astro-ph.GA - 星系天体物理学 cond-mat.soft - 软凝聚物质 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.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 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 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.AG - 代数几何 math.CO - 组合数学 math.OC - 优化与控制 math.ST - 统计理论 physics.ao-ph - 大气和海洋物理 physics.data-an - 数据分析、 统计和概率 physics.flu-dyn - 流体动力学 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

    • [astro-ph.GA]A Deep Learning Approach for Characterizing Major Galaxy Mergers
    • [cond-mat.soft]Deep learning approaches to surrogates for solving the diffusion equation for mechanistic real-world simulations
    • [cs.AI]Player Modeling via Multi-Armed Bandits
    • [cs.AI]Uncertainty Quantification and Propagation for Airline Disruption Management
    • [cs.AR]Hybrid In-memory Computing Architecture for the Training of Deep Neural Networks
    • [cs.CL]AuGPT: Dialogue with Pre-trained Language Models and Data Augmentation
    • [cs.CL]Biomedical Question Answering: A Comprehensive Review
    • [cs.CL]Broader terms curriculum mapping: Using natural language processing and visual-supported communication to create representative program planning experiences
    • [cs.CL]Decontextualization: Making Sentences Stand-Alone
    • [cs.CL]Generating Synthetic Text Data to Evaluate Causal Inference Methods
    • [cs.CL]Language Models for Lexical Inference in Context
    • [cs.CL]Multi-turn Dialogue Reading Comprehension with Pivot Turns and Knowledge
    • [cs.CL]NUVA: A Naming Utterance Verifier for Aphasia Treatment
    • [cs.CL]SensPick: Sense Picking for Word Sense Disambiguation
    • [cs.CL]Towards More Fine-grained and Reliable NLP Performance Prediction
    • [cs.CR]Concealer: SGX-based Secure, Volume Hiding, and Verifiable Processing of Spatial Time-Series Datasets
    • [cs.CR]DANTE: Predicting Insider Threat using LSTM on system logs
    • [cs.CR]Dompteur: Taming Audio Adversarial Examples
    • [cs.CR]Information Prediction using Knowledge Graphs for Contextual Malware Threat Intelligence
    • [cs.CR]Malware Knowledge Graph Generation
    • [cs.CR]Node-Level Membership Inference Attacks Against Graph Neural Networks
    • [cs.CV]A Generic Object Re-identification System for Short Videos
    • [cs.CV]Application of Yolo on Mask Detection Task
    • [cs.CV]Automated Video Labelling: Identifying Faces by Corroborative Evidence
    • [cs.CV]Classification of Long Noncoding RNA Elements Using Deep Convolutional Neural Networks and Siamese Networks
    • [cs.CV]Culture-inspired Multi-modal Color Palette Generation and Colorization: A Chinese Youth Subculture Case
    • [cs.CV]Deep Multilabel CNN for Forensic Footwear Impression Descriptor Identification
    • [cs.CV]Deep learning architectural designs for super-resolution of noisy images
    • [cs.CV]Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis
    • [cs.CV]Doctor Imitator: A Graph-based Bone Age Assessment Framework Using Hand Radiographs
    • [cs.CV]Dynamic Neural Networks: A Survey
    • [cs.CV]Enhancing Real-World Adversarial Patches with 3D Modeling Techniques
    • [cs.CV]Enhancing efficiency of object recognition in different categorization levels by reinforcement learning in modular spiking neural networks
    • [cs.CV]Exploiting Depth Information for Wildlife Monitoring
    • [cs.CV]H3D: Benchmark on Semantic Segmentation of High-Resolution 3D Point Clouds and textured Meshes from UAV LiDAR and Multi-View-Stereo
    • [cs.CV]Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement
    • [cs.CV]Is Space-Time Attention All You Need for Video Understanding?
    • [cs.CV]LIFT-CAM: Towards Better Explanations for Class Activation Mapping
    • [cs.CV]Locally Free Weight Sharing for Network Width Search
    • [cs.CV]Negative Data Augmentation
    • [cs.CV]Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learning
    • [cs.CV]Polarimetric Monocular Dense Mapping Using Relative Deep Depth Prior
    • [cs.CV]RODNet: A Real-Time Radar Object Detection Network Cross-Supervised by Camera-Radar Fused Object 3D Localization
    • [cs.CV]Regional Attention with Architecture-Rebuilt 3D Network for RGB-D Gesture Recognition
    • [cs.CV]RoBIC: A benchmark suite for assessing classifiers robustness
    • [cs.CV]Scale Normalized Image Pyramids with AutoFocus for Object Detection
    • [cs.CV]Searching for Alignment in Face Recognition
    • [cs.CV]Searching for Fast Model Families on Datacenter Accelerators
    • [cs.CV]Sequential vessel segmentation via deep channel attention network
    • [cs.CV]The Role of the Input in Natural Language Video Description
    • [cs.CV]Training Vision Transformers for Image Retrieval
    • [cs.CV]Two Novel Performance Improvements for Evolving CNN Topologies
    • [cs.CY]A First Look at COVID-19 Domain Names: Origin and Implications
    • [cs.CY]Dark Web Marketplaces and COVID-19: The vaccines
    • [cs.CY]Epidemiological and public health requirements for COVID-19 contact tracing apps and their evaluation
    • [cs.CY]Last Query Transformer RNN for knowledge tracing
    • [cs.CY]The Use and Misuse of Counterfactuals in Ethical Machine Learning
    • [cs.CY]comparing card-based vaccine credential systems with app-based vaccine credential systems
    • [cs.DB]Explaining Inference Queries with Bayesian Optimization
    • [cs.DC]A High-Performance Sparse Tensor Algebra Compiler in Multi-Level IR
    • [cs.DC]DHLink: A Microservice Platform supporting Rapid Application Development and Secure Real-time Data Sharing in Digital Health
    • [cs.DC]Energy-Aware Adaptive Offloading of Soft Real-Time Jobs in Mobile Edge Clouds
    • [cs.DC]Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures
    • [cs.DC]Using hardware performance counters to speed up autotuning convergence on GPUs
    • [cs.DS]Parallel Minimum Cuts in 今日学术视野(2021.2.12) - 图1)#card=math&code=O%28m%20%5Clog%5E2%28n%29%29) Work and Low Depth
    • [cs.HC]RECAST: Enabling User Recourse and Interpretability of Toxicity Detection Models with Interactive Visualization
    • [cs.HC]The human-AI relationship in decision-making: AI explanation to support people on justifying their decisions
    • [cs.HC]VINS: Visual Search for Mobile User Interface Design
    • [cs.IR]CNN Application in Detection of Privileged Documents in Legal Document Review
    • [cs.IR]Enhancing Reading Strategies by Exploring A Theme-based Approach to Literature Surveys
    • [cs.IR]Information Extraction From Co-Occurring Similar Entities
    • [cs.IT]Capacity Optimality of AMP in Coded Systems
    • [cs.IT]Constrained Secrecy Capacity of Partial-Response Wiretap Channels
    • [cs.IT]Delay-Phase Precoding for Wideband THz Massive MIMO
    • [cs.IT]Differential Entropy Rate Characterisations of Long Range Dependent Processes
    • [cs.IT]Differential Privacy for Binary Functions via Randomized Graph Colorings
    • [cs.IT]Downlink Channel Reconstruction for Spatial Multiplexing in Massive MIMO Systems
    • [cs.IT]Impact of Bit Allocation Strategies on Machine Learning Performance in Rate Limited Systems
    • [cs.IT]Intelligent Reflecting Surface-assisted MU-MISO Systems with Imperfect Hardware: Channel Estimation, Beamforming Design
    • [cs.IT]On the Distribution of the Sum of Double-Nakagami-m Random Vectors and Application in Reconfigurable Intelligent Surfaces
    • [cs.IT]On the Properties of Kullback-Leibler Divergence Between Gaussians
    • [cs.IT]Optimum Detection of Defective Elements in Non-Adaptive Group Testing
    • [cs.IT]Proximal Decoding for LDPC-coded Massive MIMO Channels
    • [cs.IT]Reinforcement Learning for Optimized Beam Training in Multi-Hop Terahertz Communications
    • [cs.IT]Trace Reconstruction with Bounded Edit Distance
    • [cs.LG]”What’s in the box?!”: Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models
    • [cs.LG]Addressing the Topological Defects of Disentanglement via Distributed Operators
    • [cs.LG]Advanced Ore Mine Optimisation under Uncertainty Using Evolution
    • [cs.LG]Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers
    • [cs.LG]Adversarial Robustness: What fools you makes you stronger
    • [cs.LG]Adversarially Robust Classifier with Covariate Shift Adaptation
    • [cs.LG]Agnostic Proper Learning of Halfspaces under Gaussian Marginals
    • [cs.LG]An Efficient Pessimistic-Optimistic Algorithm for Constrained Linear Bandits
    • [cs.LG]An Optimal Witness Function for Two-Sample Testing
    • [cs.LG]Attentive Gaussian processes for probabilistic time-series generation
    • [cs.LG]BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
    • [cs.LG]Backdoor Scanning for Deep Neural Networks through K-Arm Optimization
    • [cs.LG]Bayesian Inference with Certifiable Adversarial Robustness
    • [cs.LG]Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
    • [cs.LG]Boosting Template-based SSVEP Decoding by Cross-domain Transfer Learning
    • [cs.LG]Bounded Memory Active Learning through Enriched Queries
    • [cs.LG]CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
