thu, 18 Mar 2021 09:33:11 GMT", "version": "v1" }, { "created": "Fri, 19 Mar 2021 12:15:47 GMT", "version": "v2" }, { "created": "Mon, 22 Mar 2021 08:43:04 GMT", "version": "v3" }, { "created": "Fri, 20 Aug 2021 14:35:44 GMT", "version": "v4" } ]
2022-06-13
[ [ "Picek", "Lukáš", "" ], [ "Šulc", "Milan", "" ], [ "Matas", "Jiří", "" ], [ "Heilmann-Clausen", "Jacob", "" ], [ "Jeppesen", "Thomas S.", "" ], [ "Læssøe", "Thomas", "" ], [ "Frøslev", "Tobias", "" ] ]
We introduce a novel fine-grained dataset and benchmark, the Danish Fungi 2020 (DF20). The dataset, constructed from observations submitted to the Atlas of Danish Fungi, is unique in its taxonomy-accurate class labels, small number of errors, highly unbalanced long-tailed class distribution, rich observation metadata, ...
1605.00398
Akshay Khatri
Akshay Khatri, Sankalp Kolhe, Nupur Giri
Dynamic Address Allocation Algorithm for Mobile Ad hoc Networks
null
null
null
null
cs.NI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A Mobile Ad hoc network (MANET) consists of nodes which use multi-hop communication to establish connection between nodes. Traditional infrastructure based systems use a centralized architecture for address allocation. However, this is not possible in Ad hoc networks due to their dynamic structure. Many schemes have ...
[ { "created": "Mon, 2 May 2016 09:10:44 GMT", "version": "v1" } ]
2016-05-03
[ [ "Khatri", "Akshay", "" ], [ "Kolhe", "Sankalp", "" ], [ "Giri", "Nupur", "" ] ]
A Mobile Ad hoc network (MANET) consists of nodes which use multi-hop communication to establish connection between nodes. Traditional infrastructure based systems use a centralized architecture for address allocation. However, this is not possible in Ad hoc networks due to their dynamic structure. Many schemes have be...
2404.14406
Kartik Narayan
Kartik Narayan, Vishal M. Patel
Hyp-OC: Hyperbolic One Class Classification for Face Anti-Spoofing
Accepted in FG2024, Project Page - https://kartik-3004.github.io/hyp-oc/
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Face recognition technology has become an integral part of modern security systems and user authentication processes. However, these systems are vulnerable to spoofing attacks and can easily be circumvented. Most prior research in face anti-spoofing (FAS) approaches it as a two-class classification task where models ...
[ { "created": "Mon, 22 Apr 2024 17:59:18 GMT", "version": "v1" } ]
2024-04-23
[ [ "Narayan", "Kartik", "" ], [ "Patel", "Vishal M.", "" ] ]
Face recognition technology has become an integral part of modern security systems and user authentication processes. However, these systems are vulnerable to spoofing attacks and can easily be circumvented. Most prior research in face anti-spoofing (FAS) approaches it as a two-class classification task where models ar...
2212.07618
Mengnan Shi
Bohao Li, Chang Liu, Mengnan Shi, Xiaozhong Chen, Xiangyang Ji, Qixiang Ye
Proposal Distribution Calibration for Few-Shot Object Detection
This paper is under review in IEEE TNNLS
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Adapting object detectors learned with sufficient supervision to novel classes under low data regimes is charming yet challenging. In few-shot object detection (FSOD), the two-step training paradigm is widely adopted to mitigate the severe sample imbalance, i.e., holistic pre-training on base classes, then partial fi...
[ { "created": "Thu, 15 Dec 2022 05:09:11 GMT", "version": "v1" } ]
2022-12-16
[ [ "Li", "Bohao", "" ], [ "Liu", "Chang", "" ], [ "Shi", "Mengnan", "" ], [ "Chen", "Xiaozhong", "" ], [ "Ji", "Xiangyang", "" ], [ "Ye", "Qixiang", "" ] ]
Adapting object detectors learned with sufficient supervision to novel classes under low data regimes is charming yet challenging. In few-shot object detection (FSOD), the two-step training paradigm is widely adopted to mitigate the severe sample imbalance, i.e., holistic pre-training on base classes, then partial fine...
1612.08845
Toni Heidenreich
Toni Heidenreich
The formal-logical characterisation of lies, deception, and associated notions
Literature review prepared as a student at King's College London
null
null
null
cs.LO cs.AI cs.MA
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Defining various dishonest notions in a formal way is a key step to enable intelligent agents to act in untrustworthy environments. This review evaluates the literature for this topic by looking at formal definitions based on modal logic as well as other formal approaches. Criteria from philosophical groundwork is us...
[ { "created": "Wed, 28 Dec 2016 10:35:05 GMT", "version": "v1" } ]
2016-12-30
[ [ "Heidenreich", "Toni", "" ] ]
Defining various dishonest notions in a formal way is a key step to enable intelligent agents to act in untrustworthy environments. This review evaluates the literature for this topic by looking at formal definitions based on modal logic as well as other formal approaches. Criteria from philosophical groundwork is used...
2006.11456
Abiola Osho
Abiola Osho and Ethan Tucker and George Amariucai
Implicit Crowdsourcing for Identifying Abusive Behavior in Online Social Networks
null
null
null
null
cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The increased use of online social networks for the dissemination of information comes with the misuse of the internet for cyberbullying, cybercrime, spam, vandalism, amongst other things. To proactively identify abuse in the networks, we propose a model to identify abusive posts by crowdsourcing. The crowdsourcing p...
[ { "created": "Sat, 20 Jun 2020 01:14:30 GMT", "version": "v1" } ]
2020-06-23
[ [ "Osho", "Abiola", "" ], [ "Tucker", "Ethan", "" ], [ "Amariucai", "George", "" ] ]
The increased use of online social networks for the dissemination of information comes with the misuse of the internet for cyberbullying, cybercrime, spam, vandalism, amongst other things. To proactively identify abuse in the networks, we propose a model to identify abusive posts by crowdsourcing. The crowdsourcing par...
2001.09046
Bart Smets
Bart Smets, Jim Portegies, Erik Bekkers, Remco Duits
PDE-based Group Equivariant Convolutional Neural Networks
27 pages, 18 figures. v2 changes: - mentioned KerCNNs - added section Generalization of G-CNNs - clarification that the experiments utilized automatic differentiation and SGD. v3 changes: - streamlined theoretical framework - formulation and proof Thm.1 & 2 - expanded experiments. v4 changes: typos in Prop.5 an...
null
10.1007/s10851-022-01114-x
null
cs.LG cs.CV math.DG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a PDE-based framework that generalizes Group equivariant Convolutional Neural Networks (G-CNNs). In this framework, a network layer is seen as a set of PDE-solvers where geometrically meaningful PDE-coefficients become the layer's trainable weights. Formulating our PDEs on homogeneous spaces allows these n...
