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2009.09343
Yang Mingming
Tinghuai Ma, Mingming Yang, Huan Rong, Yurong Qian, Yurong Qian, Yuan Tian, NajlaAl-Nabhan
Dual-path CNN with Max Gated block for Text-Based Person Re-identification
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Text-based person re-identification(Re-id) is an important task in video surveillance, which consists of retrieving the corresponding person's image given a textual description from a large gallery of images. It is difficult to directly match visual contents with the textual descriptions due to the modality heterogen...
[ { "created": "Sun, 20 Sep 2020 03:33:29 GMT", "version": "v1" } ]
2020-09-22
[ [ "Ma", "Tinghuai", "" ], [ "Yang", "Mingming", "" ], [ "Rong", "Huan", "" ], [ "Qian", "Yurong", "" ], [ "Qian", "Yurong", "" ], [ "Tian", "Yuan", "" ], [ "NajlaAl-Nabhan", "", "" ] ]
Text-based person re-identification(Re-id) is an important task in video surveillance, which consists of retrieving the corresponding person's image given a textual description from a large gallery of images. It is difficult to directly match visual contents with the textual descriptions due to the modality heterogenei...
1910.13539
Zhipeng Xu
Yidan Zhang, Xiaolong Huang, Zhipeng Xu and Yuefan Deng
A Structured Table of Graphs with Symmetries and Other Special Properties
add details about automorphism group
null
10.3390/sym12010002
Symmetry 2020, 12(1), 2
cs.DM math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We organize a table of regular graphs with minimal diameters and minimal mean path lengths, large bisection widths and high degrees of symmetries, obtained by enumerations on supercomputers. These optimal graphs, many of which are newly discovered, may find wide applications, for example, in design of network topolog...
[ { "created": "Tue, 29 Oct 2019 21:17:38 GMT", "version": "v1" }, { "created": "Fri, 1 Nov 2019 20:39:46 GMT", "version": "v2" }, { "created": "Tue, 5 Nov 2019 21:06:02 GMT", "version": "v3" }, { "created": "Wed, 11 Dec 2019 05:49:23 GMT", "version": "v4" } ]
2019-12-30
[ [ "Zhang", "Yidan", "" ], [ "Huang", "Xiaolong", "" ], [ "Xu", "Zhipeng", "" ], [ "Deng", "Yuefan", "" ] ]
We organize a table of regular graphs with minimal diameters and minimal mean path lengths, large bisection widths and high degrees of symmetries, obtained by enumerations on supercomputers. These optimal graphs, many of which are newly discovered, may find wide applications, for example, in design of network topologie...
1407.0439
Haixia Liu
Haixia Liu, Raymond H. Chan, and Yuan Yao
Geometric Tight Frame based Stylometry for Art Authentication of van Gogh Paintings
14 pages, 13 figures
null
null
null
cs.LG cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper is about authenticating genuine van Gogh paintings from forgeries. The authentication process depends on two key steps: feature extraction and outlier detection. In this paper, a geometric tight frame and some simple statistics of the tight frame coefficients are used to extract features from the paintings...
[ { "created": "Wed, 2 Jul 2014 01:55:37 GMT", "version": "v1" }, { "created": "Sat, 13 Sep 2014 00:53:16 GMT", "version": "v2" }, { "created": "Tue, 13 Jan 2015 07:20:12 GMT", "version": "v3" } ]
2015-01-14
[ [ "Liu", "Haixia", "" ], [ "Chan", "Raymond H.", "" ], [ "Yao", "Yuan", "" ] ]
This paper is about authenticating genuine van Gogh paintings from forgeries. The authentication process depends on two key steps: feature extraction and outlier detection. In this paper, a geometric tight frame and some simple statistics of the tight frame coefficients are used to extract features from the paintings. ...
2207.09915
Nir Sochen
Nir Sochen
A note on the variation of geometric functionals
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Calculus of Variation combined with Differential Geometry as tools of modelling and solving problems in image processing and computer vision were introduced in the late 80's and the 90s of the 20th century. The beginning of an extensive work in these directions was marked by works such as Geodesic Active Contours (GA...
[ { "created": "Wed, 20 Jul 2022 14:02:57 GMT", "version": "v1" } ]
2022-07-21
[ [ "Sochen", "Nir", "" ] ]
Calculus of Variation combined with Differential Geometry as tools of modelling and solving problems in image processing and computer vision were introduced in the late 80's and the 90s of the 20th century. The beginning of an extensive work in these directions was marked by works such as Geodesic Active Contours (GAC)...
2311.02910
Yang Liu
Gianmarco Ipinze Tutuianu, Yang Liu, Ari Alam\"aki, Janne Kauttonen
Benchmarking Deep Facial Expression Recognition: An Extensive Protocol with Balanced Dataset in the Wild
* Equal contribution
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Facial expression recognition (FER) is a crucial part of human-computer interaction. Existing FER methods achieve high accuracy and generalization based on different open-source deep models and training approaches. However, the performance of these methods is not always good when encountering practical settings, whic...
[ { "created": "Mon, 6 Nov 2023 06:48:49 GMT", "version": "v1" } ]
2023-11-07
[ [ "Tutuianu", "Gianmarco Ipinze", "" ], [ "Liu", "Yang", "" ], [ "Alamäki", "Ari", "" ], [ "Kauttonen", "Janne", "" ] ]
Facial expression recognition (FER) is a crucial part of human-computer interaction. Existing FER methods achieve high accuracy and generalization based on different open-source deep models and training approaches. However, the performance of these methods is not always good when encountering practical settings, which ...
2305.14951
Jue Liu
Jue Liu
DSFFNet: Dual-Side Feature Fusion Network for 3D Pose Transfer
in Chinese language
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
To solve the problem of pose distortion in the forward propagation of pose features in existing methods, this pa-per proposes a Dual-Side Feature Fusion Network for pose transfer (DSFFNet). Firstly, a fixed-length pose code is extracted from the source mesh by a pose encoder and combined with the target vertices to f...
[ { "created": "Wed, 24 May 2023 09:42:08 GMT", "version": "v1" }, { "created": "Mon, 9 Oct 2023 08:57:38 GMT", "version": "v2" } ]
2023-10-10
[ [ "Liu", "Jue", "" ] ]
To solve the problem of pose distortion in the forward propagation of pose features in existing methods, this pa-per proposes a Dual-Side Feature Fusion Network for pose transfer (DSFFNet). Firstly, a fixed-length pose code is extracted from the source mesh by a pose encoder and combined with the target vertices to for...
2307.01465
Yunqing Zhao
Yunqing Zhao, Keshigeyan Chandrasegaran, Milad Abdollahzadeh, Chao Du, Tianyu Pang, Ruoteng Li, Henghui Ding, Ngai-Man Cheung
AdAM: Few-Shot Image Generation via Adaptation-Aware Kernel Modulation
32 pages, update additional information, discussion, and experimental sections compared to NeurIPS-22 version: arXiv:2210.16559. arXiv admin note: substantial text overlap with arXiv:2210.16559
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Few-shot image generation (FSIG) aims to learn to generate new and diverse images given few (e.g., 10) training samples. Recent work has addressed FSIG by leveraging a GAN pre-trained on a large-scale source domain and adapting it to the target domain with few target samples. Central to recent FSIG methods are knowle...
[ { "created": "Tue, 4 Jul 2023 03:56:43 GMT", "version": "v1" }, { "created": "Sat, 8 Jul 2023 06:24:52 GMT", "version": "v2" }, { "created": "Fri, 10 Nov 2023 13:00:10 GMT", "version": "v3" } ]
2023-11-14
[ [ "Zhao", "Yunqing", "" ], [ "Chandrasegaran", "Keshigeyan", "" ], [ "Abdollahzadeh", "Milad", "" ], [ "Du", "Chao", "" ], [ "Pang", "Tianyu", "" ], [ "Li", "Ruoteng", "" ], [ "Ding", "Henghui", "" ], [ ...
Few-shot image generation (FSIG) aims to learn to generate new and diverse images given few (e.g., 10) training samples. Recent work has addressed FSIG by leveraging a GAN pre-trained on a large-scale source domain and adapting it to the target domain with few target samples. Central to recent FSIG methods are knowledg...
1912.06688
Joerg Zimmermann
Kristina Enes, Hassan Errami, Moritz Wolter, Tim Krake, Bernhard Eberhardt, Andreas Weber, J\"org Zimmermann
Unsupervised and Generic Short-Term Anticipation of Human Body Motions
null
null
null
null
cs.LG cs.CV stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Various neural network based methods are capable of anticipating human body motions from data for a short period of time. What these methods lack are the interpretability and explainability of the network and its results. We propose to use Dynamic Mode Decomposition with delays to represent and anticipate human body ...
[ { "created": "Fri, 13 Dec 2019 20:13:36 GMT", "version": "v1" } ]
2019-12-17
[ [ "Enes", "Kristina", "" ], [ "Errami", "Hassan", "" ], [ "Wolter", "Moritz", "" ], [ "Krake", "Tim", "" ], [ "Eberhardt", "Bernhard", "" ], [ "Weber", "Andreas", "" ], [ "Zimmermann", "Jörg", "" ] ]
Various neural network based methods are capable of anticipating human body motions from data for a short period of time. What these methods lack are the interpretability and explainability of the network and its results. We propose to use Dynamic Mode Decomposition with delays to represent and anticipate human body mo...
1908.11628
Sagie Benaim
Sagie Benaim, Michael Khaitov, Tomer Galanti, Lior Wolf
Domain Intersection and Domain Difference
null
ICCV 2019
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a method for recovering the shared content between two visual domains as well as the content that is unique to each domain. This allows us to map from one domain to the other, in a way in which the content that is specific for the first domain is removed and the content that is specific for the second is i...
[ { "created": "Fri, 30 Aug 2019 10:08:43 GMT", "version": "v1" } ]
2019-09-02
[ [ "Benaim", "Sagie", "" ], [ "Khaitov", "Michael", "" ], [ "Galanti", "Tomer", "" ], [ "Wolf", "Lior", "" ] ]
We present a method for recovering the shared content between two visual domains as well as the content that is unique to each domain. This allows us to map from one domain to the other, in a way in which the content that is specific for the first domain is removed and the content that is specific for the second is imp...
2311.17307
Jiacong Mi
Hua Pu, Jiacong Mi, Shan Lu, Jieyue He
RoKEPG: RoBERTa and Knowledge Enhancement for Prescription Generation of Traditional Chinese Medicine
8 pages
null
null
null
cs.CL cs.AI
http://creativecommons.org/licenses/by/4.0/
Traditional Chinese medicine (TCM) prescription is the most critical form of TCM treatment, and uncovering the complex nonlinear relationship between symptoms and TCM is of great significance for clinical practice and assisting physicians in diagnosis and treatment. Although there have been some studies on TCM prescr...
[ { "created": "Wed, 29 Nov 2023 01:59:38 GMT", "version": "v1" } ]
2023-11-30
[ [ "Pu", "Hua", "" ], [ "Mi", "Jiacong", "" ], [ "Lu", "Shan", "" ], [ "He", "Jieyue", "" ] ]
Traditional Chinese medicine (TCM) prescription is the most critical form of TCM treatment, and uncovering the complex nonlinear relationship between symptoms and TCM is of great significance for clinical practice and assisting physicians in diagnosis and treatment. Although there have been some studies on TCM prescrip...
2007.08377
Simon Bernard
Simon Bernard, Hongliu Cao, Robert Sabourin, Laurent Heutte
Random Forest for Dissimilarity-based Multi-view Learning
Published in Handbook of Pattern Recognition and Computer Vision, 2020 (preprint)
null
10.1142/9789811211072_0007
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Many classification problems are naturally multi-view in the sense their data are described through multiple heterogeneous descriptions. For such tasks, dissimilarity strategies are effective ways to make the different descriptions comparable and to easily merge them, by (i) building intermediate dissimilarity repres...
[ { "created": "Thu, 16 Jul 2020 14:52:52 GMT", "version": "v1" } ]
2020-07-17
[ [ "Bernard", "Simon", "" ], [ "Cao", "Hongliu", "" ], [ "Sabourin", "Robert", "" ], [ "Heutte", "Laurent", "" ] ]
Many classification problems are naturally multi-view in the sense their data are described through multiple heterogeneous descriptions. For such tasks, dissimilarity strategies are effective ways to make the different descriptions comparable and to easily merge them, by (i) building intermediate dissimilarity represen...
2403.10123
Yuanhang Zhang
Yuanhang Zhang, Zhidi Lin, Yiyong Sun, Feng Yin, Carsten Fritsche
Regularization-Based Efficient Continual Learning in Deep State-Space Models
7 pages, 14 figures
null
null
null
cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep state-space models (DSSMs) have gained popularity in recent years due to their potent modeling capacity for dynamic systems. However, existing DSSM works are limited to single-task modeling, which requires retraining with historical task data upon revisiting a forepassed task. To address this limitation, we prop...
[ { "created": "Fri, 15 Mar 2024 09:14:18 GMT", "version": "v1" }, { "created": "Sat, 29 Jun 2024 23:01:10 GMT", "version": "v2" } ]
2024-07-02
[ [ "Zhang", "Yuanhang", "" ], [ "Lin", "Zhidi", "" ], [ "Sun", "Yiyong", "" ], [ "Yin", "Feng", "" ], [ "Fritsche", "Carsten", "" ] ]
Deep state-space models (DSSMs) have gained popularity in recent years due to their potent modeling capacity for dynamic systems. However, existing DSSM works are limited to single-task modeling, which requires retraining with historical task data upon revisiting a forepassed task. To address this limitation, we propos...
2401.05126
Teru Nagamori
Teru Nagamori, Sayaka Shiota, Hitoshi Kiya
Efficient Fine-Tuning with Domain Adaptation for Privacy-Preserving Vision Transformer
Accepted by APSIPA Transactions on Signal and Information Processing. arXiv admin note: substantial text overlap with arXiv:2309.02556
null
null
null
cs.CV cs.LG
http://creativecommons.org/licenses/by/4.0/
We propose a novel method for privacy-preserving deep neural networks (DNNs) with the Vision Transformer (ViT). The method allows us not only to train models and test with visually protected images but to also avoid the performance degradation caused from the use of encrypted images, whereas conventional methods cann...
