cs.AI - 人工智能
cs.AR - 硬件体系结构 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 econ.GN - 一般经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]An Argumentation-based Approach for Identifying and Dealing with Incompatibilities among Procedural Goals
• [cs.AI]Counterfactual Explanations & Adversarial Examples — Common Grounds, Essential Differences, and Potential Transfers
• [cs.AI]Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering
• [cs.AI]Physically Embedded Planning Problems: New Challenges for Reinforcement Learning
• [cs.AI]Results of multi-agent system and ontology to manage ideas and represent knowledge in a challenge of creativity
• [cs.AI]Systematic Generalization on gSCAN with Language Conditioned Embedding
• [cs.AR]Accelerating Recommender Systems via Hardware “scale-in”
• [cs.AR]An Open-Source Platform for High-Performance Non-Coherent On-Chip Communication
• [cs.CL]A Comparison of LSTM and BERT for Small Corpus
• [cs.CL]Accelerating Real-Time Question Answering via Question Generation
• [cs.CL]Deep Learning for Semantic Relations
• [cs.CL]FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding
• [cs.CL]IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding
• [cs.CL]RadLex Normalization in Radiology Reports
• [cs.CL]Rank over Class: The Untapped Potential of Ranking in Natural Language Processing
• [cs.CL]Robust Neural Machine Translation: Modeling Orthographic and Interpunctual Variation
• [cs.CL]Sparsifying Transformer Models with Differentiable Representation Pooling
• [cs.CL]UPB at SemEval-2020 Task 11: Propaganda Detection with Domain-Specific Trained BERT
• [cs.CL]WOLI at SemEval-2020 Task 12: Arabic Offensive Language Identification on Different Twitter Datasets
• [cs.CL]Weakly Supervised Content Selection for Improved Image Captioning
• [cs.CR]A Smart Home System based on Internet of Things
• [cs.CR]Accelerating 2PC-based ML with Limited Trusted Hardware
• [cs.CR]Federated Model Distillation with Noise-Free Differential Privacy
• [cs.CR]Improving Robustness to Model Inversion Attacks via Mutual Information Regularization
• [cs.CV]A Density-Aware PointRCNN for 3D Objection Detection in Point Clouds
• [cs.CV]AFP-SRC: Identification of Antifreeze Proteins Using Sparse Representation Classifier
• [cs.CV]Adversarial Learning for Zero-shot Domain Adaptation
• [cs.CV]An unsupervised deep learning framework via integrated optimization of representation learning and GMM-based modeling
• [cs.CV]Attribute-conditioned Layout GAN for Automatic Graphic Design
• [cs.CV]Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation
• [cs.CV]Devil’s in the Detail: Graph-based Key-point Alignment and Embedding for Person Re-ID
• [cs.CV]Enabling Image Recognition on Constrained Devices Using Neural Network Pruning and a CycleGAN
• [cs.CV]Evaluation of the Robustness of Visual SLAM Methods in Different Environments
• [cs.CV]Fairness Matters — A Data-Driven Framework Towards Fair and High Performing Facial Recognition Systems
• [cs.CV]HAA500: Human-Centric Atomic Action Dataset with Curated Videos
• [cs.CV]Heterogeneous Domain Generalization via Domain Mixup
• [cs.CV]Hybrid Space Learning for Language-based Video Retrieval
• [cs.CV]Image Conditioned Keyframe-Based Video Summarization Using Object Detection
• [cs.CV]MRZ code extraction from visa and passport documents using convolutional neural networks
• [cs.CV]Meta Learning for Few-Shot One-class Classification
• [cs.CV]Novel and Effective CNN-Based Binarization for Historically Degraded As-built Drawing Maps
• [cs.CV]Optimizing Convolutional Neural Network Architecture via Information Field
• [cs.CV]PiaNet: A pyramid input augmented convolutional neural network for GGO detection in 3D lung CT scans
• [cs.CV]SoFAr: Shortcut-based Fractal Architectures for Binary Convolutional Neural Networks
• [cs.CV]Spectral Analysis Network for Deep Representation Learning and Image Clustering
• [cs.CV]TP-LSD: Tri-Points Based Line Segment Detector
• [cs.CV]The PREVENTION Challenge: How Good Are Humans Predicting Lane Changes?