[ { "created": "Fri, 24 Jan 2020 15:00:46 GMT", "version": "v1" }, { "created": "Mon, 9 Mar 2020 14:16:16 GMT", "version": "v2" }, { "created": "Mon, 12 Jul 2021 07:56:22 GMT", "version": "v3" }, { "created": "Sat, 24 Jul 2021 11:14:06 GMT", "version": "v4" }, { "cr...
2022-08-24
[ [ "Smets", "Bart", "" ], [ "Portegies", "Jim", "" ], [ "Bekkers", "Erik", "" ], [ "Duits", "Remco", "" ] ]
We present a PDE-based framework that generalizes Group equivariant Convolutional Neural Networks (G-CNNs). In this framework, a network layer is seen as a set of PDE-solvers where geometrically meaningful PDE-coefficients become the layer's trainable weights. Formulating our PDEs on homogeneous spaces allows these net...
1304.0954
Marko Horvat
Marko Horvat, Anton Grbin, Gordan Gledec
Labeling and Retrieval of Emotionally-Annotated Images using WordNet
16 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1302.2223
International Journal of Knowledge-Based and Intelligent Engineering Systems, Vol. 17, No. 2, pp. 157-166, 2013
null
null
cs.IR cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Repositories of images with semantic and emotion content descriptions are valuable tools in many areas such as Affective Computing and Human-Computer Interaction, but they are also important in the development of multimodal searchable online databases. Ever growing number of image documents available on the Internet ...
[ { "created": "Wed, 3 Apr 2013 13:58:56 GMT", "version": "v1" }, { "created": "Fri, 10 Jan 2014 23:27:00 GMT", "version": "v2" } ]
2017-12-06
[ [ "Horvat", "Marko", "" ], [ "Grbin", "Anton", "" ], [ "Gledec", "Gordan", "" ] ]
Repositories of images with semantic and emotion content descriptions are valuable tools in many areas such as Affective Computing and Human-Computer Interaction, but they are also important in the development of multimodal searchable online databases. Ever growing number of image documents available on the Internet co...
2006.14683
Itzik Malkiel
Itzik Malkiel, Lior Wolf
MTAdam: Automatic Balancing of Multiple Training Loss Terms
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
When training neural models, it is common to combine multiple loss terms. The balancing of these terms requires considerable human effort and is computationally demanding. Moreover, the optimal trade-off between the loss term can change as training progresses, especially for adversarial terms. In this work, we genera...
[ { "created": "Thu, 25 Jun 2020 20:27:27 GMT", "version": "v1" } ]
2020-06-29
[ [ "Malkiel", "Itzik", "" ], [ "Wolf", "Lior", "" ] ]
When training neural models, it is common to combine multiple loss terms. The balancing of these terms requires considerable human effort and is computationally demanding. Moreover, the optimal trade-off between the loss term can change as training progresses, especially for adversarial terms. In this work, we generali...
1907.02841
Li Qiang
Wenxiang Zuo, Qiang Li, Xianming Liu
Depth Restoration: A fast low-rank matrix completion via dual-graph regularization
The paper will be added more experiments. The main idea of the paper needs to be revamped. Please withdraw the paper
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
As a real scenes sensing approach, depth information obtains the widespread applications. However, resulting from the restriction of depth sensing technology, the depth map captured in practice usually suffers terrible noise and missing values at plenty of pixels. In this paper, we propose a fast low-rank matrix comp...
[ { "created": "Fri, 5 Jul 2019 14:09:31 GMT", "version": "v1" }, { "created": "Mon, 28 Oct 2019 11:06:38 GMT", "version": "v2" }, { "created": "Thu, 31 Oct 2019 13:14:36 GMT", "version": "v3" }, { "created": "Wed, 8 Jan 2020 09:29:44 GMT", "version": "v4" } ]
2020-01-09
[ [ "Zuo", "Wenxiang", "" ], [ "Li", "Qiang", "" ], [ "Liu", "Xianming", "" ] ]
As a real scenes sensing approach, depth information obtains the widespread applications. However, resulting from the restriction of depth sensing technology, the depth map captured in practice usually suffers terrible noise and missing values at plenty of pixels. In this paper, we propose a fast low-rank matrix comple...
2004.10495
Dong Wang
Dong Wang, Xiaoqian Qin, Fengyi Song, Li Cheng
Stabilizing Training of Generative Adversarial Nets via Langevin Stein Variational Gradient Descent
null
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Generative adversarial networks (GANs), famous for the capability of learning complex underlying data distribution, are however known to be tricky in the training process, which would probably result in mode collapse or performance deterioration. Current approaches of dealing with GANs' issues almost utilize some pra...
[ { "created": "Wed, 22 Apr 2020 11:20:04 GMT", "version": "v1" } ]
2020-04-23
[ [ "Wang", "Dong", "" ], [ "Qin", "Xiaoqian", "" ], [ "Song", "Fengyi", "" ], [ "Cheng", "Li", "" ] ]
Generative adversarial networks (GANs), famous for the capability of learning complex underlying data distribution, are however known to be tricky in the training process, which would probably result in mode collapse or performance deterioration. Current approaches of dealing with GANs' issues almost utilize some pract...
2112.13050
Susmit Agrawal
K. Ram Prabhakar, Susmit Agrawal, R. Venkatesh Babu
Self-Gated Memory Recurrent Network for Efficient Scalable HDR Deghosting
12 pages
IEEE Transactions on Computational Imaging (Volume 7, 2021) 1228-1239
10.1109/TCI.2021.3112920
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We propose a novel recurrent network-based HDR deghosting method for fusing arbitrary length dynamic sequences. The proposed method uses convolutional and recurrent architectures to generate visually pleasing, ghosting-free HDR images. We introduce a new recurrent cell architecture, namely Self-Gated Memory (SGM) cel...
[ { "created": "Fri, 24 Dec 2021 12:36:33 GMT", "version": "v1" } ]
2021-12-28
[ [ "Prabhakar", "K. Ram", "" ], [ "Agrawal", "Susmit", "" ], [ "Babu", "R. Venkatesh", "" ] ]
We propose a novel recurrent network-based HDR deghosting method for fusing arbitrary length dynamic sequences. The proposed method uses convolutional and recurrent architectures to generate visually pleasing, ghosting-free HDR images. We introduce a new recurrent cell architecture, namely Self-Gated Memory (SGM) cell,...
1904.10522
Hyunsu Cho
Theodore Vasiloudis, Hyunsu Cho, Henrik Bostr\"om
Block-distributed Gradient Boosted Trees
SIGIR 2019
null
null
null
cs.LG cs.IR stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The Gradient Boosted Tree (GBT) algorithm is one of the most popular machine learning algorithms used in production, for tasks that include Click-Through Rate (CTR) prediction and learning-to-rank. To deal with the massive datasets available today, many distributed GBT methods have been proposed. However, they all as...
[ { "created": "Tue, 23 Apr 2019 20:10:36 GMT", "version": "v1" }, { "created": "Tue, 28 May 2019 19:32:35 GMT", "version": "v2" } ]
2019-05-30
[ [ "Vasiloudis", "Theodore", "" ], [ "Cho", "Hyunsu", "" ], [ "Boström", "Henrik", "" ] ]
The Gradient Boosted Tree (GBT) algorithm is one of the most popular machine learning algorithms used in production, for tasks that include Click-Through Rate (CTR) prediction and learning-to-rank. To deal with the massive datasets available today, many distributed GBT methods have been proposed. However, they all assu...