[ { "created": "Wed, 10 Jan 2024 12:46:31 GMT", "version": "v1" }, { "created": "Fri, 9 Feb 2024 09:55:46 GMT", "version": "v2" } ]
2024-02-12
[ [ "Nagamori", "Teru", "" ], [ "Shiota", "Sayaka", "" ], [ "Kiya", "Hitoshi", "" ] ]
We propose a novel method for privacy-preserving deep neural networks (DNNs) with the Vision Transformer (ViT). The method allows us not only to train models and test with visually protected images but to also avoid the performance degradation caused from the use of encrypted images, whereas conventional methods cannot...
2211.09855
Yining Lu
Yining Lu, Jingxi Qiu, Gaurav Gupta
ProtSi: Prototypical Siamese Network with Data Augmentation for Few-Shot Subjective Answer Evaluation
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Subjective answer evaluation is a time-consuming and tedious task, and the quality of the evaluation is heavily influenced by a variety of subjective personal characteristics. Instead, machine evaluation can effectively assist educators in saving time while also ensuring that evaluations are fair and realistic. Howev...
[ { "created": "Thu, 17 Nov 2022 19:33:35 GMT", "version": "v1" } ]
2022-11-21
[ [ "Lu", "Yining", "" ], [ "Qiu", "Jingxi", "" ], [ "Gupta", "Gaurav", "" ] ]
Subjective answer evaluation is a time-consuming and tedious task, and the quality of the evaluation is heavily influenced by a variety of subjective personal characteristics. Instead, machine evaluation can effectively assist educators in saving time while also ensuring that evaluations are fair and realistic. However...
2107.07452
G C Nandi
Priya Shukla, Nilotpal Pramanik, Deepesh Mehta and G.C. Nandi
GI-NNet \& RGI-NNet: Development of Robotic Grasp Pose Models, Trainable with Large as well as Limited Labelled Training Datasets, under supervised and semi supervised paradigms
null
null
null
null
cs.RO cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Our way of grasping objects is challenging for efficient, intelligent and optimal grasp by COBOTs. To streamline the process, here we use deep learning techniques to help robots learn to generate and execute appropriate grasps quickly. We developed a Generative Inception Neural Network (GI-NNet) model, capable of gen...
[ { "created": "Thu, 15 Jul 2021 16:55:49 GMT", "version": "v1" } ]
2021-07-16
[ [ "Shukla", "Priya", "" ], [ "Pramanik", "Nilotpal", "" ], [ "Mehta", "Deepesh", "" ], [ "Nandi", "G. C.", "" ] ]
Our way of grasping objects is challenging for efficient, intelligent and optimal grasp by COBOTs. To streamline the process, here we use deep learning techniques to help robots learn to generate and execute appropriate grasps quickly. We developed a Generative Inception Neural Network (GI-NNet) model, capable of gener...
1610.06084
Suresh Damodaran
Suresh K. Damodaran and Pedro A. Colon-Hernandez
Portable Ontological Expressions in NoSQL Queries
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
A significant barrier to the portability of queries across di- verse physical implementations of large data stores, espe- cially NoSQL data stores, is that the queries reference the physical storage attributes, such as the table and column names. In this paper, we describe a technique for embed- ding ontological expr...
[ { "created": "Wed, 19 Oct 2016 16:07:30 GMT", "version": "v1" } ]
2016-10-20
[ [ "Damodaran", "Suresh K.", "" ], [ "Colon-Hernandez", "Pedro A.", "" ] ]
A significant barrier to the portability of queries across di- verse physical implementations of large data stores, espe- cially NoSQL data stores, is that the queries reference the physical storage attributes, such as the table and column names. In this paper, we describe a technique for embed- ding ontological expres...
1608.08435
Rajasekar Venkatesan
Rajasekar Venkatesan, Meng Joo Er
Multi-Label Classification Method Based on Extreme Learning Machines
6 pages, 7 figures, 7 tables, ICARCV
null
10.1109/ICARCV.2014.7064375
null
cs.LG cs.AI cs.NE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, an Extreme Learning Machine (ELM) based technique for Multi-label classification problems is proposed and discussed. In multi-label classification, each of the input data samples belongs to one or more than one class labels. The traditional binary and multi-class classification problems are the subset ...
[ { "created": "Tue, 30 Aug 2016 13:08:06 GMT", "version": "v1" } ]
2016-09-06
[ [ "Venkatesan", "Rajasekar", "" ], [ "Er", "Meng Joo", "" ] ]
In this paper, an Extreme Learning Machine (ELM) based technique for Multi-label classification problems is proposed and discussed. In multi-label classification, each of the input data samples belongs to one or more than one class labels. The traditional binary and multi-class classification problems are the subset of...
2104.07951
Leon Derczynski
Magnus Jacobsen, Mikkel H. S{\o}rensen, Leon Derczynski
Optimal Size-Performance Tradeoffs: Weighing PoS Tagger Models
null
null
null
null
cs.CL
http://creativecommons.org/licenses/by-sa/4.0/
Improvement in machine learning-based NLP performance are often presented with bigger models and more complex code. This presents a trade-off: better scores come at the cost of larger tools; bigger models tend to require more during training and inference time. We present multiple methods for measuring the size of a ...
[ { "created": "Fri, 16 Apr 2021 08:02:56 GMT", "version": "v1" } ]
2021-04-19
[ [ "Jacobsen", "Magnus", "" ], [ "Sørensen", "Mikkel H.", "" ], [ "Derczynski", "Leon", "" ] ]
Improvement in machine learning-based NLP performance are often presented with bigger models and more complex code. This presents a trade-off: better scores come at the cost of larger tools; bigger models tend to require more during training and inference time. We present multiple methods for measuring the size of a mo...
1707.04588
Ga\"etan Hadjeres
Ga\"etan Hadjeres and Frank Nielsen and Fran\c{c}ois Pachet
GLSR-VAE: Geodesic Latent Space Regularization for Variational AutoEncoder Architectures
11 pages
null
null
null
cs.LG cs.AI stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
VAEs (Variational AutoEncoders) have proved to be powerful in the context of density modeling and have been used in a variety of contexts for creative purposes. In many settings, the data we model possesses continuous attributes that we would like to take into account at generation time. We propose in this paper GLSR...
[ { "created": "Fri, 14 Jul 2017 12:28:25 GMT", "version": "v1" } ]
2017-07-18
[ [ "Hadjeres", "Gaëtan", "" ], [ "Nielsen", "Frank", "" ], [ "Pachet", "François", "" ] ]
VAEs (Variational AutoEncoders) have proved to be powerful in the context of density modeling and have been used in a variety of contexts for creative purposes. In many settings, the data we model possesses continuous attributes that we would like to take into account at generation time. We propose in this paper GLSR-V...
2211.05963
Zhifeng Wang
Chunyan Zeng, Jiaxiang Ye, Zhifeng Wang, Nan Zhao, Minghu Wu
JSRNN: Joint Sampling and Reconstruction Neural Networks for High Quality Image Compressed Sensing
9 pages, 3 figures
null
null
null
cs.CV eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most Deep Learning (DL) based Compressed Sensing (DCS) algorithms adopt a single neural network for signal reconstruction, and fail to jointly consider the influences of the sampling operation for reconstruction. In this paper, we propose unified framework, which jointly considers the sampling and reconstruction proc...
[ { "created": "Fri, 11 Nov 2022 02:20:30 GMT", "version": "v1" } ]
2022-11-17
[ [ "Zeng", "Chunyan", "" ], [ "Ye", "Jiaxiang", "" ], [ "Wang", "Zhifeng", "" ], [ "Zhao", "Nan", "" ], [ "Wu", "Minghu", "" ] ]
Most Deep Learning (DL) based Compressed Sensing (DCS) algorithms adopt a single neural network for signal reconstruction, and fail to jointly consider the influences of the sampling operation for reconstruction. In this paper, we propose unified framework, which jointly considers the sampling and reconstruction proces...
2005.01233
Seungjun Nah
Seungjun Nah, Sanghyun Son, Radu Timofte and Kyoung Mu Lee
AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results
Published in ICCV 2019 Workshop (Advances in Image Manipulation)
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), Seoul, Korea (South), 2019, pp. 3388-3398
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Videos contain various types and strengths of motions that may look unnaturally discontinuous in time when the recorded frame rate is low. This paper reviews the first AIM challenge on video temporal super-resolution (frame interpolation) with a focus on the proposed solutions and results. From low-frame-rate (15 fps...
[ { "created": "Mon, 4 May 2020 01:51:23 GMT", "version": "v1" } ]
2020-05-05
[ [ "Nah", "Seungjun", "" ], [ "Son", "Sanghyun", "" ], [ "Timofte", "Radu", "" ], [ "Lee", "Kyoung Mu", "" ] ]
Videos contain various types and strengths of motions that may look unnaturally discontinuous in time when the recorded frame rate is low. This paper reviews the first AIM challenge on video temporal super-resolution (frame interpolation) with a focus on the proposed solutions and results. From low-frame-rate (15 fps) ...
2304.02970
Yuanhong Chen
Yuanhong Chen, Yuyuan Liu, Hu Wang, Fengbei Liu, Chong Wang, Helen Frazer, Gustavo Carneiro
Unraveling Instance Associations: A Closer Look for Audio-Visual Segmentation
Code is available at https://github.com/cyh-0/CAVP
null
null
null
cs.CV cs.MM
http://creativecommons.org/licenses/by-nc-sa/4.0/
Audio-visual segmentation (AVS) is a challenging task that involves accurately segmenting sounding objects based on audio-visual cues. The effectiveness of audio-visual learning critically depends on achieving accurate cross-modal alignment between sound and visual objects. Successful audio-visual learning requires t...
[ { "created": "Thu, 6 Apr 2023 09:54:06 GMT", "version": "v1" }, { "created": "Tue, 11 Apr 2023 09:54:06 GMT", "version": "v2" }, { "created": "Thu, 10 Aug 2023 04:08:44 GMT", "version": "v3" }, { "created": "Mon, 27 Nov 2023 13:11:20 GMT", "version": "v4" }, { "cr...
2024-08-15
[ [ "Chen", "Yuanhong", "" ], [ "Liu", "Yuyuan", "" ], [ "Wang", "Hu", "" ], [ "Liu", "Fengbei", "" ], [ "Wang", "Chong", "" ], [ "Frazer", "Helen", "" ], [ "Carneiro", "Gustavo", "" ] ]
Audio-visual segmentation (AVS) is a challenging task that involves accurately segmenting sounding objects based on audio-visual cues. The effectiveness of audio-visual learning critically depends on achieving accurate cross-modal alignment between sound and visual objects. Successful audio-visual learning requires two...
1712.08357
Liang-Wei Chen
Liang-Wei Chen, Bhargav Mangipudi, Jayachandu Bandlamudi, Richa Sehgal, Yun Hao, Meng Jiang, Huan Gui (University of Illinois at Urbana-Champaign)
Integrating Knowledge from Latent and Explicit Features for Triple Scoring - Team Radicchio's Triple Scorer at WSDM Cup 2017
Triple Scorer at WSDM Cup 2017, see arXiv:1712.08081
null
null
null
cs.IR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The objective of the triple scoring task in WSDM Cup 2017 is to compute relevance scores for knowledge-base triples of type-like relations. For example, consider Julius Caesar who has had various professions, including Politician and Author. For two given triples (Julius Caesar, profession, Politician) and (Julius Ca...
[ { "created": "Fri, 22 Dec 2017 09:09:16 GMT", "version": "v1" } ]
2017-12-25
[ [ "Chen", "Liang-Wei", "", "University of Illinois at\n Urbana-Champaign" ], [ "Mangipudi", "Bhargav", "", "University of Illinois at\n Urbana-Champaign" ], [ "Bandlamudi", "Jayachandu", "", "University of Illinois at\n Urbana-Champaign" ], [ "Sehga...
The objective of the triple scoring task in WSDM Cup 2017 is to compute relevance scores for knowledge-base triples of type-like relations. For example, consider Julius Caesar who has had various professions, including Politician and Author. For two given triples (Julius Caesar, profession, Politician) and (Julius Caes...
2302.10413
Huy Hieu Pham
Nang Hung Nguyen, Duc Long Nguyen, Trong Bang Nguyen, Thanh-Hung Nguyen, Huy Hieu Pham, Truong Thao Nguyen, Phi Le Nguyen
CADIS: Handling Cluster-skewed Non-IID Data in Federated Learning with Clustered Aggregation and Knowledge DIStilled Regularization
Accepted for presentation at the 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid 2023)
null
null
null
cs.LG cs.CV
http://creativecommons.org/licenses/by/4.0/
Federated learning enables edge devices to train a global model collaboratively without exposing their data. Despite achieving outstanding advantages in computing efficiency and privacy protection, federated learning faces a significant challenge when dealing with non-IID data, i.e., data generated by clients that ar...
[ { "created": "Tue, 21 Feb 2023 02:53:37 GMT", "version": "v1" }, { "created": "Thu, 16 Mar 2023 19:52:19 GMT", "version": "v2" }, { "created": "Sat, 15 Apr 2023 04:06:52 GMT", "version": "v3" } ]
2023-04-18
[ [ "Nguyen", "Nang Hung", "" ], [ "Nguyen", "Duc Long", "" ], [ "Nguyen", "Trong Bang", "" ], [ "Nguyen", "Thanh-Hung", "" ], [ "Pham", "Huy Hieu", "" ], [ "Nguyen", "Truong Thao", "" ], [ "Nguyen", "Phi Le", ...
Federated learning enables edge devices to train a global model collaboratively without exposing their data. Despite achieving outstanding advantages in computing efficiency and privacy protection, federated learning faces a significant challenge when dealing with non-IID data, i.e., data generated by clients that are ...
1503.06809
Konstantina Christakou
Konstantina Christakou, Dan-Cristian Tomozei, Jean-Yves Le Boudec, Mario Paolone
AC OPF in Radial Distribution Networks - Parts I,II
null
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The optimal power-flow problem (OPF) has played a key role in the planning and operation of power systems. Due to the non-linear nature of the AC power-flow equations, the OPF problem is known to be non-convex, therefore hard to solve. Most proposed methods for solving the OPF rely on approximations that render the p...
