cond-mat.dis-nn - 无序系统与神经网络
cs.AI - 人工智能 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.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.FL - 形式语言与自动机理论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 econ.GN - 一般经济学 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 hep-lat - 高能物理晶格 math.MG -公制几何 math.OC - 优化与控制 math.ST - 统计理论 physics.data-an - 数据分析、 统计和概率 physics.soc-ph - 物理学与社会 quant-ph - 量子物理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cond-mat.dis-nn]How we are leading a 3-XORSAT challenge: from the energy landscape to the algorithm and its efficient implementation on GPUs
• [cs.AI]An Efficient Diagnosis Algorithm for Inconsistent Constraint Sets
• [cs.AI]Grid Cell Path Integration For Movement-Based Visual Object Recognition
• [cs.AI]Hierarchical Learning Using Deep Optimum-Path Forest
• [cs.AI]Optimising Long-Term Outcomes using Real-World Fluent Objectives: An Application to Football
• [cs.CL]A Systematic Review of Natural Language Processing Applied to Radiology Reports
• [cs.CL]Cross-SEAN: A Cross-Stitch Semi-Supervised Neural Attention Model for COVID-19 Fake News Detection
• [cs.CL]Echo State Speech Recognition
• [cs.CL]Entity-level Factual Consistency of Abstractive Text Summarization
• [cs.CL]Fake News Detection: a comparison between available Deep Learning techniques in vector space
• [cs.CL]From Extreme Multi-label to Multi-class: A Hierarchical Approach for Automated ICD-10 Coding Using Phrase-level Attention
• [cs.CL]Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer
• [cs.CL]Learning to Select Context in a Hierarchical and Global Perspective for Open-domain Dialogue Generation
• [cs.CL]Meta-Transfer Learning for Low-Resource Abstractive Summarization
• [cs.CL]Quiz-Style Question Generation for News Stories
• [cs.CL]Regular Expressions for Fast-response COVID-19 Text Classification
• [cs.CL]UnibucKernel: Geolocating Swiss-German Jodels Using Ensemble Learning
• [cs.CR]Data Poisoning Attacks and Defenses to Crowdsourcing Systems
• [cs.CR]Deep Neural Networks based Invisible Steganography for Audio-into-Image Algorithm
• [cs.CR]Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids
• [cs.CV]A Comprehensive Review of Deep Learning-based Single Image Super-resolution
• [cs.CV]An Enhanced Adversarial Network with Combined Latent Features for Spatio-Temporal Facial Affect Estimation in the Wild
• [cs.CV]Automated Detection of Equine Facial Action Units
• [cs.CV]BEDS: Bagging ensemble deep segmentation for nucleus segmentation with testing stage stain augmentation
• [cs.CV]CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
• [cs.CV]Clockwork Variational Autoencoders for Video Prediction
• [cs.CV]Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction
• [cs.CV]Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
• [cs.CV]DSRN: an Efficient Deep Network for Image Relighting
• [cs.CV]Deep Gait Recognition: A Survey
• [cs.CV]Deep Miner: A Deep and Multi-branch Network which Mines Rich and Diverse Features for Person Re-identification
• [cs.CV]DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates
• [cs.CV]DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results
• [cs.CV]Densely Nested Top-Down Flows for Salient Object Detection
• [cs.CV]Domain Adaptation for Medical Image Analysis: A Survey
• [cs.CV]Domain Impression: A Source Data Free Domain Adaptation Method
• [cs.CV]Essentials for Class Incremental Learning
• [cs.CV]Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays
• [cs.CV]HVAQ: A High-Resolution Vision-Based Air Quality Dataset
• [cs.CV]HandTailor: Towards High-Precision Monocular 3D Hand Recovery
• [cs.CV]Hierarchical Attention Fusion for Geo-Localization
• [cs.CV]Hierarchical Similarity Learning for Language-based Product Image Retrieval
• [cs.CV]Image Compositing for Segmentation of Surgical Tools without Manual Annotations
• [cs.CV]Improved Point Transformation Methods For Self-Supervised Depth Prediction
• [cs.CV]Minimizing false negative rate in melanoma detection and providing insight into the causes of classification
• [cs.CV]Mobile Computational Photography: A Tour
• [cs.CV]Multi-Agent Reinforcement Learning of 3D Furniture Layout Simulation in Indoor Graphics Scenes
• [cs.CV]NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation
• [cs.CV]One-shot action recognition towards novel assistive therapies
• [cs.CV]SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering
• [cs.CV]Sliced Distance for Colour Grading
• [cs.CV]Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Tracking
• [cs.CV]StablePose: Learning 6D Object Poses from Geometrically Stable Patches
• [cs.CV]Unbiased Teacher for Semi-Supervised Object Detection
• [cs.CV]Understanding and Creating Art with AI: Review and Outlook
• [cs.CY]Biometrics in the Era of COVID-19: Challenges and Opportunities
• [cs.CY]Gender Bias, Social Bias and Representation: 70 Years of Bollywood
• [cs.CY]How do students test software units?
• [cs.CY]HyMap: eliciting hypotheses in early-stage software startups using cognitive mapping
• [cs.CY]Optimization Helps Scheduling Nursing Staff at the Long-Term Care Homes of the City of Toronto
• [cs.CY]The Small World Phenomenon and Network Analysis of ICT Startup Investment in Indonesia and Singapore
• [cs.DC]Consistent Lock-free Parallel Stochastic Gradient Descent for Fast and Stable Convergence
• [cs.DC]Data-Aware Device Scheduling for Federated Edge Learning
• [cs.DC]Graph based Data Dependence Identifier for Parallelization of Programs
• [cs.DC]Latency Modeling of Hyperledger Fabric for Blockchain-based IoT (BC-IoT) Networks
• [cs.DC]Locally Checkable Problems in Rooted Trees
• [cs.DC]Network Size Estimation in Small-World Networks under Byzantine Faults
• [cs.DC]Reaching Consensus for Asynchronous Distributed Key Generation
• [cs.DC]Strongly Connected Topology Model and Confirmation-based Propagation Method for Cross-chain Interaction
• [cs.DL]Is preprint the future of science? A thirty year journey of online preprint services
• [cs.DS]Locality in Online Algorithms
• [cs.FL]On Typical Hesitant Fuzzy Languages and Automata
• [cs.HC]Spacewalker: Rapid UI Design Exploration Using Lightweight Markup Enhancement and Crowd Genetic Programming
• [cs.HC]TapNet: The Design, Training, Implementation, and Applications of a Multi-Task Learning CNN for Off-Screen Mobile Input
• [cs.IR]Dynamic Memory based Attention Network for Sequential Recommendation
• [cs.IR]ELIXIR: Learning from User Feedback on Explanations to Improve Recommender Models
• [cs.IR]HSR: Hyperbolic Social Recommender
• [cs.IR]Learning Fair Representations for Bipartite Graph based Recommendation
• [cs.IR]Link Prediction Approach to Recommender Systems
• [cs.IR]Multi-Interest-Aware User Modeling for Large-Scale Sequential Recommendations
• [cs.IR]Recommender Systems for Configuration Knowledge Engineering
• [cs.IR]Sparse-Interest Network for Sequential Recommendation
• [cs.IR]TCN: Table Convolutional Network for Web Table Interpretation
• [cs.IR]Testing Lotka’s Law and Pattern of Author Productivity in the Scholarly Publications of Artificial Intelligence
• [cs.IR]Training Microsoft News Recommenders with Pretrained Language Models in the Loop
• [cs.IR]Truncation-Free Matching System for Display Advertising at Alibaba
• [cs.IT]A maximum entropy model of bounded rational decision-making with prior beliefs and market feedback
• [cs.IT]Active Privacy-utility Trade-off Against a Hypothesis Testing Adversary
• [cs.IT]Can Massive MIMO Support URLLC?
• [cs.IT]Coverage Probability of Distributed IRS Systems Under Spatially Correlated Channels
• [cs.IT]DeepMuD: Multi-user Detection for Uplink Grant-Free NOMA IoT Networks via Deep Learning
• [cs.IT]IRS-Assisted Wireless Powered NOMA: Is Dynamic Passive Beamforming Really Needed?
