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.ET - 新兴技术 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.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 hep-ex - 高能物理实验 math.NA - 数值分析 math.ST - 统计理论 physics.data-an - 数据分析、 统计和概率 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

    • [cs.AI]Automatic Intent-Slot Induction for Dialogue Systems
    • [cs.AI]Category Aware Explainable Conversational Recommendation
    • [cs.AI]Evaluation of a Bi-Directional Methodology for Automated Assessment of Compliance to Continuous Application of Clinical Guidelines, in the Type 2 Diabetes-Management Domain
    • [cs.AI]KGSynNet: A Novel Entity Synonyms Discovery Framework with Knowledge Graph
    • [cs.AI]Learning Symbolic Rules for Interpretable Deep Reinforcement Learning
    • [cs.AI]Modelling Behavioural Diversity for Learning in Open-Ended Games
    • [cs.AI]Online Double Oracle
    • [cs.AI]S今日学术视野(2021.3.18) - 图1: A Heuristic Information-Based Approximation Framework for Multi-Goal Path Finding
    • [cs.AI]Ternary Hashing
    • [cs.CL]A Multilingual African Embedding for FAQ Chatbots
    • [cs.CL]A Transition-based Parser for Unscoped Episodic Logical Forms
    • [cs.CL]Coordinate Constructions in English Enhanced Universal Dependencies: Analysis and Computational Modeling
    • [cs.CL]Covid-19 Discourse on Twitter: How the Topics, Sentiments, Subjectivity, and Figurative Frames Changed Over Time
    • [cs.CL]Discriminative Learning for Probabilistic Context-Free Grammars based on Generalized H-Criterion
    • [cs.CL]Gumbel-Attention for Multi-modal Machine Translation
    • [cs.CL]LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval
    • [cs.CL]MENYO-20k: A Multi-domain English-Yorùbá Corpus for Machine Translation and Domain Adaptation
    • [cs.CL]OkwuGbé: End-to-End Speech Recognition for Fon and Igbo
    • [cs.CL]Robustly Optimized and Distilled Training for Natural Language Understanding
    • [cs.CL]Structural Adapters in Pretrained Language Models for AMR-to-text Generation
    • [cs.CL]dictNN: A Dictionary-Enhanced CNN Approach for Classifying Hate Speech on Twitter
    • [cs.CR]SoK: Privacy-Preserving Collaborative Tree-based Model Learning
    • [cs.CR]The Influence of Dropout on Membership Inference in Differentially Private Models
    • [cs.CV]A Computer Vision System to Help Prevent the Transmission of COVID-19
    • [cs.CV]A Large-Scale Dataset for Benchmarking Elevator Button Segmentation and Character Recognition
    • [cs.CV]A LiDAR-Guided Framework for Video Enhancement
    • [cs.CV]Adversarial Driving: Attacking End-to-End Autonomous Driving Systems
    • [cs.CV]Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches
    • [cs.CV]Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation
    • [cs.CV]BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation
    • [cs.CV]Back to the Feature: Learning Robust Camera Localization from Pixels to Pose
    • [cs.CV]Balancing Biases and Preserving Privacy on Balanced Faces in the Wild
    • [cs.CV]Combining Morphological and Histogram based Text Line Segmentation in the OCR Context
    • [cs.CV]Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection
    • [cs.CV]Consistent Posterior Distributions under Vessel-Mixing: A Regularization for Cross-Domain Retinal Artery/Vein Classification
    • [cs.CV]Dense Interaction Learning for Video-based Person Re-identification
    • [cs.CV]Domain-Incremental Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognition
    • [cs.CV]EADNet: Efficient Asymmetric Dilated Network for Semantic Segmentation
    • [cs.CV]Frequency-aware Discriminative Feature Learning Supervised by Single-Center Loss for Face Forgery Detection
    • [cs.CV]GSVNet: Guided Spatially-Varying Convolution for Fast Semantic Segmentation on Video
    • [cs.CV]Hebbian Semi-Supervised Learning in a Sample Efficiency Setting
    • [cs.CV]Is it Enough to Optimize CNN Architectures on ImageNet?
    • [cs.CV]LRGNet: Learnable Region Growing for Class-Agnostic Point Cloud Segmentation
    • [cs.CV]Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition
    • [cs.CV]Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutions
    • [cs.CV]Modulating Localization and Classification for Harmonized Object Detection
    • [cs.CV]Multilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models
    • [cs.CV]PC-HMR: Pose Calibration for 3D Human Mesh Recovery from 2D Images/Videos
    • [cs.CV]QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection
    • [cs.CV]RackLay: Multi-Layer Layout Estimation for Warehouse Racks
    • [cs.CV]Revisiting Dynamic Convolution via Matrix Decomposition
    • [cs.CV]Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging
    • [cs.CV]S3Net: 3D LiDAR Sparse Semantic Segmentation Network
    • [cs.CV]Simultaneous Multi-View Camera Pose Estimation and Object Tracking with Square Planar Markers
    • [cs.CV]Skeleton Based Sign Language Recognition Using Whole-body Keypoints
    • [cs.CV]Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling
    • [cs.CV]Super-Resolving Cross-Domain Face Miniatures by Peeking at One-Shot Exemplar
    • [cs.CV]Towards Indirect Top-Down Road Transport Emissions Estimation