[ { "created": "Mon, 23 Mar 2015 20:03:48 GMT", "version": "v1" }, { "created": "Mon, 20 Jul 2015 10:46:04 GMT", "version": "v2" }, { "created": "Tue, 5 Jul 2016 21:12:17 GMT", "version": "v3" } ]
2016-07-07
[ [ "Christakou", "Konstantina", "" ], [ "Tomozei", "Dan-Cristian", "" ], [ "Boudec", "Jean-Yves Le", "" ], [ "Paolone", "Mario", "" ] ]
The optimal power-flow problem (OPF) has played a key role in the planning and operation of power systems. Due to the non-linear nature of the AC power-flow equations, the OPF problem is known to be non-convex, therefore hard to solve. Most proposed methods for solving the OPF rely on approximations that render the pro...
2102.08473
Yu Meng
Yu Meng, Chenyan Xiong, Payal Bajaj, Saurabh Tiwary, Paul Bennett, Jiawei Han, Xia Song
COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining
NeurIPS 2021. (Code and Models: https://github.com/microsoft/COCO-LM)
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We present a self-supervised learning framework, COCO-LM, that pretrains Language Models by COrrecting and COntrasting corrupted text sequences. Following ELECTRA-style pretraining, COCO-LM employs an auxiliary language model to corrupt text sequences, upon which it constructs two new tasks for pretraining the main m...
[ { "created": "Tue, 16 Feb 2021 22:24:29 GMT", "version": "v1" }, { "created": "Wed, 27 Oct 2021 02:02:39 GMT", "version": "v2" } ]
2021-10-28
[ [ "Meng", "Yu", "" ], [ "Xiong", "Chenyan", "" ], [ "Bajaj", "Payal", "" ], [ "Tiwary", "Saurabh", "" ], [ "Bennett", "Paul", "" ], [ "Han", "Jiawei", "" ], [ "Song", "Xia", "" ] ]
We present a self-supervised learning framework, COCO-LM, that pretrains Language Models by COrrecting and COntrasting corrupted text sequences. Following ELECTRA-style pretraining, COCO-LM employs an auxiliary language model to corrupt text sequences, upon which it constructs two new tasks for pretraining the main mod...
1609.09065
Marasi Mwencha
Marasi Mwencha (John Snow, Inc), James Rosen (Avenir Health)
Better Data Visibility & Data Use Result in Lower Cost and Improved Performance in Medicine Supply Chains
Presented at the Data For Good Exchange 2016
null
null
null
cs.CY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In 2013-2014, Tanzania embarked on a major revamp of the management of its public health supply chains for medicines and other health supplies. These upgrades include the establishment of a national electronic logistics management information system (eLMIS) and the introduction of a Logistics Management Unit (LMU) to...
[ { "created": "Wed, 28 Sep 2016 03:22:57 GMT", "version": "v1" } ]
2016-09-30
[ [ "Mwencha", "Marasi", "", "John Snow, Inc" ], [ "Rosen", "James", "", "Avenir Health" ] ]
In 2013-2014, Tanzania embarked on a major revamp of the management of its public health supply chains for medicines and other health supplies. These upgrades include the establishment of a national electronic logistics management information system (eLMIS) and the introduction of a Logistics Management Unit (LMU) to u...
2305.18842
Xingyu Fu
Xingyu Fu and Sheng Zhang and Gukyeong Kwon and Pramuditha Perera and Henghui Zhu and Yuhao Zhang and Alexander Hanbo Li and William Yang Wang and Zhiguo Wang and Vittorio Castelli and Patrick Ng and Dan Roth and Bing Xiang
Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge
Accepted to ACL 2023 Findings
null
null
null
cs.CL cs.AI cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
The open-ended Visual Question Answering (VQA) task requires AI models to jointly reason over visual and natural language inputs using world knowledge. Recently, pre-trained Language Models (PLM) such as GPT-3 have been applied to the task and shown to be powerful world knowledge sources. However, these methods suffe...
[ { "created": "Tue, 30 May 2023 08:34:13 GMT", "version": "v1" } ]
2023-05-31
[ [ "Fu", "Xingyu", "" ], [ "Zhang", "Sheng", "" ], [ "Kwon", "Gukyeong", "" ], [ "Perera", "Pramuditha", "" ], [ "Zhu", "Henghui", "" ], [ "Zhang", "Yuhao", "" ], [ "Li", "Alexander Hanbo", "" ], [ "Wa...
The open-ended Visual Question Answering (VQA) task requires AI models to jointly reason over visual and natural language inputs using world knowledge. Recently, pre-trained Language Models (PLM) such as GPT-3 have been applied to the task and shown to be powerful world knowledge sources. However, these methods suffer ...
1611.08198
Travis Gagie
Felipe A. Louza, Travis Gagie and Guilherme P. Telles
Burrows-Wheeler transform and LCP array construction in constant space
Accepted to JDA
Journal of Discrete Algorithms, 42 (2017) 14-22
10.1016/j.jda.2016.11.003
null
cs.DS
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this article we extend the elegant in-place Burrows-Wheeler transform (BWT) algorithm proposed by Crochemore et al. (Crochemore et al., 2015). Our extension is twofold: we first show how to compute simultaneously the longest common prefix (LCP) array as well as the BWT, using constant additional space; we then sho...
[ { "created": "Thu, 24 Nov 2016 14:43:57 GMT", "version": "v1" } ]
2018-06-08
[ [ "Louza", "Felipe A.", "" ], [ "Gagie", "Travis", "" ], [ "Telles", "Guilherme P.", "" ] ]
In this article we extend the elegant in-place Burrows-Wheeler transform (BWT) algorithm proposed by Crochemore et al. (Crochemore et al., 2015). Our extension is twofold: we first show how to compute simultaneously the longest common prefix (LCP) array as well as the BWT, using constant additional space; we then show ...
2101.04927
Boris Faizov
Anton Konushin, Boris Faizov, Vlad Shakhuro
Road images augmentation with synthetic traffic signs using neural networks
The paper was submitted to the journal "Computer Optics" and is currently under review
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Traffic sign recognition is a well-researched problem in computer vision. However, the state of the art methods works only for frequent sign classes, which are well represented in training datasets. We consider the task of rare traffic sign detection and classification. We aim to solve that problem by using synthetic...
[ { "created": "Wed, 13 Jan 2021 08:10:33 GMT", "version": "v1" } ]
2021-01-14
[ [ "Konushin", "Anton", "" ], [ "Faizov", "Boris", "" ], [ "Shakhuro", "Vlad", "" ] ]
Traffic sign recognition is a well-researched problem in computer vision. However, the state of the art methods works only for frequent sign classes, which are well represented in training datasets. We consider the task of rare traffic sign detection and classification. We aim to solve that problem by using synthetic t...
1204.1746
Eugene Goldberg
Eugene Goldberg and Panagiotis Manolios
Removal of Quantifiers by Elimination of Boundary Points
The only change with respect to the previous version is a modification of the acknowledgement section
null
null
null
cs.LO cs.DM
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider the problem of elimination of existential quantifiers from a Boolean CNF formula. Our approach is based on the following observation. One can get rid of dependency on a set of variables of a quantified CNF formula F by adding resolvent clauses of F eliminating boundary points. This approach is similar to ...
[ { "created": "Sun, 8 Apr 2012 17:00:25 GMT", "version": "v1" }, { "created": "Tue, 5 Jun 2012 14:34:11 GMT", "version": "v2" } ]
2012-06-06
[ [ "Goldberg", "Eugene", "" ], [ "Manolios", "Panagiotis", "" ] ]
We consider the problem of elimination of existential quantifiers from a Boolean CNF formula. Our approach is based on the following observation. One can get rid of dependency on a set of variables of a quantified CNF formula F by adding resolvent clauses of F eliminating boundary points. This approach is similar to th...
2105.09926
Frederik Mallmann-Trenn
Nan Kang, Frederik Mallmann-Trenn and Nicol\'as Rivera
Diversity, Fairness, and Sustainability in Population Protocols
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Over the years, population protocols with the goal of reaching consensus have been studied in great depth. However, many systems in the real-world do not result in all agents eventually reaching consensus, but rather in the opposite: they converge to a state of rich diversity. Consider for example task allocation in ...
[ { "created": "Thu, 20 May 2021 17:39:56 GMT", "version": "v1" }, { "created": "Mon, 7 Jun 2021 09:41:22 GMT", "version": "v2" } ]
2021-06-08
[ [ "Kang", "Nan", "" ], [ "Mallmann-Trenn", "Frederik", "" ], [ "Rivera", "Nicolás", "" ] ]
Over the years, population protocols with the goal of reaching consensus have been studied in great depth. However, many systems in the real-world do not result in all agents eventually reaching consensus, but rather in the opposite: they converge to a state of rich diversity. Consider for example task allocation in an...
2210.17335
Peter Thiemann
Hannes Saffrich and Peter Thiemann
Polymorphic Typestate for Session Types
29 pages. Short version appears in PPDP 2023
null
10.1145/3610612.3610624
null
cs.PL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Session types provide a principled approach to typed communication protocols that guarantee type safety and protocol fidelity. Formalizations of session-typed communication are typically based on process calculi, concurrent lambda calculi, or linear logic. An alternative model based on context-sensitive typing and ty...
[ { "created": "Mon, 31 Oct 2022 13:56:23 GMT", "version": "v1" }, { "created": "Mon, 14 Aug 2023 09:19:40 GMT", "version": "v2" } ]
2023-08-15
[ [ "Saffrich", "Hannes", "" ], [ "Thiemann", "Peter", "" ] ]
Session types provide a principled approach to typed communication protocols that guarantee type safety and protocol fidelity. Formalizations of session-typed communication are typically based on process calculi, concurrent lambda calculi, or linear logic. An alternative model based on context-sensitive typing and type...
2209.03090
Juan Carlos Andresen
Kuo-Yun Liang, Abhishek Srinivasan, Juan Carlos Andresen
Modular Federated Learning
To be published in IEEE IJCNN 2022 proceedings
International Joint Conference on Neural Networks (IJCNN), 2022, pp. 1-8
10.1109/IJCNN55064.2022.9892377
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Federated learning is an approach to train machine learning models on the edge of the networks, as close as possible where the data is produced, motivated by the emerging problem of the inability to stream and centrally store the large amount of data produced by edge devices as well as by data privacy concerns. This ...
[ { "created": "Wed, 7 Sep 2022 11:54:55 GMT", "version": "v1" } ]
2022-10-07
[ [ "Liang", "Kuo-Yun", "" ], [ "Srinivasan", "Abhishek", "" ], [ "Andresen", "Juan Carlos", "" ] ]
Federated learning is an approach to train machine learning models on the edge of the networks, as close as possible where the data is produced, motivated by the emerging problem of the inability to stream and centrally store the large amount of data produced by edge devices as well as by data privacy concerns. This le...
2311.17035
Nicholas Carlini
Milad Nasr, Nicholas Carlini, Jonathan Hayase, Matthew Jagielski, A. Feder Cooper, Daphne Ippolito, Christopher A. Choquette-Choo, Eric Wallace, Florian Tram\`er, Katherine Lee
Scalable Extraction of Training Data from (Production) Language Models
null
null
null
null
cs.LG cs.CL cs.CR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper studies extractable memorization: training data that an adversary can efficiently extract by querying a machine learning model without prior knowledge of the training dataset. We show an adversary can extract gigabytes of training data from open-source language models like Pythia or GPT-Neo, semi-open mode...
[ { "created": "Tue, 28 Nov 2023 18:47:03 GMT", "version": "v1" } ]
2023-11-29
[ [ "Nasr", "Milad", "" ], [ "Carlini", "Nicholas", "" ], [ "Hayase", "Jonathan", "" ], [ "Jagielski", "Matthew", "" ], [ "Cooper", "A. Feder", "" ], [ "Ippolito", "Daphne", "" ], [ "Choquette-Choo", "Christopher A...
This paper studies extractable memorization: training data that an adversary can efficiently extract by querying a machine learning model without prior knowledge of the training dataset. We show an adversary can extract gigabytes of training data from open-source language models like Pythia or GPT-Neo, semi-open models...
1705.00464
Ted Zhang
Ted Zhang, Dengxin Dai, Tinne Tuytelaars, Marie-Francine Moens, Luc Van Gool
Speech-Based Visual Question Answering
null
null
null
null
cs.CL cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces speech-based visual question answering (VQA), the task of generating an answer given an image and a spoken question. Two methods are studied: an end-to-end, deep neural network that directly uses audio waveforms as input versus a pipelined approach that performs ASR (Automatic Speech Recognition...
[ { "created": "Mon, 1 May 2017 10:43:28 GMT", "version": "v1" }, { "created": "Sat, 16 Sep 2017 03:43:20 GMT", "version": "v2" } ]
2017-09-19
[ [ "Zhang", "Ted", "" ], [ "Dai", "Dengxin", "" ], [ "Tuytelaars", "Tinne", "" ], [ "Moens", "Marie-Francine", "" ], [ "Van Gool", "Luc", "" ] ]
This paper introduces speech-based visual question answering (VQA), the task of generating an answer given an image and a spoken question. Two methods are studied: an end-to-end, deep neural network that directly uses audio waveforms as input versus a pipelined approach that performs ASR (Automatic Speech Recognition) ...
2306.03842
Nimrod Megiddo
Nimrod Megiddo
Remarks on Utility in Repeated Bets
null
null
null
null
cs.AI math.PR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The use of von Neumann -- Morgenstern utility is examined in the context of multiple choices between lotteries. Different conclusions are reached if the choices are simultaneous or sequential. It is demonstrated that utility cannot be additive.
[ { "created": "Tue, 6 Jun 2023 16:29:31 GMT", "version": "v1" } ]
2023-06-07
[ [ "Megiddo", "Nimrod", "" ] ]
The use of von Neumann -- Morgenstern utility is examined in the context of multiple choices between lotteries. Different conclusions are reached if the choices are simultaneous or sequential. It is demonstrated that utility cannot be additive.