    • [cs.LG]CaPC Learning: Confidential and Private Collaborative Learning
    • [cs.LG]Classifier Calibration: with implications to threat scores in cybersecurity
    • [cs.LG]Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels
    • [cs.LG]Continuous-Time Model-Based Reinforcement Learning
    • [cs.LG]Detecting corruption in single-bidder auctions via positive-unlabelled learning
    • [cs.LG]Domain Invariant Representation Learning with Domain Density Transformations
    • [cs.LG]Driver2vec: Driver Identification from Automotive Data
    • [cs.LG]Dynamic 今日学术视野(2021.2.12) - 图2-VAEs for quantifying biodiversity by clustering optically recorded insect signals
    • [cs.LG]Early Abandoning and Pruning for Elastic Distances
    • [cs.LG]Energy-Harvesting Distributed Machine Learning
    • [cs.LG]FLOP: Federated Learning on Medical Datasets using Partial Networks
    • [cs.LG]Fast Classification Learning with Neural Networks and Conceptors for Speech Recognition and Car Driving Maneuvers
    • [cs.LG]Finding the Stochastic Shortest Path with Low Regret: The Adversarial Cost and Unknown Transition Case
    • [cs.LG]Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF)
    • [cs.LG]GuiltyWalker: Distance to illicit nodes in the Bitcoin network
    • [cs.LG]Hyperbolic Generative Adversarial Network
    • [cs.LG]Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov noise
    • [cs.LG]Improving Model-Based Reinforcement Learning with Internal State Representations through Self-Supervision
    • [cs.LG]Inductive Granger Causal Modeling for Multivariate Time Series
    • [cs.LG]Input Similarity from the Neural Network Perspective
    • [cs.LG]Input Similarity from the Neural Network Perspective
    • [cs.LG]Label Smoothed Embedding Hypothesis for Out-of-Distribution Detection
    • [cs.LG]Learning Equational Theorem Proving
    • [cs.LG]Locally Adaptive Label Smoothing for Predictive Churn
    • [cs.LG]MAIN:
    1000
    Multihead-Attention Imputation Networks
    • [cs.LG]Memory-Associated Differential Learning
    • [cs.LG]Meta Federated Learning
    • [cs.LG]NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series Forecasting
    • [cs.LG]Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach
    • [cs.LG]Nonstochastic Bandits with Infinitely Many Experts
    • [cs.LG]On Explainability of Graph Neural Networks via Subgraph Explorations
    • [cs.LG]On Minibatch Noise: Discrete-Time SGD, Overparametrization, and Bayes
    • [cs.LG]On PyTorch Implementation of Density Estimators for von Mises-Fisher and Its Mixture
    • [cs.LG]Output Perturbation for Differentially Private Convex Optimization with Improved Population Loss Bounds, Runtimes and Applications to Private Adversarial Training
    • [cs.LG]Patterns, predictions, and actions: A story about machine learning
    • [cs.LG]Personalization for Web-based Services using Offline Reinforcement Learning
    • [cs.LG]Policy Augmentation: An Exploration Strategy for Faster Convergence of Deep Reinforcement Learning Algorithms
    • [cs.LG]Regression Oracles and Exploration Strategies for Short-Horizon Multi-Armed Bandits
    • [cs.LG]Risk-Averse Offline Reinforcement Learning
    • [cs.LG]Robust Federated Learning with Attack-Adaptive Aggregation
    • [cs.LG]Robustness in Compressed Neural Networks for Object Detection
    • [cs.LG]Scheduling the NASA Deep Space Network with Deep Reinforcement Learning
    • [cs.LG]Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent State
    • [cs.LG]Simple and Near-Optimal MAP Inference for Nonsymmetric DPPs
    • [cs.LG]Stability of SGD: Tightness Analysis and Improved Bounds
    • [cs.LG]Systematic Generalization for Predictive Control in Multivariate Time Series
    • [cs.LG]Task-Optimal Exploration in Linear Dynamical Systems
    • [cs.LG]The importance of understanding instance-level noisy labels
    • [cs.LG]Towards Certifying 今日学术视野(2021.2.12) - 图3 Robustness using Neural Networks with 今日学术视野(2021.2.12) - 图4-dist Neurons
    • [cs.LG]Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network
    • [cs.LG]Using Deep LSD to build operators in GANs latent space with meaning in real space
    • [cs.NE]A Neural Network with Local Learning Rules for Minor Subspace Analysis
    • [cs.NE]A Similarity-preserving Neural Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit
    • [cs.NE]Heuristic Strategies for Solving Complex Interacting Stockpile Blending Problem with Chance Constraints
    • [cs.NE]Pruning of Convolutional Neural Networks Using Ising Energy Model
    • [cs.NE]Towards Feature-Based Performance Regression Using Trajectory Data
    • [cs.NI]Interrupting Real-Time IoT Tasks: How Bad Can It Be to Connect Your Critical Embedded System to the Internet?
    • [cs.RO]Belief Space Planning for Mobile Robots with Range Sensors using iLQG
    • [cs.RO]DARE-SLAM: Degeneracy-Aware and Resilient Loop Closing in Perceptually-Degraded Environments
    • [cs.RO]Learning Interaction-Aware Trajectory Predictions for Decentralized Multi-Robot Motion Planning in Dynamic Environments
    • [cs.RO]Manipulability optimization for multi-arm teleoperation
    • [cs.RO]Origami spring-inspired shape morphing for flexible robotics
    • [cs.RO]PLGRIM: Hierarchical Value Learning for Large-scale Exploration in Unknown Environments
    • [cs.RO]Toward Safe and Efficient Human-Robot Interaction via Behavior-Driven Danger Signaling
    • [cs.RO]Transfer Reinforcement Learning across Homotopy Classes
    • [cs.SD]Enhancing Audio Augmentation Methods with Consistency Learning
    • [cs.SD]Voice Cloning: a Multi-Speaker Text-to-Speech Synthesis Approach based on Transfer Learning
    • [cs.SE]GitHub Discussions: An Exploratory Study of Early Adoption
    • [cs.SI]A note on (matricial and fast) ways to compute Burt’s structural holes
    • [cs.SI]ParmoSense: A Scenario-based Participatory Mobile Urban Sensing Platform with User Motivation Engine
    • [cs.SI]Sampling Subgraph Network with Application to Graph Classification
    • [eess.AS]CDPAM: Contrastive learning for perceptual audio similarity
    • [eess.IV]D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention Mechanism
    • [eess.IV]Dysplasia grading of colorectal polyps through CNN analysis of WSI
    • [eess.IV]Learning to Enhance Visual Quality via Hyperspectral Domain Mapping
    • [eess.IV]Reference-based Texture transfer for Single Image Super-resolution of Magnetic Resonance images
    • [eess.SP]Joint Design of Transmit Waveforms and Receive Filters for MIMO Radar via Manifold Optimization
    • [eess.SY]Adaptive Processor Frequency Adjustment for Mobile Edge Computing with Intermittent Energy Supply
    • [math.AG]Rational points on cubic surfaces and AG codes from the Norm-Trace curve
    • [math.CO]Slicing the hypercube is not easy
    • [math.OC]A Framework of Inertial Alternating Direction Method of Multipliers for Non-Convex Non-Smooth Optimization
    • [math.OC]An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians
    • [math.OC]Local and Global Uniform Convexity Conditions
    • [math.OC]Nonlinear Observers Design for Vision-Aided Inertial Navigation Systems
    • [math.ST]Global jump filters and realized volatility
    • [math.ST]There are natural scores: Full comment on Shafer, “Testing by betting: A strategy for statistical and scientific communication”
    • [physics.ao-ph]Sub-seasonal forecasting with a large ensemble of deep-learning weather prediction models
    • [physics.data-an]Point Cloud Transformers applied to Collider Physics
    • [physics.flu-dyn]Dynamic Mode Decomposition of inertial particle caustics in Taylor-Green flow
    • [physics.soc-ph]No Echo in the Chambers of Political Interactions on Reddit
    • [quant-ph]On the Hardness of PAC-learning stabilizer States with Noise
    • [stat.AP]Designing group sequential clinical trials when a delayed effect is anticipated: A practical guidance
    • [stat.ME]Bayesian Knockoff Filter Using Gibbs Sampler
    • [stat.ME]Currents and K-functions for Fiber Point Processes
    • [stat.ME]Fisher Scoring for crossed factor Linear Mixed Models
    • [stat.ME]On a Bivariate Copula for Modeling Negative Dependence
    • [stat.ME]On structural and practical identifiability
    • [stat.ML]An exact solver for the Weston-Watkins SVM subproblem
    • [stat.ML]Argmax Flows and Multinomial Diffusion: Towards Non-Autoregressive Language Models
    • [stat.ML]Concentrated Document Topic Model
    • [stat.ML]Conditional Versus Adversarial Euler-based Generators For Time Series
    • [stat.ML]Emotion Transfer Using Vector-Valued Infinite Task Learning
    • [stat.ML]On Disentanglement in Gaussian Process Variational Autoencoders
    • [stat.ML]On the Existence of Optimal Transport Gradient for Learning Generative Models
    • [stat.ML]On the Regularity of Attention
    • [stat.ML]On the Suboptimality of Thompson Sampling in High Dimensions
    • [stat.ML]Regularization Strategies for Quantile Regression
    • [stat.ML]Robust estimation of tree structured models
    • [stat.ML]Statistical Inference for Polyak-Ruppert Averaged Zeroth-order Stochastic Gradient Algorithm