    • [cs.CV]Track to Detect and Segment: An Online Multi-Object Tracker
    • [cs.CV]UPANets: Learning from the Universal Pixel Attention Networks
    • [cs.CY]Data Mining and Visualization to Understand Accident-prone Areas
    • [cs.CY]OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning
    • [cs.DC]An Efficient Vectorization Scheme for Stencil Computation
    • [cs.DC]Autotuning Benchmarking Techniques: A Roofline Model Case Study
    • [cs.DC]Byzantine-tolerant Distributed Grow-only Sets: Specification and Applications
    • [cs.DC]Distributed Deep Learning Using Volunteer Computing-Like Paradigm
    • [cs.DC]Improving scalability and reliability of MPI-agnostic transparent checkpointing for production workloads at NERSC
    • [cs.DC]Intelligent colocation of HPC workloads
    • [cs.DC]PerfSim: A Performance Simulator for Cloud Native Computing
    • [cs.DC]Wait-free approximate agreement on graphs
    • [cs.DC]Workflows Community Summit: Bringing the Scientific Workflows Community Together
    • [cs.DL]Two tales of science technology linkage: Patent in-text versus front-page references
    • [cs.ET]ARXON: A Framework for Approximate Communication over Photonic Networks-on-Chip
    • [cs.IR]A Novel Paper Recommendation Method Empowered by Knowledge Graph: for Research Beginners
    • [cs.IR]Dual Side Deep Context-aware Modulation for Social Recommendation
    • [cs.IR]Fairness and Transparency in Recommendation: The Users’ Perspective
    • [cs.IR]TLSAN: Time-aware Long- and Short-term Attention Network for Next-item Recommendation
    • [cs.IT]A Semiclassical Proof of Duality Between the Classical BSC and the Quantum PSC
    • [cs.IT]Channel Estimation for Intelligent Reflecting Surface Assisted Backscatter Communication
    • [cs.IT]Decoding of Variable Length PLH Codes
    • [cs.IT]Large System Achievable Rate Analysis of RIS-Assisted MIMO Wireless Communication with Statistical CSIT
    • [cs.IT]On Bounds for Ring-Based Coding Theory
    • [cs.IT]Reconfigurable Intelligent Surface aided Massive MIMO Systems with Low-Resolution DACs
    • [cs.IT]STAR: Simultaneous Transmission And Reflection for 360° Coverage by Intelligent Surfaces
    • [cs.IT]Vertical Beamforming in Reconfigurable Intelligent Surface-aided Cognitive Radio Networks
    • [cs.LG]A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models
    • [cs.LG]EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry
    • [cs.LG]Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties
    • [cs.LG]GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks
    • [cs.LG]Growing 3D Artefacts and Functional Machines with Neural Cellular Automata
    • [cs.LG]Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design
    • [cs.LG]Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones
    • [cs.LG]Learned Gradient Compression for Distributed Deep Learning
    • [cs.LG]Learning to Shape Rewards using a Game of Switching Controls
    • [cs.LG]Learning with Feature-Dependent Label Noise: A Progressive Approach
    • [cs.LG]Learning without gradient descent encoded by the dynamics of a neurobiological model
    • [cs.LG]Lyapunov Barrier Policy Optimization
    • [cs.LG]Multi-task learning for virtual flow metering
    • [cs.LG]Predicting Early Dropout: Calibration and Algorithmic Fairness Considerations
    • [cs.LG]Predicting Opioid Use Disorder from Longitudinal Healthcare Data using Multi-stream Transformer
    • [cs.LG]Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning
    • [cs.LG]Reweighting Augmented Samples by Minimizing the Maximal Expected Loss
    • [cs.LG]Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise
    • [cs.LG]Semi-Supervised Graph-to-Graph Translation
    • [cs.LG]TinyOL: TinyML with Online-Learning on Microcontrollers
    • [cs.LG]dNNsolve: an efficient NN-based PDE solver
    • [cs.NE]HDTest: Differential Fuzz Testing of Brain-Inspired Hyperdimensional Computing
    • [cs.NE]Training Dynamical Binary Neural Networks with Equilibrium Propagation
    • [cs.RO]A New Autoregressive Neural Network Model with Command Compensation for Imitation Learning Based on Bilateral Control
    • [cs.RO]A Normal Distribution Transform-Based Radar Odometry Designed For Scanning and Automotive Radars
    • [cs.RO]Analysis of a 3-RUU Parallel Manipulator
    • [cs.RO]Autonomous Drone Racing with Deep Reinforcement Learning
    • [cs.RO]Behavior-Tree-Based Person Search for Symbiotic Autonomous Mobile Robot Tasks
    • [cs.RO]Closed-Loop Error Learning Control for Uncertain Nonlinear Systems With Experimental Validation on a Mobile Robot
    • [cs.RO]Cognitive architecture aided by working-memory for self-supervised multi-modal humans recognition
    • [cs.RO]Combining Planning and Learning of Behavior Trees for Robotic Assembly
    • [cs.RO]Design and Development of Autonomous Delivery Robot
    • [cs.RO]Distributed motion coordination for multi-robot systems under LTL specifications
    • [cs.RO]Few Shot System Identification for Reinforcement Learning
    • [cs.RO]Formation Control for UAVs Using a Flux Guided Approach
    • [cs.RO]Human-Robot Motion Retargeting via Neural Latent Optimization