2306.09547
Daria Reshetova
Daria Reshetova, Wei-Ning Chen, Ayfer \"Ozg\"ur
Training generative models from privatized data
null
null
null
null
cs.LG cs.CR cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Local differential privacy is a powerful method for privacy-preserving data collection. In this paper, we develop a framework for training Generative Adversarial Networks (GANs) on differentially privatized data. We show that entropic regularization of optimal transport - a popular regularization method in the litera...
[ { "created": "Thu, 15 Jun 2023 23:28:45 GMT", "version": "v1" }, { "created": "Fri, 1 Mar 2024 01:54:15 GMT", "version": "v2" } ]
2024-03-04
[ [ "Reshetova", "Daria", "" ], [ "Chen", "Wei-Ning", "" ], [ "Özgür", "Ayfer", "" ] ]
Local differential privacy is a powerful method for privacy-preserving data collection. In this paper, we develop a framework for training Generative Adversarial Networks (GANs) on differentially privatized data. We show that entropic regularization of optimal transport - a popular regularization method in the literatu...
1809.01301
Pamela Shapiro
Pamela Shapiro and Kevin Duh
BPE and CharCNNs for Translation of Morphology: A Cross-Lingual Comparison and Analysis
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Neural Machine Translation (NMT) in low-resource settings and of morphologically rich languages is made difficult in part by data sparsity of vocabulary words. Several methods have been used to help reduce this sparsity, notably Byte-Pair Encoding (BPE) and a character-based CNN layer (charCNN). However, the charCNN ...
[ { "created": "Wed, 5 Sep 2018 02:26:09 GMT", "version": "v1" }, { "created": "Sat, 8 Sep 2018 23:36:53 GMT", "version": "v2" } ]
2018-09-11
[ [ "Shapiro", "Pamela", "" ], [ "Duh", "Kevin", "" ] ]
Neural Machine Translation (NMT) in low-resource settings and of morphologically rich languages is made difficult in part by data sparsity of vocabulary words. Several methods have been used to help reduce this sparsity, notably Byte-Pair Encoding (BPE) and a character-based CNN layer (charCNN). However, the charCNN ha...
cs/0109012
Michael Geist
Michael Geist
Is There a There There: Towards Greater Certainty for Internet Jurisdiction
29th TPRC Conference, 2001
16 (3) Berkeley Tech. LJ (forthcoming 2001)
null
TPRC-2001-017
cs.CY
null
The unique challenge presented by the Internet is that compliance with local laws is rarely sufficient to assure a business that it has limited its exposure to legal risk. The paper identifies why the challenge of adequately accounting for the legal risk arising from Internet jurisdiction has been aggravated in recen...
[ { "created": "Tue, 11 Sep 2001 03:22:25 GMT", "version": "v1" } ]
2007-05-23
[ [ "Geist", "Michael", "" ] ]
The unique challenge presented by the Internet is that compliance with local laws is rarely sufficient to assure a business that it has limited its exposure to legal risk. The paper identifies why the challenge of adequately accounting for the legal risk arising from Internet jurisdiction has been aggravated in recent ...
2303.06611
Weilin Lin
Weilin Lin, Xiangyu Zhao, Yejing Wang, Yuanshao Zhu, Wanyu Wang
AutoDenoise: Automatic Data Instance Denoising for Recommendations
9 pages, 4 figures, 5 tables, conference
null
10.1145/3543507.3583339
null
cs.IR
http://creativecommons.org/licenses/by-nc-nd/4.0/
Historical user-item interaction datasets are essential in training modern recommender systems for predicting user preferences. However, the arbitrary user behaviors in most recommendation scenarios lead to a large volume of noisy data instances being recorded, which cannot fully represent their true interests. While...
[ { "created": "Sun, 12 Mar 2023 08:36:15 GMT", "version": "v1" } ]
2023-03-14
[ [ "Lin", "Weilin", "" ], [ "Zhao", "Xiangyu", "" ], [ "Wang", "Yejing", "" ], [ "Zhu", "Yuanshao", "" ], [ "Wang", "Wanyu", "" ] ]
Historical user-item interaction datasets are essential in training modern recommender systems for predicting user preferences. However, the arbitrary user behaviors in most recommendation scenarios lead to a large volume of noisy data instances being recorded, which cannot fully represent their true interests. While a...
2301.07849
Giovanni Viglietta
Giuseppe A. Di Luna and Giovanni Viglietta
Efficient Computation in Congested Anonymous Dynamic Networks
26 pages, 2 figures
null
null
null
cs.DC cs.DM
http://creativecommons.org/licenses/by/4.0/
An anonymous dynamic network is a network of indistinguishable processes whose communication links may appear or disappear unpredictably over time. Previous research has shown that deterministically computing an arbitrary function of a multiset of input values given to these processes takes only a linear number of co...
[ { "created": "Thu, 19 Jan 2023 02:11:47 GMT", "version": "v1" }, { "created": "Sat, 6 May 2023 15:22:15 GMT", "version": "v2" }, { "created": "Tue, 5 Sep 2023 03:03:07 GMT", "version": "v3" }, { "created": "Sat, 29 Jun 2024 12:53:12 GMT", "version": "v4" } ]
2024-07-02
[ [ "Di Luna", "Giuseppe A.", "" ], [ "Viglietta", "Giovanni", "" ] ]
An anonymous dynamic network is a network of indistinguishable processes whose communication links may appear or disappear unpredictably over time. Previous research has shown that deterministically computing an arbitrary function of a multiset of input values given to these processes takes only a linear number of comm...
2407.18813
Chenming Wu
Zhe Xin and Yufeng Yue and Liangjun Zhang and Chenming Wu
HERO-SLAM: Hybrid Enhanced Robust Optimization of Neural SLAM
Accepted to ICRA 2024
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Simultaneous Localization and Mapping (SLAM) is a fundamental task in robotics, driving numerous applications such as autonomous driving and virtual reality. Recent progress on neural implicit SLAM has shown encouraging and impressive results. However, the robustness of neural SLAM, particularly in challenging or dat...
[ { "created": "Fri, 26 Jul 2024 15:22:14 GMT", "version": "v1" } ]
2024-07-29
[ [ "Xin", "Zhe", "" ], [ "Yue", "Yufeng", "" ], [ "Zhang", "Liangjun", "" ], [ "Wu", "Chenming", "" ] ]
Simultaneous Localization and Mapping (SLAM) is a fundamental task in robotics, driving numerous applications such as autonomous driving and virtual reality. Recent progress on neural implicit SLAM has shown encouraging and impressive results. However, the robustness of neural SLAM, particularly in challenging or data-...
cs/0702083
Serebrenik Alexander
Alexander Serebrenik, Tom Schrijvers, Bart Demoen
Improving Prolog programs: Refactoring for Prolog
To appear in Theory and Practice of Logic Programming (TPLP)
null
null
2006-1
cs.SE
null
Refactoring is an established technique from the object-oriented (OO) programming community to restructure code: it aims at improving software readability, maintainability and extensibility. Although refactoring is not tied to the OO-paradigm in particular, its ideas have not been applied to Logic Programming until n...