• [cs.CV]Unsupervised Partial Point Set Registration via Joint Shape Completion and Registration
• [cs.CV]Variance Loss: A Confidence-Based Reweighting Strategy for Coarse Semantic Segmentation
• [cs.CY]”Is it a Qoincidence?”: A First Step Towards Understanding and Characterizing the QAnon Movement on Voat.co
• [cs.CY]A Review on Security and Privacy of Internet of Medical Things
• [cs.CY]Narratives and Needs: Analyzing Experiences of Cyclone Amphan Using Twitter Discourse
• [cs.CY]On the Fairness of ‘Fake’ Data in Legal AI
• [cs.DC]CASH: A Credit Aware Scheduling for Public Cloud Platforms
• [cs.DC]Hierarchical Roofline Performance Analysis for Deep Learning Applications
• [cs.DC]Kvik: A task based middleware with composable scheduling policies
• [cs.HC]Visually Analyzing and Steering Zero Shot Learning
• [cs.IR]Patient Cohort Retrieval using Transformer Language Models
• [cs.IR]TRec: Sequential Recommender Based On Latent Item Trend Information
• [cs.IT]An Improved Multi-access Coded Caching with Uncoded Placement
• [cs.IT]Capacity-Approaching Autoencoders for Communications
• [cs.IT]Construction of Hyperbolic Signal Sets from the Uniformization of Hyperelliptic Curves
• [cs.IT]Efficient Detectors for Telegram Splitting based Transmission in Low Power Wide Area Networks with Bursty Interference
• [cs.IT]End-to-end Learning for OFDM: From Neural Receivers to Pilotless Communication
• [cs.IT]Finite-Alphabet Wiener Filter Precoding for mmWave Massive MU-MIMO Systems
• [cs.IT]Generalized Energy Detection Under Generalized Noise Channels
• [cs.LG]A First Step Towards Distribution Invariant Regression Metrics
• [cs.LG]A kernel function for Signal Temporal Logic formulae
• [cs.LG]Accurate and Intuitive Contextual Explanations using Linear Model Trees
• [cs.LG]Achieving Adversarial Robustness via Sparsity
• [cs.LG]Adversarial score matching and improved sampling for image generation
• [cs.LG]CatGCN: Graph Convolutional Networks with Categorical Node Features
• [cs.LG]CounteRGAN: Generating Realistic Counterfactuals with Residual Generative Adversarial Nets
• [cs.LG]DART: Data Addition and Removal Trees
• [cs.LG]Deep Switching Auto-Regressive Factorization:Application to Time Series Forecasting
• [cs.LG]Defending Against Multiple and Unforeseen Adversarial Videos
• [cs.LG]Disentangling Neural Architectures and Weights: A Case Study in Supervised Classification
• [cs.LG]Extending Label Smoothing Regularization with Self-Knowledge Distillation
• [cs.LG]GTEA: Representation Learning for Temporal Interaction Graphs via Edge Aggregation
• [cs.LG]Learning Product Rankings Robust to Fake Users
• [cs.LG]Machine Learning and Data Science approach towards trend and predictors analysis of CDC Mortality Data for the USA
• [cs.LG]TREX: Tree-Ensemble Representer-Point Explanations
• [cs.LG]Towards Interpretable Multi-Task Learning Using Bilevel Programming
• [cs.LG]Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization
• [cs.LG]Visual Neural Decomposition to Explain Multivariate Data Sets
• [cs.NE]Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain
• [cs.NI]Graph Neural Network based Service Function Chaining for Automatic Network Control
• [cs.RO]A Toolkit to Generate Social Navigation Datasets
• [cs.RO]Embodied Visual Navigation with Automatic Curriculum Learning in Real Environments
• [cs.RO]Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning
• [cs.RO]Sentinel: An Onboard System for Intelligent Vehicles to Reduce Traffic Delay during Freeway Incidents
• [cs.RO]The Robotic Vision Scene Understanding Challenge
• [cs.RO]Towards Safe Locomotion Navigation in Partially Observable Environments with Uneven Terrain
• [cs.SD]SONYC-UST-V2: An Urban Sound Tagging Dataset with Spatiotemporal Context
• [cs.SE]The AIQ Meta-Testbed: Pragmatically Bridging Academic AI Testing and Industrial Q Needs
• [cs.SI]A deep-learning model for evaluating and predicting the impact of lockdown policies on COVID-19 cases
• [cs.SI]Beyond Localized Graph Neural Networks: An Attributed Motif Regularization Framework
• [cs.SI]CasGCN: Predicting future cascade growth based on information diffusion graph
• [cs.SI]Sequential seeding in multilayer networks
• [econ.EM]Inference for high-dimensional exchangeable arrays
• [econ.GN]Object Recognition for Economic Development from Daytime Satellite Imagery
• [eess.AS]On Multitask Loss Function for Audio Event Detection and Localization
• [eess.AS]RECOApy: Data recording, pre-processing and phonetic transcription for end-to-end speech-based applications
• [eess.IV]Boosting the Sliding Frank-Wolfe solver for 3D deconvolution
• [eess.IV]Phase Sampling Profilometry
• [eess.SP]Deep Transfer Learning for Signal Detection in Ambient Backscatter Communications
• [eess.SP]Energy-Efficient Design of IRS-NOMA Networks
• [eess.SP]Machine learning-based EDFA Gain Model Generalizable to Multiple Physical Devices
• [eess.SP]Power Evolution Prediction and Optimization in a Multi-span System Based on Component-wise System Modeling
• [math.ST]Bootstrap method for misspecified ergodic Lévy driven stochastic differential equation models
• [math.ST]Estimation of all parameters in the reflected Orntein-Uhlenbeck process from discrete observations