• [cs.IT]Mean-Based Trace Reconstruction over Practically any Replication-Insertion Channel
• [cs.IT]On isodual double Toeplitz codes
• [cs.IT]On the advantages of stochastic encoders
• [cs.LG]A Bit Better? Quantifying Information for Bandit Learning
• [cs.LG]A Machine Learning model of the combination of normalized SD1 and SD2 indexes from 24h-Heart Rate Variability as a predictor of myocardial infarction
• [cs.LG]A Mathematical Principle of Deep Learning: Learn the Geodesic Curve in the Wasserstein Space
• [cs.LG]A Novel Non-Invasive Estimation of Respiration Rate from Photoplethysmograph Signal Using Machine Learning Model
• [cs.LG]A matrix approach to detect temporal behavioral patterns at electric vehicle charging stations
• [cs.LG]BORE: Bayesian Optimization by Density-Ratio Estimation
• [cs.LG]Boosting for Online Convex Optimization
• [cs.LG]Closing the Closed-Loop Distribution Shift in Safe Imitation Learning
• [cs.LG]Combinatorial optimization and reasoning with graph neural networks
• [cs.LG]Composable Generative Models
• [cs.LG]Consistent Non-Parametric Methods for Adaptive Robustness
• [cs.LG]Continuous Doubly Constrained Batch Reinforcement Learning
• [cs.LG]Convergence of stochastic gradient descent schemes for Lojasiewicz-landscapes
• [cs.LG]DINO: A Conditional Energy-Based GAN for Domain Translation
• [cs.LG]Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters
• [cs.LG]Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction
• [cs.LG]Delving into Deep Imbalanced Regression
• [cs.LG]Differential Private Hogwild! over Distributed Local Data Sets
• [cs.LG]Distributed Algorithms for Linearly-Solvable Optimal Control in Networked Multi-Agent Systems
• [cs.LG]Domain Adaptive Learning Based on Sample-Dependent and Learnable Kernels
• [cs.LG]Don’t Fix What ain’t Broke: Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization
• [cs.LG]Edge Sparse Basis Network: An Deep Learning Framework for EEG Source Localization
• [cs.LG]Efficient Reinforcement Learning in Resource Allocation Problems Through Permutation Invariant Multi-task Learning
• [cs.LG]Estimate Three-Phase Distribution Line Parameters With Physics-Informed Graphical Learning Method
• [cs.LG]Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm
• [cs.LG]FrugalMCT: Efficient Online ML API Selection for Multi-Label Classification Tasks
• [cs.LG]Fuzzy clustering algorithms with distance metric learning and entropy regularization
• [cs.LG]GradFreeBits: Gradient Free Bit Allocation for Dynamic Low Precision Neural Networks
• [cs.LG]Improving Hierarchical Adversarial Robustness of Deep Neural Networks
• [cs.LG]Knowledge Hypergraph Embedding Meets Relational Algebra
• [cs.LG]L2E: Learning to Exploit Your Opponent
• [cs.LG]Learning Continuous Exponential Families Beyond Gaussian
• [cs.LG]Learning Memory-Dependent Continuous Control from Demonstrations
• [cs.LG]Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder
• [cs.LG]No-Substitution -means Clustering with Low Center Complexity and Memory
• [cs.LG]Off-policy Confidence Sequences
• [cs.LG]Optimizing Black-box Metrics with Iterative Example Weighting
• [cs.LG]Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm
• [cs.LG]PLAM: a Posit Logarithm-Approximate Multiplier for Power Efficient Posit-based DNNs
• [cs.LG]Random Projections for Improved Adversarial Robustness
• [cs.LG]Recurrent Rational Networks
• [cs.LG]Reduced-Order Neural Network Synthesis with Robustness Guarantees
• [cs.LG]Reinforcement Learning for Datacenter Congestion Control
• [cs.LG]Robust PDF Document Conversion Using Recurrent Neural Networks
• [cs.LG]Robust and Differentially Private Mean Estimation
• [cs.LG]SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning
• [cs.LG]State Entropy Maximization with Random Encoders for Efficient Exploration
• [cs.LG]Strategic bidding in freight transport using deep reinforcement learning
• [cs.LG]Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics
• [cs.LG]Unsupervised Clustering of Time Series Signals using Neuromorphic Energy-Efficient Temporal Neural Networks
• [cs.LG]Using Distance Correlation for Efficient Bayesian Optimization
• [cs.LG]VAE Approximation Error: ELBO and Conditional Independence
• [cs.LG]Verifying Probabilistic Specifications with Functional Lagrangians
• [cs.RO]A Visibility Roadmap Sampling Approach for a Multi-Robot Visibility-Based Pursuit-Evasion Problem
• [cs.RO]Communication-free Cohesive Flexible-Object Transport using Decentralized Robot Networks
• [cs.RO]Hough2Map — Iterative Event-based Hough Transform for High-Speed Railway Mapping
• [cs.RO]Improved Deep Reinforcement Learning with Expert Demonstrations for Urban Autonomous Driving
• [cs.RO]Learning Invariant Representation of Tasks for Robust Surgical State Estimation
• [cs.RO]ReSonAte: A Runtime Risk Assessment Framework for Autonomous Systems
• [cs.RO]Stochastic Spatio-Temporal Optimization for Control and Co-Design of Systems in Robotics and Applied Physics
• [cs.RO]iX-BSP: Incremental Belief Space Planning
• [cs.SI]A Query-Driven System for Discovering Interesting Subgraphs in Social Media
• [cs.SI]A two-layer model for coevolving opinion dynamics and collective decision-making in complex social systems
• [cs.SI]Graph Sampling Approach for Reducing Computational Complexity of Large-Scale Social Network
• [econ.GN]A Core of E-Commerce Customer Experience based on Conversational Data using Network Text Methodology
• [econ.GN]Supportive 5G infrastructure policies are essential for universal 6G: Evidence from an open-source techno-economic simulation model using remote sensing
• [econ.GN]The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?
• [econ.GN]Understanding algorithmic collusion with experience replay
• [eess.IV]Enhanced Magnetic Resonance Image Synthesis with Contrast-Aware Generative Adversarial Networks
• [eess.IV]Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data
• [eess.IV]NFCNN: Toward a Noise Fusion Convolutional Neural Network for Image Denoising
• [eess.IV]SRDTI: Deep learning-based super-resolution for diffusion tensor MRI
• [eess.SP]Analysis of EEG data using complex geometric structurization
• [eess.SP]EEG-based Texture Roughness Classification in Active Tactile Exploration with Invariant Representation Learning Networks
• [eess.SP]Inferring Graph Signal Translations as Invariant Transformations for Classification Tasks
• [eess.SP]Reinforcement Learning for Beam Pattern Design in Millimeter Wave and Massive MIMO Systems
• [eess.SP]Vision-Aided 6G Wireless Communications: Blockage Prediction and Proactive Handoff
• [eess.SY]Online Optimization and Learning in Uncertain Dynamical Environments with Performance Guarantees
• [hep-lat]Quantum field-theoretic machine learning
• [math.MG]Center Power and Loci of Poncelet Triangles
• [math.OC]ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks
• [math.OC]Joint Continuous and Discrete Model Selection via Submodularity