    • [cs.RO]Inclined Quadrotor Landing using Deep Reinforcement Learning
    • [cs.RO]Manipulator-Independent Representations for Visual Imitation
    • [cs.RO]Map completion from partial observation using the global structure of multiple environmental maps
    • [cs.RO]Mobile Teleoperation: Evaluation of Wireless Wearable Sensing of the Operator’s Arm Motion
    • [cs.RO]Multi-Robot Routing with Time Windows: A Column Generation Approach
    • [cs.RO]Robotics During a Pandemic: The 2020 NSF CPS Virtual Challenge — SoilScope, Mars Edition
    • [cs.RO]Sparse Curriculum Reinforcement Learning for End-to-End Driving
    • [cs.RO]Variable compliance and geometry regulation of Soft-Bubble grippers with active pressure control
    • [cs.SD]Fast Development of ASR in African Languages using Self Supervised Speech Representation Learning
    • [cs.SE]Cost-aware Integration Process Modeling in Multiclouds
    • [cs.SE]Embedding Code Contexts for Cryptographic API Suggestion:New Methodologies and Comparisons
    • [cs.SE]LabelGit: A Dataset for Software Repositories Classification using Attributed Dependency Graphs
    • [cs.SE]Please Don’t Go — A Comprehensive Approach to Increase Women’s Participation in Open Source Software
    • [cs.SE]Software Architecture for ML-based Systems: What Exists and What Lies Ahead
    • [cs.SI]Clandestino or Rifugiato? Anti-immigration Facebook Ad Targeting in Italy
    • [cs.SI]Predicting hyperlinks via hypernetwork loop structure
    • [eess.AS]Flow-based Self-supervised Density Estimation for Anomalous Sound Detection
    • [eess.IV]Deep Learning for Chest X-ray Analysis: A Survey
    • [eess.IV]Deep Reinforcement Learning for Band Selection in Hyperspectral Image Classification
    • [eess.IV]Invertible Residual Network with Regularization for Effective Medical Image Segmentation
    • [eess.IV]ReconResNet: Regularised Residual Learning for MR Image Reconstruction of Undersampled Cartesian and Radial Data
    • [eess.IV]Unsupervised Anomaly Segmentation using Image-Semantic Cycle Translation
    • [eess.IV]Unsupervised Missing Cone Deep Learning in Optical Diffraction Tomography
    • [eess.IV]Unsupervised anomaly detection in digital pathology using GANs
    • [eess.SP]Data Discover Using Lossless Compression-Based Sparse Representation
    • [eess.SP]Graph-Based Multiobject Tracking with Embedded Particle Flow
    • [eess.SY]Data-driven Thermal Anomaly Detection for Batteries using Unsupervised Shape Clustering
    • [hep-ex]Learning to increase matching efficiency in identifying additional b-jets in the 今日学术视野(2021.3.18) - 图2 process
    • [math.NA]Parareal Neural Networks Emulating a Parallel-in-time Algorithm
    • [math.ST]A refined continuity correction for the negative binomial distribution and asymptotics of the median
    • [math.ST]Deep learning: a statistical viewpoint
    • [math.ST]Extreme value analysis for mixture models with heavy-tailed impurity
    • [physics.data-an]Determining the maximum information gain and optimising experimental design in neutron reflectometry using the Fisher information
    • [quant-ph]Tomography of time-dependent quantum spin networks with machine learning
    • [stat.AP]Effect of social isolation in dengue cases in the state of Sao Paulo, Brazil: an analysis during the COVID-19 pandemic
    • [stat.AP]Identification of COVID-19 mortality patterns in Brazil by a functional QR decomposition analysis
    • [stat.AP]Modeling Weather-induced Home Insurance Risks with Support Vector Machine Regression
    • [stat.AP]The role of mobility and sanitary measures on Covid-19 in Costa Rica, March through July 2020
    • [stat.ME]A two-way factor model for high-dimensional matrix data
    • [stat.ME]Estimation of parameters of the Gumbel type-II distribution under AT-II PHCS with an application of Covid-19 data
    • [stat.ME]Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization
    • [stat.ME]Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-Differentiable Priors
    • [stat.ME]Incorporating External Data into the Analysis of Clinical Trials via Bayesian Additive Regression Trees
    • [stat.ME]Modeling proportion of success in high school leaving examination- A comparative study of Inflated Unit Lindley and Inflated Beta distribution
    • [stat.ME]Newcomb-Benford’s law as a fast ersatz of discrepancy measures
    • [stat.ME]Rollage: Efficient Rolling Average Algorithm to Estimate ARMA Models for Big Time Series Data
    • [stat.ME]Valid sequential inference on probability forecast performance
    • [stat.ME]Visualizing Outliers in High Dimensional Functional Data for Task fMRI data exploration
    • [stat.ME]Workflow Techniques for the Robust Use of Bayes Factors
    • [stat.ML]A Central Limit Theorem for Differentially Private Query Answering
    • [stat.ML]Differentiable Learning Under Triage
    • [stat.ML]Function approximation by deep neural networks with parameters 今日学术视野(2021.3.18) - 图3
    • [stat.ML]Quick Learning Mechanism with Cross-Domain Adaptation for Intelligent Fault Diagnosis
    • [stat.ML]Soft and subspace robust multivariate rank tests based on entropy regularized optimal transport