[ { "created": "Wed, 14 Feb 2007 09:53:37 GMT", "version": "v1" } ]
2007-05-23
[ [ "Serebrenik", "Alexander", "" ], [ "Schrijvers", "Tom", "" ], [ "Demoen", "Bart", "" ] ]
Refactoring is an established technique from the object-oriented (OO) programming community to restructure code: it aims at improving software readability, maintainability and extensibility. Although refactoring is not tied to the OO-paradigm in particular, its ideas have not been applied to Logic Programming until now...
2306.01116
Julien Launay
Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra Cojocaru, Alessandro Cappelli, Hamza Alobeidli, Baptiste Pannier, Ebtesam Almazrouei, Julien Launay
The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only
null
null
null
null
cs.CL cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Large language models are commonly trained on a mixture of filtered web data and curated high-quality corpora, such as social media conversations, books, or technical papers. This curation process is believed to be necessary to produce performant models with broad zero-shot generalization abilities. However, as large...
[ { "created": "Thu, 1 Jun 2023 20:03:56 GMT", "version": "v1" } ]
2023-06-05
[ [ "Penedo", "Guilherme", "" ], [ "Malartic", "Quentin", "" ], [ "Hesslow", "Daniel", "" ], [ "Cojocaru", "Ruxandra", "" ], [ "Cappelli", "Alessandro", "" ], [ "Alobeidli", "Hamza", "" ], [ "Pannier", "Baptiste", ...
Large language models are commonly trained on a mixture of filtered web data and curated high-quality corpora, such as social media conversations, books, or technical papers. This curation process is believed to be necessary to produce performant models with broad zero-shot generalization abilities. However, as larger ...
1701.00416
Tom Mens
Alexandre Decan, Mathieu Goeminne, Tom Mens
On the Interaction of Relational Database Access Technologies in Open Source Java Projects
Postproceeding of the SATTOSE 2015 Research Seminar on Advanced Tools and Techniques for Software Evolution. To be published in CEUR.WS workshop proceedings (2017)
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This article presents an empirical study of how the use of relational database access technologies in open source Java projects evolves over time. Our observations may be useful to project managers to make more informed decisions on which technologies to introduce into an existing project and when. We selected 2,457 ...
[ { "created": "Mon, 2 Jan 2017 15:07:36 GMT", "version": "v1" } ]
2017-01-03
[ [ "Decan", "Alexandre", "" ], [ "Goeminne", "Mathieu", "" ], [ "Mens", "Tom", "" ] ]
This article presents an empirical study of how the use of relational database access technologies in open source Java projects evolves over time. Our observations may be useful to project managers to make more informed decisions on which technologies to introduce into an existing project and when. We selected 2,457 Ja...
1401.3556
Sergiy Vorobyov A.
Alex E. Geyer, Reza Nikjah, Sergiy A. Vorobyov, and Norman C. Beaulieu
Equivalent Codes, Optimality, and Performance Analysis of OSTBC: Textbook Study
33 pages, 12 figures, 5 tables, full size journal paper, Finished in Oct. 2009, Unpublished
IEEE Trans. Communications, vol. 63, no. 8, pp. 2912-2923, Aug. 2015
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An equivalent model for a multi-input multi-output (MIMO) communication system with orthogonal space-time block codes (OSTBCs) is proposed based on a newly revealed connection between OSTBCs and Euclidean codes. Examples of distance spectra, signal constellations, and signal coordinate diagrams of Euclidean codes equ...
[ { "created": "Wed, 15 Jan 2014 12:07:56 GMT", "version": "v1" } ]
2016-03-03
[ [ "Geyer", "Alex E.", "" ], [ "Nikjah", "Reza", "" ], [ "Vorobyov", "Sergiy A.", "" ], [ "Beaulieu", "Norman C.", "" ] ]
An equivalent model for a multi-input multi-output (MIMO) communication system with orthogonal space-time block codes (OSTBCs) is proposed based on a newly revealed connection between OSTBCs and Euclidean codes. Examples of distance spectra, signal constellations, and signal coordinate diagrams of Euclidean codes equiv...
1910.05268
Asier Mujika
Florian Meier and Asier Mujika and Marcelo Matheus Gauy and Angelika Steger
Improving Gradient Estimation in Evolutionary Strategies With Past Descent Directions
null
null
null
null
cs.NE cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Evolutionary Strategies (ES) are known to be an effective black-box optimization technique for deep neural networks when the true gradients cannot be computed, such as in Reinforcement Learning. We continue a recent line of research that uses surrogate gradients to improve the gradient estimation of ES. We propose a ...
[ { "created": "Fri, 11 Oct 2019 16:00:39 GMT", "version": "v1" } ]
2019-10-14
[ [ "Meier", "Florian", "" ], [ "Mujika", "Asier", "" ], [ "Gauy", "Marcelo Matheus", "" ], [ "Steger", "Angelika", "" ] ]
Evolutionary Strategies (ES) are known to be an effective black-box optimization technique for deep neural networks when the true gradients cannot be computed, such as in Reinforcement Learning. We continue a recent line of research that uses surrogate gradients to improve the gradient estimation of ES. We propose a no...
2204.03479
Zuzana Jel\v{c}icov\'a
Zuzana Jel\v{c}icov\'a and Marian Verhelst
Delta Keyword Transformer: Bringing Transformers to the Edge through Dynamically Pruned Multi-Head Self-Attention
null
null
null
null
cs.CL cs.LG
http://creativecommons.org/licenses/by-sa/4.0/
Multi-head self-attention forms the core of Transformer networks. However, their quadratically growing complexity with respect to the input sequence length impedes their deployment on resource-constrained edge devices. We address this challenge by proposing a dynamic pruning method, which exploits the temporal stabil...
[ { "created": "Sun, 20 Mar 2022 20:59:13 GMT", "version": "v1" } ]
2022-04-08
[ [ "Jelčicová", "Zuzana", "" ], [ "Verhelst", "Marian", "" ] ]
Multi-head self-attention forms the core of Transformer networks. However, their quadratically growing complexity with respect to the input sequence length impedes their deployment on resource-constrained edge devices. We address this challenge by proposing a dynamic pruning method, which exploits the temporal stabilit...
2404.03081
Hans De Sterck
Yifan Qu, Oliver Krzysik, Hans De Sterck, Omer Ege Kara
First-order PDES for Graph Neural Networks: Advection And Burgers Equation Models
null
null
null
null
cs.LG cs.NA math.NA
http://creativecommons.org/licenses/by/4.0/
Graph Neural Networks (GNNs) have established themselves as the preferred methodology in a multitude of domains, ranging from computer vision to computational biology, especially in contexts where data inherently conform to graph structures. While many existing methods have endeavored to model GNNs using various tech...