• [math.OC]On the Convergence of Step Decay Step-Size for Stochastic Optimization
• [math.ST]Convolution of a symmetric log-concave distribution and a symmetric bimodal distribution can have any number of modes
• [math.ST]Linear Functions to the Extended Reals
• [math.ST]Regression-type analysis for block maxima on block maxima
• [math.ST]Transfer Learning for Linear Regression: a Statistical Test of Gain
• [physics.data-an]Data-driven formulation of natural laws by recursive-LASSO-based symbolic regression
• [physics.soc-ph]Monitoring behavioural responses during pandemic via reconstructed contact matrices from online and representative surveys
• [quant-ph]Evaluating the Performance of Some Local Optimizers for Variational Quantum Classifiers
• [quant-ph]Generalization in Quantum Machine Learning: a Quantum Information Perspective
• [stat.AP]A mathematical take on the competitive balance of a football league
• [stat.AP]Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data
• [stat.AP]Experimental Designs for Accelerated Degradation Tests Based on Linear Mixed Effects Models
• [stat.AP]hesim: Health Economic Simulation Modeling and Decision Analysis
• [stat.ME]A Generative Approach to Joint Modeling of Quantitative and Qualitative Responses
• [stat.ME]Adaptive Step-Length Selection in Gradient Boosting for Generalized Additive Models for Location, Scale and Shape
• [stat.ME]Adjusting the Benjamini-Hochberg method for controlling the false discovery rate in knockoff assisted variable selection
• [stat.ME]Big Data meets Causal Survey Research: Understanding Nonresponse in the Recruitment of a Mixed-mode Online Panel
• [stat.ME]Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding
• [stat.ME]Counterfactual Inference of the Mean Outcome under a Convergence of Average Logging Probability
• [stat.ME]Divide-and-Conquer MCMC for Multivariate Binary Data
• [stat.ME]Estimating Perinatal Critical Windows to Environmental Mixtures via Structured Bayesian Regression Tree Pairs
• [stat.ME]Estimating The Proportion of Signal Variables Under Arbitrary Covariance Dependence
• [stat.ME]Multilevel calibration weighting for survey data
• [stat.ME]The Variational Bayesian Inference for Network Autoregression Models
• [stat.ML]Convex regularization in statistical inverse learning problems
• [stat.ML]Deep Extreme Value Copulas for Estimation and Sampling
• [stat.ML]Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm
• [stat.ML]Towards a mathematical theory of trajectory inference
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• [cond-mat.dis-nn]How we are leading a 3-XORSAT challenge: from the energy landscape to the algorithm and its efficient implementation on GPUs
M. Bernaschi, M. Bisson, M. Fatica, E. Marinari, V. Martin-Mayor, G. Parisi, F. Ricci-Tersenghi
http://arxiv.org/abs/2102.09510v1
• [cs.AI]An Efficient Diagnosis Algorithm for Inconsistent Constraint Sets
Alexander Felfernig, Monika Schubert, Christoph Zehentner
http://arxiv.org/abs/2102.09005v1
• [cs.AI]Grid Cell Path Integration For Movement-Based Visual Object Recognition
Niels Leadholm, Marcus Lewis, Subutai Ahmad
http://arxiv.org/abs/2102.09076v1
• [cs.AI]Hierarchical Learning Using Deep Optimum-Path Forest
Luis C. S. Afonso, Clayton R. Pereira, Silke A. T. Weber, Christian Hook, Alexandre X. Falcão, João P. Papa
http://arxiv.org/abs/2102.09312v1
• [cs.AI]Optimising Long-Term Outcomes using Real-World Fluent Objectives: An Application to Football
Ryan Beal, Georgios Chalkiadakis, Timothy J. Norman, Sarvapali D. Ramchurn
http://arxiv.org/abs/2102.09469v1
• [cs.CL]A Systematic Review of Natural Language Processing Applied to Radiology Reports
Arlene Casey, Emma Davidson, Michael Poon, Hang Dong, Daniel Duma, Andreas Grivas, Claire Grover, Víctor Suárez-Paniagua, Richard Tobin, William Whiteley, Honghan Wu, Beatrice Alex
http://arxiv.org/abs/2102.09553v1
• [cs.CL]Cross-SEAN: A Cross-Stitch Semi-Supervised Neural Attention Model for COVID-19 Fake News Detection
William Scott Paka, Rachit Bansal, Abhay Kaushik, Shubhashis Sengupta, Tanmoy Chakraborty
http://arxiv.org/abs/2102.08924v2
• [cs.CL]Echo State Speech Recognition
Harsh Shrivastava, Ankush Garg, Yuan Cao, Yu Zhang, Tara Sainath
http://arxiv.org/abs/2102.09114v1
• [cs.CL]Entity-level Factual Consistency of Abstractive Text Summarization
Feng Nan, Ramesh Nallapati, Zhiguo Wang, Cicero Nogueira dos Santos, Henghui Zhu, Dejiao Zhang, Kathleen McKeown, Bing Xiang
http://arxiv.org/abs/2102.09130v1
• [cs.CL]Fake News Detection: a comparison between available Deep Learning techniques in vector space
Lovedeep Singh
http://arxiv.org/abs/2102.09470v1
• [cs.CL]From Extreme Multi-label to Multi-class: A Hierarchical Approach for Automated ICD-10 Coding Using Phrase-level Attention
Cansu Sen, Bingyang Ye, Javed Aslam, Amir Tahmasebi
http://arxiv.org/abs/2102.09136v1
• [cs.CL]Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer
Rafał Powalski, Łukasz Borchmann, Dawid Jurkiewicz, Tomasz Dwojak, Michał Pietruszka, Gabriela Pałka
http://arxiv.org/abs/2102.09550v1
• [cs.CL]Learning to Select Context in a Hierarchical and Global Perspective for Open-domain Dialogue Generation
Lei Shen, Haolan Zhan, Xin Shen, Yang Feng
http://arxiv.org/abs/2102.09282v1
• [cs.CL]Meta-Transfer Learning for Low-Resource Abstractive Summarization
Yi-Syuan Chen, Hong-Han Shuai
http://arxiv.org/abs/2102.09397v1
• [cs.CL]Quiz-Style Question Generation for News Stories
Adam D. Lelkes, Vinh Q. Tran, Cong Yu
http://arxiv.org/abs/2102.09094v1
• [cs.CL]Regular Expressions for Fast-response COVID-19 Text Classification
Igor L. Markov, Jacqueline Liu, Adam Vagner
http://arxiv.org/abs/2102.09507v1
• [cs.CL]UnibucKernel: Geolocating Swiss-German Jodels Using Ensemble Learning
Mihaela Gaman, Sebastian Cojocariu, Radu Tudor Ionescu
http://arxiv.org/abs/2102.09379v1
• [cs.CR]Data Poisoning Attacks and Defenses to Crowdsourcing Systems
Minghong Fang, Minghao Sun, Qi Li, Neil Zhenqiang Gong, Jin Tian, Jia Liu
http://arxiv.org/abs/2102.09171v1
• [cs.CR]Deep Neural Networks based Invisible Steganography for Audio-into-Image Algorithm
Quang Pham Huu, Thoi Hoang Dinh, Ngoc N. Tran, Toan Pham Van, Thanh Ta Minh
http://arxiv.org/abs/2102.09173v1
• [cs.CR]Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids
Jiangnan Li, Yingyuan Yang, Jinyuan Stella Sun, Kevin Tomsovic, Hairong Qi
http://arxiv.org/abs/2102.09057v1
• [cs.CV]A Comprehensive Review of Deep Learning-based Single Image Super-resolution
Syed Muhammad Arsalan Bashir, Yi Wang, Mahrukh Khan
http://arxiv.org/abs/2102.09351v1
• [cs.CV]An Enhanced Adversarial Network with Combined Latent Features for Spatio-Temporal Facial Affect Estimation in the Wild
Decky Aspandi, Federico Sukno, Björn Schuller, Xavier Binefa
http://arxiv.org/abs/2102.09150v1
• [cs.CV]Automated Detection of Equine Facial Action Units
Zhenghong Li, Sofia Broomé, Pia Haubro Andersen, Hedvig Kjellström
http://arxiv.org/abs/2102.08983v1