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

    • [cs.AI]Automatic Intent-Slot Induction for Dialogue Systems
    Zengfeng Zeng, Dan Ma, Haiqin Yang, Zhen Gou, Jianping Shen
    http://arxiv.org/abs/2103.08886v1

    • [cs.AI]Category Aware Explainable Conversational Recommendation
    Nikolaos Kondylidis, Jie Zou, Evangelos Kanoulas
    http://arxiv.org/abs/2103.08733v1

    • [cs.AI]Evaluation of a Bi-Directional Methodology for Automated Assessment of Compliance to Continuous Application of Clinical Guidelines, in the Type 2 Diabetes-Management Domain
    Avner Hatsek, Irit Hochberg, Deeb Daoud Naccache, Aya Biderman, Yuval Shahar
    http://arxiv.org/abs/2103.09031v1

    • [cs.AI]KGSynNet: A Novel Entity Synonyms Discovery Framework with Knowledge Graph
    Yiying Yang, Xi Yin, Haiqin Yang, Xingjian Fei, Hao Peng, Kaijie Zhou, Kunfeng Lai, Jianping Shen
    http://arxiv.org/abs/2103.08893v1

    • [cs.AI]Learning Symbolic Rules for Interpretable Deep Reinforcement Learning
    Zhihao Ma, Yuzheng Zhuang, Paul Weng, Hankz Hankui Zhuo, Dong Li, Wulong Liu, Jianye Hao
    http://arxiv.org/abs/2103.08228v2

    • [cs.AI]Modelling Behavioural Diversity for Learning in Open-Ended Games
    Nicolas Perez Nieves, Yaodong Yang, Oliver Slumbers, David Henry Mguni, Jun Wang
    http://arxiv.org/abs/2103.07927v1