[ { "created": "Wed, 3 Apr 2024 21:47:02 GMT", "version": "v1" } ]
2024-04-05
[ [ "Qu", "Yifan", "" ], [ "Krzysik", "Oliver", "" ], [ "De Sterck", "Hans", "" ], [ "Kara", "Omer Ege", "" ] ]
Graph Neural Networks (GNNs) have established themselves as the preferred methodology in a multitude of domains, ranging from computer vision to computational biology, especially in contexts where data inherently conform to graph structures. While many existing methods have endeavored to model GNNs using various techni...
1705.02038
Jiazi Zhang
Jiazi Zhang and Zhigang Chu and Lalitha Sankar and Oliver Kosut
False Data Injection Attacks on Phasor Measurements That Bypass Low-rank Decomposition
6 pages, 4 figures, submitted to 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm)
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies the vulnerability of phasor measurement units (PMUs) to false data injection (FDI) attacks. Prior work demonstrated that unobservable FDI attacks that can bypass traditional bad data detectors based on measurement residuals can be identified by detector based on low-rank decomposition (LD). In this...
[ { "created": "Thu, 4 May 2017 22:33:04 GMT", "version": "v1" } ]
2017-05-08
[ [ "Zhang", "Jiazi", "" ], [ "Chu", "Zhigang", "" ], [ "Sankar", "Lalitha", "" ], [ "Kosut", "Oliver", "" ] ]
This paper studies the vulnerability of phasor measurement units (PMUs) to false data injection (FDI) attacks. Prior work demonstrated that unobservable FDI attacks that can bypass traditional bad data detectors based on measurement residuals can be identified by detector based on low-rank decomposition (LD). In this w...
1907.12430
Alexander V Terekhov
Alexander V. Terekhov and J. Kevin O'Regan
Learning abstract perceptual notions: the example of space
arXiv admin note: text overlap with arXiv:1308.2124
null
null
null
cs.AI q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Humans are extremely swift learners. We are able to grasp highly abstract notions, whether they come from art perception or pure mathematics. Current machine learning techniques demonstrate astonishing results in extracting patterns in information. Yet the abstract notions we possess are more than just statistical pa...
[ { "created": "Wed, 24 Jul 2019 17:57:54 GMT", "version": "v1" } ]
2019-07-30
[ [ "Terekhov", "Alexander V.", "" ], [ "O'Regan", "J. Kevin", "" ] ]
Humans are extremely swift learners. We are able to grasp highly abstract notions, whether they come from art perception or pure mathematics. Current machine learning techniques demonstrate astonishing results in extracting patterns in information. Yet the abstract notions we possess are more than just statistical patt...
2203.05735
Quoc Nguyen
Huu-Quoc Nguyen, Tien-Dung Nguyen, Van-Nam Pham, Xuan-Qui Pham, Quang-Thai Ngo, Eui-Nam Huh
An Efficient Video Streaming Architecture with QoS Control for Virtual Desktop Infrastructure in Cloud Computing
26 pages, Multimedia Tools and Applications Journal
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
In virtual desktop infrastructure (VDI) environments, the remote display protocol has a big responsibility to transmit video data from a data center-hosted desktop to the endpoint. The protocol must ensure a high level of client perceived end-to-end quality of service (QoS) under heavy work load conditions. Each remo...
[ { "created": "Fri, 11 Mar 2022 03:22:11 GMT", "version": "v1" } ]
2022-03-14
[ [ "Nguyen", "Huu-Quoc", "" ], [ "Nguyen", "Tien-Dung", "" ], [ "Pham", "Van-Nam", "" ], [ "Pham", "Xuan-Qui", "" ], [ "Ngo", "Quang-Thai", "" ], [ "Huh", "Eui-Nam", "" ] ]
In virtual desktop infrastructure (VDI) environments, the remote display protocol has a big responsibility to transmit video data from a data center-hosted desktop to the endpoint. The protocol must ensure a high level of client perceived end-to-end quality of service (QoS) under heavy work load conditions. Each remote...
2008.07689
Yaorui Zhang
Yitong Deng, Yaorui Zhang, Xingzhe He, Shuqi Yang, Yunjin Tong, Michael Zhang, Daniel DiPietro, Bo Zhu
Soft Multicopter Control using Neural Dynamics Identification
null
null
null
null
cs.RO cs.GR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Dynamic control of a soft-body robot to deliver complex behaviors with low-dimensional actuation inputs is challenging. In this paper, we present a computational approach to automatically generate versatile, underactuated control policies that drives soft-bodied machines with complicated structures and nonlinear dyna...
[ { "created": "Tue, 18 Aug 2020 01:38:18 GMT", "version": "v1" }, { "created": "Mon, 31 Aug 2020 19:37:18 GMT", "version": "v2" }, { "created": "Wed, 2 Sep 2020 09:44:15 GMT", "version": "v3" }, { "created": "Tue, 1 Dec 2020 09:11:02 GMT", "version": "v4" } ]
2020-12-02
[ [ "Deng", "Yitong", "" ], [ "Zhang", "Yaorui", "" ], [ "He", "Xingzhe", "" ], [ "Yang", "Shuqi", "" ], [ "Tong", "Yunjin", "" ], [ "Zhang", "Michael", "" ], [ "DiPietro", "Daniel", "" ], [ "Zhu", ...
Dynamic control of a soft-body robot to deliver complex behaviors with low-dimensional actuation inputs is challenging. In this paper, we present a computational approach to automatically generate versatile, underactuated control policies that drives soft-bodied machines with complicated structures and nonlinear dynami...
1206.4126
Yousuf Ibrahim Khan
Yousuf Ibrahim Khan
Image based Cryptography from a distance
null
null
null
null
cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
An information is a message which is received and understood. Information can be sent one person to another over a long range but the process of sending information must be done in a secure way especially in case of a private message. Mathematicians and Engineers have historically relied on different algorithmic tech...
[ { "created": "Tue, 19 Jun 2012 06:02:32 GMT", "version": "v1" } ]
2012-06-20
[ [ "Khan", "Yousuf Ibrahim", "" ] ]
An information is a message which is received and understood. Information can be sent one person to another over a long range but the process of sending information must be done in a secure way especially in case of a private message. Mathematicians and Engineers have historically relied on different algorithmic techni...
1908.01650
Chunming Tang
Sihem Mesnager, Yanfeng Qi, Hongming Ru, Chunming Tang
Minimal linear codes from characteristic functions
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Minimal linear codes have interesting applications in secret sharing schemes and secure two-party computation. This paper uses characteristic functions of some subsets of $\mathbb{F}_q$ to construct minimal linear codes. By properties of characteristic functions, we can obtain more minimal binary linear codes from kn...
[ { "created": "Mon, 5 Aug 2019 14:40:23 GMT", "version": "v1" }, { "created": "Wed, 20 Nov 2019 11:45:55 GMT", "version": "v2" } ]
2019-11-21
[ [ "Mesnager", "Sihem", "" ], [ "Qi", "Yanfeng", "" ], [ "Ru", "Hongming", "" ], [ "Tang", "Chunming", "" ] ]
Minimal linear codes have interesting applications in secret sharing schemes and secure two-party computation. This paper uses characteristic functions of some subsets of $\mathbb{F}_q$ to construct minimal linear codes. By properties of characteristic functions, we can obtain more minimal binary linear codes from know...