• [cs.CV]BEDS: Bagging ensemble deep segmentation for nucleus segmentation with testing stage stain augmentation
Xing Li, Haichun Yang, Jiaxin He, Aadarsh Jha, Agnes B. Fogo, Lee E. Wheless, Shilin Zhao, Yuankai Huo
http://arxiv.org/abs/2102.08990v1
• [cs.CV]CReST: A Class-Rebalancing Self-Training Framework for Imbalanced Semi-Supervised Learning
Chen Wei, Kihyuk Sohn, Clayton Mellina, Alan Yuille, Fan Yang
http://arxiv.org/abs/2102.09559v1
• [cs.CV]Clockwork Variational Autoencoders for Video Prediction
Vaibhav Saxena, Jimmy Ba, Danijar Hafner
http://arxiv.org/abs/2102.09532v1
• [cs.CV]Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction
Daniel Gehrig, Michelle Rüegg, Mathias Gehrig, Javier Hidalgo Carrio, Davide Scaramuzza
http://arxiv.org/abs/2102.09320v1
• [cs.CV]Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts
Soravit Changpinyo, Piyush Sharma, Nan Ding, Radu Soricut
http://arxiv.org/abs/2102.08981v1
• [cs.CV]DSRN: an Efficient Deep Network for Image Relighting
Sourya Dipta Das, Nisarg A. Shah, Saikat Dutta, Himanshu Kumar
http://arxiv.org/abs/2102.09242v1
• [cs.CV]Deep Gait Recognition: A Survey
Alireza Sepas-Moghaddam, Ali Etemad
http://arxiv.org/abs/2102.09546v1
• [cs.CV]Deep Miner: A Deep and Multi-branch Network which Mines Rich and Diverse Features for Person Re-identification
Abdallah Benzine, Mohamed El Amine Seddik, Julien Desmarais
http://arxiv.org/abs/2102.09321v1
• [cs.CV]DeepMetaHandles: Learning Deformation Meta-Handles of 3D Meshes with Biharmonic Coordinates
Minghua Liu, Minhyuk Sung, Radomir Mech, Hao Su
http://arxiv.org/abs/2102.09105v1
• [cs.CV]DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results
Liming Jiang, Zhengkui Guo, Wayne Wu, Zhaoyang Liu, Ziwei Liu, Chen Change Loy, Shuo Yang, Yuanjun Xiong, Wei Xia, Baoying Chen, Peiyu Zhuang, Sili Li, Shen Chen, Taiping Yao, Shouhong Ding, Jilin Li, Feiyue Huang, Liujuan Cao, Rongrong Ji, Changlei Lu, Ganchao Tan
http://arxiv.org/abs/2102.09471v1
• [cs.CV]Densely Nested Top-Down Flows for Salient Object Detection
Chaowei Fang, Haibin Tian, Dingwen Zhang, Qiang Zhang, Jungong Han, Junwei Han
http://arxiv.org/abs/2102.09133v1
• [cs.CV]Domain Adaptation for Medical Image Analysis: A Survey
Hao Guan, Mingxia Liu
http://arxiv.org/abs/2102.09508v1
• [cs.CV]Domain Impression: A Source Data Free Domain Adaptation Method
Vinod K Kurmi, Venkatesh K Subramanian, Vinay P Namboodiri
http://arxiv.org/abs/2102.09003v1
• [cs.CV]Essentials for Class Incremental Learning
Sudhanshu Mittal, Silvio Galesso, Thomas Brox
http://arxiv.org/abs/2102.09517v1
• [cs.CV]Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays
Joseph Paul Cohen, Rupert Brooks, Sovann En, Evan Zucker, Anuj Pareek, Matthew P. Lungren, Akshay Chaudhari
http://arxiv.org/abs/2102.09475v1
• [cs.CV]HVAQ: A High-Resolution Vision-Based Air Quality Dataset
Zuohui Chen, Tony Zhang, Zhuangzhi Chen, Yun Xiang, Qi Xuan, Robert P. Dick
http://arxiv.org/abs/2102.09332v1
• [cs.CV]HandTailor: Towards High-Precision Monocular 3D Hand Recovery
Jun Lv, Wenqiang Xu, Lixin Yang, Sucheng Qian, Chongzhao Mao, Cewu Lu
http://arxiv.org/abs/2102.09244v1
• [cs.CV]Hierarchical Attention Fusion for Geo-Localization
Liqi Yan, Yiming Cui, Yingjie Chen, Dongfang Liu
http://arxiv.org/abs/2102.09186v1
• [cs.CV]Hierarchical Similarity Learning for Language-based Product Image Retrieval
Zhe Ma, Fenghao Liu, Jianfeng Dong, Xiaoye Qu, Yuan He, Shouling Ji
http://arxiv.org/abs/2102.09375v1
• [cs.CV]Image Compositing for Segmentation of Surgical Tools without Manual Annotations
Luis C. Garcia-Peraza-Herrera, Lucas Fidon, Claudia D’Ettorre, Danail Stoyanov, Tom Vercauteren, Sebastien Ourselin
http://arxiv.org/abs/2102.09528v1
• [cs.CV]Improved Point Transformation Methods For Self-Supervised Depth Prediction
Chen Ziwen, Zixuan Guo, Jerod Weinman
http://arxiv.org/abs/2102.09142v1
• [cs.CV]Minimizing false negative rate in melanoma detection and providing insight into the causes of classification
Ellák Somfai, Benjámin Baffy, Kristian Fenech, Changlu Guo, Rita Hosszú, Dorina Korózs, Marcell Pólik, Attila Ulbert, András Lőrincz
http://arxiv.org/abs/2102.09199v1
• [cs.CV]Mobile Computational Photography: A Tour
Mauricio Delbracio, Damien Kelly, Michael S. Brown, Peyman Milanfar
http://arxiv.org/abs/2102.09000v1
• [cs.CV]Multi-Agent Reinforcement Learning of 3D Furniture Layout Simulation in Indoor Graphics Scenes
Xinhan Di, Pengqian Yu
http://arxiv.org/abs/2102.09137v1
• [cs.CV]NuCLS: A scalable crowdsourcing, deep learning approach and dataset for nucleus classification, localization and segmentation
Mohamed Amgad, Lamees A. Atteya, Hagar Hussein, Kareem Hosny Mohammed, Ehab Hafiz, Maha A. T. Elsebaie, Ahmed M. Alhusseiny, Mohamed Atef AlMoslemany, Abdelmagid M. Elmatboly, Philip A. Pappalardo, Rokia Adel Sakr, Pooya Mobadersany, Ahmad Rachid, Anas M. Saad, Ahmad M. Alkashash, Inas A. Ruhban, Anas Alrefai, Nada M. Elgazar, Ali Abdulkarim, Abo-Alela Farag, Amira Etman, Ahmed G. Elsaeed, Yahya Alagha, Yomna A. Amer, Ahmed M. Raslan, Menatalla K. Nadim, Mai A. T. Elsebaie, Ahmed Ayad, Liza E. Hanna, Ahmed Gadallah, Mohamed Elkady, Bradley Drumheller, David Jaye, David Manthey, David A. Gutman, Habiba Elfandy, Lee A. D. Cooper
http://arxiv.org/abs/2102.09099v1
• [cs.CV]One-shot action recognition towards novel assistive therapies
Alberto Sabater, Laura Santos, Jose Santos-Victor, Alexandre Bernardino, Luis Montesano, Ana C. Murillo
http://arxiv.org/abs/2102.08997v1
• [cs.CV]SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering
Bo Liu, Li-Ming Zhan, Li Xu, Lin Ma, Yan Yang, Xiao-Ming Wu
http://arxiv.org/abs/2102.09542v1
• [cs.CV]Sliced Distance for Colour Grading
Hana Alghamdi, Rozenn Dahyot
http://arxiv.org/abs/2102.09297v1
• [cs.CV]Spatio-Temporal Graph Dual-Attention Network for Multi-Agent Prediction and Tracking
Jiachen Li, Hengbo Ma, Zhihao Zhang, Jinning Li, Masayoshi Tomizuka
http://arxiv.org/abs/2102.09117v1
• [cs.CV]StablePose: Learning 6D Object Poses from Geometrically Stable Patches
Junwen Huang, Yifei Shi, Xin Xu, Yifan Zhang, Kai Xu
http://arxiv.org/abs/2102.09334v1
• [cs.CV]Unbiased Teacher for Semi-Supervised Object Detection
Yen-Cheng Liu, Chih-Yao Ma, Zijian He, Chia-Wen Kuo, Kan Chen, Peizhao Zhang, Bichen Wu, Zsolt Kira, Peter Vajda
http://arxiv.org/abs/2102.09480v1
• [cs.CV]Understanding and Creating Art with AI: Review and Outlook
Eva Cetinic, James She
http://arxiv.org/abs/2102.09109v1
• [cs.CY]Biometrics in the Era of COVID-19: Challenges and Opportunities
Marta Gomez-Barrero, Pawel Drozdowski, Christian Rathgeb, Jose Patino, Massimmiliano Todisco, Andras Nautsch, Naser Damer, Jannis Priesnitz, Nicholas Evans, Christoph Busch
http://arxiv.org/abs/2102.09258v1
• [cs.CY]Gender Bias, Social Bias and Representation: 70 Years of Bollywood
Kunal Khadilkar, Ashiqur R. KhudaBukhsh, Tom M. Mitchell
http://arxiv.org/abs/2102.09103v1
• [cs.CY]How do students test software units?