• [math.ST]Families of discrete circular distributions with some novel applications
• [math.ST]On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms
• [physics.comp-ph]Symplectic Gaussian Process Regression of Hamiltonian Flow Maps
• [physics.soc-ph]Community detection in networks using graph embeddings
• [physics.soc-ph]Information flow in political elections: a stochastic perspective
• [stat.AP]A Bayesian hierarchical model to estimate land surface phenology parameters with harmonized Landsat 8 and Sentinel-2 images
• [stat.AP]A Study on the Possible Effects of the Implementation of the Nordic Model in India on Crime Rates and Sexually Transmitted Diseases
• [stat.AP]Bayesian Beta-Binomial Prevalence Estimation Using an Imperfect Test
• [stat.AP]Explaining the Decline of Child Mortality in 44 Developing Countries: A Bayesian Extension of Oaxaca Decomposition Methods
• [stat.AP]Limousine Service Management: Capacity Planning with Predictive Analytics and Optimization
• [stat.AP]Modelling COVID-19 — I A dynamic SIR(D) with application to Indian data
• [stat.AP]Portfolio Decisions and Brain Reactions via the CEAD method
• [stat.AP]Power and sample size for cluster randomized and stepped wedge trials: Comparing estimates obtained by applying design effects or by direct estimation in GLMM
• [stat.AP]Probabilistic and mean-field model of COVID-19 epidemics with user mobility and contact tracing
• [stat.CO]Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes
• [stat.ME]A Family of Mixture Models for Biclustering
• [stat.ME]A simulation study of semiparametric estimation in copula models based on minimum Alpha-Divergence
• [stat.ME]Directional quantile classifiers
• [stat.ME]Finding Stable Groups of Cross-Correlated Features in Multi-View data
• [stat.ME]Narrowest Significance Pursuit: inference for multiple change-points in linear models
• [stat.ME]TCA and TLRA: A comparison on contingency tables and compositional data
• [stat.ML]Bayesian Screening: Multi-test Bayesian Optimization Applied to in silico Material Screening
• [stat.ML]Deducing neighborhoods of classes from a fitted model
• [stat.ML]Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems using Feature Importance Fusion
·····································
• [cs.AI]An Argumentation-based Approach for Identifying and Dealing with Incompatibilities among Procedural Goals
Mariela Morveli-Espinoza, Juan Carlos Nieves, Ayslan Possebom, Josep Puyol-Gruart, Cesar Augusto Tacla
http://arxiv.org/abs/2009.05186v1
• [cs.AI]Counterfactual Explanations & Adversarial Examples — Common Grounds, Essential Differences, and Potential Transfers
Timo Freiesleben
http://arxiv.org/abs/2009.05487v1
• [cs.AI]Multi-Goal Multi-Agent Path Finding via Decoupled and Integrated Goal Vertex Ordering
Pavel Surynek
http://arxiv.org/abs/2009.05161v1
• [cs.AI]Physically Embedded Planning Problems: New Challenges for Reinforcement Learning
Mehdi Mirza, Andrew Jaegle, Jonathan J. Hunt, Arthur Guez, Saran Tunyasuvunakool, Alistair Muldal, Théophane Weber, Peter Karkus, Sébastien Racanière, Lars Buesing, Timothy Lillicrap, Nicolas Heess
http://arxiv.org/abs/2009.05524v1
• [cs.AI]Results of multi-agent system and ontology to manage ideas and represent knowledge in a challenge of creativity
Pedro Barrios, Davy Monticolo, Sahbi Sidhom
http://arxiv.org/abs/2009.05282v1
• [cs.AI]Systematic Generalization on gSCAN with Language Conditioned Embedding
Tong Gao, Qi Huang, Raymond J. Mooney
http://arxiv.org/abs/2009.05552v1
• [cs.AR]Accelerating Recommender Systems via Hardware “scale-in”
Suresh Krishna, Ravi Krishna
http://arxiv.org/abs/2009.05230v1
• [cs.AR]An Open-Source Platform for High-Performance Non-Coherent On-Chip Communication
Andreas Kurth, Wolfgang Rönninger, Thomas Benz, Matheus Cavalcante, Fabian Schuiki, Florian Zaruba, Luca Benini
http://arxiv.org/abs/2009.05334v1
• [cs.CL]A Comparison of LSTM and BERT for Small Corpus
Aysu Ezen-Can
http://arxiv.org/abs/2009.05451v1
• [cs.CL]Accelerating Real-Time Question Answering via Question Generation
Yuwei Fang, Shuohang Wang, Zhe Gan, Siqi Sun, Jingjing Liu
http://arxiv.org/abs/2009.05167v1
• [cs.CL]Deep Learning for Semantic Relations
Vivi Nastase, Stan Szpakowicz
http://arxiv.org/abs/2009.05426v1
• [cs.CL]FILTER: An Enhanced Fusion Method for Cross-lingual Language Understanding
Yuwei Fang, Shuohang Wang, Zhe Gan, Siqi Sun, Jingjing Liu
http://arxiv.org/abs/2009.05166v1
• [cs.CL]IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding
Bryan Wilie, Karissa Vincentio, Genta Indra Winata, Samuel Cahyawijaya, Xiaohong Li, Zhi Yuan Lim, Sidik Soleman, Rahmad Mahendra, Pascale Fung, Syafri Bahar, Ayu Purwarianti
http://arxiv.org/abs/2009.05387v1
• [cs.CL]RadLex Normalization in Radiology Reports
Surabhi Datta, Jordan Godfrey-Stovall, Kirk Roberts
http://arxiv.org/abs/2009.05128v1
• [cs.CL]Rank over Class: The Untapped Potential of Ranking in Natural Language Processing
Amir Atapour-Abarghouei, Stephen Bonner, Andrew Stephen McGough
http://arxiv.org/abs/2009.05160v1
• [cs.CL]Robust Neural Machine Translation: Modeling Orthographic and Interpunctual Variation
Toms Bergmanis, Artūrs Stafanovičs, Mārcis Pinnis
http://arxiv.org/abs/2009.05460v1