    ·····································

    • [astro-ph.GA]A Deep Learning Approach for Characterizing Major Galaxy Mergers
    Skanda Koppula, Victor Bapst, Marc Huertas-Company, Sam Blackwell, Agnieszka Grabska-Barwinska, Sander Dieleman, Andrea Huber, Natasha Antropova, Mikolaj Binkowski, Hannah Openshaw, Adria Recasens, Fernando Caro, Avishai Deke, Yohan Dubois, Jesus Vega Ferrero, David C. Koo, Joel R. Primack, Trevor Back
    http://arxiv.org/abs/2102.05182v1

    • [cond-mat.soft]Deep learning approaches to surrogates for solving the diffusion equation for mechanistic real-world simulations
    J. Quetzalcóatl Toledo-Marín, Geoffrey Fox, James P. Sluka, James A. Glazier
    http://arxiv.org/abs/2102.05527v1

    • [cs.AI]Player Modeling via Multi-Armed Bandits
    Robert C. Gray, Jichen Zhu, Dannielle Arigo, Evan Forman, Santiago Ontañón
    http://arxiv.org/abs/2102.05264v1

    • [cs.AI]Uncertainty Quantification and Propagation for Airline Disruption Management
    Kolawole Ogunsina, Marios Papamichalis, Daniel DeLaurentis
    http://arxiv.org/abs/2102.05147v1

    • [cs.AR]Hybrid In-memory Computing Architecture for the Training of Deep Neural Networks
    Vinay Joshi, Wangxin He, Jae-sun Seo, Bipin Rajendran
    http://arxiv.org/abs/2102.05271v1

    • [cs.CL]AuGPT: Dialogue with Pre-trained Language Models and Data Augmentation
    Jonáš Kulhánek, Vojtěch Hudeček, Tomáš Nekvinda, Ondřej Dušek
    http://arxiv.org/abs/2102.05126v1

    • [cs.CL]Biomedical Question Answering: A Comprehensive Review
    Qiao Jin, Zheng Yuan, Guangzhi Xiong, Qianlan Yu, Chuanqi Tan, Mosha Chen, Songfang Huang, Xiaozhong Liu, Sheng Yu
    http://arxiv.org/abs/2102.05281v1

    • [cs.CL]Broader terms curriculum mapping: Using natural language processing and visual-supported communication to create representative program planning experiences
    Rogério Duarte, Ângela Lacerda Nobre, Fernando Pimentel, Marc Jacquinet
    http://arxiv.org/abs/2102.04811v2

    • [cs.CL]Decontextualization: Making Sentences Stand-Alone
    Eunsol Choi, Jennimaria Palomaki, Matthew Lamm, Tom Kwiatkowski, Dipanjan Das, Michael Collins
    http://arxiv.org/abs/2102.05169v1

    • [cs.CL]Generating Synthetic Text Data to Evaluate Causal Inference Methods
    Zach Wood-Doughty, Ilya Shpitser, Mark Dredze
    http://arxiv.org/abs/2102.05638v1

    • [cs.CL]Language Models for Lexical Inference in Context
    Martin Schmitt, Hinrich Schütze
    http://arxiv.org/abs/2102.05331v1

    • [cs.CL]Multi-turn Dialogue Reading Comprehension with Pivot Turns and Knowledge
    Zhuosheng Zhang, Junlong Li, Hai Zhao
    http://arxiv.org/abs/2102.05474v1

    • [cs.CL]NUVA: A Naming Utterance Verifier for Aphasia Treatment
    David Sabate Barbera, Mark Huckvale, Victoria Fleming, Emily Upton, Henry Coley-Fisher, Catherine Doogan, Ian Shaw, William Latham, Alexander P. Leff, Jenny Crinion
    http://arxiv.org/abs/2102.05408v1

    • [cs.CL]SensPick: Sense Picking for Word Sense Disambiguation
    Sm Zobaed, Md Enamul Haque, Md Fazle Rabby, Mohsen Amini Salehi
    http://arxiv.org/abs/2102.05260v1

    • [cs.CL]Towards More Fine-grained and Reliable NLP Performance Prediction
    Zihuiwen Ye, Pengfei Liu, Jinlan Fu, Graham Neubig
    http://arxiv.org/abs/2102.05486v1

    • [cs.CR]Concealer: SGX-based Secure, Volume Hiding, and Verifiable Processing of Spatial Time-Series Datasets
    Peeyush Gupta, Sharad Mehrotra, Shantanu Sharma, Nalini Venkatasubramanian, Guoxi Wang
    http://arxiv.org/abs/2102.05238v1

    • [cs.CR]DANTE: Predicting Insider Threat using LSTM on system logs
    Nidhi Rastogi, Qicheng Ma
    http://arxiv.org/abs/2102.05600v1

    • [cs.CR]Dompteur: Taming Audio Adversarial Examples
    Thorsten Eisenhofer, Lea Schönherr, Joel Frank, Lars Speckemeier, Dorothea Kolossa, Thorsten Holz
    http://arxiv.org/abs/2102.05431v1

    • [cs.CR]Information Prediction using Knowledge Graphs for Contextual Malware Threat Intelligence
    Nidhi Rastogi, Sharmishtha Dutta, Ryan Christian, Mohammad Zaki, Alex Gittens, Charu Aggarwal
    http://arxiv.org/abs/2102.05571v1

    • [cs.CR]Malware Knowledge Graph Generation
    Sharmishtha Dutta, Nidhi Rastogi, Destin Yee, Chuqiao Gu, Qicheng Ma
    http://arxiv.org/abs/2102.05583v1

    • [cs.CR]Node-Level Membership Inference Attacks Against Graph Neural Networks
    Xinlei He, Rui Wen, Yixin Wu, Michael Backes, Yun Shen, Yang Zhang
    http://arxiv.org/abs/2102.05429v1

    • [cs.CV]A Generic Object Re-identification System for Short Videos
    Tairu Qiu, Guanxian Chen, Zhongang Qi, Bin Li, Ying Shan, Xiangyang Xue
    http://arxiv.org/abs/2102.05275v1

    • [cs.CV]Application of Yolo on Mask Detection Task
    Ren Liu, Ziang Ren
    http://arxiv.org/abs/2102.05402v1

    • [cs.CV]Automated Video Labelling: Identifying Faces by Corroborative Evidence
    Andrew Brown, Ernesto Coto, Andrew Zisserman
    http://arxiv.org/abs/2102.05645v1

    • [cs.CV]Classification of Long Noncoding RNA Elements Using Deep Convolutional Neural Networks and Siamese Networks
    Brian McClannahan, Cucong Zhong, Guanghui Wang
    http://arxiv.org/abs/2102.05582v1

    • [cs.CV]Culture-inspired Multi-modal Color Palette Generation and Colorization: A Chinese Youth Subculture Case
    Yufan Li, Jinggang Zhuo, Ling Fan, Harry Jiannan Wang
    http://arxiv.org/abs/2102.05231v1

    • [cs.CV]Deep Multilabel CNN for Forensic Footwear Impression Descriptor Identification
    Marcin Budka, Akanda Wahid Ul Ashraf, Scott Neville, Alun Mackrill, Matthew Bennett
    http://arxiv.org/abs/2102.05090v1

    • [cs.CV]Deep learning architectural designs for super-resolution of noisy images
    Angel Villar-Corrales, Franziska Schirrmacher, Christian Riess
    http://arxiv.org/abs/2102.05105v1