Lex Bijlsma, Niels Doorn, Harrie Passier, Harold Pootjes, Sylvia Stuurman
http://arxiv.org/abs/2102.09368v1
• [cs.CY]HyMap: eliciting hypotheses in early-stage software startups using cognitive mapping
Jorge Melegati, Eduardo Guerra, Xiaofeng Wang
http://arxiv.org/abs/2102.09387v1
• [cs.CY]Optimization Helps Scheduling Nursing Staff at the Long-Term Care Homes of the City of Toronto
Manion Anderson, Merve Bodur, Scott Rathwell, Vahid Sarhangian
http://arxiv.org/abs/2102.09461v1
• [cs.CY]The Small World Phenomenon and Network Analysis of ICT Startup Investment in Indonesia and Singapore
Farid Naufal Aslam, Andry Alamsyah
http://arxiv.org/abs/2102.09102v1
• [cs.DC]Consistent Lock-free Parallel Stochastic Gradient Descent for Fast and Stable Convergence
Karl Bäckström, Ivan Walulya, Marina Papatriantafilou, Philippas Tsigas
http://arxiv.org/abs/2102.09032v1
• [cs.DC]Data-Aware Device Scheduling for Federated Edge Learning
Afaf Taik, Zoubeir Mlika, Soumaya Cherkaoui
http://arxiv.org/abs/2102.09491v1
• [cs.DC]Graph based Data Dependence Identifier for Parallelization of Programs
Kavya Alluru, Jeganathan. L
http://arxiv.org/abs/2102.09317v1
• [cs.DC]Latency Modeling of Hyperledger Fabric for Blockchain-based IoT (BC-IoT) Networks
Sungho Lee, Minsu Kim, Jemin Lee, Ruei-Hau Hsu, Tony Q. S. Quek
http://arxiv.org/abs/2102.09166v1
• [cs.DC]Locally Checkable Problems in Rooted Trees
Alkida Balliu, Sebastian Brandt, Dennis Olivetti, Jan Studený, Jukka Suomela, Aleksandr Tereshchenko
http://arxiv.org/abs/2102.09277v1
• [cs.DC]Network Size Estimation in Small-World Networks under Byzantine Faults
Soumyottam Chatterjee, Gopal Pandurangan, Peter Robinson
http://arxiv.org/abs/2102.09197v1
• [cs.DC]Reaching Consensus for Asynchronous Distributed Key Generation
Ittai Abraham, Philipp Jovanovic, Mary Maller, Sarah Meiklejohn, Gilad Stern, Alin Tomescu
http://arxiv.org/abs/2102.09041v1
• [cs.DC]Strongly Connected Topology Model and Confirmation-based Propagation Method for Cross-chain Interaction
Hong Su, Bing Guo, Yan Shen, Tao Li
http://arxiv.org/abs/2102.09237v1
• [cs.DL]Is preprint the future of science? A thirty year journey of online preprint services
Boya Xie, Zhihong Shen, Kuansan Wang
http://arxiv.org/abs/2102.09066v1
• [cs.DS]Locality in Online Algorithms
Maciej Pacut, Mahmoud Parham, Joel Rybicki, Stefan Schmid, Jukka Suomela, Aleksandr Tereshchenko
http://arxiv.org/abs/2102.09413v1
• [cs.FL]On Typical Hesitant Fuzzy Languages and Automata
Valdigleis S. Costa, Benjamín C. Bedregal, Regivan H. N. Santiago
http://arxiv.org/abs/2102.09347v1
• [cs.HC]Spacewalker: Rapid UI Design Exploration Using Lightweight Markup Enhancement and Crowd Genetic Programming
Mingyuan Zhong, Gang Li, Yang Li
http://arxiv.org/abs/2102.09039v1
• [cs.HC]TapNet: The Design, Training, Implementation, and Applications of a Multi-Task Learning CNN for Off-Screen Mobile Input
Michael Xuelin Huang, Yang Li, Nazneen Nazneen, Alexander Chao, Shumin Zhai
http://arxiv.org/abs/2102.09087v1
• [cs.IR]Dynamic Memory based Attention Network for Sequential Recommendation
Qiaoyu Tan, Jianwei Zhang, Ninghao Liu, Xiao Huang, Hongxia Yang, Jingren Zhou, Xia Hu
http://arxiv.org/abs/2102.09269v1
• [cs.IR]ELIXIR: Learning from User Feedback on Explanations to Improve Recommender Models
Azin Ghazimatin, Soumajit Pramanik, Rishiraj Saha Roy, Gerhard Weikum
http://arxiv.org/abs/2102.09388v1
• [cs.IR]HSR: Hyperbolic Social Recommender
Anchen Li, Bo Yang
http://arxiv.org/abs/2102.09389v1
• [cs.IR]Learning Fair Representations for Bipartite Graph based Recommendation
Le Wu, Lei Chen, Pengyang Shao, Richang Hong, Xiting Wang, Meng Wang
http://arxiv.org/abs/2102.09140v1
• [cs.IR]Link Prediction Approach to Recommender Systems
T. Jaya Lakshmi, S. Durga Bhavani
http://arxiv.org/abs/2102.09185v1
• [cs.IR]Multi-Interest-Aware User Modeling for Large-Scale Sequential Recommendations
Jianxun Lian, Iyad Batal, Zheng Liu, Akshay Soni, Eun Yong Kang, Yajun Wang, Xing Xie
http://arxiv.org/abs/2102.09211v1
• [cs.IR]Recommender Systems for Configuration Knowledge Engineering
Alexander Felfernig, Stefan Reiterer, Martin Stettinger, Florian Reinfrank, Michael Jeran, Gerald Ninaus
http://arxiv.org/abs/2102.08113
8000
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8000
v1)
• [cs.IR]Sparse-Interest Network for Sequential Recommendation
Qiaoyu Tan, Jianwei Zhang, Jiangchao Yao, Ninghao Liu, Jingren Zhou, Hongxia Yang, Xia Hu
http://arxiv.org/abs/2102.09267v1
• [cs.IR]TCN: Table Convolutional Network for Web Table Interpretation
Daheng Wang, Prashant Shiralkar, Colin Lockard, Binxuan Huang, Xin Luna Dong, Meng Jiang
http://arxiv.org/abs/2102.09460v1
• [cs.IR]Testing Lotka’s Law and Pattern of Author Productivity in the Scholarly Publications of Artificial Intelligence
Muneer Ahmad, Dr M Sadik Batcha, S Roselin Jahina
http://arxiv.org/abs/2102.09182v1
• [cs.IR]Training Microsoft News Recommenders with Pretrained Language Models in the Loop
Shitao Xiao, Zheng Liu, Yingxia Shao, Tao Di, Xing Xie
http://arxiv.org/abs/2102.09268v1
• [cs.IR]Truncation-Free Matching System for Display Advertising at Alibaba
Jin Li, Jie Liu, Shangzhou Li, Yao Xu, Ran Cao, Qi Li, Biye Jiang, Guan Wang, Han Zhu, Kun Gai, Xiaoqiang Zhu
http://arxiv.org/abs/2102.09283v1
• [cs.IT]A maximum entropy model of bounded rational decision-making with prior beliefs and market feedback
Benjamin Patrick Evans, Mikhail Prokopenko
http://arxiv.org/abs/2102.09180v1
• [cs.IT]Active Privacy-utility Trade-off Against a Hypothesis Testing Adversary
Ecenaz Erdemir, Pier Luigi Dragotti, Deniz Gunduz
http://arxiv.org/abs/2102.08308v2
• [cs.IT]Can Massive MIMO Support URLLC?
Hangsong Yan, Alexei Ashikhmin, Hong Yang
http://arxiv.org/abs/2102.09156v1
• [cs.IT]Coverage Probability of Distributed IRS Systems Under Spatially Correlated Channels
Anastasios Papazafeiropoulos, Cunhua Pan, Ahmet Elbir, Pandelis Kourtessis, Symeon Chatzinotas, John M. Senior
http://arxiv.org/abs/2102.09416v1
• [cs.IT]DeepMuD: Multi-user Detection for Uplink Grant-Free NOMA IoT Networks via Deep Learning
Ahmet Emir, Ferdi Kara, Hakan Kaya, Halim Yanikomeroglu
http://arxiv.org/abs/2102.09196v1
• [cs.IT]IRS-Assisted Wireless Powered NOMA: Is Dynamic Passive Beamforming Really Needed?