• [cs.CL]Sparsifying Transformer Models with Differentiable Representation Pooling
Michał Pietruszka, Łukasz Borchmann, Filip Graliński
http://arxiv.org/abs/2009.05169v1
• [cs.CL]UPB at SemEval-2020 Task 11: Propaganda Detection with Domain-Specific Trained BERT
Andrei Paraschiv, Dumitru-Clementin Cercel, Mihai Dascalu
http://arxiv.org/abs/2009.05289v1
• [cs.CL]WOLI at SemEval-2020 Task 12: Arabic Offensive Language Identification on Different Twitter Datasets
Yasser Otiefy, Ahmed Abdelmalek, Islam El Hosary
http://arxiv.org/abs/2009.05456v1
• [cs.CL]Weakly Supervised Content Selection for Improved Image Captioning
Khyathi Raghavi Chandu, Piyush Sharma, Soravit Changpinyo, Ashish Thapliyal, Radu Soricut
http://arxiv.org/abs/2009.05175v1
• [cs.CR]A Smart Home System based on Internet of Things
Rihab Fahd Al-Mutawa, Fathy Albouraey Eassa
http://arxiv.org/abs/2009.05328v1
• [cs.CR]Accelerating 2PC-based ML with Limited Trusted Hardware
Muqsit Nawaz, Aditya Gulati, Kunlong Liu, Vishwajeet Agrawal, Prabhanjan Ananth, Trinabh Gupta
http://arxiv.org/abs/2009.05566v1
• [cs.CR]Federated Model Distillation with Noise-Free Differential Privacy
Lichao Sun, Lingjuan Lyu
http://arxiv.org/abs/2009.05537v1
• [cs.CR]Improving Robustness to Model Inversion Attacks via Mutual Information Regularization
Tianhao Wang, Yuheng Zhang, Ruoxi Jia
http://arxiv.org/abs/2009.05241v1
• [cs.CV]A Density-Aware PointRCNN for 3D Objection Detection in Point Clouds
Jie Li, Yu Hu
http://arxiv.org/abs/2009.05307v1
• [cs.CV]AFP-SRC: Identification of Antifreeze Proteins Using Sparse Representation Classifier
Shujaat Khan, Muhammad Usman
http://arxiv.org/abs/2009.05277v1
• [cs.CV]Adversarial Learning for Zero-shot Domain Adaptation
Jinghua Wang, Jianmin Jiang
http://arxiv.org/abs/2009.05214v1
• [cs.CV]An unsupervised deep learning framework via integrated optimization of representation learning and GMM-based modeling
Jinghua Wang, Jianmin Jiang
http://arxiv.org/abs/2009.05234v1
• [cs.CV]Attribute-conditioned Layout GAN for Automatic Graphic Design
Jianan Li, Jimei Yang, Jianming Zhang, Christina Wang, Tingfa Xu
http://arxiv.org/abs/2009.05284v1
• [cs.CV]Conditional Coupled Generative Adversarial Networks for Zero-Shot Domain Adaptation
Jinghua Wang, Jianmin Jiang
http://arxiv.org/abs/2009.05228v1
• [cs.CV]Devil’s in the Detail: Graph-based Key-point Alignment and Embedding for Person Re-ID
Xinyang Jiang, Fufu Yu, Yifei Gong, Shizhen Zhao, Xiaowei Guo, Feiyue Huang, Wei-Shi Zheng, Xing Sun
http://arxiv.org/abs/2009.05250v1
• [cs.CV]Enabling Image Recognition on Constrained Devices Using Neural Network Pruning and a CycleGAN
August Lidfelt, Daniel Isaksson, Ludwig Hedlund, Simon Åberg, Markus Borg, Erik Larsson
http://arxiv.org/abs/2009.05300v1
• [cs.CV]Evaluation of the Robustness of Visual SLAM Methods in Different Environments
Joonas Lomps, Artjom Lind, Amnir Hadachi
http://arxiv.org/abs/2009.05427v1
• [cs.CV]Fairness Matters — A Data-Driven Framework Towards Fair and High Performing Facial Recognition Systems
Yushi Cao, David Berend, Palina Tolmach, Moshe Levy, Guy Amit, Asaf Shabtai, Yuval Elovici, Yang Liu
http://arxiv.org/abs/2009.05283v1
• [cs.CV]HAA500: Human-Centric Atomic Action Dataset with Curated Videos
Jihoon Chung, Cheng-hsin Wuu, Hsuan-ru Yang, Yu-Wing Tai, Chi-Keung Tang
http://arxiv.org/abs/2009.05224v1
• [cs.CV]Heterogeneous Domain Generalization via Domain Mixup
Yufei Wang, Haoliang Li, Alex C. Kot
http://arxiv.org/abs/2009.05448v1
• [cs.CV]Hybrid Space Learning for Language-based Video Retrieval
Jianfeng Dong, Xirong Li, Chaoxi Xu, Gang Yang, Xun Wang
http://arxiv.org/abs/2009.05381v1
• [cs.CV]Image Conditioned Keyframe-Based Video Summarization Using Object Detection
Neeraj Baghel, Suresh C. Raikwar, Charul Bhatnagar
http://arxiv.org/abs/2009.05269v1
• [cs.CV]MRZ code extraction from visa and passport documents using convolutional neural networks
Yichuan Liu, Hailey James, Otkrist Gupta, Dan Raviv
http://arxiv.org/abs/2009.05489v1
• [cs.CV]Meta Learning for Few-Shot One-class Classification
Gabriel Dahia, Maurício Pamplona Segundo
http://arxiv.org/abs/2009.05353v1
• [cs.CV]Novel and Effective CNN-Based Binarization for Historically Degraded As-built Drawing Maps
Kuo-Liang Chung, De-Wei Hsieh
http://arxiv.org/abs/2009.05252v1
• [cs.CV]Optimizing Convolutional Neural Network Architecture via Information Field
Yuke Wang, Boyuan Feng, Xueqiao Peng, Yufei Ding
http://arxiv.org/abs/2009.05236v1
• [cs.CV]PiaNet: A pyramid input augmented convolutional neural network for GGO detection in 3D lung CT scans
Weihua Liu, Xiabi Liua, Xiongbiao Luo, Murong Wang, Guangyuan Zheng, Guanghui Han
http://arxiv.org/abs/2009.05267v1
• [cs.CV]SoFAr: Shortcut-based Fractal Architectures for Binary Convolutional Neural Networks
Zhu Baozhou, Peter Hofstee, Jinho Lee, Zaid Al-Ars
http://arxiv.org/abs/2009.05317v1
• [cs.CV]Spectral Analysis Network for Deep Representation Learning and Image Clustering
Jinghua Wang, Adrian Hilton, Jianmin Jiang
http://arxiv.org/abs/2009.05235v1
• [cs.CV]TP-LSD: Tri-Points Based Line Segment Detector
Siyu Huang, Fangbo Qin, Pengfei Xiong, Ning Ding, Yijia He, Xiao Liu
http://arxiv.org/abs/2009.05505v1
• [cs.CV]The PREVENTION Challenge: How Good Are Humans Predicting Lane Changes?