1607.02533
Alexey Kurakin
Alexey Kurakin, Ian Goodfellow and Samy Bengio
Adversarial examples in the physical world
14 pages, 6 figures. Demo available at https://youtu.be/zQ_uMenoBCk
null
null
null
cs.CV cs.CR cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Most existing machine learning classifiers are highly vulnerable to adversarial examples. An adversarial example is a sample of input data which has been modified very slightly in a way that is intended to cause a machine learning classifier to misclassify it. In many cases, these modifications can be so subtle that ...
[ { "created": "Fri, 8 Jul 2016 21:12:11 GMT", "version": "v1" }, { "created": "Tue, 23 Aug 2016 22:57:31 GMT", "version": "v2" }, { "created": "Fri, 4 Nov 2016 20:34:37 GMT", "version": "v3" }, { "created": "Sat, 11 Feb 2017 00:39:39 GMT", "version": "v4" } ]
2017-02-14
[ [ "Kurakin", "Alexey", "" ], [ "Goodfellow", "Ian", "" ], [ "Bengio", "Samy", "" ] ]
Most existing machine learning classifiers are highly vulnerable to adversarial examples. An adversarial example is a sample of input data which has been modified very slightly in a way that is intended to cause a machine learning classifier to misclassify it. In many cases, these modifications can be so subtle that a ...
1011.0253
Albert Xin Jiang
Albert Xin Jiang and Kevin Leyton-Brown
Polynomial-time Computation of Exact Correlated Equilibrium in Compact Games
15 pages
null
null
null
cs.GT cs.CC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In a landmark paper, Papadimitriou and Roughgarden described a polynomial-time algorithm ("Ellipsoid Against Hope") for computing sample correlated equilibria of concisely-represented games. Recently, Stein, Parrilo and Ozdaglar showed that this algorithm can fail to find an exact correlated equilibrium, but can be e...
[ { "created": "Mon, 1 Nov 2010 05:06:59 GMT", "version": "v1" } ]
2015-03-17
[ [ "Jiang", "Albert Xin", "" ], [ "Leyton-Brown", "Kevin", "" ] ]
In a landmark paper, Papadimitriou and Roughgarden described a polynomial-time algorithm ("Ellipsoid Against Hope") for computing sample correlated equilibria of concisely-represented games. Recently, Stein, Parrilo and Ozdaglar showed that this algorithm can fail to find an exact correlated equilibrium, but can be eas...
1105.3531
Jonathan Scarlett
Jonathan Scarlett, Jamie Evans, Subhrakanti Dey
On the Tradeoff Between Multiuser Diversity and Training Overhead in Multiple Access Channels
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We consider a single antenna narrowband multiple access channel in which users send training sequences to the base station and scheduling is performed based on minimum mean square error (MMSE) channel estimates. In such a system, there is an inherent tradeoff between training overhead and the amount of multiuser dive...
[ { "created": "Wed, 18 May 2011 04:44:33 GMT", "version": "v1" }, { "created": "Sun, 22 May 2011 11:11:31 GMT", "version": "v2" }, { "created": "Thu, 4 Aug 2011 07:49:30 GMT", "version": "v3" }, { "created": "Sun, 11 Dec 2011 15:27:26 GMT", "version": "v4" } ]
2011-12-13
[ [ "Scarlett", "Jonathan", "" ], [ "Evans", "Jamie", "" ], [ "Dey", "Subhrakanti", "" ] ]
We consider a single antenna narrowband multiple access channel in which users send training sequences to the base station and scheduling is performed based on minimum mean square error (MMSE) channel estimates. In such a system, there is an inherent tradeoff between training overhead and the amount of multiuser divers...
1909.10549
Gregory Farquhar
Gregory Farquhar, Shimon Whiteson, Jakob Foerster
Loaded DiCE: Trading off Bias and Variance in Any-Order Score Function Estimators for Reinforcement Learning
null
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Gradient-based methods for optimisation of objectives in stochastic settings with unknown or intractable dynamics require estimators of derivatives. We derive an objective that, under automatic differentiation, produces low-variance unbiased estimators of derivatives at any order. Our objective is compatible with arb...
[ { "created": "Mon, 23 Sep 2019 18:13:50 GMT", "version": "v1" } ]
2019-09-25
[ [ "Farquhar", "Gregory", "" ], [ "Whiteson", "Shimon", "" ], [ "Foerster", "Jakob", "" ] ]
Gradient-based methods for optimisation of objectives in stochastic settings with unknown or intractable dynamics require estimators of derivatives. We derive an objective that, under automatic differentiation, produces low-variance unbiased estimators of derivatives at any order. Our objective is compatible with arbit...
1909.00124
Hao Wang
Hao Wang, Bing Liu, Chaozhuo Li, Yan Yang, and Tianrui Li
Learning with Noisy Labels for Sentence-level Sentiment Classification
to appear in EMNLP-IJCNLP 2019
null
null
null
cs.CL cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Deep neural networks (DNNs) can fit (or even over-fit) the training data very well. If a DNN model is trained using data with noisy labels and tested on data with clean labels, the model may perform poorly. This paper studies the problem of learning with noisy labels for sentence-level sentiment classification. We pr...
[ { "created": "Sat, 31 Aug 2019 04:18:50 GMT", "version": "v1" } ]
2019-09-04
[ [ "Wang", "Hao", "" ], [ "Liu", "Bing", "" ], [ "Li", "Chaozhuo", "" ], [ "Yang", "Yan", "" ], [ "Li", "Tianrui", "" ] ]
Deep neural networks (DNNs) can fit (or even over-fit) the training data very well. If a DNN model is trained using data with noisy labels and tested on data with clean labels, the model may perform poorly. This paper studies the problem of learning with noisy labels for sentence-level sentiment classification. We prop...
1402.4247
Jae-Hyeon Parq
Jae-Hyeon Parq, Erik Sevre and Sang-Mook Lee
Effects of Easy Hybrid Parallelization with CUDA for Numerical-Atomic-Orbital Density Functional Theory Calculation
20 pages, 3 figures
International Journal of Computer Applications, Volume 98, No.13, pp. 20-27 (2014)
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We modified a MPI-friendly density functional theory (DFT) source code within hybrid parallelization including CUDA. Our objective is to find out how simple conversions within the hybrid parallelization with mid-range GPUs affect DFT code not originally suitable to CUDA. We settled several rules of hybrid paralleliza...
[ { "created": "Tue, 18 Feb 2014 08:25:47 GMT", "version": "v1" } ]
2014-07-23
[ [ "Parq", "Jae-Hyeon", "" ], [ "Sevre", "Erik", "" ], [ "Lee", "Sang-Mook", "" ] ]
We modified a MPI-friendly density functional theory (DFT) source code within hybrid parallelization including CUDA. Our objective is to find out how simple conversions within the hybrid parallelization with mid-range GPUs affect DFT code not originally suitable to CUDA. We settled several rules of hybrid parallelizati...
2106.04112
Siqi Deng
Siqi Deng, Yuanjun Xiong, Meng Wang, Wei Xia, Stefano Soatto
Harnessing Unrecognizable Faces for Improving Face Recognition
null
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
The common implementation of face recognition systems as a cascade of a detection stage and a recognition or verification stage can cause problems beyond failures of the detector. When the detector succeeds, it can detect faces that cannot be recognized, no matter how capable the recognition system. Recognizability, ...
[ { "created": "Tue, 8 Jun 2021 05:25:03 GMT", "version": "v1" }, { "created": "Tue, 14 Sep 2021 19:43:53 GMT", "version": "v2" } ]
2021-09-16
[ [ "Deng", "Siqi", "" ], [ "Xiong", "Yuanjun", "" ], [ "Wang", "Meng", "" ], [ "Xia", "Wei", "" ], [ "Soatto", "Stefano", "" ] ]
The common implementation of face recognition systems as a cascade of a detection stage and a recognition or verification stage can cause problems beyond failures of the detector. When the detector succeeds, it can detect faces that cannot be recognized, no matter how capable the recognition system. Recognizability, a ...
2405.03153
Md Main Uddin Rony
Md Main Uddin Rony, Md Mahfuzul Haque, Mohammad Ali, Ahmed Shatil Alam, Naeemul Hassan
Exploring the Potential of the Large Language Models (LLMs) in Identifying Misleading News Headlines
5 pages, 2 tables, 1st HEAL Workshop at CHI Conference on Human Factors in Computing Systems, May 12, Honolulu, HI, USA 2024
null
null
null
cs.CL cs.CY cs.LG
http://creativecommons.org/licenses/by/4.0/
In the digital age, the prevalence of misleading news headlines poses a significant challenge to information integrity, necessitating robust detection mechanisms. This study explores the efficacy of Large Language Models (LLMs) in identifying misleading versus non-misleading news headlines. Utilizing a dataset of 60 ...
[ { "created": "Mon, 6 May 2024 04:06:45 GMT", "version": "v1" } ]
2024-05-07
[ [ "Rony", "Md Main Uddin", "" ], [ "Haque", "Md Mahfuzul", "" ], [ "Ali", "Mohammad", "" ], [ "Alam", "Ahmed Shatil", "" ], [ "Hassan", "Naeemul", "" ] ]
In the digital age, the prevalence of misleading news headlines poses a significant challenge to information integrity, necessitating robust detection mechanisms. This study explores the efficacy of Large Language Models (LLMs) in identifying misleading versus non-misleading news headlines. Utilizing a dataset of 60 ar...
1501.07847
Adebayo Omotosho Mr
Adebayo Omotosho, Mikhail Olaniyi, Justice Emuoyibofarhe, Funbi Osobu
Electronic Medication Prescribing Support System for Diagnosing Tropical Diseases
null
null
null
null
cs.CY cs.HC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper presents the development of an e-prescription system for diagnosing tropical diseases.Results after testing the developed system by medical experts indicated that the e-prescription systems is more efficient and less susceptible to common errors associated with the conventional handwritten medical prescrip...
[ { "created": "Fri, 30 Jan 2015 17:13:50 GMT", "version": "v1" } ]
2015-02-02
[ [ "Omotosho", "Adebayo", "" ], [ "Olaniyi", "Mikhail", "" ], [ "Emuoyibofarhe", "Justice", "" ], [ "Osobu", "Funbi", "" ] ]
This paper presents the development of an e-prescription system for diagnosing tropical diseases.Results after testing the developed system by medical experts indicated that the e-prescription systems is more efficient and less susceptible to common errors associated with the conventional handwritten medical prescripti...
2405.20138
Toshio Suzuki
Fuki Ito, Toshio Suzuki
Separation and Collapse of Equilibria Inequalities on AND-OR Trees without Shape Constraints
42 pages, 1 figure
null
null
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Herein, we investigate the randomized complexity, which is the least cost against the worst input, of AND-OR tree computation by imposing various restrictions on the algorithm to find the Boolean value of the root of that tree and no restrictions on the tree shape. When a tree satisfies a certain condition regarding ...
[ { "created": "Thu, 30 May 2024 15:13:46 GMT", "version": "v1" } ]
2024-05-31
[ [ "Ito", "Fuki", "" ], [ "Suzuki", "Toshio", "" ] ]
Herein, we investigate the randomized complexity, which is the least cost against the worst input, of AND-OR tree computation by imposing various restrictions on the algorithm to find the Boolean value of the root of that tree and no restrictions on the tree shape. When a tree satisfies a certain condition regarding it...
2105.03289
Hichem Mrabet
Hichem Mrabet, Elias Giaccoumidis and Iyad Dayoub
A Survey of Applied Machine Learning Techniques for Optical OFDM based Networks
26 pages, 4 figures and 4 tables
null
null
null
cs.LG eess.SP
http://creativecommons.org/licenses/by/4.0/
In this survey, we analyze the newest machine learning (ML) techniques for optical orthogonal frequency division multiplexing (O-OFDM)-based optical communications. ML has been proposed to mitigate channel and transceiver imperfections. For instance, ML can improve the signal quality under low modulation extinction r...
[ { "created": "Fri, 7 May 2021 14:29:25 GMT", "version": "v1" } ]
2021-05-10
[ [ "Mrabet", "Hichem", "" ], [ "Giaccoumidis", "Elias", "" ], [ "Dayoub", "Iyad", "" ] ]
In this survey, we analyze the newest machine learning (ML) techniques for optical orthogonal frequency division multiplexing (O-OFDM)-based optical communications. ML has been proposed to mitigate channel and transceiver imperfections. For instance, ML can improve the signal quality under low modulation extinction rat...
2112.01781
Mohammed Lalou
Mohammed Lalou
On the Complexity of the K-way Vertex Cut Problem
3 figures, 5 pages (double column), conference
null
null
null
cs.CC cs.DS
http://creativecommons.org/licenses/by-nc-nd/4.0/
The K-way vertex cut problem} consists in, given a graph G, finding a subset of vertices of a given size, whose removal partitions G into the maximum number of connected components. This problem has many applications in several areas. It has been proven to be NP-complete on general graphs, as well as on split and pla...
[ { "created": "Fri, 3 Dec 2021 08:29:14 GMT", "version": "v1" } ]
2021-12-06
[ [ "Lalou", "Mohammed", "" ] ]
The K-way vertex cut problem} consists in, given a graph G, finding a subset of vertices of a given size, whose removal partitions G into the maximum number of connected components. This problem has many applications in several areas. It has been proven to be NP-complete on general graphs, as well as on split and plana...
2006.13704
Liting Sun
Zheng Wu, Liting Sun, Wei Zhan, Chenyu Yang, Masayoshi Tomizuka
Efficient Sampling-Based Maximum Entropy Inverse Reinforcement Learning with Application to Autonomous Driving
Accepted by IEEE Robotics and Automation Letters. June 2020
null
null
null
cs.RO cs.AI cs.LG
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In the past decades, we have witnessed significant progress in the domain of autonomous driving. Advanced techniques based on optimization and reinforcement learning (RL) become increasingly powerful at solving the forward problem: given designed reward/cost functions, how should we optimize them and obtain driving p...
[ { "created": "Mon, 22 Jun 2020 01:41:13 GMT", "version": "v1" } ]
2020-06-25
[ [ "Wu", "Zheng", "" ], [ "Sun", "Liting", "" ], [ "Zhan", "Wei", "" ], [ "Yang", "Chenyu", "" ], [ "Tomizuka", "Masayoshi", "" ] ]
In the past decades, we have witnessed significant progress in the domain of autonomous driving. Advanced techniques based on optimization and reinforcement learning (RL) become increasingly powerful at solving the forward problem: given designed reward/cost functions, how should we optimize them and obtain driving pol...