Qingqing Wu, Xiaobo Zhou, Robert Schober
http://arxiv.org/abs/2102.08739v2
• [cs.IT]Mean-Based Trace Reconstruction over Practically any Replication-Insertion Channel
Mahdi Cheraghchi, Joseph Downs, João Ribeiro, Alexandra Veliche
http://arxiv.org/abs/2102.09490v1
• [cs.IT]On isodual double Toeplitz codes
Minjia Shi, Li Xu, Patrick Solé
http://arxiv.org/abs/2102.09233v1
• [cs.IT]On the advantages of stochastic encoders
Lucas Theis, Eirikur Agustsson
http://arxiv.org/abs/2102.09270v1
• [cs.LG]A Bit Better? Quantifying Information for Bandit Learning
Adithya M. Devraj, Benjamin Van Roy, Kuang Xu
http://arxiv.org/abs/2102.09488v1
• [cs.LG]A Machine Learning model of the combination of normalized SD1 and SD2 indexes from 24h-Heart Rate Variability as a predictor of myocardial infarction
Antonio Carlos Silva-Filho, Sara Raquel Dutra-Macedo, Adeilson Serra Mendes Vieira, Cristiano Mostarda
http://arxiv.org/abs/2102.09410v1
• [cs.LG]A Mathematical Principle of Deep Learning: Learn the Geodesic Curve in the Wasserstein Space
Kuo Gai, Shihua Zhang
http://arxiv.org/abs/2102.09235v1
• [cs.LG]A Novel Non-Invasive Estimation of Respiration Rate from Photoplethysmograph Signal Using Machine Learning Model
Md Nazmul Islam Shuzan, Moajjem Hossain Chowdhury, Muhammad E. H. Chowdhury, M. Monir Uddin, Amith Khandakar, Zaid B. Mahbub, Naveed Nawaz
http://arxiv.org/abs/2102.09483v1
• [cs.LG]A matrix approach to detect temporal behavioral patterns at electric vehicle charging stations
Milan Straka, Lucia Piatriková, Peter van Bokhoven, Ľuboš Buzna
http://arxiv.org/abs/2102.09260v1
• [cs.LG]BORE: Bayesian Optimization by Density-Ratio Estimation
Louis C. Tiao, Aaron Klein, Matthias Seeger, Edwin V. Bonilla, Cedric Archambeau, Fabio Ramos
http://arxiv.org/abs/2102.09009v1
• [cs.LG]Boosting for Online Convex Optimization
Elad Hazan, Karan Singh
http://arxiv.org/abs/2102.09305v1
• [cs.LG]Closing the Closed-Loop Distribution Shift in Safe Imitation Learning
Stephen Tu, Alexander Robey, Nikolai Matni
http://arxiv.org/abs/2102.09161v1
• [cs.LG]Combinatorial optimization and reasoning with graph neural networks
Quentin Cappart, Didier Chételat, Elias Khalil, Andrea Lodi, Christopher Morris, Petar Veličković
http://arxiv.org/abs/2102.09544v1
• [cs.LG]Composable Generative Models
Johan Leduc, Nicolas Grislain
http://arxiv.org/abs/2102.09249v1
• [cs.LG]Consistent Non-Parametric Methods for Adaptive Robustness
Robi Bhattacharjee, Kamalika Chaudhuri
http://arxiv.org/abs/2102.09086v1
• [cs.LG]Continuous Doubly Constrained Batch Reinforcement Learning
Rasool Fakoor, Jonas Mueller, Pratik Chaudhari, Alexander J. Smola
http://arxiv.org/abs/2102.09225v1
• [cs.LG]Convergence of stochastic gradient descent schemes for Lojasiewicz-landscapes
Steffen Dereich, Sebastian Kassing
http://arxiv.org/abs/2102.09385v1
• [cs.LG]DINO: A Conditional Energy-Based GAN for Domain Translation
Konstantinos Vougioukas, Stavros Petridis, Maja Pantic
http://arxiv.org/abs/2102.09281v1
• [cs.LG]Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters
Mohita Chaudhary, Mohamed Sadok Gastli, Lobna Nassar, Fakhri Karray
http://arxiv.org/abs/2102.09024v1
• [cs.LG]Deep Learning for Suicide and Depression Identification with Unsupervised Label Correction
Ayaan Haque, Viraaj Reddi, Tyler Giallanza
http://arxiv.org/abs/2102.09427v1
• [cs.LG]Delving into Deep Imbalanced Regression
Yuzhe Yang, Kaiwen Zha, Ying-Cong Chen, Hao Wang, Dina Katabi
http://arxiv.org/abs/2102.09554v1
• [cs.LG]Differential Private Hogwild! over Distributed Local Data Sets
Marten van Dijk, Nhuong V. Nguyen, Toan N. Nguyen, Lam M. Nguyen, Phuong Ha Nguyen
http://arxiv.org/abs/2102.09030v1
• [cs.LG]Distributed Algorithms for Linearly-Solvable Optimal Control in Networked Multi-Agent Systems
Neng Wan, Aditya Gahlawat, Naira Hovakimyan, Evangelos A. Theodorou, Petros G. Voulgaris
http://arxiv.org/abs/2102.09104v1
• [cs.LG]Domain Adaptive Learning Based on Sample-Dependent and Learnable Kernels
Xinlong Lu, Zhengming Ma, Yuanping Lin
http://arxiv.org/abs/2102.09340v1
• [cs.LG]Don’t Fix What ain’t Broke: Near-optimal Local Convergence of Alternating Gradient Descent-Ascent for Minimax Optimization
Guodong Zhang, Yuanhao Wang, Laurent Lessard, Roger Grosse
http://arxiv.org/abs/2102.09468v1
• [cs.LG]Edge Sparse Basis Network: An Deep Learning Framework for EEG Source Localization
Chen Wei, Kexin Lou, Zhengyang Wang, Mingqi Zhao, Dante Mantini, Quanying Liu
http://arxiv.org/abs/2102.09188v1
• [cs.LG]Efficient Reinforcement Learning in Resource Allocation Problems Through Permutation Invariant Multi-task Learning
Desmond Cai, Shiau Hong Lim, Laura Wynter
http://arxiv.org/abs/2102.09361v1
• [cs.LG]Estimate Three-Phase Distribution Line Parameters With Physics-Informed Graphical Learning Method
Wenyu Wang, Nanpeng Yu
http://arxiv.org/abs/2102.09023v1
• [cs.LG]Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm
Sajad Khodadadian, Zaiwei Chen, Siva Theja Maguluri
http://arxiv.org/abs/2102.09318v1
• [cs.LG]FrugalMCT: Efficient Online ML API Selection for Multi-Label Classification Tasks
Lingjiao Chen, Matei Zaharia, James Zou
http://arxiv.org/abs/2102.09127v1
• [cs.LG]Fuzzy clustering algorithms with distance metric learning and entropy regularization
Sara Ines Rizo Rodriguez, Francisco de Assis Tenorio de Carvalho
http://arxiv.org/abs/2102.09529v1
• [cs.LG]GradFreeBits: Gradient Free Bit Allocation for Dynamic Low Precision Neural Networks
Benjamin J. Bodner, Gil Ben Shalom, Eran Treister
http://arxiv.org/abs/2102.09298v1
• [cs.LG]Improving Hierarchical Adversarial Robustness of Deep Neural Networks
Avery Ma, Aladin Virmaux, Kevin Scaman, Juwei Lu
http://arxiv.org/abs/2102.09012v1
• [cs.LG]Knowledge Hypergraph Embedding Meets Relational Algebra
Bahare Fatemi, Perouz Taslakian, David Vazquez, David Poole
http://arxiv.org/abs/2102.09557v1
• [cs.LG]L2E: Learning to Exploit Your Opponent
Zhe Wu, Kai Li, Enmin Zhao, Hang Xu, Meng Zhang, Haobo Fu, Bo An, Junliang Xing
http://arxiv.org/abs/2102.09381v1
• [cs.LG]Learning Continuous Exponential Families Beyond Gaussian
Christopher X. Ren, Sidhant Misra, Marc Vuffray, Andrey Y. Lokhov
http://arxiv.org/abs/2102.09198v1
• [cs.LG]Learning Memory-Dependent Continuous Control from Demonstrations