A. Quintanar, R. Izquierdo, I. Parra, D. Fernández-Llorca, M. A. Sotelo
http://arxiv.org/abs/2009.05331v1
• [cs.CV]Unsupervised Partial Point Set Registration via Joint Shape Completion and Registration
Xiang Li, Lingjing Wang, Yi Fang
http://arxiv.org/abs/2009.05290v1
• [cs.CV]Variance Loss: A Confidence-Based Reweighting Strategy for Coarse Semantic Segmentation
Jingchao Liu, Ye Du, Qingjie Liu, Yunhong Wang
http://arxiv.org/abs/2009.05205v1
• [cs.CY]“Is it a Qoincidence?”: A First Step Towards Understanding and Characterizing the QAnon Movement on Voat.co
Antonis Papasavva, Jeremy Blackburn, Gianluca Stringhini, Savvas Zannettou, Emiliano De Cristofaro
http://arxiv.org/abs/2009.04885v2
• [cs.CY]A Review on Security and Privacy of Internet of Medical Things
Mohan Krishna Kagita, Navod Thilakarathne, Thippa Reddy Gadekallu, Praveen Kumar Reddy Maddikunta
http://arxiv.org/abs/2009.05394v1
• [cs.CY]Narratives and Needs: Analyzing Experiences of Cyclone Amphan Using Twitter Discourse
Ancil Crayton, João Fonseca, Kanav Mehra, Michelle Ng, Jared Ross, Marcelo Sandoval-Castañeda, Rachel von Gnechten
http://arxiv.org/abs/2009.05560v1
• [cs.CY]On the Fairness of ‘Fake’ Data in Legal AI
Lauren Boswell, Arjun Prakash
http://arxiv.org/abs/2009.04640v2
• [cs.DC]CASH: A Credit Aware Scheduling for Public Cloud Platforms
Aakash Sharma, Saravanan Dhakshinamurthy, George Kesidis, Chita R. Das
http://arxiv.org/abs/2009.04561v2
• [cs.DC]Hierarchical Roofline Performance Analysis for Deep Learning Applications
Yunsong Wang, Charlene Yang, Steven Farrell, Thorsten Kurth, Samuel Williams
http://arxiv.org/abs/2009.05257v1
• [cs.DC]Kvik: A task based middleware with composable scheduling policies
Saurabh Raje, Frédéric Wagner
http://arxiv.org/abs/2009.05504v1
• [cs.HC]Visually Analyzing and Steering Zero Shot Learning
Saroj Sahoo, Matthew Berger
http://arxiv.org/abs/2009.05254v1
• [cs.IR]Patient Cohort Retrieval using Transformer Language Models
Sarvesh Soni, Kirk Roberts
http://arxiv.org/abs/2009.05121v1
• [cs.IR]TRec: Sequential Recommender Based On Latent Item Trend Information
Ye Tao, Can Wang, Lina Yao, Weimin Li, Yonghong Yu
http://arxiv.org/abs/2009.05183v1
• [cs.IT]An Improved Multi-access Coded Caching with Uncoded Placement
Shanuja Sasi, B. Sundar Rajan
http://arxiv.org/abs/2009.05377v1
• [cs.IT]Capacity-Approaching Autoencoders for Communications
Nunzio A. Letizia, Andrea M. Tonello
http://arxiv.org/abs/2009.05273v1
• [cs.IT]Construction of Hyperbolic Signal Sets from the Uniformization of Hyperelliptic Curves
Erika Patricia Dantas de Oliveira Guazzi, Reginaldo Palazzo Junior
http://arxiv.org/abs/2009.05563v1
• [cs.IT]Efficient Detectors for Telegram Splitting based Transmission in Low Power Wide Area Networks with Bursty Interference
Steven Kisseleff, Jakob Kneissl, Gerd Kilian, Wolfgang H. Gerstacker
http://arxiv.org/abs/2009.05072v1
• [cs.IT]End-to-end Learning for OFDM: From Neural Receivers to Pilotless Communication
Fayçal Ait Aoudia, Jakob Hoydis
http://arxiv.org/abs/2009.05261v1
• [cs.IT]Finite-Alphabet Wiener Filter Precoding for mmWave Massive MU-MIMO Systems
Oscar Castañeda, Sven Jacobsson, Giuseppe Durisi, Tom Goldstein, Christoph Studer
http://arxiv.org/abs/2009.05133v1
• [cs.IT]Generalized Energy Detection Under Generalized Noise Channels
Nikolaos I. Miridakis, Theodoros A. Tsiftsis, Guanghua Yang
http://arxiv.org/abs/2009.04564v2
• [cs.LG]A First Step Towards Distribution Invariant Regression Metrics
Mario Michael Krell, Bilal Wehbe
http://arxiv.org/abs/2009.05176v1
• [cs.LG]A kernel function for Signal Temporal Logic formulae
Luca Bortolussi, Giuseppe Maria Gallo, Laura Nenzi
http://arxiv.org/abs/2009.05484v1
• [cs.LG]Accurate and Intuitive Contextual Explanations using Linear Model Trees
Aditya Lahiri, Narayanan Unny Edakunni
http://arxiv.org/abs/2009.05322v1