    • [cs.CV]Detecting Localized Adversarial Examples: A Generic Approach using Critical Region Analysis
    Fengting Li, Xuankai Liu, Xiaoli Zhang, Qi Li, Kun Sun, Kang Li
    http://arxiv.org/abs/2102.05241v1

    • [cs.CV]Doctor Imitator: A Graph-based Bone Age Assessment Framework Using Hand Radiographs
    Jintai Chen, Bohan Yu, Biwen Lei, Ruiwei Feng, Danny Z. Chen, Jian Wu
    http://arxiv.org/abs/2102.05424v1

    • [cs.CV]Dynamic Neural Networks: A Survey
    Yizeng Han, Gao Huang, Shiji Song, Le Yang, Honghui Wang, Yulin Wang
    http://arxiv.org/abs/2102.04906v2

    • [cs.CV]Enhancing Real-World Adversarial Patches with 3D Modeling Techniques
    Yael Mathov, Lior Rokach, Lior Rokach
    http://arxiv.org/abs/2102.05334v1

    • [cs.CV]Enhancing efficiency of object recognition in different categorization levels by reinforcement learning in modular spiking neural networks
    Fatemeh Sharifizadeh, Mohammad Ganjtabesh, Abbas Nowzari-Dalini
    http://arxiv.org/abs/2102.05401v1

    • [cs.CV]Exploiting Depth Information for Wildlife Monitoring
    Timm Haucke, Volker Steinhage
    http://arxiv.org/abs/2102.05607v1

    • [cs.CV]H3D: Benchmark on Semantic Segmentation of High-Resolution 3D Point Clouds and textured Meshes from UAV LiDAR and Multi-View-Stereo
    Michael Kölle, Dominik Laupheimer, Stefan Schmohl, Norbert Haala, Franz Rottensteiner, Jan Dirk Wegner, Hugo Ledoux
    http://arxiv.org/abs/2102.05346v1

    • [cs.CV]Improving Aerial Instance Segmentation in the Dark with Self-Supervised Low Light Enhancement
    Prateek Garg, Murari Mandal, Pratik Narang
    http://arxiv.org/abs/2102.05399v1

    • [cs.CV]Is Space-Time Attention All You Need for Video Understanding?
    Gedas Bertasius, Heng Wang, Lorenzo Torresani
    http://arxiv.org/abs/2102.05095v1

    • [cs.CV]LIFT-CAM: Towards Better Explanations for Class Activation Mapping
    Hyungsik Jung, Youngrock Oh
    http://arxiv.org/abs/2102.05228v1

    • [cs.CV]Locally Free Weight Sharing for Network Width Search
    Xiu Su, Shan You, Tao Huang, Fei Wang, Chen Qian, Changshui Zhang, Chang Xu
    http://arxiv.org/abs/2102.05258v1

    • [cs.CV]Negative Data Augmentation
    Abhishek Sinha, Kumar Ayush, Jiaming Song, Burak Uzkent, Hongxia Jin, Stefano Ermon
    http://arxiv.org/abs/2102.05113v1

    • [cs.CV]Partial transfusion: on the expressive influence of trainable batch norm parameters for transfer learning
    Fahdi Kanavati, Masayuki Tsuneki
    http://arxiv.org/abs/2102.05543v1

    • [cs.CV]Polarimetric Monocular Dense Mapping Using Relative Deep Depth Prior
    Moein Shakeri, Shing Yan Loo, Hong Zhang
    http://arxiv.org/abs/2102.05212v1

    • [cs.CV]RODNet: A Real-Time Radar Object Detection Network Cross-Supervised by Camera-Radar Fused Object 3D Localization
    Yizhou Wang, Zhongyu Jiang, Yudong Li, Jenq-Neng Hwang, Guanbin Xing, Hui Liu
    http://arxiv.org/abs/2102.05150v1

    • [cs.CV]Regional Attention with Architecture-Rebuilt 3D Network for RGB-D Gesture Recognition
    Benjia Zhou, Yunan Li, Jun Wan
    http://arxiv.org/abs/2102.05348v1

    • [cs.CV]RoBIC: A benchmark suite for assessing classifiers robustness
    Thibault Maho, Benoît Bonnet, Teddy Furon, Erwan Le Merrer
    http://arxiv.org/abs/2102.05368v1

    • [cs.CV]Scale Normalized Image Pyramids with AutoFocus for Object Detection
    Bharat Singh, Mahyar Najibi, Abhishek Sharma, Larry S. Davis
    http://arxiv.org/abs/2102.05646v1

    • [cs.CV]Searching for Alignment in Face Recognition
    Xiaqing Xu, Qiang Meng, Yunxiao Qin, Jianzhu Guo, Chenxu Zhao, Feng Zhou, Zhen Lei
    http://arxiv.org/abs/2102.05447v1

    • [cs.CV]Searching for Fast Model Families on Datacenter Accelerators
    Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc Le, Norman P. Jouppi
    http://arxiv.org/abs/2102.05610v1

    • [cs.CV]Sequential vessel segmentation via deep channel attention network
    Dongdong Hao, Song Ding, Linwei Qiu, Yisong Lv, Baowei Fei, Yueqi Zhu, Binjie Qin
    http://arxiv.org/abs/2102.05229v1

    • [cs.CV]The Role of the Input in Natural Language Video Description
    Silvia Cascianelli, Gabriele Costante, Alessandro Devo, Thomas A. Ciarfuglia, Paolo Valigi, Mario L. Fravolini
    http://arxiv.org/abs/2102.05067v1

    • [cs.CV]Training Vision Transformers for Image Retrieval
    Alaaeldin El-Nouby, Natalia Neverova, Ivan Laptev, Hervé Jégou
    http://arxiv.org/abs/2102.05644v1

    • [cs.CV]Two Novel Performance Improvements for Evolving CNN Topologies
    Yaron Strauch, Jo Grundy
    http://arxiv.org/abs/2102.05451v1

    • [cs.CY]A First Look at COVID-19 Domain Names: Origin and Implications
    Ryo Kawaoka, Daiki Chiba, Takuya Watanabe, Mitsuaki Akiyama, Tatsuya Mori
    http://arxiv.org/abs/2102.05290v1

    • [cs.CY]Dark Web Marketplaces and COVID-19: The vaccines
    Alberto Bracci, Matthieu Nadini, Maxwell Aliapoulios, Damon McCoy, Ian Gray, Alexander Teytelboym, Angela Gallo, Andrea Baronchelli
    http://arxiv.org/abs/2102.05470v1

    • [cs.CY]Epidemiological and public health requirements for COVID-19 contact tracing apps and their evaluation
    Vittoria Colizza, Eva Grill, Rafael Mikolajczyk, Ciro Cattuto, Adam Kucharski, Steven Riley, Michelle Kendall, Katrina Lythgoe, Lucie Abeler-Dörner, Chris Wymant, David Bonsall, Luca Ferretti, Christophe Fraser
    http://arxiv.org/abs/2102.05445v1

    • [cs.CY]Last Query Transformer RNN for knowledge tracing
    SeungKee Jeon
    http://arxiv.org/abs/2102.05038v1

    • [cs.CY]The Use and Misuse of Counterfactuals in Ethical Machine Learning
    Atoosa Kasirzadeh, Andrew Smart
    http://arxiv.org/abs/2102.05085v1

    • [cs.CY]comparing card-based vaccine credential systems with app-based vaccine credential systems
    Aryan Mahindra, Chandan CV, Priyanshi Katiyar, Anshuman Sharma, Sheshank Shankar, Rohan Sukumaran, Saurish Srivastava, Armaan Bhojwani, Rohan Iyer, Ishaan Singh, Ramesh Raskar
    http://arxiv.org/abs/2102.04512v2

    • [cs.DB]Explaining Inference Queries with Bayesian Optimization
    Brandon Lockhart, Jinglin Peng, Weiyuan Wu, Jiannan Wang, Eugene Wu
    http://arxiv.org/abs/2102.05308v1

    • [cs.DC]A High-Performance Sparse Tensor Algebra Compiler in Multi-Level IR
    Ruiqin Tian, Luanzheng Guo, Jiajia Li, Bin Ren, Gokcen Kestor
    http://arxiv.org/abs/2102.05187v1

    • [cs.DC]DHLink: A Microservice Platform supporting Rapid Application Development and Secure Real-time Data Sharing in Digital Health
    Wenhao Li, Niranjan Bidargaddi, John Fouyaxis
    http://arxiv.org/abs/2102.05191v1

    • [cs.DC]Energy-Aware Adaptive Offloading of Soft Real-Time Jobs in Mobile Edge Clouds
    Joaquim Silva, Eduardo R. B. Marques, Luís M. B Lopes, Fernando Silva
    http://arxiv.org/abs/2102.05504v1