Siqing Hou, Dongqi Han, Jun Tani
http://arxiv.org/abs/2102.09208v1
• [cs.LG]Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder
Shuqi Lu, Chenyan Xiong, Di He, Guolin Ke, Waleed Malik, Zhicheng Dou, Paul Bennett, Tieyan Liu, Arnold Overwijk
http://arxiv.org/abs/2102.09206v1
• [cs.LG]No-Substitution -means Clustering with Low Center Complexity and Memory
Robi Bhattacharjee, Jacob Imola
http://arxiv.org/abs/2102.09101v1
• [cs.LG]Off-policy Confidence Sequences
Nikos Karampatziakis, Paul Mineiro, Aaditya Ramdas
http://arxiv.org/abs/2102.09540v1
• [cs.LG]Optimizing Black-box Metrics with Iterative Example Weighting
Gaurush Hiranandani, Jatin Mathur, Oluwasanmi Koyejo, Mahdi Milani Fard, Harikrishna Narasimhan
http://arxiv.org/abs/2102.09492v1
• [cs.LG]Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm
Bin Gu, Guodong Liu, Yanfu Zhang, Xiang Geng, Heng Huang
http://arxiv.org/abs/2102.09026v1
• [cs.LG]PLAM: a Posit Logarithm-Approximate Multiplier for Power Efficient Posit-based DNNs
Raul Murillo, Alberto A. Del Barrio, Guillermo Botella, Min Soo Kim, HyunJin Kim, Nader Bagherzadeh
http://arxiv.org/abs/2102.09262v1
• [cs.LG]Random Projections for Improved Adversarial Robustness
Ginevra Carbone, Guido Sanguinetti, Luca Bortolussi
http://arxiv.org/abs/2102.09230v1
• [cs.LG]Recurrent Rational Networks
Quentin Delfosse, Patrick Schramowski, Alejandro Molina, Kristian Kersting
http://arxiv.org/abs/2102.09407v1
• [cs.LG]Reduced-Order Neural Network Synthesis with Robustness Guarantees
Ross Drummond, Mathew C. Turner, Stephen R. Duncan
http://arxiv.org/abs/2102.09284v1
• [cs.LG]Reinforcement Learning for Datacenter Congestion Control
Chen Tessler, Yuval Shpigelman, Gal Dalal, Amit Mandelbaum, Doron Haritan Kazakov, Benjamin Fuhrer, Gal Chechik, Shie Mannor
http://arxiv.org/abs/2102.09337v1
• [cs.LG]Robust PDF Document Conversion Using Recurrent Neural Networks
Nikolaos Livathinos, Cesar Berrospi, Maksym Lysak, Viktor Kuropiatnyk, Ahmed Nassar, Andre Carvalho, Michele Dolfi, Christoph Auer, Kasper Dinkla, Peter Staar
http://arxiv.org/abs/2102.09395v1
• [cs.LG]Robust and Differentially Private Mean Estimation
Xiyang Liu, Weihao Kong, Sham Kakade, Sewoong Oh
http://arxiv.org/abs/2102.09159v1
• [cs.LG]SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning
Félix Chalumeau, Ilan Coulon, Quentin Cappart, Louis-Martin Rousseau
http://arxiv.org/abs/2102.09193v1
• [cs.LG]State Entropy Maximization with Random Encoders for Efficient Exploration
Younggyo Seo, Lili Chen, Jinwoo Shin, Honglak Lee, Pieter Abbeel, Kimin Lee
http://arxiv.org/abs/2102.09430v1
• [cs.LG]Strategic bidding in freight transport using deep reinforcement learning
Wouter van Heeswijk
http://arxiv.org/abs/2102.09253v1
• [cs.LG]Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics
Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik
http://arxiv.org/abs/2102.09548v1
• [cs.LG]Unsupervised Clustering of Time Series Signals using Neuromorphic Energy-Efficient Temporal Neural Networks
Shreyas Chaudhari, Harideep Nair, José M. F. Moura, John Paul Shen
http://arxiv.org/abs/2102.09200v1
• [cs.LG]Using Distance Correlation for Efficient Bayesian Optimization
Takuya Kanazawa
http://arxiv.org/abs/2102.08993v1
• [cs.LG]VAE Approximation Error: ELBO and Conditional Independence
Dmitrij Schlesinger, Alexander Shekhovtsov, Boris Flach
http://arxiv.org/abs/2102.09310v1
• [cs.LG]Verifying Probabilistic Specifications with Functional Lagrangians
Leonard Berrada, Sumanth Dathathri, Krishnamurthy, Dvijotham, Robert Stanforth, Rudy Bunel, Jonathan Uesato, Sven Gowal, M. Pawan Kumar
http://arxiv.org/abs/2102.09479v1
• [cs.RO]A Visibility Roadmap Sampling Approach for a Multi-Robot Visibility-Based Pursuit-Evasion Problem
Trevor Olsen, Anne M. Tumlin, Nicholas M. Stiffler, Jason M. O’Kane
http://arxiv.org/abs/2102.09013v1
• [cs.RO]Communication-free Cohesive Flexible-Object Transport using Decentralized Robot Networks
Yoshua Gombo, Anuj Tiwari, Santosh Devasia
http://arxiv.org/abs/2102.09056v1
• [cs.RO]Hough2Map — Iterative Event-based Hough Transform for High-Speed Railway Mapping
Florian Tschopp, Cornelius von Einem, Andrei Cramariuc, David Hug, Andrew William Palmer, Roland Siegwart, Margarita Chli, Juan Nieto
http://arxiv.org/abs/2102.08145v2
• [cs.RO]Improved Deep Reinforcement Learning with Expert Demonstrations for Urban Autonomous Driving
Haochen Liu, Zhiyu Huang, Chen Lv
http://arxiv.org/abs/2102.09243v1
• [cs.RO]Learning Invariant Representation of Tasks for Robust Surgical State Estimation
Yidan Qin, Max Allan, Yisong Yue, Joel W. Burdick, Mahdi Azizian
http://arxiv.org/abs/2102.09119v1
• [cs.RO]ReSonAte: A Runtime Risk Assessment Framework for Autonomous Systems
Charles Hartsell, Shreyas Ramakrishna, Abhishek Dubey, Daniel Stojcsics, Nagabhushan Mahadevan, Gabor Karsai
http://arxiv.org/abs/2102.09419v1
• [cs.RO]Stochastic Spatio-Temporal Optimization for Control and Co-Design of Systems in Robotics and Applied Physics
Ethan N. Evans, Andrew P. Kendall, Evangelos A. Theodorou
http://arxiv.org/abs/2102.09144v1
• [cs.RO]iX-BSP: Incremental Belief Space Planning
Elad I. Farhi, Vadim Indelman
http://arxiv.org/abs/2102.09539v1
• [cs.SI]A Query-Driven System for Discovering Interesting Subgraphs in Social Media
Subhasis Dasgupta, Amarnath Gupta
http://arxiv.org/abs/2102.09120v1
• [cs.SI]A two-layer model for coevolving opinion dynamics and collective decision-making in complex social systems
Lorenzo Zino, Mengbin Ye, Ming Cao
http://arxiv.org/abs/2102.09285v1
• [cs.SI]Graph Sampling Approach for Reducing Computational Complexity of Large-Scale Social Network
Andry Alamsyah, Yahya Peranginangin, Intan Muchtadi-Alamsyah, Budi Rahardjo, Kuspriyanto
http://arxiv.org/abs/2102.08881v2
• [econ.GN]A Core of E-Commerce Customer Experience based on Conversational Data using Network Text Methodology
Andry Alamsyah, Nurlisa Laksmiani, Lies Anisa Rahimi
http://arxiv.org/abs/2102.09107v1
• [econ.GN]Supportive 5G infrastructure policies are essential for universal 6G: Evidence from an open-source techno-economic simulation model using remote sensing
Edward J. Oughton, Ashutosh Jha
http://arxiv.org/abs/2102.08086v2
• [econ.GN]The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?