2108.02559
Shixiang Feng
Shixiang Feng, Yuhang Zhou, Xiaoman Zhang, Ya Zhang, and Yanfeng Wang
MS-KD: Multi-Organ Segmentation with Multiple Binary-Labeled Datasets
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Annotating multiple organs in 3D medical images is time-consuming and costly. Meanwhile, there exist many single-organ datasets with one specific organ annotated. This paper investigates how to learn a multi-organ segmentation model leveraging a set of binary-labeled datasets. A novel Multi-teacher Single-student Kno...
[ { "created": "Thu, 5 Aug 2021 12:29:26 GMT", "version": "v1" } ]
2021-08-06
[ [ "Feng", "Shixiang", "" ], [ "Zhou", "Yuhang", "" ], [ "Zhang", "Xiaoman", "" ], [ "Zhang", "Ya", "" ], [ "Wang", "Yanfeng", "" ] ]
Annotating multiple organs in 3D medical images is time-consuming and costly. Meanwhile, there exist many single-organ datasets with one specific organ annotated. This paper investigates how to learn a multi-organ segmentation model leveraging a set of binary-labeled datasets. A novel Multi-teacher Single-student Knowl...
2405.06356
Daniel De Pascale
Daniel De Pascale, Giuseppe Cascavilla, Damian A. Tamburri, Willem-Jan Van Den Heuvel
CRATOR: a Dark Web Crawler
null
null
null
null
cs.CR
http://creativecommons.org/licenses/by-nc-sa/4.0/
Dark web crawling is a complex process that involves specific methodologies and techniques to navigate the Tor network and extract data from hidden services. This study proposes a general dark web crawler designed to extract pages handling security protocols, such as captchas, efficiently. Our approach uses a combina...
[ { "created": "Fri, 10 May 2024 09:39:12 GMT", "version": "v1" } ]
2024-05-13
[ [ "De Pascale", "Daniel", "" ], [ "Cascavilla", "Giuseppe", "" ], [ "Tamburri", "Damian A.", "" ], [ "Heuvel", "Willem-Jan Van Den", "" ] ]
Dark web crawling is a complex process that involves specific methodologies and techniques to navigate the Tor network and extract data from hidden services. This study proposes a general dark web crawler designed to extract pages handling security protocols, such as captchas, efficiently. Our approach uses a combinati...
cs/0302036
Evgueni Petrov
Evgueni Petrov, Eric Monfroy
Constraint-based analysis of composite solvers
submitted to AI SAC 2004
null
null
null
cs.AI
null
Cooperative constraint solving is an area of constraint programming that studies the interaction between constraint solvers with the aim of discovering the interaction patterns that amplify the positive qualities of individual solvers. Automatisation and formalisation of such studies is an important issue of cooperat...
[ { "created": "Tue, 25 Feb 2003 14:33:08 GMT", "version": "v1" }, { "created": "Sun, 7 Sep 2003 23:03:03 GMT", "version": "v2" } ]
2007-05-23
[ [ "Petrov", "Evgueni", "" ], [ "Monfroy", "Eric", "" ] ]
Cooperative constraint solving is an area of constraint programming that studies the interaction between constraint solvers with the aim of discovering the interaction patterns that amplify the positive qualities of individual solvers. Automatisation and formalisation of such studies is an important issue of cooperativ...
2405.14712
Sam Kriegman
Luke Strgar, David Matthews, Tyler Hummer, Sam Kriegman
Evolution and learning in differentiable robots
null
null
null
null
cs.RO cs.AI
http://creativecommons.org/licenses/by/4.0/
The automatic design of robots has existed for 30 years but has been constricted by serial non-differentiable design evaluations, premature convergence to simple bodies or clumsy behaviors, and a lack of sim2real transfer to physical machines. Thus, here we employ massively-parallel differentiable simulations to rapi...
[ { "created": "Thu, 23 May 2024 15:45:43 GMT", "version": "v1" }, { "created": "Sun, 26 May 2024 17:24:12 GMT", "version": "v2" } ]
2024-05-28
[ [ "Strgar", "Luke", "" ], [ "Matthews", "David", "" ], [ "Hummer", "Tyler", "" ], [ "Kriegman", "Sam", "" ] ]
The automatic design of robots has existed for 30 years but has been constricted by serial non-differentiable design evaluations, premature convergence to simple bodies or clumsy behaviors, and a lack of sim2real transfer to physical machines. Thus, here we employ massively-parallel differentiable simulations to rapidl...
2010.10995
Harikrishnan Nellippallil Balakrishnan
Harikrishnan NB and Pranay SY and Nithin Nagaraj
A Neurochaos Learning Architecture for Genome Classification
20 pages, 20 images
null
null
null
cs.NE cs.LG q-bio.NC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
There has been empirical evidence of presence of non-linearity and chaos at the level of single neurons in biological neural networks. The properties of chaotic neurons inspires us to employ them in artificial learning systems. Here, we propose a Neurochaos Learning (NL) architecture, where the neurons used to extrac...
[ { "created": "Mon, 12 Oct 2020 19:07:02 GMT", "version": "v1" } ]
2020-10-22
[ [ "NB", "Harikrishnan", "" ], [ "SY", "Pranay", "" ], [ "Nagaraj", "Nithin", "" ] ]
There has been empirical evidence of presence of non-linearity and chaos at the level of single neurons in biological neural networks. The properties of chaotic neurons inspires us to employ them in artificial learning systems. Here, we propose a Neurochaos Learning (NL) architecture, where the neurons used to extract ...
1903.03431
Cristina Dalf\'o
C. Dalf\'o, M. A. Fiol
El m\`etode de les l\'inies per a la resoluci\'o num\`erica d'equacions en derivades parcials. The method of lines for numerical solutions of partial differential equations
in Catalonian
null
null
null
cs.NA math.CO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we describe a semi-discrete method for a numerical resolution of a type of partial differential equations, called the method of lines (MOL). This method is based on the discretization of all but one of the variables of the problem. We illustrate this method by solving the Laplace equation in Cartesian ...
[ { "created": "Wed, 27 Feb 2019 11:33:14 GMT", "version": "v1" } ]
2019-03-11
[ [ "Dalfó", "C.", "" ], [ "Fiol", "M. A.", "" ] ]
In this paper, we describe a semi-discrete method for a numerical resolution of a type of partial differential equations, called the method of lines (MOL). This method is based on the discretization of all but one of the variables of the problem. We illustrate this method by solving the Laplace equation in Cartesian co...
1809.10932
Huy Phan
Huy Phan, Fernando Andreotti, Navin Cooray, Oliver Y. Ch\'en, Maarten De Vos
SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging
This article has been published in IEEE Transactions on Neural Systems and Rehabilitation Engineering
null
10.1109/TNSRE.2019.2896659
null
cs.LG eess.SP stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatic sleep staging has been often treated as a simple classification problem that aims at determining the label of individual target polysomnography (PSG) epochs one at a time. In this work, we tackle the task as a sequence-to-sequence classification problem that receives a sequence of multiple epochs as input a...
[ { "created": "Fri, 28 Sep 2018 09:37:48 GMT", "version": "v1" }, { "created": "Mon, 1 Oct 2018 08:17:21 GMT", "version": "v2" }, { "created": "Sat, 2 Feb 2019 01:46:14 GMT", "version": "v3" } ]
2019-02-05
[ [ "Phan", "Huy", "" ], [ "Andreotti", "Fernando", "" ], [ "Cooray", "Navin", "" ], [ "Chén", "Oliver Y.", "" ], [ "De Vos", "Maarten", "" ] ]
Automatic sleep staging has been often treated as a simple classification problem that aims at determining the label of individual target polysomnography (PSG) epochs one at a time. In this work, we tackle the task as a sequence-to-sequence classification problem that receives a sequence of multiple epochs as input and...
2308.04778
Yasser KHALAFAOUI
Yasser Khalafaoui (Alteca, ETIS - UMR 8051, CY), Nistor Grozavu (ETIS - UMR 8051, CY), Basarab Matei (LIPN), Laurent-Walter Goix
Multi-modal Multi-view Clustering based on Non-negative Matrix Factorization
null
2022 IEEE Symposium Series on Computational Intelligence (SSCI), Dec 2022, Singapore, Singapore. pp.1386-1391
10.1109/SSCI51031.2022.10022129
null
cs.AI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
By combining related objects, unsupervised machine learning techniques aim to reveal the underlying patterns in a data set. Non-negative Matrix Factorization (NMF) is a data mining technique that splits data matrices by imposing restrictions on the elements' non-negativity into two matrices: one representing the data...
[ { "created": "Wed, 9 Aug 2023 08:06:03 GMT", "version": "v1" } ]
2023-08-10
[ [ "Khalafaoui", "Yasser", "", "Alteca, ETIS - UMR 8051, CY" ], [ "Grozavu", "Nistor", "", "ETIS\n - UMR 8051, CY" ], [ "Matei", "Basarab", "", "LIPN" ], [ "Goix", "Laurent-Walter", "" ] ]
By combining related objects, unsupervised machine learning techniques aim to reveal the underlying patterns in a data set. Non-negative Matrix Factorization (NMF) is a data mining technique that splits data matrices by imposing restrictions on the elements' non-negativity into two matrices: one representing the data p...
2305.13303
Jannis Vamvas
Jannis Vamvas and Rico Sennrich
Towards Unsupervised Recognition of Token-level Semantic Differences in Related Documents
EMNLP 2023
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Automatically highlighting words that cause semantic differences between two documents could be useful for a wide range of applications. We formulate recognizing semantic differences (RSD) as a token-level regression task and study three unsupervised approaches that rely on a masked language model. To assess the appr...
[ { "created": "Mon, 22 May 2023 17:58:04 GMT", "version": "v1" }, { "created": "Tue, 17 Oct 2023 11:58:37 GMT", "version": "v2" }, { "created": "Fri, 20 Oct 2023 12:27:41 GMT", "version": "v3" } ]
2023-10-23
[ [ "Vamvas", "Jannis", "" ], [ "Sennrich", "Rico", "" ] ]
Automatically highlighting words that cause semantic differences between two documents could be useful for a wide range of applications. We formulate recognizing semantic differences (RSD) as a token-level regression task and study three unsupervised approaches that rely on a masked language model. To assess the approa...
2012.04550
Sang Michael Xie
Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness
ICLR 2021
null
null
null
cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Consider a prediction setting with few in-distribution labeled examples and many unlabeled examples both in- and out-of-distribution (OOD). The goal is to learn a model which performs well both in-distribution and OOD. In these settings, auxiliary information is often cheaply available for every input. How should we ...
[ { "created": "Tue, 8 Dec 2020 16:43:07 GMT", "version": "v1" }, { "created": "Wed, 16 Dec 2020 22:00:59 GMT", "version": "v2" }, { "created": "Wed, 7 Apr 2021 16:47:17 GMT", "version": "v3" } ]
2021-04-08
[ [ "Xie", "Sang Michael", "" ], [ "Kumar", "Ananya", "" ], [ "Jones", "Robbie", "" ], [ "Khani", "Fereshte", "" ], [ "Ma", "Tengyu", "" ], [ "Liang", "Percy", "" ] ]
Consider a prediction setting with few in-distribution labeled examples and many unlabeled examples both in- and out-of-distribution (OOD). The goal is to learn a model which performs well both in-distribution and OOD. In these settings, auxiliary information is often cheaply available for every input. How should we be...
2202.06003
Parameswaran Kamalaruban Dr.
Luca Viano, Yu-Ting Huang, Parameswaran Kamalaruban, Craig Innes, Subramanian Ramamoorthy, Adrian Weller
Robust Learning from Observation with Model Misspecification
accepted to AAMAS 2022 (camera-ready version)
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Imitation learning (IL) is a popular paradigm for training policies in robotic systems when specifying the reward function is difficult. However, despite the success of IL algorithms, they impose the somewhat unrealistic requirement that the expert demonstrations must come from the same domain in which a new imitator...
[ { "created": "Sat, 12 Feb 2022 07:04:06 GMT", "version": "v1" }, { "created": "Tue, 15 Feb 2022 10:35:34 GMT", "version": "v2" } ]
2022-02-16
[ [ "Viano", "Luca", "" ], [ "Huang", "Yu-Ting", "" ], [ "Kamalaruban", "Parameswaran", "" ], [ "Innes", "Craig", "" ], [ "Ramamoorthy", "Subramanian", "" ], [ "Weller", "Adrian", "" ] ]
Imitation learning (IL) is a popular paradigm for training policies in robotic systems when specifying the reward function is difficult. However, despite the success of IL algorithms, they impose the somewhat unrealistic requirement that the expert demonstrations must come from the same domain in which a new imitator p...
2205.10872
Usman Mahmood
Usman Mahmood and Daniel Pimentel-Alarc\'on
Fusion Subspace Clustering for Incomplete Data
Accepted at IJCNN 2022. arXiv admin note: substantial text overlap with arXiv:1808.00628
null
null
null
cs.LG stat.ML
http://creativecommons.org/licenses/by/4.0/
This paper introduces {\em fusion subspace clustering}, a novel method to learn low-dimensional structures that approximate large scale yet highly incomplete data. The main idea is to assign each datum to a subspace of its own, and minimize the distance between the subspaces of all data, so that subspaces of the same...
[ { "created": "Sun, 22 May 2022 17:23:41 GMT", "version": "v1" } ]
2022-05-24
[ [ "Mahmood", "Usman", "" ], [ "Pimentel-Alarcón", "Daniel", "" ] ]
This paper introduces {\em fusion subspace clustering}, a novel method to learn low-dimensional structures that approximate large scale yet highly incomplete data. The main idea is to assign each datum to a subspace of its own, and minimize the distance between the subspaces of all data, so that subspaces of the same c...
2308.05731
Marcel Hallgarten
Steffen Hagedorn, Marcel Hallgarten, Martin Stoll, Alexandru Condurache
Rethinking the Integration of Prediction and Planning in Deep Learning-Based Automated Driving Systems: A Review
null
null
null
null
cs.RO cs.AI cs.CV cs.LG cs.MA
http://creativecommons.org/licenses/by-nc-sa/4.0/
Automated driving has the potential to revolutionize personal, public, and freight mobility. Beside accurately perceiving the environment, automated vehicles must plan a safe, comfortable, and efficient motion trajectory. To promote safety and progress, many works rely on modules that predict the future motion of sur...