2202.04076
Kun Wang
Kun Wang, Jingyi Wang, Christopher M. Poskitt, Xiangxiang Chen, Jun Sun, and Peng Cheng
K-ST: A Formal Executable Semantics of the Structured Text Language for PLCs
Accepted by IEEE Transactions on Software Engineering
IEEE Trans. Software Eng., 2023
10.1109/TSE.2023.3315292
null
cs.PL cs.SE
http://creativecommons.org/licenses/by/4.0/
Programmable Logic Controllers (PLCs) are responsible for automating process control in many industrial systems (e.g. in manufacturing and public infrastructure), and thus it is critical to ensure that they operate correctly and safely. The majority of PLCs are programmed in languages such as Structured Text (ST). Ho...
[ { "created": "Tue, 8 Feb 2022 17:34:08 GMT", "version": "v1" }, { "created": "Tue, 12 Sep 2023 02:05:17 GMT", "version": "v2" } ]
2023-09-19
[ [ "Wang", "Kun", "" ], [ "Wang", "Jingyi", "" ], [ "Poskitt", "Christopher M.", "" ], [ "Chen", "Xiangxiang", "" ], [ "Sun", "Jun", "" ], [ "Cheng", "Peng", "" ] ]
Programmable Logic Controllers (PLCs) are responsible for automating process control in many industrial systems (e.g. in manufacturing and public infrastructure), and thus it is critical to ensure that they operate correctly and safely. The majority of PLCs are programmed in languages such as Structured Text (ST). Howe...
2306.17804
Darren Strash
Anthony Hevia, Benjamin Kallus, Summer McClintic, Samantha Reisner, Darren Strash, and Johnathan Wilson
Solving Edge Clique Cover Exactly via Synergistic Data Reduction
22 pages, 5 figures, 6 tables, accepted at the 31st Annual European Symposium on Algorithms (ESA 2023)
null
null
null
cs.DS
http://creativecommons.org/licenses/by/4.0/
The edge clique cover (ECC) problem -- where the goal is to find a minimum cardinality set of cliques that cover all the edges of a graph -- is a classic NP-hard problem that has received much attention from both the theoretical and experimental algorithms communities. While small sparse graphs can be solved exactly ...
[ { "created": "Fri, 30 Jun 2023 17:06:04 GMT", "version": "v1" }, { "created": "Tue, 4 Jul 2023 18:04:39 GMT", "version": "v2" } ]
2023-07-06
[ [ "Hevia", "Anthony", "" ], [ "Kallus", "Benjamin", "" ], [ "McClintic", "Summer", "" ], [ "Reisner", "Samantha", "" ], [ "Strash", "Darren", "" ], [ "Wilson", "Johnathan", "" ] ]
The edge clique cover (ECC) problem -- where the goal is to find a minimum cardinality set of cliques that cover all the edges of a graph -- is a classic NP-hard problem that has received much attention from both the theoretical and experimental algorithms communities. While small sparse graphs can be solved exactly vi...
2209.14468
Yiheng Shen
Kamesh Munagala, Yiheng Shen, Kangning Wang
Auditing for Core Stability in Participatory Budgeting
accepted by the 18th Conference on Web and Internet Economics (WINE 2022)
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the participatory budgeting problem where each of $n$ voters specifies additive utilities over $m$ candidate projects with given sizes, and the goal is to choose a subset of projects (i.e., a committee) with total size at most $k$. Participatory budgeting mathematically generalizes multiwinner elections, ...
[ { "created": "Wed, 28 Sep 2022 23:13:06 GMT", "version": "v1" } ]
2022-09-30
[ [ "Munagala", "Kamesh", "" ], [ "Shen", "Yiheng", "" ], [ "Wang", "Kangning", "" ] ]
We consider the participatory budgeting problem where each of $n$ voters specifies additive utilities over $m$ candidate projects with given sizes, and the goal is to choose a subset of projects (i.e., a committee) with total size at most $k$. Participatory budgeting mathematically generalizes multiwinner elections, an...
2408.01196
Zhang Shanfan
Shanfan Zhang, Xiaoting Shen, Zhan Bu
Game Theory Based Community-Aware Opinion Dynamics
36 pages, 15figures
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Examining the mechanisms underlying the formation and evolution of opinions within real-world social systems, which consist of numerous individuals, can provide valuable insights for effective social functioning and informed business decision making. The focus of our study is on the dynamics of opinions inside a netw...
[ { "created": "Fri, 2 Aug 2024 11:24:56 GMT", "version": "v1" } ]
2024-08-05
[ [ "Zhang", "Shanfan", "" ], [ "Shen", "Xiaoting", "" ], [ "Bu", "Zhan", "" ] ]
Examining the mechanisms underlying the formation and evolution of opinions within real-world social systems, which consist of numerous individuals, can provide valuable insights for effective social functioning and informed business decision making. The focus of our study is on the dynamics of opinions inside a networ...
1912.12204
Boyi Liu
Boyi Liu, Lujia Wang, Ming Liu, Cheng-Zhong Xu
Federated Imitation Learning: A Novel Framework for Cloud Robotic Systems with Heterogeneous Sensor Data
arXiv admin note: substantial text overlap with arXiv:1909.00895
null
null
null
cs.RO cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Humans are capable of learning a new behavior by observing others to perform the skill. Similarly, robots can also implement this by imitation learning. Furthermore, if with external guidance, humans can master the new behavior more efficiently. So, how can robots achieve this? To address the issue, we present a nove...
[ { "created": "Tue, 24 Dec 2019 11:23:23 GMT", "version": "v1" } ]
2019-12-30
[ [ "Liu", "Boyi", "" ], [ "Wang", "Lujia", "" ], [ "Liu", "Ming", "" ], [ "Xu", "Cheng-Zhong", "" ] ]
Humans are capable of learning a new behavior by observing others to perform the skill. Similarly, robots can also implement this by imitation learning. Furthermore, if with external guidance, humans can master the new behavior more efficiently. So, how can robots achieve this? To address the issue, we present a novel ...
2311.15512
Dong Yonghao
Yonghao Dong, Le Wang, Sanpin Zhou, Gang Hua, and Changyin Sun
Sparse Pedestrian Character Learning for Trajectory Prediction
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Pedestrian trajectory prediction in a first-person view has recently attracted much attention due to its importance in autonomous driving. Recent work utilizes pedestrian character information, \textit{i.e.}, action and appearance, to improve the learned trajectory embedding and achieves state-of-the-art performance....
[ { "created": "Mon, 27 Nov 2023 03:15:48 GMT", "version": "v1" } ]
2023-11-28
[ [ "Dong", "Yonghao", "" ], [ "Wang", "Le", "" ], [ "Zhou", "Sanpin", "" ], [ "Hua", "Gang", "" ], [ "Sun", "Changyin", "" ] ]
Pedestrian trajectory prediction in a first-person view has recently attracted much attention due to its importance in autonomous driving. Recent work utilizes pedestrian character information, \textit{i.e.}, action and appearance, to improve the learned trajectory embedding and achieves state-of-the-art performance. H...