• [cs.LG]Achieving Adversarial Robustness via Sparsity
Shufan Wang, Ningyi Liao, Liyao Xiang, Nanyang Ye, Quanshi Zhang
http://arxiv.org/abs/2009.05423v1
• [cs.LG]Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau, Rémi Piché-Taillefer, Rémi Tachet des Combes, Ioannis Mitliagkas
http://arxiv.org/abs/2009.05475v1
• [cs.LG]CatGCN: Graph Convolutional Networks with Categorical Node Features
Weijian Chen, Fuli Feng, Qifan Wang, Xiangnan He, Chonggang Song, Guohui Ling, Yongdong Zhang
http://arxiv.org/abs/2009.05303v1
• [cs.LG]CounteRGAN: Generating Realistic Counterfactuals with Residual Generative Adversarial Nets
Daniel Nemirovsky, Nicolas Thiebaut, Ye Xu, Abhishek Gupta
http://arxiv.org/abs/2009.05199v1
• [cs.LG]DART: Data Addition and Removal Trees
Jonathan Brophy, Daniel Lowd
http://arxiv.org/abs/2009.05567v1
• [cs.LG]Deep Switching Auto-Regressive Factorization:Application to Time Series Forecasting
Amirreza Farnoosh, Bahar Azari, Sarah Ostadabbas
http://arxiv.org/abs/2009.05135v1
• [cs.LG]Defending Against Multiple and Unforeseen Adversarial Videos
Shao-Yuan Lo, Vishal M. Patel
http://arxiv.org/abs/2009.05244v1
• [cs.LG]Disentangling Neural Architectures and Weights: A Case Study in Supervised Classification
Nicolo Colombo, Yang Gao
http://arxiv.org/abs/2009.05346v1
• [cs.LG]Extending Label Smoothing Regularization with Self-Knowledge Distillation
Ji-Yue Wang, Pei Zhang, Wen-feng Pang, Jie Li
http://arxiv.org/abs/2009.05226v1
• [cs.LG]GTEA: Representation Learning for Temporal Interaction Graphs via Edge Aggregation
Yiming Li, Da Sun Handason Tam, Siyue Xie, Xiaxin Liu, Qiu Fang Ying, Wing Cheong Lau, Dah Ming Chiu, Shou Zhi Chen
http://arxiv.org/abs/2009.05266v1
• [cs.LG]Learning Product Rankings Robust to Fake Users
Negin Golrezaei, Vahideh Manshadi, Jon Schneider, Shreyas Sekar
http://arxiv.org/abs/2009.05138v1
• [cs.LG]Machine Learning and Data Science approach towards trend and predictors analysis of CDC Mortality Data for the USA
Yasir Nadeem, Awais Ahmed
http://arxiv.org/abs/2009.05400v1
• [cs.LG]TREX: Tree-Ensemble Representer-Point Explanations
Jonathan Brophy, Daniel Lowd
http://arxiv.org/abs/2009.05530v1
• [cs.LG]Towards Interpretable Multi-Task Learning Using Bilevel Programming
Francesco Alesiani, Shujian Yu, Ammar Shaker, Wenzhe Yin
http://arxiv.org/abs/2009.05483v1
• [cs.LG]Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization
Qi Zhu, Yidan Xu, Haonan Wang, Chao Zhang, Jiawei Han, Carl Yang
http://arxiv.org/abs/2009.05204v1
• [cs.LG]Visual Neural Decomposition to Explain Multivariate Data Sets
Johannes Knittel, Andres Lalama, Steffen Koch, Thomas Ertl
http://arxiv.org/abs/2009.05502v1
• [cs.NE]Activation Relaxation: A Local Dynamical Approximation to Backpropagation in the Brain
Beren Millidge, Alexander Tschantz, Christopher L Buckley, Anil Seth
http://arxiv.org/abs/2009.05359v1
• [cs.NI]Graph Neural Network based Service Function Chaining for Automatic Network Control
DongNyeong Heo, Stanislav Lange, Hee-Gon Kim, Heeyoul Choi
http://arxiv.org/abs/2009.05240v1
• [cs.RO]A Toolkit to Generate Social Navigation Datasets
Rishabh Baghel, Aditya Kapoor, Pilar Bachiller, Ronit R. Jorvekar, Daniel Rodriguez-Criado, Luis J. Manso
http://arxiv.org/abs/2009.05345v1
• [cs.RO]Embodied Visual Navigation with Automatic Curriculum Learning in Real Environments
Steven D. Morad, Roberto Mecca, Rudra P. K. Poudel, Stephan Liwicki, Roberto Cipolla
http://arxiv.org/abs/2009.05429v1
• [cs.RO]Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning
Lucas Manuelli, Yunzhu Li, Pete Florence, Russ Tedrake
http://arxiv.org/abs/2009.05085v1
• [cs.RO]Sentinel: An Onboard System for Intelligent Vehicles to Reduce Traffic Delay during Freeway Incidents
Goodarz Mehr, Azim Eskandarian
http://arxiv.org/abs/2009.05165v1
• [cs.RO]The Robotic Vision Scene Understanding Challenge