[ { "created": "Thu, 10 Aug 2023 17:53:03 GMT", "version": "v1" }, { "created": "Wed, 17 Jul 2024 09:35:26 GMT", "version": "v2" } ]
2024-07-18
[ [ "Hagedorn", "Steffen", "" ], [ "Hallgarten", "Marcel", "" ], [ "Stoll", "Martin", "" ], [ "Condurache", "Alexandru", "" ] ]
Automated driving has the potential to revolutionize personal, public, and freight mobility. Beside accurately perceiving the environment, automated vehicles must plan a safe, comfortable, and efficient motion trajectory. To promote safety and progress, many works rely on modules that predict the future motion of surro...
1906.06821
Shiliang Sun
Shiliang Sun, Zehui Cao, Han Zhu, and Jing Zhao
A Survey of Optimization Methods from a Machine Learning Perspective
null
null
null
null
cs.LG math.OC stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Machine learning develops rapidly, which has made many theoretical breakthroughs and is widely applied in various fields. Optimization, as an important part of machine learning, has attracted much attention of researchers. With the exponential growth of data amount and the increase of model complexity, optimization m...
[ { "created": "Mon, 17 Jun 2019 02:54:51 GMT", "version": "v1" }, { "created": "Wed, 23 Oct 2019 08:26:31 GMT", "version": "v2" } ]
2019-10-24
[ [ "Sun", "Shiliang", "" ], [ "Cao", "Zehui", "" ], [ "Zhu", "Han", "" ], [ "Zhao", "Jing", "" ] ]
Machine learning develops rapidly, which has made many theoretical breakthroughs and is widely applied in various fields. Optimization, as an important part of machine learning, has attracted much attention of researchers. With the exponential growth of data amount and the increase of model complexity, optimization met...
2309.08849
Yu Zhang
Yu Zhang, Yongxiang Zou, Haoyu Zhang, Xiuze Xia and Long Cheng
Learning a Stable Dynamic System with a Lyapunov Energy Function for Demonstratives Using Neural Networks
null
null
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Autonomous Dynamic System (DS)-based algorithms hold a pivotal and foundational role in the field of Learning from Demonstration (LfD). Nevertheless, they confront the formidable challenge of striking a delicate balance between achieving precision in learning and ensuring the overall stability of the system. In respo...
[ { "created": "Sat, 16 Sep 2023 03:03:53 GMT", "version": "v1" }, { "created": "Fri, 23 Feb 2024 16:43:54 GMT", "version": "v2" }, { "created": "Mon, 26 Feb 2024 06:20:40 GMT", "version": "v3" }, { "created": "Tue, 5 Mar 2024 17:08:31 GMT", "version": "v4" }, { "cr...
2024-05-14
[ [ "Zhang", "Yu", "" ], [ "Zou", "Yongxiang", "" ], [ "Zhang", "Haoyu", "" ], [ "Xia", "Xiuze", "" ], [ "Cheng", "Long", "" ] ]
Autonomous Dynamic System (DS)-based algorithms hold a pivotal and foundational role in the field of Learning from Demonstration (LfD). Nevertheless, they confront the formidable challenge of striking a delicate balance between achieving precision in learning and ensuring the overall stability of the system. In respons...
2406.15053
Ishaan Watts
Ishaan Watts, Varun Gumma, Aditya Yadavalli, Vivek Seshadri, Manohar Swaminathan and Sunayana Sitaram
PARIKSHA : A Large-Scale Investigation of Human-LLM Evaluator Agreement on Multilingual and Multi-Cultural Data
Work in progress
null
null
null
cs.CL
http://creativecommons.org/licenses/by/4.0/
Evaluation of multilingual Large Language Models (LLMs) is challenging due to a variety of factors -- the lack of benchmarks with sufficient linguistic diversity, contamination of popular benchmarks into LLM pre-training data and the lack of local, cultural nuances in translated benchmarks. In this work, we study hum...
[ { "created": "Fri, 21 Jun 2024 11:00:38 GMT", "version": "v1" } ]
2024-06-24
[ [ "Watts", "Ishaan", "" ], [ "Gumma", "Varun", "" ], [ "Yadavalli", "Aditya", "" ], [ "Seshadri", "Vivek", "" ], [ "Swaminathan", "Manohar", "" ], [ "Sitaram", "Sunayana", "" ] ]
Evaluation of multilingual Large Language Models (LLMs) is challenging due to a variety of factors -- the lack of benchmarks with sufficient linguistic diversity, contamination of popular benchmarks into LLM pre-training data and the lack of local, cultural nuances in translated benchmarks. In this work, we study human...
2105.10282
Mohsen Pourghasemian
Mohsen Pourghasemian, Mohammad Reza Abedi, Shima Salarhosseini, Nader Mokari, Mohammad Reza Javan, Eduard A. Jorswieck
AI-Based and Mobility-Aware Energy Efficient Resource Allocation and Trajectory Design for NFV Enabled Aerial Networks
null
null
null
null
cs.NI eess.SP
http://creativecommons.org/licenses/by/4.0/
In this paper, we propose a novel joint intelligent trajectory design and resource allocation algorithm based on user's mobility and their requested services for unmanned aerial vehicles (UAVs) assisted networks, where UAVs act as nodes of a network function virtualization (NFV) enabled network. Our objective is to m...
[ { "created": "Fri, 21 May 2021 11:13:06 GMT", "version": "v1" } ]
2021-05-24
[ [ "Pourghasemian", "Mohsen", "" ], [ "Abedi", "Mohammad Reza", "" ], [ "Salarhosseini", "Shima", "" ], [ "Mokari", "Nader", "" ], [ "Javan", "Mohammad Reza", "" ], [ "Jorswieck", "Eduard A.", "" ] ]
In this paper, we propose a novel joint intelligent trajectory design and resource allocation algorithm based on user's mobility and their requested services for unmanned aerial vehicles (UAVs) assisted networks, where UAVs act as nodes of a network function virtualization (NFV) enabled network. Our objective is to max...
1801.09029
Shahram Shahsavari
Shahram Shahsavari, S. Amir Hosseini, Chris Ng, and Elza Erkip
Adaptive Hybrid Beamforming with Massive Phased Arrays in Macro-Cellular Networks
null
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Hybrid beamforming via large antenna arrays has shown a great potential for increasing data rate in cellular networks by delivering multiple data streams simultaneously. In this paper, several beamforming design algorithms are proposed based on the long-term channel information for macro-cellular environments where t...
[ { "created": "Sat, 27 Jan 2018 03:38:34 GMT", "version": "v1" }, { "created": "Sat, 3 Feb 2018 23:36:20 GMT", "version": "v2" } ]
2018-02-06
[ [ "Shahsavari", "Shahram", "" ], [ "Hosseini", "S. Amir", "" ], [ "Ng", "Chris", "" ], [ "Erkip", "Elza", "" ] ]
Hybrid beamforming via large antenna arrays has shown a great potential for increasing data rate in cellular networks by delivering multiple data streams simultaneously. In this paper, several beamforming design algorithms are proposed based on the long-term channel information for macro-cellular environments where the...
2407.13483
Hao Lu
Yujia Liang, Zixuan Ye, Wenze Liu, Hao Lu
SCAPE: A Simple and Strong Category-Agnostic Pose Estimator
Accepted to ECCV 2024. Code is available at https://github.com/tiny-smart/SCAPE
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Category-Agnostic Pose Estimation (CAPE) aims to localize keypoints on an object of any category given few exemplars in an in-context manner. Prior arts involve sophisticated designs, e.g., sundry modules for similarity calculation and a two-stage framework, or takes in extra heatmap generation and supervision. We no...
[ { "created": "Thu, 18 Jul 2024 13:02:57 GMT", "version": "v1" } ]
2024-07-19
[ [ "Liang", "Yujia", "" ], [ "Ye", "Zixuan", "" ], [ "Liu", "Wenze", "" ], [ "Lu", "Hao", "" ] ]
Category-Agnostic Pose Estimation (CAPE) aims to localize keypoints on an object of any category given few exemplars in an in-context manner. Prior arts involve sophisticated designs, e.g., sundry modules for similarity calculation and a two-stage framework, or takes in extra heatmap generation and supervision. We noti...
2106.14943
Pu Zhao
Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Bin Ren, Yanzhi Wang, Xue Lin
Achieving Real-Time Object Detection on MobileDevices with Neural Pruning Search
Presented on the HiPEAC 2021 workshop (cogarch 2021)
null
null
null
cs.CV cs.AI
http://creativecommons.org/licenses/by-sa/4.0/
Object detection plays an important role in self-driving cars for security development. However, mobile systems on self-driving cars with limited computation resources lead to difficulties for object detection. To facilitate this, we propose a compiler-aware neural pruning search framework to achieve high-speed infer...
[ { "created": "Mon, 28 Jun 2021 18:59:20 GMT", "version": "v1" } ]
2021-06-30
[ [ "Zhao", "Pu", "" ], [ "Niu", "Wei", "" ], [ "Yuan", "Geng", "" ], [ "Cai", "Yuxuan", "" ], [ "Ren", "Bin", "" ], [ "Wang", "Yanzhi", "" ], [ "Lin", "Xue", "" ] ]
Object detection plays an important role in self-driving cars for security development. However, mobile systems on self-driving cars with limited computation resources lead to difficulties for object detection. To facilitate this, we propose a compiler-aware neural pruning search framework to achieve high-speed inferen...
2212.06714
Wenshuo Li
Wenshuo Li
CNN-transformer mixed model for object detection
null
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Object detection, one of the three main tasks of computer vision, has been used in various applications. The main process is to use deep neural networks to extract the features of an image and then use the features to identify the class and location of an object. Therefore, the main direction to improve the accuracy ...
[ { "created": "Tue, 13 Dec 2022 16:35:35 GMT", "version": "v1" } ]
2022-12-14
[ [ "Li", "Wenshuo", "" ] ]
Object detection, one of the three main tasks of computer vision, has been used in various applications. The main process is to use deep neural networks to extract the features of an image and then use the features to identify the class and location of an object. Therefore, the main direction to improve the accuracy of...
2108.13886
Yanqiao Zhu
Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu, Shu Wu
Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning
KDD Workshop on Deep Learning on Graphs: Method and Applications (DLG@KDD 2021)
null
null
null
cs.LG cs.SI
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recently, heterogeneous Graph Neural Networks (GNNs) have become a de facto model for analyzing HGs, while most of them rely on a relative large number of labeled data. In this work, we investigate Contrastive Learning (CL), a key component in self-supervised approaches, on HGs to alleviate the label scarcity problem...
[ { "created": "Tue, 31 Aug 2021 14:44:49 GMT", "version": "v1" } ]
2021-09-01
[ [ "Zhu", "Yanqiao", "" ], [ "Xu", "Yichen", "" ], [ "Cui", "Hejie", "" ], [ "Yang", "Carl", "" ], [ "Liu", "Qiang", "" ], [ "Wu", "Shu", "" ] ]
Recently, heterogeneous Graph Neural Networks (GNNs) have become a de facto model for analyzing HGs, while most of them rely on a relative large number of labeled data. In this work, we investigate Contrastive Learning (CL), a key component in self-supervised approaches, on HGs to alleviate the label scarcity problem. ...
2203.13716
Muhammad Zaigham Zaheer
Muhammad Zaigham Zaheer, Jin Ha Lee, Arif Mahmood, Marcella Astrid, Seung-Ik Lee
Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies
This work has been submitted to the IEEE Transactions on Image Processing for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible
null
null
null
cs.CV
http://creativecommons.org/licenses/by-nc-sa/4.0/
Recently, anomaly scores have been formulated using reconstruction loss of the adversarially learned generators and/or classification loss of discriminators. Unavailability of anomaly examples in the training data makes optimization of such networks challenging. Attributed to the adversarial training, performance of ...
[ { "created": "Fri, 25 Mar 2022 15:37:52 GMT", "version": "v1" } ]
2022-03-28
[ [ "Zaheer", "Muhammad Zaigham", "" ], [ "Lee", "Jin Ha", "" ], [ "Mahmood", "Arif", "" ], [ "Astrid", "Marcella", "" ], [ "Lee", "Seung-Ik", "" ] ]
Recently, anomaly scores have been formulated using reconstruction loss of the adversarially learned generators and/or classification loss of discriminators. Unavailability of anomaly examples in the training data makes optimization of such networks challenging. Attributed to the adversarial training, performance of su...
2108.10515
Shan An
Shan An, Guangfu Che, Jinghao Guo, Haogang Zhu, Junjie Ye, Fangru Zhou, Zhaoqi Zhu, Dong Wei, Aishan Liu, Wei Zhang
ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones
Accepted by ACM Multimedia 2021
null
10.1145/3474085.3481537
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
Virtual try-on technology enables users to try various fashion items using augmented reality and provides a convenient online shopping experience. However, most previous works focus on the virtual try-on for clothes while neglecting that for shoes, which is also a promising task. To this concern, this work proposes a...
[ { "created": "Tue, 24 Aug 2021 03:54:45 GMT", "version": "v1" } ]
2021-08-25
[ [ "An", "Shan", "" ], [ "Che", "Guangfu", "" ], [ "Guo", "Jinghao", "" ], [ "Zhu", "Haogang", "" ], [ "Ye", "Junjie", "" ], [ "Zhou", "Fangru", "" ], [ "Zhu", "Zhaoqi", "" ], [ "Wei", "Dong", ...
Virtual try-on technology enables users to try various fashion items using augmented reality and provides a convenient online shopping experience. However, most previous works focus on the virtual try-on for clothes while neglecting that for shoes, which is also a promising task. To this concern, this work proposes a r...
1901.10501
Hao Wang
Hao Wang, Berk Ustun, Flavio P. Calmon
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions
null
null
null
null
cs.LG cs.CY cs.IT math.IT stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
When the performance of a machine learning model varies over groups defined by sensitive attributes (e.g., gender or ethnicity), the performance disparity can be expressed in terms of the probability distributions of the input and output variables over each group. In this paper, we exploit this fact to reduce the dis...