2209.09653
Tonio Ball
Maryna Kapitonova, Philipp Kellmeyer, Simon Vogt and Tonio Ball
A Framework for Preserving Privacy and Cybersecurity in Brain-Computer Interfacing Applications
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-nd/4.0/
Brain-Computer Interfaces (BCIs) comprise a rapidly evolving field of technology with the potential of far-reaching impact in domains ranging from medical over industrial to artistic, gaming, and military. Today, these emerging BCI applications are typically still at early technology readiness levels, but because BCI...
[ { "created": "Mon, 19 Sep 2022 15:45:13 GMT", "version": "v1" } ]
2022-09-21
[ [ "Kapitonova", "Maryna", "" ], [ "Kellmeyer", "Philipp", "" ], [ "Vogt", "Simon", "" ], [ "Ball", "Tonio", "" ] ]
Brain-Computer Interfaces (BCIs) comprise a rapidly evolving field of technology with the potential of far-reaching impact in domains ranging from medical over industrial to artistic, gaming, and military. Today, these emerging BCI applications are typically still at early technology readiness levels, but because BCIs ...
2112.14890
Ke Wang
Jiayi Wang, Ke Wang, Boxing Chen, Yu Zhao, Weihua Luo, and Yuqi Zhang
QEMind: Alibaba's Submission to the WMT21 Quality Estimation Shared Task
Winner of WMT 2021 QE shared task 1
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Quality Estimation, as a crucial step of quality control for machine translation, has been explored for years. The goal is to investigate automatic methods for estimating the quality of machine translation results without reference translations. In this year's WMT QE shared task, we utilize the large-scale XLM-Robert...
[ { "created": "Thu, 30 Dec 2021 02:27:29 GMT", "version": "v1" } ]
2022-01-03
[ [ "Wang", "Jiayi", "" ], [ "Wang", "Ke", "" ], [ "Chen", "Boxing", "" ], [ "Zhao", "Yu", "" ], [ "Luo", "Weihua", "" ], [ "Zhang", "Yuqi", "" ] ]
Quality Estimation, as a crucial step of quality control for machine translation, has been explored for years. The goal is to investigate automatic methods for estimating the quality of machine translation results without reference translations. In this year's WMT QE shared task, we utilize the large-scale XLM-Roberta ...
2008.05297
Umberto Straccia
Franco Alberto Cardillo and Umberto Straccia
Fuzzy OWL-BOOST: Learning Fuzzy Concept Inclusions via Real-Valued Boosting
null
null
10.1016/j.fss.2021.07.002
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
OWL ontologies are nowadays a quite popular way to describe structured knowledge in terms of classes, relations among classes and class instances. In this paper, given a target class T of an OWL ontology, we address the problem of learning fuzzy concept inclusion axioms that describe sufficient conditions for being a...
[ { "created": "Mon, 3 Aug 2020 15:19:31 GMT", "version": "v1" }, { "created": "Fri, 26 Mar 2021 07:10:04 GMT", "version": "v2" } ]
2022-03-10
[ [ "Cardillo", "Franco Alberto", "" ], [ "Straccia", "Umberto", "" ] ]
OWL ontologies are nowadays a quite popular way to describe structured knowledge in terms of classes, relations among classes and class instances. In this paper, given a target class T of an OWL ontology, we address the problem of learning fuzzy concept inclusion axioms that describe sufficient conditions for being an ...
2305.09281
Fatma Elsafoury
Fatma Elsafoury, Gavin Abercrombie
On the Origins of Bias in NLP through the Lens of the Jim Code
10 pages
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
In this paper, we trace the biases in current natural language processing (NLP) models back to their origins in racism, sexism, and homophobia over the last 500 years. We review literature from critical race theory, gender studies, data ethics, and digital humanities studies, and summarize the origins of bias in NLP ...
[ { "created": "Tue, 16 May 2023 08:37:13 GMT", "version": "v1" } ]
2023-05-17
[ [ "Elsafoury", "Fatma", "" ], [ "Abercrombie", "Gavin", "" ] ]
In this paper, we trace the biases in current natural language processing (NLP) models back to their origins in racism, sexism, and homophobia over the last 500 years. We review literature from critical race theory, gender studies, data ethics, and digital humanities studies, and summarize the origins of bias in NLP mo...
2305.11059
Muhammad Husnain Mubarik
Ramakrishna Kanungo, Swamynathan Siva, Nathaniel Bleier, Muhammad Husnain Mubarik, Lav Varshney and Rakesh Kumar
Understanding Interactions Between Chip Architecture and Uncertainties in Semiconductor Supply and Demand
null
null
null
null
cs.AR cs.CE
http://creativecommons.org/licenses/by/4.0/
Mitigating losses from supply and demand volatility in the semiconductor supply chain and market has traditionally been cast as a logistics and forecasting problem. We investigate how the architecture of a family of chips influences how it is affected by supply and demand uncertainties. We observe that semiconductor ...
[ { "created": "Wed, 10 May 2023 18:07:34 GMT", "version": "v1" } ]
2023-05-19
[ [ "Kanungo", "Ramakrishna", "" ], [ "Siva", "Swamynathan", "" ], [ "Bleier", "Nathaniel", "" ], [ "Mubarik", "Muhammad Husnain", "" ], [ "Varshney", "Lav", "" ], [ "Kumar", "Rakesh", "" ] ]
Mitigating losses from supply and demand volatility in the semiconductor supply chain and market has traditionally been cast as a logistics and forecasting problem. We investigate how the architecture of a family of chips influences how it is affected by supply and demand uncertainties. We observe that semiconductor su...
2204.02464
Stefan Bosse
Stefan Bosse
BeeTS: Smart Distributed Sensor Tuple Spaces combined with Agents using Bluetooth and IP Broadcasting
null
null
null
null
cs.NI cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most Internet-of-Things (IoT) devices and smart sensors are connected via the Internet using IP communication driectly accessed by a server that collect sensor information periodically or event-based. Although, Internet access is widely available, there are places that are not covered and WLAN and mobile cell communi...
[ { "created": "Tue, 5 Apr 2022 19:47:21 GMT", "version": "v1" } ]
2022-04-07
[ [ "Bosse", "Stefan", "" ] ]
Most Internet-of-Things (IoT) devices and smart sensors are connected via the Internet using IP communication driectly accessed by a server that collect sensor information periodically or event-based. Although, Internet access is widely available, there are places that are not covered and WLAN and mobile cell communica...
1901.06212
Dmitry Kangin
Dmitry Kangin and Nicolas Pugeault
On-Policy Trust Region Policy Optimisation with Replay Buffers
null
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Building upon the recent success of deep reinforcement learning methods, we investigate the possibility of on-policy reinforcement learning improvement by reusing the data from several consecutive policies. On-policy methods bring many benefits, such as ability to evaluate each resulting policy. However, they usually...