David Hall, Ben Talbot, Suman Raj Bista, Haoyang Zhang, Rohan Smith, Feras Dayoub, Niko Sünderhauf
http://arxiv.org/abs/2009.05246v1
• [cs.RO]Towards Safe Locomotion Navigation in Partially Observable Environments with Uneven Terrain
Jonas Warnke, Abdulaziz Shamsah, Yingke Li, Ye Zhao
http://arxiv.org/abs/2009.05168v1
• [cs.SD]SONYC-UST-V2: An Urban Sound Tagging Dataset with Spatiotemporal Context
Mark Cartwright, Jason Cramer, Ana Elisa Mendez Mendez, Yu Wang, Ho-Hsiang Wu, Vincent Lostanlen, Magdalena Fuentes, Graham Dove, Charlie Mydlarz, Justin Salamon, Oded Nov, Juan Pablo Bello
http://arxiv.org/abs/2009.05188v1
• [cs.SE]The AIQ Meta-Testbed: Pragmatically Bridging Academic AI Testing and Industrial Q Needs
Markus Borg
http://arxiv.org/abs/2009.05260v1
• [cs.SI]A deep-learning model for evaluating and predicting the impact of lockdown policies on COVID-19 cases
Ahmed Ben Said, Abdelkarim Erradi, Hussein Aly, Abdelmonem Mohamed
http://arxiv.org/abs/2009.05481v1
• [cs.SI]Beyond Localized Graph Neural Networks: An Attributed Motif Regularization Framework
Aravind Sankar, Junting Wang, Adit Krishnan, Hari Sundaram
http://arxiv.org/abs/2009.05197v1
• [cs.SI]CasGCN: Predicting future cascade growth based on information diffusion graph
Zhixuan Xu, Minghui Qian, Xiaowei Huang, Jie Meng
http://arxiv.org/abs/2009.05152v1
• [cs.SI]Sequential seeding in multilayer networks
Piotr Bródka, Jarosław Jankowski, Radosław Michalski
http://arxiv.org/abs/2009.05335v1
• [econ.EM]Inference for high-dimensional exchangeable arrays
Harold D. Chiang, Kengo Kato, Yuya Sasaki
http://arxiv.org/abs/2009.05150v1
• [econ.GN]Object Recognition for Economic Development from Daytime Satellite Imagery
Klaus Ackermann, Alexey Chernikov, Nandini Anantharama, Miethy Zaman, Paul A Raschky
http://arxiv.org/abs/2009.05455v1
• [eess.AS]On Multitask Loss Function for Audio Event Detection and Localization
Huy Phan, Lam Pham, Philipp Koch, Ngoc Q. K. Duong, Ian McLoughlin, Alfred Mertins
http://arxiv.org/abs/2009.05527v1
• [eess.AS]RECOApy: Data recording, pre-processing and phonetic transcription for end-to-end speech-based applications
Adriana Stan
http://arxiv.org/abs/2009.05493v1
• [eess.IV]Boosting the Sliding Frank-Wolfe solver for 3D deconvolution
Jean-Baptiste Courbot, Bruno Colicchio
http://arxiv.org/abs/2009.05473v1
• [eess.IV]Phase Sampling Profilometry
Zhenzhou Wang
http://arxiv.org/abs/2009.05406v1
• [eess.SP]Deep Transfer Learning for Signal Detection in Ambient Backscatter Communications
Chang Liu, Zhiqiang Wei, Derrick Wing Kwan Ng, Jinhong Yuan, Ying-Chang Liang
http://arxiv.org/abs/2009.05231v1
• [eess.SP]Energy-Efficient Design of IRS-NOMA Networks
Fang Fang, Yanqing Xu, Quoc-Viet Pham, Zhiguo Ding
http://arxiv.org/abs/2009.05344v1
• [eess.SP]Machine learning-based EDFA Gain Model Generalizable to Multiple Physical Devices
Francesco Da Ros, Uiara Celine de Moura, Metodi P. Yankov
http://arxiv.org/abs/2009.05326v1
• [eess.SP]Power Evolution Prediction and Optimization in a Multi-span System Based on Component-wise System Modeling
Metodi P. Yankov, Uiara Celine de Moura, Francesco Da Ros
http://arxiv.org/abs/2009.05348v1
• [math.ST]Bootstrap method for misspecified ergodic Lévy driven stochastic differential equation models
Yuma Uehara
http://arxiv.org/abs/2009.05232v1
• [math.ST]Estimation of all parameters in the reflected Orntein-Uhlenbeck process from discrete observations
Yaozhong Hu, Yuejuan Xi
http://arxiv.org/abs/2009.05162v1
• [math.ST]Families of discrete circular distributions with some novel applications
Kanti V. Mardia, Karthik Sriram
http://arxiv.org/abs/2009.05437v1
• [math.ST]On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms
Richard Nickl, Sven Wang
http://arxiv.org/abs/2009.05298v1
• [physics.comp-ph]Symplectic Gaussian Process Regression of Hamiltonian Flow Maps