    • [cs.DC]Searching CUDA code autotuning spaces with hardware performance counters: data from benchmarks running on various GPU architectures
    Jiří Filipovič, Jana Hozzová, Amin Nezarat, Jaroslav Oľha, Filip Petrovič
    http://arxiv.org/abs/2102.05299v1

    • [cs.DC]Using hardware performance counters to speed up autotuning convergence on GPUs
    Jiří Filipovič, Jana Hozzová, Amin Nezarat, Jaroslav Oľha, Filip Petrovič
    http://arxiv.org/abs/2102.05297v1

    • [cs.DS]Parallel Minimum Cuts in 今日学术视野(2021.2.12) - 图5)#card=math&code=O%28m%20%5Clog%5E2%28n%29%29) Work and Low Depth
    Daniel Anderson, Guy E. Blelloch
    http://arxiv.org/abs/2102.05301v1

    • [cs.HC]RECAST: Enabling User Recourse and Interpretability of Toxicity Detection Models with Interactive Visualization
    Austin P Wright, Omar Shaikh, Haekyu Park, Will Epperson, Muhammed Ahmed, Stephane Pinel, Duen Horng Chau, Diyi Yang
    http://arxiv.org/abs/2102.04427v2

    • [cs.HC]The human-AI relationship in decision-making: AI explanation to support people on justifying their decisions
    Juliana Jansen Ferreira, Mateus Monteiro
    http://arxiv.org/abs/2102.05460v1

    • [cs.HC]VINS: Visual Search for Mobile User Interface Design
    Sara Bunian, Kai Li, Chaima Jemmali, Casper Harteveld, Yun Fu, Magy Seif El-Nasr
    http://arxiv.org/abs/2102.05216v1

    • [cs.IR]CNN Application in Detection of Privileged Documents in Legal Document Review
    Rishi Chhatwal, Robert Keeling, Peter Gronvall, Nathaniel Huber-Fliflet, Jianping Zhang, Haozhen Zhao
    http://arxiv.org/abs/2102.04845v1

    • [cs.IR]Enhancing Reading Strategies by Exploring A Theme-based Approach to Literature Surveys
    Tanya Howden, Pierre Le Bras, Thomas S. Methven, Stefano Padilla, Mike J. Chantler
    http://arxiv.org/abs/2102.05374v1

    • [cs.IR]Information Extraction From Co-Occurring Similar Entities
    Nicolas Heist, Heiko Paulheim
    http://arxiv.org/abs/2102.05444v1

    • [cs.IT]Capacity Optimality of AMP in Coded Systems
    Lei Liu, Chulong Liang, Junjie Ma, Li Ping
    http://arxiv.org/abs/2102.05441v1

    • [cs.IT]Constrained Secrecy Capacity of Partial-Response Wiretap Channels
    Aria Nouri, Reza Asvadi, Jun Chen, Pascal O. Vontobel
    http://arxiv.org/abs/2102.04941v2

    • [cs.IT]Delay-Phase Precoding for Wideband THz Massive MIMO
    Linglong Dai, Jingbo Tan, H. Vincent Poor
    http://arxiv.org/abs/2102.05211v1

    • [cs.IT]Differential Entropy Rate Characterisations of Long Range Dependent Processes
    Andrew Feutrill, Matthew Roughan
    http://arxiv.org/abs/2102.05306v1

    • [cs.IT]Differential Privacy for Binary Functions via Randomized Graph Colorings
    Rafael G. L. D’Oliveira, Muriel Medard, Parastoo Sadeghi
    http://arxiv.org/abs/2102.05172v1

    • [cs.IT]Downlink Channel Reconstruction for Spatial Multiplexing in Massive MIMO Systems
    Hyeongtaek Lee, Hyuckjin Choi, Hwanjin Kim, Sucheol Kim, Chulhee Jang, Yongyun Choi, Junil Choi
    http://arxiv.org/abs/2102.05224v1

    • [cs.IT]Impact of Bit Allocation Strategies on Machine Learning Performance in Rate Limited Systems
    Afsaneh Gharouni, Peter Rost, Andreas Maeder, Hans Schotten
    http://arxiv.org/abs/2102.05389v1

    • [cs.IT]Intelligent Reflecting Surface-assisted MU-MISO Systems with Imperfect Hardware: Channel Estimation, Beamforming Design
    Anastasios Papazafeiropoulos, Cunhua Pan, Pandelis Kourtessis, Symeon Chatzinotas, John M. Senior
    http://arxiv.org/abs/2102.05333v1

    • [cs.IT]On the Distribution of the Sum of Double-Nakagami-m Random Vectors and Application in Reconfigurable Intelligent Surfaces
    Sotiris A. Tegos, Dimitrios Tyrovolas, Panagiotis D. Diamantoulakis, George K. Karagiannidis
    http://arxiv.org/abs/2102.05591v1

    • [cs.IT]On the Properties of Kullback-Leibler Divergence Between Gaussians
    Yufeng Zhang, Wanwei Liu, Zhenbang Chen, Kenli Li, Ji Wang
    http://arxiv.org/abs/2102.05485v1

    • [cs.IT]Optimum Detection of Defective Elements in Non-Adaptive Group Testing
    Gianluigi Liva, Enrico Paolini, Marco Chiani
    http://arxiv.org/abs/2102.05508v1

    • [cs.IT]Proximal Decoding for LDPC-coded Massive MIMO Channels
    Tadashi Wadayama, Satoshi Takabe
    http://arxiv.org/abs/2102.05256v1

    • [cs.IT]Reinforcement Learning for Optimized Beam Training in Multi-Hop Terahertz Communications
    Arian Ahmadi, Omid Semiari
    http://arxiv.org/abs/2102.05269v1

    • [cs.IT]Trace Reconstruction with Bounded Edit Distance
    Jin Sima, Jehoshua Bruck
    http://arxiv.org/abs/2102.05372v1

    • [cs.LG]“What’s in the box?!”: Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models
    Sahar Abdelnabi, Mario Fritz
    http://arxiv.org/abs/2102.05104v1

    • [cs.LG]Addressing the Topological Defects of Disentanglement via Distributed Operators
    Diane Bouchacourt, Mark Ibrahim, Stéphane Deny
    http://arxiv.org/abs/2102.05623v1

    • [cs.LG]Advanced Ore Mine Optimisation under Uncertainty Using Evolution
    William Reid, Aneta Neumann, Simon Ratcliffe, Frank Neumann
    http://arxiv.org/abs/2102.05235v1

    • [cs.LG]Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers
    Jacob M. Springer, Melanie Mitchell, Garrett T. Kenyon
    http://arxiv.org/abs/2102.05110v1

    • [cs.LG]Adversarial Robustness: What fools you makes you stronger
    Grzegorz Głuch, Rüdiger Urbanke
    http://arxiv.org/abs/2102.05475v1

    • [cs.LG]Adversarially Robust Classifier with Covariate Shift Adaptation
    Jay Nandy, Sudipan Saha, Wynne Hsu, Mong Li Lee, Xiao Xiang Zhu
    http://arxiv.org/abs/2102.05096v1

    • [cs.LG]Agnostic Proper Learning of Halfspaces under Gaussian Marginals
    Ilias Diakonikolas, Daniel M. Kane, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
    http://arxiv.org/abs/2102.05629v1

    • [cs.LG]An Efficient Pessimistic-Optimistic Algorithm for Constrained Linear Bandits
    Xin Liu, Bin Li, Pengyi Shi, Lei Ying
    http://arxiv.org/abs/2102.05295v1

    • [cs.LG]An Optimal Witness Function for Two-Sample Testing
    Jonas M. Kübler, Wittawat Jitkrittum, Bernhard Schölkopf, Krikamol Muandet
    http://arxiv.org/abs/2102.05573v1

    • [cs.LG]Attentive Gaussian processes for probabilistic time-series generation
    Kuilin Chen, Chi-Guhn Lee
    http://arxiv.org/abs/2102.05208v1

    • [cs.LG]BRECQ: Pushing the Limit of Post-Training Quantization by Block Reconstruction
    Yuhang Li, Ruihao Gong, Xu Tan, Yang Yang, Peng Hu, Qi Zhang, Fengwei Yu, Wei Wang, Shi Gu
    http://arxiv.org/abs/2102.05426v1

    • [cs.LG]Backdoor Scanning for Deep Neural Networks through K-Arm Optimization
    Guangyu Shen, Yingqi Liu, Guanhong Tao, Shengwei An, Qiuling Xu, Siyuan Cheng, Shiqing Ma, Xiangyu Zhang
    http://arxiv.org/abs/2102.05123v1