[ { "created": "Tue, 29 Jan 2019 19:21:10 GMT", "version": "v1" }, { "created": "Fri, 17 May 2019 15:42:11 GMT", "version": "v2" } ]
2019-05-20
[ [ "Wang", "Hao", "" ], [ "Ustun", "Berk", "" ], [ "Calmon", "Flavio P.", "" ] ]
When the performance of a machine learning model varies over groups defined by sensitive attributes (e.g., gender or ethnicity), the performance disparity can be expressed in terms of the probability distributions of the input and output variables over each group. In this paper, we exploit this fact to reduce the dispa...
2108.01612
Saeideh Nabipour
Saeideh Nabipour, Javad Javidan, Majid Khorrami, Jila Azimzadeh
An Efficient Digital Watermarking Algorithm Based on DCT and BCH Error Correcting Code
null
null
null
null
cs.MM cs.CR cs.IT math.IT
http://creativecommons.org/licenses/by/4.0/
Watermarking is a technique for hiding of data in a medium coverage so that its presence is not detectable by a human eye and is recoverable only by the authorized recipient. Two of the most important features of watermarked image are transparency and robustness which are largely related to the security of watermarki...
[ { "created": "Tue, 3 Aug 2021 16:30:23 GMT", "version": "v1" }, { "created": "Mon, 29 Aug 2022 07:53:32 GMT", "version": "v2" }, { "created": "Thu, 17 Nov 2022 14:43:31 GMT", "version": "v3" } ]
2022-11-18
[ [ "Nabipour", "Saeideh", "" ], [ "Javidan", "Javad", "" ], [ "Khorrami", "Majid", "" ], [ "Azimzadeh", "Jila", "" ] ]
Watermarking is a technique for hiding of data in a medium coverage so that its presence is not detectable by a human eye and is recoverable only by the authorized recipient. Two of the most important features of watermarked image are transparency and robustness which are largely related to the security of watermarking...
1805.02790
Amy Tai
Amy Tai, Andrew Kryczka, Shobhit Kanaujia, Chris Petersen, Mikhail Antonov, Muhammad Waliji, Kyle Jamieson, Michael J. Freedman, Asaf Cidon
Live Recovery of Bit Corruptions in Datacenter Storage Systems
null
null
null
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Due to its high performance and decreasing cost per bit, flash is becoming the main storage medium in datacenters for hot data. However, flash endurance is a perpetual problem, and due to technology trends, subsequent generations of flash devices exhibit progressively shorter lifetimes before they experience uncorrec...
[ { "created": "Tue, 8 May 2018 00:58:10 GMT", "version": "v1" }, { "created": "Wed, 9 May 2018 00:34:44 GMT", "version": "v2" } ]
2018-05-10
[ [ "Tai", "Amy", "" ], [ "Kryczka", "Andrew", "" ], [ "Kanaujia", "Shobhit", "" ], [ "Petersen", "Chris", "" ], [ "Antonov", "Mikhail", "" ], [ "Waliji", "Muhammad", "" ], [ "Jamieson", "Kyle", "" ], [ ...
Due to its high performance and decreasing cost per bit, flash is becoming the main storage medium in datacenters for hot data. However, flash endurance is a perpetual problem, and due to technology trends, subsequent generations of flash devices exhibit progressively shorter lifetimes before they experience uncorrecta...
1603.04037
Umar Iqbal
Umar Iqbal, Martin Garbade, Juergen Gall
Pose for Action - Action for Pose
Accepted to FG-2017
null
null
null
cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this work we propose to utilize information about human actions to improve pose estimation in monocular videos. To this end, we present a pictorial structure model that exploits high-level information about activities to incorporate higher-order part dependencies by modeling action specific appearance models and p...
[ { "created": "Sun, 13 Mar 2016 15:09:35 GMT", "version": "v1" }, { "created": "Fri, 10 Feb 2017 14:01:09 GMT", "version": "v2" } ]
2017-02-13
[ [ "Iqbal", "Umar", "" ], [ "Garbade", "Martin", "" ], [ "Gall", "Juergen", "" ] ]
In this work we propose to utilize information about human actions to improve pose estimation in monocular videos. To this end, we present a pictorial structure model that exploits high-level information about activities to incorporate higher-order part dependencies by modeling action specific appearance models and pos...
1911.05055
Brian Wandell
Fabian H. Reith and Brian A. Wandell
A convolutional neural network reaches optimal sensitivity for detecting some, but not all, patterns
22 pages, 8 figures, pre-print
null
null
null
cs.CV
http://creativecommons.org/licenses/by/4.0/
We investigate the performance of modern convolutional neural networks (CNN) and a linear support vector machine (SVM) with respect to spatial contrast sensitivity. Specifically, we compare CNN sensitivity to that of a Bayesian ideal observer (IO) with the signal-known-exactly and noise known statistically. A ResNet-...
[ { "created": "Tue, 12 Nov 2019 18:26:02 GMT", "version": "v1" }, { "created": "Sat, 22 Feb 2020 20:27:01 GMT", "version": "v2" }, { "created": "Thu, 9 Jul 2020 17:49:59 GMT", "version": "v3" } ]
2020-07-10
[ [ "Reith", "Fabian H.", "" ], [ "Wandell", "Brian A.", "" ] ]
We investigate the performance of modern convolutional neural networks (CNN) and a linear support vector machine (SVM) with respect to spatial contrast sensitivity. Specifically, we compare CNN sensitivity to that of a Bayesian ideal observer (IO) with the signal-known-exactly and noise known statistically. A ResNet-18...
2103.05351
Xiaoxi Wei
Xiaoxi Wei, Pablo Ortega and A. Aldo Faisal
Inter-subject Deep Transfer Learning for Motor Imagery EEG Decoding
Accepted manuscript IEEE/EMBS Neural Engineering (NER) 2021
null
null
null
cs.LG
http://creativecommons.org/licenses/by/4.0/
Convolutional neural networks (CNNs) have become a powerful technique to decode EEG and have become the benchmark for motor imagery EEG Brain-Computer-Interface (BCI) decoding. However, it is still challenging to train CNNs on multiple subjects' EEG without decreasing individual performance. This is known as the nega...
[ { "created": "Tue, 9 Mar 2021 11:01:02 GMT", "version": "v1" } ]
2021-03-10
[ [ "Wei", "Xiaoxi", "" ], [ "Ortega", "Pablo", "" ], [ "Faisal", "A. Aldo", "" ] ]
Convolutional neural networks (CNNs) have become a powerful technique to decode EEG and have become the benchmark for motor imagery EEG Brain-Computer-Interface (BCI) decoding. However, it is still challenging to train CNNs on multiple subjects' EEG without decreasing individual performance. This is known as the negati...
2312.00055
Eadom Dessalene
Eadom Dessalene, Michael Maynord, Cornelia Ferm\"uller, and Yiannis Aloimonos
LEAP: LLM-Generation of Egocentric Action Programs
Dataset: https://drive.google.com/drive/folders/1Cpkw_TI1IIxXdzor0pOXG3rWJWuKU5Ex?usp=drive_link
null
null
null
cs.CV cs.LG cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We introduce LEAP (illustrated in Figure 1), a novel method for generating video-grounded action programs through use of a Large Language Model (LLM). These action programs represent the motoric, perceptual, and structural aspects of action, and consist of sub-actions, pre- and post-conditions, and control flows. LEA...
[ { "created": "Wed, 29 Nov 2023 04:25:52 GMT", "version": "v1" } ]
2023-12-04
[ [ "Dessalene", "Eadom", "" ], [ "Maynord", "Michael", "" ], [ "Fermüller", "Cornelia", "" ], [ "Aloimonos", "Yiannis", "" ] ]
We introduce LEAP (illustrated in Figure 1), a novel method for generating video-grounded action programs through use of a Large Language Model (LLM). These action programs represent the motoric, perceptual, and structural aspects of action, and consist of sub-actions, pre- and post-conditions, and control flows. LEAP'...
1910.04953
Chaitanya Mitash
Chaitanya Mitash, Bowen Wen, Kostas Bekris, and Abdeslam Boularias
Scene-level Pose Estimation for Multiple Instances of Densely Packed Objects
To appear at the Conference on Robot Learning (CoRL) - 2019
null
null
null
cs.RO cs.CV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
This paper introduces key machine learning operations that allow the realization of robust, joint 6D pose estimation of multiple instances of objects either densely packed or in unstructured piles from RGB-D data. The first objective is to learn semantic and instance-boundary detectors without manual labeling. An adv...
[ { "created": "Fri, 11 Oct 2019 03:17:55 GMT", "version": "v1" } ]
2019-10-14
[ [ "Mitash", "Chaitanya", "" ], [ "Wen", "Bowen", "" ], [ "Bekris", "Kostas", "" ], [ "Boularias", "Abdeslam", "" ] ]
This paper introduces key machine learning operations that allow the realization of robust, joint 6D pose estimation of multiple instances of objects either densely packed or in unstructured piles from RGB-D data. The first objective is to learn semantic and instance-boundary detectors without manual labeling. An adver...
2007.09120
Daniel Schneider
Daniel Schneider and Hannes Frey
Analytical Derivation of Outage Correlation in Random Media Access with Application to Average Consensus in Wireless Networks: Extended Paper Version
This is the extended version of the paper "Analytical Derivation of Outage Correlation in Random Media Access with Application to Average Consensus in Wireless Networks", IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2020
null
null
null
cs.IT cs.NI cs.SY eess.SY math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We study a finite and fixed relative formation of possibly mobile wireless networked nodes. The nodes apply average consensus to agree on a common value like the formation's center. %Performance of consensus in terms of convergence speed is affected by message losses due path loss and interference. We assume framed s...
[ { "created": "Fri, 17 Jul 2020 17:19:30 GMT", "version": "v1" } ]
2020-07-20
[ [ "Schneider", "Daniel", "" ], [ "Frey", "Hannes", "" ] ]
We study a finite and fixed relative formation of possibly mobile wireless networked nodes. The nodes apply average consensus to agree on a common value like the formation's center. %Performance of consensus in terms of convergence speed is affected by message losses due path loss and interference. We assume framed slo...
2403.09933
Xingyu Liu
Pragna Mannam, Xingyu Liu, Ding Zhao, Jean Oh, Nancy Pollard
Design and Control Co-Optimization for Automated Design Iteration of Dexterous Anthropomorphic Soft Robotic Hands
null
IEEE-RAS International Conference on Soft Robotics (RoboSoft) 2024
null
null
cs.RO
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
We automate soft robotic hand design iteration by co-optimizing design and control policy for dexterous manipulation skills in simulation. Our design iteration pipeline combines genetic algorithms and policy transfer to learn control policies for nearly 400 hand designs, testing grasp quality under external force dis...
[ { "created": "Fri, 15 Mar 2024 00:17:38 GMT", "version": "v1" }, { "created": "Tue, 25 Jun 2024 23:26:47 GMT", "version": "v2" } ]
2024-06-27
[ [ "Mannam", "Pragna", "" ], [ "Liu", "Xingyu", "" ], [ "Zhao", "Ding", "" ], [ "Oh", "Jean", "" ], [ "Pollard", "Nancy", "" ] ]
We automate soft robotic hand design iteration by co-optimizing design and control policy for dexterous manipulation skills in simulation. Our design iteration pipeline combines genetic algorithms and policy transfer to learn control policies for nearly 400 hand designs, testing grasp quality under external force distu...
2405.01301
Angelo Feraudo
Angelo Feraudo, Andrea Garbugli, Paolo Bellavista
Controlling Communications Quality in V2V Platooning: a TSN-like Slot-Based Scheduler Approach
8 pages, WIP
null
null
null
cs.NI
http://creativecommons.org/licenses/by/4.0/
Connected vehicles, facilitated by Vehicle-to-Vehicle (V2V) communications, play a key role in enhancing road safety and traffic efficiency. However, V2V communications primarily rely on wireless protocols, such as Wi-Fi, that require additional collision avoidance mechanisms to better ensure bounded latency and reli...
[ { "created": "Thu, 2 May 2024 14:06:31 GMT", "version": "v1" } ]
2024-05-03
[ [ "Feraudo", "Angelo", "" ], [ "Garbugli", "Andrea", "" ], [ "Bellavista", "Paolo", "" ] ]
Connected vehicles, facilitated by Vehicle-to-Vehicle (V2V) communications, play a key role in enhancing road safety and traffic efficiency. However, V2V communications primarily rely on wireless protocols, such as Wi-Fi, that require additional collision avoidance mechanisms to better ensure bounded latency and reliab...
1903.00167
Chul-Ho Lee
Chul-Ho Lee, Srinivas Tenneti, Do Young Eun
Transient Dynamics of Epidemic Spreading and Its Mitigation on Large Networks
A conference version of this paper will appear in ACM MobiHoc 2019
null
null
null
cs.SI physics.soc-ph
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we aim to understand the transient dynamics of a susceptible-infected (SI) epidemic spreading process on a large network. The SI model has been largely overlooked in the literature, while it is naturally a better fit for modeling the malware propagation in early times when patches/vaccines are not avai...
[ { "created": "Fri, 1 Mar 2019 06:05:44 GMT", "version": "v1" }, { "created": "Tue, 9 Apr 2019 21:22:32 GMT", "version": "v2" }, { "created": "Mon, 20 May 2019 12:18:31 GMT", "version": "v3" } ]
2019-05-21
[ [ "Lee", "Chul-Ho", "" ], [ "Tenneti", "Srinivas", "" ], [ "Eun", "Do Young", "" ] ]
In this paper, we aim to understand the transient dynamics of a susceptible-infected (SI) epidemic spreading process on a large network. The SI model has been largely overlooked in the literature, while it is naturally a better fit for modeling the malware propagation in early times when patches/vaccines are not availa...
1905.10889
Andy Zaidman
Gemma Catolino and Fabio Palomba and Francesca Arcelli Fontana and Andrea De Lucia and Andy Zaidman and Filomena Ferrucci
Improving Change Prediction Models with Code Smell-Related Information
null
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Code smells represent sub-optimal implementation choices applied by developers when evolving software systems. The negative impact of code smells has been widely investigated in the past: besides developers' productivity and ability to comprehend source code, researchers empirically showed that the presence of code s...