    • [cs.AI]Online Double Oracle
    Le Cong Dinh, Yaodong Yang, Zheng Tian, Nicolas Perez Nieves, Oliver Slumbers, David Henry Mguni, Haitham Bou Ammar, Jun Wang
    http://arxiv.org/abs/2103.07780v2

    • [cs.AI]S今日学术视野(2021.3.18) - 图4: A Heuristic Information-Based Approximation Framework for Multi-Goal Path Finding
    Kenny Chour, Sivakumar Rathinam, Ramamoorthi Ravi
    http://arxiv.org/abs/2103.08155v2

    • [cs.AI]Ternary Hashing
    Kam Woh Ng, Chang Liu, Lixin Fan, Yilun Jin, Ce Ju, Tianyu Zhang, Chee Seng Chan, Qiang Yang
    http://arxiv.org/abs/2103.09173v1

    • [cs.CL]A Multilingual African Embedding for FAQ Chatbots
    Aymen Ben Elhaj Mabrouk, Moez Ben Haj Hmida, Chayma Fourati, Hatem Haddad, Abir Messaoudi
    http://arxiv.org/abs/2103.09185v1

    • [cs.CL]A Transition-based Parser for Unscoped Episodic Logical Forms
    Gene Louis Kim, Viet Duong, Xin Lu, Lenhart Schubert
    http://arxiv.org/abs/2103.08759v1

    • [cs.CL]Coordinate Constructions in English Enhanced Universal Dependencies: Analysis and Computational Modeling
    Stefan Grünewald, Prisca Piccirilli, Annemarie Friedrich
    http://arxiv.org/abs/2103.08955v1

    • [cs.CL]Covid-19 Discourse on Twitter: How the Topics, Sentiments, Subjectivity, and Figurative Frames Changed Over Time
    Philipp Wicke, Marianna M. Bolognesi
    http://arxiv.org/abs/2103.08952v1

    • [cs.CL]Discriminative Learning for Probabilistic Context-Free Grammars based on Generalized H-Criterion
    Mauricio Maca, José Miguel Benedí, Joan Andreu Sánchez
    http://arxiv.org/abs/2103.08656v1

    • [cs.CL]Gumbel-Attention for Multi-modal Machine Translation
    Pengbo Liu, Hailong Cao, Tiejun Zhao
    http://arxiv.org/abs/2103.08862v1

    • [cs.CL]LightningDOT: Pre-training Visual-Semantic Embeddings for Real-Time Image-Text Retrieval
    Siqi Sun, Yen-Chun Chen, Linjie Li, Shuohang Wang, Yuwei Fang, Jingjing Liu
    http://arxiv.org/abs/2103.08784v1

    • [cs.CL]MENYO-20k: A Multi-domain English-Yorùbá Corpus for Machine Translation and Domain Adaptation
    David I. Adelani, Dana Ruiter, Jesujoba O. Alabi, Damilola Adebonojo, Adesina Ayeni, Mofe Adeyemi, Ayodele Awokoya, Cristina España-Bonet
    http://arxiv.org/abs/2103.08647v1

    • [cs.CL]OkwuGbé: End-to-End Speech Recognition for Fon and Igbo
    Bonaventure F. P. Dossou, Chris C. Emezue
    http://arxiv.org/abs/2103.07762v2

    • [cs.CL]Robustly Optimized and Distilled Training for Natural Language Understanding
    Haytham ElFadeel, Stan Peshterliev
    http://arxiv.org/abs/2103.08809v1

    • [cs.CL]Structural Adapters in Pretrained Language Models for AMR-to-text Generation
    Leonardo F. R. Ribeiro, Yue Zhang, Iryna Gurevych
    http://arxiv.org/abs/2103.09120v1

    • [cs.CL]dictNN: A Dictionary-Enhanced CNN Approach for Classifying Hate Speech on Twitter
    Maximilian Kupi, Michael Bodnar, Nikolas Schmidt, Carlos Eduardo Posada
    http://arxiv.org/abs/2103.08780v1

    • [cs.CR]SoK: Privacy-Preserving Collaborative Tree-based Model Learning
    Sylvain Chatel, Apostolos Pyrgelis, Juan Ramon Troncoso-Pastoriza, Jean-Pierre Hubaux
    http://arxiv.org/abs/2103.08987v1

    • [cs.CR]The Influence of Dropout on Membership Inference in Differentially Private Models
    Erick Galinkin
    http://arxiv.org/abs/2103.09008v1