    • [cs.LG]Bayesian Inference with Certifiable Adversarial Robustness
    Matthew Wicker, Luca Laurenti, Andrea Patane, Zhoutong Chen, Zheng Zhang, Marta Kwiatkowska
    http://arxiv.org/abs/2102.05289v1

    • [cs.LG]Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
    Andrew Slavin Ross, Finale Doshi-Velez
    http://arxiv.org/abs/2102.05185v1

    • [cs.LG]Boosting Template-based SSVEP Decoding by Cross-domain Transfer Learning
    Kuan-Jung Chiang, Chun-Shu Wei, Masaki Nakanishi, Tzyy-Ping Jung
    http://arxiv.org/abs/2102.05194v1

    • [cs.LG]Bounded Memory Active Learning through Enriched Queries
    Max Hopkins, Daniel Kane, Shachar Lovett, Michal Moshkovitz
    http://arxiv.org/abs/2102.05047v1

    • [cs.LG]CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection
    Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Y. F. Tan, Masashi Sugiyama
    http://arxiv.org/abs/2102.05311v1

    • [cs.LG]CaPC Learning: Confidential and Private Collaborative Learning
    Christopher A. Choquette-Choo, Natalie Dullerud, Adam Dziedzic, Yunxiang Zhang, Somesh Jha, Nicolas Papernot, Xiao Wang
    http://arxiv.org/abs/2102.05188v1

    • [cs.LG]Classifier Calibration: with implications to threat scores in cybersecurity
    Waleed A. Yousef, Issa Traore, William Briguglio
    http://arxiv.org/abs/2102.05143v1

    • [cs.LG]Clusterability as an Alternative to Anchor Points When Learning with Noisy Labels
    Zhaowei Zhu, Yiwen Song, Yang Liu
    http://arxiv.org/abs/2102.05291v1

    • [cs.LG]Continuous-Time Model-Based Reinforcement Learning
    Çağatay Yıldız, Markus Heinonen, Harri Lähdesmäki
    http://arxiv.org/abs/2102.04764v2

    • [cs.LG]Detecting corruption in single-bidder auctions via positive-unlabelled learning
    Natalya Goryunova, Artem Baklanov, Egor Ianovski
    http://arxiv.org/abs/2102.05523v1

    • [cs.LG]Domain Invariant Representation Learning with Domain Density Transformations
    A. Tuan Nguyen, Toan Tran, Yarin Gal, Atilim Gunes Baydin
    http://arxiv.org/abs/2102.05082v1

    • [cs.LG]Driver2vec: Driver Identification from Automotive Data
    Jingbo Yang, Ruge Zhao, Meixian Zhu, David Hallac, Jaka Sodnik, Jure Leskovec
    http://arxiv.org/abs/2102.05234v1

    • [cs.LG]Dynamic 今日学术视野(2021.2.12) - 图6-VAEs for quantifying biodiversity by clustering optically recorded insect signals
    Klas Rydhmer, Raghavendra Selvan
    http://arxiv.org/abs/2102.05526v1

    • [cs.LG]Early Abandoning and Pruning for Elastic Distances
    Matthieu Herrmann, Geoffrey I. Webb
    http://arxiv.org/abs/2102.05221v1

    • [cs.LG]Energy-Harvesting Distributed Machine Learning
    Basak Guler, Aylin Yener
    http://arxiv.org/abs/2102.05639v1

    • [cs.LG]FLOP: Federated Learning on Medical Datasets using Partial Networks
    Qian Yang, Jianyi Zhang, Weituo Hao, Gregory Spell, Lawrence Carin
    http://arxiv.org/abs/2102.05218v1

    • [cs.LG]Fast Classification Learning with Neural Networks and Conceptors for Speech Recognition and Car Driving Maneuvers
    Stefanie Krause, Oliver Otto, Frieder Stolzenburg
    http://arxiv.org/abs/2102.05588v1

    • [cs.LG]Finding the Stochastic Shortest Path with Low Regret: The Adversarial Cost and Unknown Transition Case
    Liyu Chen, Haipeng Luo
    http://arxiv.org/abs/2102.05284v1

    • [cs.LG]Forecasting Nonnegative Time Series via Sliding Mask Method (SMM) and Latent Clustered Forecast (LCF)
    Yohann de Castro, Luca Mencarelli
    http://arxiv.org/abs/2102.05314v1

    • [cs.LG]GuiltyWalker: Distance to illicit nodes in the Bitcoin network
    Catarina Oliveira, João Torres, Maria Inês Silva, David Aparício, João Tiago Ascensão, Pedro Bizarro
    http://arxiv.org/abs/2102.05373v1

    • [cs.LG]Hyperbolic Generative Adversarial Network
    Diego Lazcano, Nicolás Fredes, Werner Creixell
    http://arxiv.org/abs/2102.05567v1

    • [cs.LG]Improved Algorithms for Efficient Active Learning Halfspaces with Massart and Tsybakov noise
    Chicheng Zhang, Yinan Li
    http://arxiv.org/abs/2102.05312v1

    • [cs.LG]Improving Model-Based Reinforcement Learning with Internal State Representations through Self-Supervision
    Julien Scholz, Cornelius Weber, Muhammad Burhan Hafez, Stefan Wermter
    http://arxiv.org/abs/2102.05599v1

    • [cs.LG]Inductive Granger Causal Modeling for Multivariate Time Series
    Yunfei Chu, Xiaowei Wang, Jianxin Ma, Kunyang Jia, Jingren Zhou, Hongxia Yang
    http://arxiv.org/abs/2102.05298v1

    • [cs.LG]Input Similarity from the Neural Network Perspective
    Guillaume Charpiat, Nicolas Girard, Loris Felardos, Yuliya Tarabalka
    http://arxiv.org/abs/2102.05262v1

    • [cs.LG]Input Similarity from the Neural Network Perspective
    Guillaume Charpiat, Nicolas Girard, Loris Felardos, Yuliya Tarabalka
    http://arxiv.org/abs/
    g/abs/2102.05262v1
    g/abs/2102.05262v1)

    • [cs.LG]Label Smoothed Embedding Hypothesis for Out-of-Distribution Detection
    Dara Bahri, Heinrich Jiang, Yi Tay, Donald Metzler
    http://arxiv.org/abs/2102.05131v1

    • [cs.LG]Learning Equational Theorem Proving
    Jelle Piepenbrock, Tom Heskes, Mikoláš Janota, Josef Urban
    http://arxiv.org/abs/2102.05547v1

    • [cs.LG]Locally Adaptive Label Smoothing for Predictive Churn
    Dara Bahri, Heinrich Jiang
    http://arxiv.org/abs/2102.05140v1

    • [cs.LG]MAIN:
    1000
    Multihead-Attention Imputation Networks
    Spyridon Mouselinos, Kyriakos Polymenakos, Antonis Nikitakis, Konstantinos Kyriakopoulos
    http://arxiv.org/abs/2102.05428v1

    • [cs.LG]Memory-Associated Differential Learning
    Yi Luo, Aiguo Chen, Bei Hui, Ke Yan
    http://arxiv.org/abs/2102.05246v1

    • [cs.LG]Meta Federated Learning
    Omid Aramoon, Pin-Yu Chen, Gang Qu, Yuan Tian
    http://arxiv.org/abs/2102.05561v1

    • [cs.LG]NAST: Non-Autoregressive Spatial-Temporal Transformer for Time Series Forecasting
    Kai Chen, Guang Chen, Dan Xu, Lijun Zhang, Yuyao Huang, Alois Knoll
    http://arxiv.org/abs/2102.05624v1

    • [cs.LG]Non-stationary Reinforcement Learning without Prior Knowledge: An Optimal Black-box Approach
    Chen-Yu Wei, Haipeng Luo
    http://arxiv.org/abs/2102.05406v1

    • [cs.LG]Nonstochastic Bandits with Infinitely Many Experts
    X. Flora Meng, Tuhin Sarkar, Munther A. Dahleh
    http://arxiv.org/abs/2102.05164v1

    • [cs.LG]On Explainability of Graph Neural Networks via Subgraph Explorations
    Hao Yuan, Haiyang Yu, Jie Wang, Kang Li, Shuiwang Ji
    http://arxiv.org/abs/2102.05152v1

    • [cs.LG]On Minibatch Noise: Discrete-Time SGD, Overparametrization, and Bayes
    Liu Ziyin, Kangqiao Liu, Takashi Mori, Masahito Ueda
    http://arxiv.org/abs/2102.05375v1

    • [cs.LG]On PyTorch Implementation of Density Estimators for von Mises-Fisher and Its Mixture
    Minyoung Kim
    http://arxiv.org/abs/2102.05340v1

    • [cs.LG]Output Perturbation for Differentially Private Convex Optimization with Improved Population Loss Bounds, Runtimes and Applications to Private Adversarial Training
    Andrew Lowy, Meisam Razaviyayn
    http://arxiv.org/abs/2102.04704v
    b3f
    1
    b3f
    1)