[ { "created": "Sun, 26 May 2019 21:44:29 GMT", "version": "v1" } ]
2019-05-28
[ [ "Catolino", "Gemma", "" ], [ "Palomba", "Fabio", "" ], [ "Fontana", "Francesca Arcelli", "" ], [ "De Lucia", "Andrea", "" ], [ "Zaidman", "Andy", "" ], [ "Ferrucci", "Filomena", "" ] ]
Code smells represent sub-optimal implementation choices applied by developers when evolving software systems. The negative impact of code smells has been widely investigated in the past: besides developers' productivity and ability to comprehend source code, researchers empirically showed that the presence of code sme...
2405.18216
Zezhou Yang
Zezhou Yang, Cuiyun Gao, Zhaoqiang Guo, Zhenhao Li, Kui Liu, Xin Xia, Yuming Zhou
A Survey on Modern Code Review: Progresses, Challenges and Opportunities
62 pages
null
null
null
cs.SE
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Over the past decade, modern code review (MCR) has been deemed as a crucial practice of software quality assurance, which is applied to improve software quality and transfer development knowledge within a software team. Despite its importance, MCR is often a complicated and time-consuming activity for practitioners. ...
[ { "created": "Tue, 28 May 2024 14:20:38 GMT", "version": "v1" } ]
2024-05-29
[ [ "Yang", "Zezhou", "" ], [ "Gao", "Cuiyun", "" ], [ "Guo", "Zhaoqiang", "" ], [ "Li", "Zhenhao", "" ], [ "Liu", "Kui", "" ], [ "Xia", "Xin", "" ], [ "Zhou", "Yuming", "" ] ]
Over the past decade, modern code review (MCR) has been deemed as a crucial practice of software quality assurance, which is applied to improve software quality and transfer development knowledge within a software team. Despite its importance, MCR is often a complicated and time-consuming activity for practitioners. In...
1607.05142
Matthias Gall\'e
Matthias Galle, Jean-Michel Renders, Guillaume Jacquet
Joint Event Detection and Entity Resolution: a Virtuous Cycle
null
null
null
null
cs.CL
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Clustering web documents has numerous applications, such as aggregating news articles into meaningful events, detecting trends and hot topics on the Web, preserving diversity in search results, etc. At the same time, the importance of named entities and, in particular, the ability to recognize them and to solve the a...
[ { "created": "Mon, 18 Jul 2016 15:51:11 GMT", "version": "v1" } ]
2016-07-19
[ [ "Galle", "Matthias", "" ], [ "Renders", "Jean-Michel", "" ], [ "Jacquet", "Guillaume", "" ] ]
Clustering web documents has numerous applications, such as aggregating news articles into meaningful events, detecting trends and hot topics on the Web, preserving diversity in search results, etc. At the same time, the importance of named entities and, in particular, the ability to recognize them and to solve the ass...
2212.08755
Aurelien Bouteiller
Aurelien Bouteiller and George Bosilca
Implicit Actions and Non-blocking Failure Recovery with MPI
Accepted in FTXS'22 https://sites.google.com/view/ftxs2022
null
10.1109/FTXS56515.2022.00009
null
cs.DC
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Scientific applications have long embraced the MPI as the environment of choice to execute on large distributed systems. The User-Level Failure Mitigation (ULFM) specification extends the MPI standard to address resilience and enable MPI applications to restore their communication capability after a failure. This wor...
[ { "created": "Fri, 16 Dec 2022 23:29:33 GMT", "version": "v1" } ]
2023-01-27
[ [ "Bouteiller", "Aurelien", "" ], [ "Bosilca", "George", "" ] ]
Scientific applications have long embraced the MPI as the environment of choice to execute on large distributed systems. The User-Level Failure Mitigation (ULFM) specification extends the MPI standard to address resilience and enable MPI applications to restore their communication capability after a failure. This works...
2312.08214
Hamed Alizadeh Ghazijahani Dr.
Mahmoud Atashbar, Hamed Alizadeh Ghazijahani, Yong Liang Guan, Zhaojie Yang
A Precoding for ORIS-Assisted MIMO Multi-User VLC System
5 pages, 3 figures
null
null
null
cs.IT eess.SP math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we study a multi-user visible light communication (VLC) system assisted with optical reflecting intelligent surface (ORIS). Joint precoding and alignment matrices are designed to maximize the average signal-to-interference plus noise ratio (SINR) criteria. Considering the constraints of the constant me...
[ { "created": "Wed, 13 Dec 2023 15:33:09 GMT", "version": "v1" } ]
2023-12-14
[ [ "Atashbar", "Mahmoud", "" ], [ "Ghazijahani", "Hamed Alizadeh", "" ], [ "Guan", "Yong Liang", "" ], [ "Yang", "Zhaojie", "" ] ]
In this paper, we study a multi-user visible light communication (VLC) system assisted with optical reflecting intelligent surface (ORIS). Joint precoding and alignment matrices are designed to maximize the average signal-to-interference plus noise ratio (SINR) criteria. Considering the constraints of the constant mean...
1507.07115
Qingjiang Shi
Qingjiang Shi, Meisam Razavayan, Mingyi Hong, Zhi-Quan Luo
SINR Constrained Beamforming for a MIMO Multi-user Downlink System
34 pages, 6 figures
null
null
null
cs.IT math.IT
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Consider a multi-input multi-output (MIMO) downlink multi-user channel. A well-studied problem in such system is the design of linear beamformers for power minimization with the quality of service (QoS) constraints. The most representative algorithms for solving this class of problems are the so-called MMSE-SOCP algo...
[ { "created": "Sat, 25 Jul 2015 16:21:23 GMT", "version": "v1" } ]
2015-07-28
[ [ "Shi", "Qingjiang", "" ], [ "Razavayan", "Meisam", "" ], [ "Hong", "Mingyi", "" ], [ "Luo", "Zhi-Quan", "" ] ]
Consider a multi-input multi-output (MIMO) downlink multi-user channel. A well-studied problem in such system is the design of linear beamformers for power minimization with the quality of service (QoS) constraints. The most representative algorithms for solving this class of problems are the so-called MMSE-SOCP algori...
2109.03292
Vikram Voleti
David Kanaa and Vikram Voleti and Samira Ebrahimi Kahou and Christopher Pal
Simple Video Generation using Neural ODEs
8 pages, 4 figures, NeurIPS 2019 workshop
NeurIPS 2019 Workshop
null
null
cs.CV cs.LG eess.IV
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Despite having been studied to a great extent, the task of conditional generation of sequences of frames, or videos, remains extremely challenging. It is a common belief that a key step towards solving this task resides in modelling accurately both spatial and temporal information in video signals. A promising direct...
[ { "created": "Tue, 7 Sep 2021 19:03:33 GMT", "version": "v1" } ]
2021-09-09
[ [ "Kanaa", "David", "" ], [ "Voleti", "Vikram", "" ], [ "Kahou", "Samira Ebrahimi", "" ], [ "Pal", "Christopher", "" ] ]
Despite having been studied to a great extent, the task of conditional generation of sequences of frames, or videos, remains extremely challenging. It is a common belief that a key step towards solving this task resides in modelling accurately both spatial and temporal information in video signals. A promising directio...
2004.04286
Masoud Salehpour
Masoud Salehpour and Joseph G. Davis
The Effects of Different JSON Representations on Querying Knowledge Graphs
null
null
null
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Knowledge Graphs (KGs) have emerged as the de-facto standard for modeling and querying datasets with a graph-like structure in the Semantic Web domain. Our focus is on the performance challenges associated with querying KGs. We developed three informationally equivalent JSON-based representations for KGs, namely, Sub...
[ { "created": "Wed, 8 Apr 2020 22:37:39 GMT", "version": "v1" } ]
2020-04-10
[ [ "Salehpour", "Masoud", "" ], [ "Davis", "Joseph G.", "" ] ]
Knowledge Graphs (KGs) have emerged as the de-facto standard for modeling and querying datasets with a graph-like structure in the Semantic Web domain. Our focus is on the performance challenges associated with querying KGs. We developed three informationally equivalent JSON-based representations for KGs, namely, Subje...
1902.09584
Wensheng Gan
Wensheng Gan, Jerry Chun-Wei Lin, Philippe Fournier-Viger, Han-Chieh Chao, and Philip S Yu
Beyond Frequency: Utility Mining with Varied Item-Specific Minimum Utility
Under review in ACM Trans. on Data Science, 31 pages
ACM Transactions on Internet Technology, 2021
10.1145/3425498
null
cs.DB
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Utility-oriented mining which integrates utility theory and data mining is a useful tool for understanding economic consumer behavior. Traditional algorithms for mining high-utility patterns (HUPs) applies a single/uniform minimum high-utility threshold (minutil) to obtain the set of HUPs, but in some real-life circu...
[ { "created": "Mon, 25 Feb 2019 19:41:15 GMT", "version": "v1" } ]
2021-04-01
[ [ "Gan", "Wensheng", "" ], [ "Lin", "Jerry Chun-Wei", "" ], [ "Fournier-Viger", "Philippe", "" ], [ "Chao", "Han-Chieh", "" ], [ "Yu", "Philip S", "" ] ]
Utility-oriented mining which integrates utility theory and data mining is a useful tool for understanding economic consumer behavior. Traditional algorithms for mining high-utility patterns (HUPs) applies a single/uniform minimum high-utility threshold (minutil) to obtain the set of HUPs, but in some real-life circums...
1403.7380
Nikolaos Kavvadias
Nikolaos Kavvadias
Generating and evaluating application-specific hardware extensions
11 pages, 15 figures, 5 tables. An unpublished journal paper presenting the YARDstick custom instruction generation environment
null
null
null
cs.AR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Modern platform-based design involves the application-specific extension of embedded processors to fit customer requirements. To accomplish this task, the possibilities offered by recent custom/extensible processors for tuning their instruction set and microarchitecture to the applications of interest have to be expl...
[ { "created": "Fri, 28 Mar 2014 14:06:17 GMT", "version": "v1" } ]
2014-03-31
[ [ "Kavvadias", "Nikolaos", "" ] ]
Modern platform-based design involves the application-specific extension of embedded processors to fit customer requirements. To accomplish this task, the possibilities offered by recent custom/extensible processors for tuning their instruction set and microarchitecture to the applications of interest have to be exploi...
1204.4498
Martin Haenggi
Martin Haenggi
Diversity Loss due to Interference Correlation
4 pages, 5 figures
null
null
null
cs.IT cs.NI math.IT math.PR
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Interference in wireless systems is both temporally and spatially correlated. Yet very little research has analyzed the effect of such correlation. Here we focus on its impact on the diversity in Poisson networks with multi-antenna receivers. Most work on multi-antenna communication does not consider interference, an...
[ { "created": "Thu, 19 Apr 2012 23:33:23 GMT", "version": "v1" } ]
2012-04-23
[ [ "Haenggi", "Martin", "" ] ]
Interference in wireless systems is both temporally and spatially correlated. Yet very little research has analyzed the effect of such correlation. Here we focus on its impact on the diversity in Poisson networks with multi-antenna receivers. Most work on multi-antenna communication does not consider interference, and ...
1509.00536
Masashi Wakaiki Dr.
Masashi Wakaiki and Yutaka Yamamoto
Stabilization of continuous-time switched linear systems with quantized output feedback
This journal-version paper is based on the conference paper (arXiv:1403.4670)
null
null
null
cs.SY
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this paper, we study the problem of stabilizing continuous-time switched linear systems with quantized output feedback. We assume that the observer and the control gain are given for each mode. Also, the plant mode is known to the controller and the quantizer. Extending the result in the non-switched case, we deve...
[ { "created": "Wed, 2 Sep 2015 01:21:59 GMT", "version": "v1" } ]
2015-09-03
[ [ "Wakaiki", "Masashi", "" ], [ "Yamamoto", "Yutaka", "" ] ]
In this paper, we study the problem of stabilizing continuous-time switched linear systems with quantized output feedback. We assume that the observer and the control gain are given for each mode. Also, the plant mode is known to the controller and the quantizer. Extending the result in the non-switched case, we develo...
2003.03819
Yongxing Wang
Yongxing Wang, Peter K. Jimack, Mark A. Walkley and Olivier Pironneau
An energy stable one-field monolithic arbitrary Lagrangian-Eulerian formulation for fluid-structure interaction
null
null
10.1016/j.jfluidstructs.2020.103117
null
cs.CE math.AP
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
In this article we present a one-field monolithic finite element method in the Arbitrary Lagrangian-Eulerian (ALE) formulation for Fluid-Structure Interaction (FSI) problems. The method only solves for one velocity field in the whole FSI domain, and it solves in a monolithic manner so that the fluid solid interface c...
[ { "created": "Sun, 8 Mar 2020 17:53:44 GMT", "version": "v1" } ]
2020-08-26
[ [ "Wang", "Yongxing", "" ], [ "Jimack", "Peter K.", "" ], [ "Walkley", "Mark A.", "" ], [ "Pironneau", "Olivier", "" ] ]
In this article we present a one-field monolithic finite element method in the Arbitrary Lagrangian-Eulerian (ALE) formulation for Fluid-Structure Interaction (FSI) problems. The method only solves for one velocity field in the whole FSI domain, and it solves in a monolithic manner so that the fluid solid interface con...
1808.06640
Yanai Elazar
Yanai Elazar and Yoav Goldberg
Adversarial Removal of Demographic Attributes from Text Data
null
null
null
null
cs.CL cs.LG stat.ML
http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Recent advances in Representation Learning and Adversarial Training seem to succeed in removing unwanted features from the learned representation. We show that demographic information of authors is encoded in -- and can be recovered from -- the intermediate representations learned by text-based neural classifiers. Th...
[ { "created": "Mon, 20 Aug 2018 18:20:01 GMT", "version": "v1" }, { "created": "Sun, 2 Sep 2018 10:29:44 GMT", "version": "v2" } ]
2018-09-05
[ [ "Elazar", "Yanai", "" ], [ "Goldberg", "Yoav", "" ] ]
Recent advances in Representation Learning and Adversarial Training seem to succeed in removing unwanted features from the learned representation. We show that demographic information of authors is encoded in -- and can be recovered from -- the intermediate representations learned by text-based neural classifiers. The ...