Anthony Strittmatter, Conny Wunsch
http://arxiv.org/abs/2102.09207v1
• [econ.GN]Understanding algorithmic collusion with experience replay
Bingyan Han
http://arxiv.org/abs/2102.09139v1
• [eess.IV]Enhanced Magnetic Resonance Image Synthesis with Contrast-Aware Generative Adversarial Networks
Jonas Denck, Jens Guehring, Andreas Maier, Eva Rothgang
http://arxiv.org/abs/2102.09386v1
• [eess.IV]Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Functions from Spherical Data
Axel Elaldi, Neel Dey, Heejong Kim, Guido Gerig
http://arxiv.org/abs/2102.09462v1
• [eess.IV]NFCNN: Toward a Noise Fusion Convolutional Neural Network for Image Denoising
Maoyuan Xu, Xiaoping Xie
http://arxiv.org/abs/2102.09376v1
• [eess.IV]SRDTI: Deep learning-based super-resolution for diffusion tensor MRI
Qiyuan Tian, Ziyu Li, Qiuyun Fan, Chanon Ngamsombat, Yuxin Hu, Congyu Liao, Fuyixue Wang, Kawin Setsompop, Jonathan R. Polimeni, Berkin Bilgic, Susie Y. Huang
http://arxiv.org/abs/2102.09069v1
• [eess.SP]Analysis of EEG data using complex geometric structurization
Eddy Kwessi, Lloyd Edwards
http://arxiv.org/abs/2102.09061v1
• [eess.SP]EEG-based Texture Roughness Classification in Active Tactile Exploration with Invariant Representation Learning Networks
Ozan Ozdenizci, Safaa Eldeeb, Andac Demir, Deniz Erdogmus, Murat Akcakaya
http://arxiv.org/abs/2102.08976v1
• [eess.SP]Inferring Graph Signal Translations as Invariant Transformations for Classification Tasks
Raphael Baena, Lucas Drumetz, Vincent Gripon
http://arxiv.org/abs/2102.09493v1
• [eess.SP]Reinforcement Learning for Beam Pattern Design in Millimeter Wave and Massive MIMO Systems
Yu Zhang, Muhammad Alrabeiah, Ahmed Alkhateeb
http://arxiv.org/abs/2102.09084v1
• [eess.SP]Vision-Aided 6G Wireless Communications: Blockage Prediction and Proactive Handoff
Gouranga Charan, Muhammad Alrabeiah, Ahmed Alkhateeb
http://arxiv.org/abs/2102.09527v1
• [eess.SY]Online Optimization and Learning in Uncertain Dynamical Environments with Performance Guarantees
Dan Li, Dariush Fooladivanda, Sonia Martinez
http://arxiv.org/abs/2102.09111v1
• [hep-lat]Quantum field-theoretic machine learning
Dimitrios Bachtis, Gert Aarts, Biagio Lucini
http://arxiv.org/abs/2102.09449v1
• [math.MG]Center Power and Loci of Poncelet Triangles
Mark Helman, Dominique Laurain, Ronaldo Garcia, Dan Reznik
http://arxiv.org/abs/2102.09438v1
• [math.OC]ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks
Dmitry Kovalev, Egor Shulgin, Peter Richtárik, Alexander Rogozin, Alexander Gasnikov
http://arxiv.org/abs/2102.09234v1
• [math.OC]Joint Continuous and Discrete Model Selection via Submodularity
Jonathan Bunton, Paulo Tabuada
http://arxiv.org/abs/2102.09029v1
• [math.OC]On the Convergence of Step Decay Step-Size for Stochastic Optimization
Xiaoyu Wang, Sindri Magnússon, Mikael Johansson
http://arxiv.org/abs/2102.09393v1
• [math.ST]Convolution of a symmetric log-concave distribution and a symmetric bimodal distribution can have any number of modes
Charles Arnal
http://arxiv.org/abs/2102.09293v1
• [math.ST]Linear Functions to the Extended Reals
Bo Waggoner
http://arxiv.org/abs/2102.09552v1
• [math.ST]Regression-type analysis for block maxima on block maxima
Miguel de Carvalho, Gonçalo dos Reis, Alina Kumukova
http://arxiv.org/abs/2102.09497v1
• [math.ST]Transfer Learning for Linear Regression: a Statistical Test of Gain
David Obst, Badih Ghattas, Jairo Cugliari, Georges Oppenheim, Sandra Claudel, Yannig Goude
http://arxiv.org/abs/2102.09504v1
• [physics.data-an]Data-driven formulation of natural laws by recursive-LASSO-based symbolic regression
Yuma Iwasaki, Masahiko Ishida
http://arxiv.org/abs/2102.09210v1
• [physics.soc-ph]Monitoring behavioural responses during pandemic via reconstructed contact matrices from online and representative surveys
Júlia Koltai, Orsolya Vásárhelyi, Gergely Röst, Márton Karsai
http://arxiv.org/abs/2102.09021v1
• [quant-ph]Evaluating the Performance of Some Local Optimizers for Variational Quantum Classifiers
Nisheeth Joshi, Pragya Katyayan, Syed Afroz Ahmed
http://arxiv.org/abs/2102.08949v1
• [quant-ph]Generalization in Quantum Machine Learning: a Quantum Information Perspective
Leonardo Banchi, Jason Pereira, Stefano Pirandola
http://arxiv.org/abs/2102.08991v1
• [stat.AP]A mathematical take on the competitive balance of a football league
Soudeep Deb
http://arxiv.org/abs/2102.09288v1
• [stat.AP]Bayesian nonparametric analysis for the detection of spikes in noisy calcium imaging data
Laura D’Angelo, Antonio Canale, Zhaoxia Yu, Michele Guindani
http://arxiv.org/abs/2102.09403v1
• [stat.AP]Experimental Designs for Accelerated Degradation Tests Based on Linear Mixed Effects Models
Helmi Shat, Rainer Schwabe
http://arxiv.org/abs/2102.09446v1
• [stat.AP]hesim: Health Economic Simulation Modeling and Decision Analysis
Devin Incerti, Jeroen P Jansen
http://arxiv.org/abs/2102.09437v1
• [stat.ME]A Generative Approach to Joint Modeling of Quantitative and Qualitative Responses
Xiaoning Kang, Lulu Kang, Wei Chen, Xinwei Deng
http://arxiv.org/abs/2102.09448v1
• [stat.ME]Adaptive Step-Length Selection in Gradient Boosting for Generalized Additive Models for Location, Scale and Shape
Boyao Zhang, Tobias Hepp, Sonja Greven, Elisabeth Bergherr
http://arxiv.org/abs/2102.09248v1
• [stat.ME]Adjusting the Benjamini-Hochberg method for controlling the false discovery rate in knockoff assisted variable selection
Sanat K. Sarkar, Cheng Yong Tang
http://arxiv.org/abs/2102.09080v1
• [stat.ME]Big Data meets Causal Survey Research: Understanding Nonresponse in the Recruitment of a Mixed-mode Online Panel
Barbara Felderer, Jannis Kueck, Martin Spindler
http://arxiv.org/abs/2102.08994v1
• [stat.ME]Copula-based Sensitivity Analysis for Multi-Treatment Causal Inference with Unobserved Confounding
Jiajing Zheng, Alexander D’Amour, Alexander Franks
http://arxiv.org/abs/2102.09412v1
• [stat.ME]Counterfactual Inference of the Mean Outcome under a Convergence of Average Logging Probability
Masahiro Kato
http://arxiv.org/abs/2102.08975v1
• [stat.ME]Divide-and-Conquer MCMC for Multivariate Binary Data
Suchit Mehrotra, Halley Brantley, Jacob Westman, Lauren Bangerter, Arnab Maity
http://arxiv.org/abs/2102.09008v1
• [stat.ME]Estimating Perinatal Critical Windows to Environmental Mixtures via Structured Bayesian Regression Tree Pairs
Daniel Mork, Ander Wilson
http://arxiv.org/abs/2102.09071v1
• [stat.ME]Estimating The Proportion of Signal Variables Under Arbitrary Covariance Dependence
X. Jessie Jeng
http://arxiv.org/abs/2102.09053v1
• [stat.ME]Multilevel calibration weighting for survey data
Eli Ben-Michael, Avi Feller, Erin Hartman
http://arxiv.org/abs/2102.09052v1
• [stat.ME]The Variational Bayesian Inference for Network Autoregression Models
Wei-Ting Lai, Ray-Bing Chen, Ying Chen, Thorsten Koch
http://arxiv.org/abs/2102.09232v1
• [stat.ML]Convex regularization in statistical inverse learning problems
Tatiana A. Bubba, Martin Burger, Tapio Helin and
http://arxiv.org/abs/2102.09526v1
• [stat.ML]Deep Extreme Value Copulas for Estimation and Sampling
Ali Hasan, Khalil Elkhalil, Joao M. Pereira, Sina Farsiu, Jose H. Blanchet, Vahid Tarokh
http://arxiv.org/abs/2102.09042v1
• [stat.ML]Non-approximate Inference for Collective Graphical Models on Path Graphs via Discrete Difference of Convex Algorithm
Yasunori Akagi, Naoki Marumo, Hideaki Kim, Takeshi Kurashima, Hiroyuki Toda
http://arxiv.org/abs/2102.09191v1
• [stat.ML]Towards a mathematical theory of trajectory inference
Hugo Lavenant, Stephen Zhang, Young-Heon Kim, Geoffrey Schiebinger
http://arxiv.org/abs/2102.09204v1
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