    • [cs.LG]Patterns, predictions, and actions: A story about machine learning
    Moritz Hardt, Benjamin Recht
    http://arxiv.org/abs/2102.05242v1

    • [cs.LG]Personalization for Web-based Services using Offline Reinforcement Learning
    Pavlos Athanasios Apostolopoulos, Zehui Wang, Hanson Wang, Chad Zhou, Kittipat Virochsiri, Norm Zhou, Igor L. Markov
    http://arxiv.org/abs/2102.05612v1

    • [cs.LG]Policy Augmentation: An Exploration Strategy for Faster Convergence of Deep Reinforcement Learning Algorithms
    Arash Mahyari
    http://arxiv.org/abs/2102.05249v1

    • [cs.LG]Regression Oracles and Exploration Strategies for Short-Horizon Multi-Armed Bandits
    Robert C. Gray, Jichen Zhu, Santiago Ontañón
    http://arxiv.org/abs/2102.05263v1

    • [cs.LG]Risk-Averse Offline Reinforcement Learning
    Núria Armengol Urpí, Sebastian Curi, Andreas Krause
    http://arxiv.org/abs/2102.05371v1

    • [cs.LG]Robust Federated Learning with Attack-Adaptive Aggregation
    Ching Pui Wan, Qifeng Chen
    http://arxiv.org/abs/2102.05257v1

    • [cs.LG]Robustness in Compressed Neural Networks for Object Detection
    Sebastian Cygert, Andrzej Czyzewski
    http://arxiv.org/abs/2102.05509v1

    • [cs.LG]Scheduling the NASA Deep Space Network with Deep Reinforcement Learning
    Edwin Goh, Hamsa Shwetha Venkataram, Mark Hoffmann, Mark Johnston, Brian Wilson
    http://arxiv.org/abs/2102.05167v1

    • [cs.LG]Simple Agent, Complex Environment: Efficient Reinforcement Learning with Agent State
    Shi Dong, Benjamin Van Roy, Zhengyuan Zhou
    http://arxiv.org/abs/2102.05261v1

    • [cs.LG]Simple and Near-Optimal MAP Inference for Nonsymmetric DPPs
    Nima Anari, Thuy-Duong Vuong
    http://arxiv.org/abs/2102.05347v1

    • [cs.LG]Stability of SGD: Tightness Analysis and Improved Bounds
    Yikai Zhang, Wenjia Zhang, Sammy Bald, Vamsi Pingali, Chao Chen, Mayank Goswami
    http://arxiv.org/abs/2102.05274v1

    • [cs.LG]Systematic Generalization for Predictive Control in Multivariate Time Series
    Hritik Bansal, Gantavya Bhatt, Pankaj Malhotra, Prathosh A. P
    http://arxiv.org/abs/2102.05602v1

    • [cs.LG]Task-Optimal Exploration in Linear Dynamical Systems
    Andrew Wagenmaker, Max Simchowitz, Kevin Jamieson
    http://arxiv.org/abs/2102.05214v1

    • [cs.LG]The importance of understanding instance-level noisy labels
    Yang Liu
    http://arxiv.org/abs/2102.05336v1

    • [cs.LG]Towards Certifying 今日学术视野(2021.2.12) - 图7 Robustness using Neural Networks with 今日学术视野(2021.2.12) - 图8-dist Neurons
    Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang
    http://arxiv.org/abs/2102.05363v1

    • [cs.LG]Transfer learning based few-shot classification using optimal transport mapping from preprocessed latent space of backbone neural network
    Tomáš Chobola, Daniel Vašata, Pavel Kordík
    http://arxiv.org/abs/2102.05176v1

    • [cs.LG]Using Deep LSD to build operators in GANs latent space with meaning in real space
    J. Quetzalcoatl Toledo-Marin, James A. Glazier
    http://arxiv.org/abs/2102.05132v1

    • [cs.NE]A Neural Network with Local Learning Rules for Minor Subspace Analysis
    Yanis Bahroun, Dmitri B. Chklovskii
    http://arxiv.org/abs/2102.05501v1

    • [cs.NE]A Similarity-preserving Neural Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit
    Yanis Bahroun, Anirvan M. Sengupta, Dmitri B. Chklovskii
    http://arxiv.org/abs/2102.05503v1

    • [cs.NE]Heuristic Strategies for Solving Complex Interacting Stockpile Blending Problem with Chance Constraints
    Yue Xie, Aneta Neumann, Frank Neumann
    http://arxiv.org/abs/2102.05303v1

    • [cs.NE]Pruning of Convolutional Neural Networks Using Ising Energy Model
    Hojjat Salehinejad, Shahrokh Valaee
    http://arxiv.org/abs/2102.05437v1

    • [cs.NE]Towards Feature-Based Performance Regression Using Trajectory Data
    Anja Jankovic, Tome Eftimov, Carola Doerr
    http://arxiv.org/abs/2102.05370v1

    • [cs.NI]Interrupting Real-Time IoT Tasks: How Bad Can It Be to Connect Your Critical Embedded System to the Internet?
    Ilja Behnke, Lukas Pirl, Lauritz Thamsen, Robert Danicki, Andreas Polze, Odej Kao
    http://arxiv.org/abs/2102.05559v1

    • [cs.RO]Belief Space Planning for Mobile Robots with Range Sensors using iLQG
    Ke Sun, Vijay Kumar
    http://arxiv.org/abs/2102.05466v1

    • [cs.RO]DARE-SLAM: Degeneracy-Aware and Resilient Loop Closing in Perceptually-Degraded Environments
    Kamak Ebadi, Matteo Palieri, Sally Wood, Curtis Padgett, Ali-akbar Agha-mohammadi
    http://arxiv.org/abs/2102.05117v1

    • [cs.RO]Learning Interaction-Aware Trajectory Predictions for Decentralized Multi-Robot Motion Planning in Dynamic Environments
    Hai Zhu, Francisco Martinez Claramunt, Bruno Brito, Javier Alonso-Mora
    http://arxiv.org/abs/2102.05382v1

    • [cs.RO]Manipulability optimization for multi-arm teleoperation
    Florian Kennel-Maushart, Roi Poranne, Stelian Coros
    http://arxiv.org/abs/2102.05414v1

    • [cs.RO]Origami spring-inspired shape morphing for flexible robotics
    Qianying Chen, Fan Feng, Pengyu Lv, Huiling Duan
    http://arxiv.org/abs/2102.05378v1

    • [cs.RO]PLGRIM: Hierarchical Value Learning for Large-scale Exploration in Unknown Environments
    Sung-Kyun Kim, Amanda Bouman, Gautam Salhotra, David D. Fan, Kyohei Otsu, Joel Burdick, Ali-akbar Agha-mohammadi
    http://arxiv.org/abs/2102.05633v1

    • [cs.RO]Toward Safe and Efficient Human-Robot Interaction via Behavior-Driven Danger Signaling
    Mehdi Hosseinzadeh, Bruno Sinopoli, Aaron F. Bobick
    http://arxiv.org/abs/2102.05144v1

    • [cs.RO]Transfer Reinforcement Learning across Homotopy Classes
    Zhangjie Cao, Minae Kwon, Dorsa Sadigh
    http://arxiv.org/abs/2102.05207v1

    • [cs.SD]Enhancing Audio Augmentation Methods with Consistency Learning
    Turab Iqbal, Karim Helwani, Arvindh Krishnaswamy, Wenwu Wang
    http://arxiv.org/abs/2102.05151v1

    • [cs.SD]Voice Cloning: a Multi-Speaker Text-to-Speech Synthesis Approach based on Transfer Learning
    Giuseppe Ruggiero, Enrico Zovato, Luigi Di Caro, Vincent Pollet
    http://arxiv.org/abs/2102.05630v1

    • [cs.SE]GitHub Discussions: An Exploratory Study of Early Adoption
    Hideaki Hata, Nicole Novielli, Sebastian Baltes, Raula Gaikovina Kula, Christoph Treude
    http://arxiv.org/abs/2102.05230v1

    • [cs.SI]A note on (matricial and fast) ways to compute Burt’s structural holes
    Alessio Muscillo
    http://arxiv.org/abs/2102.05114v1

    • [cs.SI]ParmoSense: A Scenario-based Participatory Mobile Urban Sensing Platform with User Motivation Engine
    Yuki Matsuda, Shogo Kawanaka, Hirohiko Suwa, Yutaka Arakawa, Keiichi Yasumoto
    http://arxiv.org/abs/2102.05586v1

    • [cs.SI]Sampling Subgraph Network with Application to Graph Classification
    Jinhuan Wang, Pengtao Chen, Bin Ma, Jiajun Zhou, Zhongyuan Ruan, Guanrong Chen, Qi Xuan
    http://arxiv.org/abs/2102.05272v1