[ { "created": "Fri, 18 Jan 2019 13:09:18 GMT", "version": "v1" } ]
2019-01-21
[ [ "Kangin", "Dmitry", "" ], [ "Pugeault", "Nicolas", "" ] ]
Building upon the recent success of deep reinforcement learning methods, we investigate the possibility of on-policy reinforcement learning improvement by reusing the data from several consecutive policies. On-policy methods bring many benefits, such as ability to evaluate each resulting policy. However, they usually d...
2306.06791
Shugang Hao
Shugang Hao and Lingjie Duan
To Save Mobile Crowdsourcing from Cheap-talk: A Game Theoretic Learning Approach
null
null
null
null
cs.GT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Today mobile crowdsourcing platforms invite users to provide anonymous reviews about service experiences, yet many reviews are found biased to be extremely positive or negative. The existing methods find it difficult to learn from biased reviews to infer the actual service state, as the state can also be extreme and ...
[ { "created": "Sun, 11 Jun 2023 22:07:18 GMT", "version": "v1" }, { "created": "Fri, 29 Dec 2023 05:10:44 GMT", "version": "v2" } ]
2024-01-01
[ [ "Hao", "Shugang", "" ], [ "Duan", "Lingjie", "" ] ]
Today mobile crowdsourcing platforms invite users to provide anonymous reviews about service experiences, yet many reviews are found biased to be extremely positive or negative. The existing methods find it difficult to learn from biased reviews to infer the actual service state, as the state can also be extreme and th...
2210.14638
Marcin Pilipczuk
Daniel Lokshtanov and Marcin Pilipczuk and Micha{\l} Pilipczuk and Saket Saurabh
Fixed-parameter tractability of Graph Isomorphism in graphs with an excluded minor
Part I of a full version of a paper accepted at STOC 2022
null
null
null
cs.DS cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We prove that Graph Isomorphism and Canonization in graphs excluding a fixed graph $H$ as a minor can be solved by an algorithm working in time $f(H)\cdot n^{O(1)}$, where $f$ is some function. In other words, we show that these problems are fixed-parameter tractable when parameterized by the size of the excluded min...
[ { "created": "Wed, 26 Oct 2022 11:32:55 GMT", "version": "v1" } ]
2022-10-27
[ [ "Lokshtanov", "Daniel", "" ], [ "Pilipczuk", "Marcin", "" ], [ "Pilipczuk", "Michał", "" ], [ "Saurabh", "Saket", "" ] ]
We prove that Graph Isomorphism and Canonization in graphs excluding a fixed graph $H$ as a minor can be solved by an algorithm working in time $f(H)\cdot n^{O(1)}$, where $f$ is some function. In other words, we show that these problems are fixed-parameter tractable when parameterized by the size of the excluded minor...
1911.02423
Dorjan Hitaj
Fabio De Gaspari, Dorjan Hitaj, Giulio Pagnotta, Lorenzo De Carli, Luigi V. Mancini
The Naked Sun: Malicious Cooperation Between Benign-Looking Processes
15 pages, 6 figures, 4 tables
null
null
null
cs.CR cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent progress in machine learning has generated promising results in behavioral malware detection. Behavioral modeling identifies malicious processes via features derived by their runtime behavior. Behavioral features hold great promise as they are intrinsically related to the functioning of each malware, and are t...
[ { "created": "Wed, 6 Nov 2019 15:04:07 GMT", "version": "v1" } ]
2019-11-07
[ [ "De Gaspari", "Fabio", "" ], [ "Hitaj", "Dorjan", "" ], [ "Pagnotta", "Giulio", "" ], [ "De Carli", "Lorenzo", "" ], [ "Mancini", "Luigi V.", "" ] ]
Recent progress in machine learning has generated promising results in behavioral malware detection. Behavioral modeling identifies malicious processes via features derived by their runtime behavior. Behavioral features hold great promise as they are intrinsically related to the functioning of each malware, and are the...
cs/0609009
Virginia Vassilevska
Virginia Vassilevska, Ryan Williams and Raphael Yuster
Finding heaviest H-subgraphs in real weighted graphs, with applications
23 pages
null
null
null
cs.DS cs.DM
null
For a graph G with real weights assigned to the vertices (edges), the MAX H-SUBGRAPH problem is to find an H-subgraph of G with maximum total weight, if one exists. The all-pairs MAX H-SUBGRAPH problem is to find for every pair of vertices u,v, a maximum H-subgraph containing both u and v, if one exists. Our main res...
[ { "created": "Mon, 4 Sep 2006 08:08:00 GMT", "version": "v1" } ]
2007-05-23
[ [ "Vassilevska", "Virginia", "" ], [ "Williams", "Ryan", "" ], [ "Yuster", "Raphael", "" ] ]
For a graph G with real weights assigned to the vertices (edges), the MAX H-SUBGRAPH problem is to find an H-subgraph of G with maximum total weight, if one exists. The all-pairs MAX H-SUBGRAPH problem is to find for every pair of vertices u,v, a maximum H-subgraph containing both u and v, if one exists. Our main resul...
0912.1216
Ying Cui
Ying Cui, Vincent K.N.Lau and Rui Wang
Distributive Subband Allocation, Power and Rate Control for Relay-Assisted OFDMA Cellular System with Imperfect System State Knowledge
11 pages, 8 figures
null
null
null
cs.NI cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we consider distributive subband, power and rate allocation for a two-hop transmission in an orthogonal frequency-division multiple-access (OFDMA) cellular system with fixed relays which operate in decode-and-forward strategy. We take into account of system fairness by considering weighted sum goodput ...
[ { "created": "Mon, 7 Dec 2009 12:30:57 GMT", "version": "v1" } ]
2009-12-08
[ [ "Cui", "Ying", "" ], [ "Lau", "Vincent K. N.", "" ], [ "Wang", "Rui", "" ] ]
In this paper, we consider distributive subband, power and rate allocation for a two-hop transmission in an orthogonal frequency-division multiple-access (OFDMA) cellular system with fixed relays which operate in decode-and-forward strategy. We take into account of system fairness by considering weighted sum goodput as...
1810.03717
Judy Hanwen Shen
Judy Hanwen Shen, Matthias Hofer, Bjarke Felbo, Roger Levy
Comparing Models of Associative Meaning: An Empirical Investigation of Reference in Simple Language Games
Conference on Computational Natural Language Learning (CoNLL) 2018
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Simple reference games are of central theoretical and empirical importance in the study of situated language use. Although language provides rich, compositional truth-conditional semantics to facilitate reference, speakers and listeners may sometimes lack the overall lexical and cognitive resources to guarantee succe...
[ { "created": "Mon, 8 Oct 2018 21:51:44 GMT", "version": "v1" } ]
2018-10-10
[ [ "Shen", "Judy Hanwen", "" ], [ "Hofer", "Matthias", "" ], [ "Felbo", "Bjarke", "" ], [ "Levy", "Roger", "" ] ]
Simple reference games are of central theoretical and empirical importance in the study of situated language use. Although language provides rich, compositional truth-conditional semantics to facilitate reference, speakers and listeners may sometimes lack the overall lexical and cognitive resources to guarantee success...