Katharina Rath, Christopher G. Albert, Bernd Bischl, Udo von Toussaint
http://arxiv.org/abs/2009.05569v1
• [physics.soc-ph]Community detection in networks using graph embeddings
Aditya Tandon, Aiiad Albeshri, Vijey Thayananthan, Wadee Alhalabi, Filippo Radicchi, Santo Fortunato
http://arxiv.org/abs/2009.05265v1
• [physics.soc-ph]Information flow in political elections: a stochastic perspective
Santosh Kumar Radha
http://arxiv.org/abs/2009.05198v1
• [stat.AP]A Bayesian hierarchical model to estimate land surface phenology parameters with harmonized Landsat 8 and Sentinel-2 images
Chad Babcock, Andrew O. Finley, Nathaniel Looker
http://arxiv.org/abs/2009.05203v1
• [stat.AP]A Study on the Possible Effects of the Implementation of the Nordic Model in India on Crime Rates and Sexually Transmitted Diseases
Sabarinath Vinod Nair, Shreya Sharma, Swarnava Ghosh
http://arxiv.org/abs/2009.05319v1
• [stat.AP]Bayesian Beta-Binomial Prevalence Estimation Using an Imperfect Test
Jonathan Baxter
http://arxiv.org/abs/2009.05446v1
• [stat.AP]Explaining the Decline of Child Mortality in 44 Developing Countries: A Bayesian Extension of Oaxaca Decomposition Methods
Antonio P. Ramos, Martin J. Flores, Leiwen Gao, Patrick Heuveline, Robert E. Weiss
http://arxiv.org/abs/2009.05417v1
• [stat.AP]Limousine Service Management: Capacity Planning with Predictive Analytics and Optimization
Peng Liu, Ying Chen, Chung-Piaw Teo
http://arxiv.org/abs/2009.05422v1
• [stat.AP]Modelling COVID-19 — I A dynamic SIR(D) with application to Indian data
Madhuchhanda Bhattacharjee, Arup Bose
http://arxiv.org/abs/2009.05044v1
• [stat.AP]Portfolio Decisions and Brain Reactions via the CEAD method
Piotr Majer, Peter N. C. Mohr, Hauke R. Heekeren, Wolfgang K. Härdle
http://arxiv.org/abs/2009.05142v1
• [stat.AP]Power and sample size for cluster randomized and stepped wedge trials: Comparing estimates obtained by applying design effects or by direct estimation in GLMM
David M. Thompson
http://arxiv.org/abs/2009.05171v1
• [stat.AP]Probabilistic and mean-field model of COVID-19 epidemics with user mobility and contact tracing
M. Akian, L. Ganassali, S. Gaubert, L. Massoulié
http://arxiv.org/abs/2009.05304v1
• [stat.CO]Augmented pseudo-marginal Metropolis-Hastings for partially observed diffusion processes
Andrew Golightly, Chris Sherlock
http://arxiv.org/abs/2009.05318v1
• [stat.ME]A Family of Mixture Models for Biclustering
Wangshu Tu, Sanjeena Subedi
http://arxiv.org/abs/2009.05098v1
• [stat.ME]A simulation study of semiparametric estimation in copula models based on minimum Alpha-Divergence
Morteza Mohammadi, Mohammad Amini, Mahdi Emadi
http://arxiv.org/abs/2009.05247v1
• [stat.ME]Directional quantile classifiers
Alessio Farcomeni, Marco Geraci, Cinzia Viroli
http://arxiv.org/abs/2009.05007v2
• [stat.ME]Finding Stable Groups of Cross-Correlated Features in Multi-View data
Miheer Dewaskar, John Palowitch, Mark He, Michael I. Love, Andrew Nobel
http://arxiv.org/abs/2009.05079v1
• [stat.ME]Narrowest Significance Pursuit: inference for multiple change-points in linear models
Piotr Fryzlewicz
http://arxiv.org/abs/2009.05431v1
• [stat.ME]TCA and TLRA: A comparison on contingency tables and compositional data
J. Allard, S. Champigny, V. Choulakian, S. Mahdi
http://arxiv.org/abs/2009.05482v1
• [stat.ML]Bayesian Screening: Multi-test Bayesian Optimization Applied to in silico Material Screening
James Hook, Calum Hand, Emma Whitfield
http://arxiv.org/abs/2009.05418v1
• [stat.ML]Deducing neighborhoods of classes from a fitted model
Alexander Gerharz, Andreas Groll, Gunther Schauberger
http://arxiv.org/abs/2009.05516v1
• [stat.ML]Towards a More Reliable Interpretation of Machine Learning Outputs for Safety-Critical Systems using Feature Importance Fusion
Divish Rengasamy, Benjamin Rothwell, Grazziela Figueredo
http://arxiv.org/abs/2009.05501v1