    • [eess.AS]CDPAM: Contrastive learning for perceptual audio similarity
    Pranay Manocha, Zeyu Jin, Richard Zhang, Adam Finkelstein
    http://arxiv.org/abs/2102.05109v1

    • [eess.IV]D2A U-Net: Automatic Segmentation of COVID-19 Lesions from CT Slices with Dilated Convolution and Dual Attention Mechanism
    Xiangyu Zhao, Peng Zhang, Fan Song, Guangda Fan, Yangyang Sun, Yujia Wang, Zheyuan Tian, Luqi Zhang, Guanglei Zhang
    http://arxiv.org/abs/2102.05210v1

    • [eess.IV]Dysplasia grading of colorectal polyps through CNN analysis of WSI
    Daniele Perlo, Enzo Tartaglione, Luca Bertero, Paola Cassoni, Marco Grangetto
    http://arxiv.org/abs/2102.05498v1

    • [eess.IV]Learning to Enhance Visual Quality via Hyperspectral Domain Mapping
    Harsh Sinha, Aditya Mehta, Murari Mandal, Pratik Narang
    http://arxiv.org/abs/2102.05418v1

    • [eess.IV]Reference-based Texture transfer for Single Image Super-resolution of Magnetic Resonance images
    Madhu Mithra K K, Sriprabha Ramanarayanan, Keerthi Ram, Mohanasankar Sivaprakasam
    http://arxiv.org/abs/2102.05450v1

    • [eess.SP]Joint Design of Transmit Waveforms and Receive Filters for MIMO Radar via Manifold Optimization
    Huanyu Zhang, Ziping Zhao
    http://arxiv.org/abs/2102.05457v1

    • [eess.SY]Adaptive Processor Frequency Adjustment for Mobile Edge Computing with Intermittent Energy Supply
    Tiansheng Huang, Weiwei Lin, Ying Li, Xiumin Wang, Qingbo Wu, Rui Li, Ching-Hsien Hsu, Albert Y. Zomaya
    http://arxiv.org/abs/2102.05449v1

    • [math.AG]Rational points on cubic surfaces and AG codes from the Norm-Trace curve
    Matteo Bonini, Massimiliano Sala, Lara Vicino
    http://arxiv.org/abs/2102.05478v1

    • [math.CO]Slicing the hypercube is not easy
    Gal Yehuda, Amir Yehudayoff
    http://arxiv.org/abs/2102.05536v1

    • [math.OC]A Framework of Inertial Alternating Direction Method of Multipliers for Non-Convex Non-Smooth Optimization
    Le Thi Khanh Hien, Duy Nhat Phan, Nicolas Gillis
    http://arxiv.org/abs/2102.05433v1

    • [math.OC]An Adaptive Stochastic Sequential Quadratic Programming with Differentiable Exact Augmented Lagrangians
    Sen Na, Mihai Anitescu, Mladen Kolar
    http://arxiv.org/abs/2102.05320v1

    • [math.OC]Local and Global Uniform Convexity Conditions
    Thomas Kerdreux, Alexandre d’Aspremont, Sebastian Pokutta
    http://arxiv.org/abs/2102.05134v1

    • [math.OC]Nonlinear Observers Design for Vision-Aided Inertial Navigation Systems
    Miaomiao Wang, Soulaimane Berkane, Abdelhamid Tayebi
    http://arxiv.org/abs/2102.05111v1

    • [math.ST]Global jump filters and realized volatility
    Haruhiko Inatsugu, Nakahiro Yoshida
    http://arxiv.org/abs/2102.05307v1

    • [math.ST]There are natural scores: Full comment on Shafer, “Testing by betting: A strategy for statistical and scientific communication”
    Sander Greenland
    http://arxiv.org/abs/2102.05569v1

    • [physics.ao-ph]Sub-seasonal forecasting with a large ensemble of deep-learning weather prediction models
    Jonathan A. Weyn, Dale R. Durran, Rich Caruana, Nathaniel Cresswell-Clay
    http://arxiv.org/abs/2102.05107v1

    • [physics.data-an]Point Cloud Transformers applied to Collider Physics
    Vinicius Mikuni, Florencia Canelli
    http://arxiv.org/abs/2102.05073v1

    • [physics.flu-dyn]Dynamic Mode Decomposition of inertial particle caustics in Taylor-Green flow
    Omstavan Samant, Jaya Kumar Alageshan, Sarveshwar Sharma, Animesh Kuley
    http://arxiv.org/abs/2102.05120v1

    • [physics.soc-ph]No Echo in the Chambers of Political Interactions on Reddit
    Gianmarco De Francisci Morales, Corrado Monti, Michele Starnini
    http://arxiv.org/abs/2102.05477v1

    • [quant-ph]On the Hardness of PAC-learning stabilizer States with Noise
    Aravind Gollakota, Daniel Liang
    http://arxiv.org/abs/2102.05174v1

    • [stat.AP]Designing group sequential clinical trials when a delayed effect is anticipated: A practical guidance
    Dominic Magirr, José L. Jiménez
    http://arxiv.org/abs/2102.05535v1

    • [stat.ME]Bayesian Knockoff Filter Using Gibbs Sampler
    Jiaqi Gu, Guosheng Yin
    http://arxiv.org/abs/2102.05223v1

    • [stat.ME]Currents and K-functions for Fiber Point Processes
    Pernille EH. Hansen, Rasmus Waagepetersen, Anne Marie Svane, Jon Sporring, Hans JT. Stephensen, Stine Hasselholt, Stefan Sommer
    http://arxiv.org/abs/2102.05329v1

    • [stat.ME]Fisher Scoring for crossed factor Linear Mixed Models
    Thomas Maullin-Sapey, Thomas E. Nichols
    http://arxiv.org/abs/2102.05103v1

    • [stat.ME]On a Bivariate Copula for Modeling Negative Dependence
    Shyamal Ghosh, Prajamitra Bhuyan, Maxim Finkelstein
    http://arxiv.org/abs/2102.05386v1

    • [stat.ME]On structural and practical identifiability
    Franz-Georg Wieland, Adrian L. Hauber, Marcus Rosenblatt, Christian Tönsing, Jens Timmer
    http://arxiv.org/abs/2102.05100v1

    • [stat.ML]An exact solver for the Weston-Watkins SVM subproblem
    Yutong Wang, Clayton D. Scott
    http://arxiv.org/abs/2102.05640v1

    • [stat.ML]Argmax Flows and Multinomial Diffusion: Towards Non-Autoregressive Language Models
    Emiel Hoogeboom, Didrik Nielsen, Priyank Jaini, Patrick Forré, Max Welling
    http://arxiv.org/abs/2102.05379v1

    • [stat.ML]Concentrated Document Topic Model
    Hao Lei, Ying Chen
    http://arxiv.org/abs/2102.04449v1

    • [stat.ML]Conditional Versus Adversarial Euler-based Generators For Time Series
    Carl Remlinger, Joseph Mikael, Romuald Elie
    http://arxiv.org/abs/2102.05313v1

    • [stat.ML]Emotion Transfer Using Vector-Valued Infinite Task Learning
    Alex Lambert, Sanjeel Parekh, Zoltán Szabó, Florence d’Alché-Buc
    http://arxiv.org/abs/2102.05075v1

    • [stat.ML]On Disentanglement in Gaussian Process Variational Autoencoders
    Simon Bing, Vincent Fortuin, Gunnar Rätsch
    http://arxiv.org/abs/2102.05507v1

    • [stat.ML]On the Existence of Optimal Transport Gradient for Learning Generative Models
    Antoine Houdard, Arthur Leclaire, Nicolas Papadakis, Julien Rabin
    http://arxiv.org/abs/2102.05542v1

    • [stat.ML]On the Regularity of Attention
    James Vuckovic, Aristide Baratin, Remi Tachet des Combes
    http://arxiv.org/abs/2102.05628v1

    • [stat.ML]On the Suboptimality of Thompson Sampling in High Dimensions
    Raymond Zhang, Richard Combes
    http://arxiv.org/abs/2102.05502v1

    • [stat.ML]Regularization Strategies for Quantile Regression
    Taman Narayan, Serena Wang, Kevin Canini, Maya Gupta
    http://arxiv.org/abs/2102.05135v1

    • [stat.ML]Robust estimation of tree structured models
    Marta Casanellas, Marina Garrote-López, Piotr Zwiernik
    http://arxiv.org/abs/2102.05472v1

    • [stat.ML]Statistical Inference for Polyak-Ruppert Averaged Zeroth-order Stochastic Gradient Algorithm
    Yanhao Jin, Tesi Xiao, Krishnakumar Balasubramanian
    http://arxiv.org/abs/2102.05198v1