    • [cs.CV]A Computer Vision System to Help Prevent the Transmission of COVID-19
    Fevziye Irem Eyiokur, Hazım Kemal Ekenel, Alexander Waibel
    http://arxiv.org/abs/2103.08773v1

    • [cs.CV]A Large-Scale Dataset for Benchmarking Elevator Button Segmentation and Character Recognition
    Jianbang Liu, Yuqi Fang, Delong Zhu, Nachuan Ma, Jin Pan, Max Q. -H. Meng
    http://arxiv.org/abs/2103.09030v1

    • [cs.CV]A LiDAR-Guided Framework for Video Enhancement
    Yu Feng, Patrick Hansen, Paul N. Whatmough, Guoyu Lu, Yuhao Zhu
    http://arxiv.org/abs/2103.08764v1

    • [cs.CV]Adversarial Driving: Attacking End-to-End Autonomous Driving Systems
    Han Wu, Wenjie Ruan
    http://arxiv.org/abs/2103.09151v1

    • [cs.CV]Adversarial YOLO: Defense Human Detection Patch Attacks via Detecting Adversarial Patches
    Nan Ji, YanFei Feng, Haidong Xie, Xueshuang Xiang, Naijin Liu
    http://arxiv.org/abs/2103.08860v1

    • [cs.CV]Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation
    Jungbeom Lee, Eunji Kim, Sungroh Yoon
    http://arxiv.org/abs/2103.08896v1

    • [cs.CV]BBAM: Bounding Box Attribution Map for Weakly Supervised Semantic and Instance Segmentation
    Jungbeom Lee, Jihun Yi, Chaehun Shin, Sungroh Yoon
    http://arxiv.org/abs/2103.08907v1

    • [cs.CV]Back to the Feature: Learning Robust Camera Localization from Pixels to Pose
    Paul-Edouard Sarlin, Ajaykumar Unagar, Måns Larsson, Hugo Germain, Carl Toft, Viktor Larsson, Marc Pollefeys, Vincent Lepetit, Lars Hammarstrand, Fredrik Kahl, Torsten Sattler
    http://arxiv.org/abs/2103.09213v1

    • [cs.CV]Balancing Biases and Preserving Privacy on Balanced Faces in the Wild
    Joseph P Robinson, Can Qin, Yann Henon, Samson Timoner, Yun Fu
    http://arxiv.org/abs/2103.09118v1

    • [cs.CV]Combining Morphological and Histogram based Text Line Segmentation in the OCR Context
    Pit Schneider
    http://arxiv.org/abs/2103.08922v1

    • [cs.CV]Conceptual Text Region Network: Cognition-Inspired Accurate Scene Text Detection
    Chenwei Cui, Liangfu Lu, Zhiyuan Tan, Amir Hussain
    http://arxiv.org/abs/2103.09179v1

    • [cs.CV]Consistent Posterior Distributions under Vessel-Mixing: A Regularization for Cross-Domain Retinal Artery/Vein Classification
    Chenxin Li, Yunlong Zhang, Zhehan Liang, Wenao Ma, Yue Huang, Xinghao Ding
    http://arxiv.org/abs/2103.09097v1

    • [cs.CV]Dense Interaction Learning for Video-based Person Re-identification
    Tianyu He, Xin Jin, Xu Shen, Jianqiang Huang, Zhibo Chen, Xian-Sheng Hua
    http://arxiv.org/abs/2103.09013v1

    • [cs.CV]Domain-Incremental Continual Learning for Mitigating Bias in Facial Expression and Action Unit Recognition
    Nikhil Churamani, Ozgur Kara, Hatice Gunes
    http://arxiv.org/abs/2103.08637v1

    • [cs.CV]EADNet: Efficient Asymmetric Dilated Network for Semantic Segmentation
    Qihang Yang, Tao Chen, Jiayuan Fan, Ye Lu, Chongyan Zuo, Qinghua Chi
    http://arxiv.org/abs/2103.08914v1

    • [cs.CV]Frequency-aware Discriminative Feature Learning Supervised by Single-Center Loss for Face Forgery Detection
    Jiaming Li, Hongtao Xie, Jiahong Li, Zhongyuan Wang, Yongdong Zhang
    http://arxiv.org/abs/2103.09096v1

    • [cs.CV]GSVNet: Guided Spatially-Varying Convolution for Fast Semantic Segmentation on Video
    Shih-Po Lee, Si-Cun Chen, Wen-Hsiao Peng
    http://arxiv.org/abs/2103.08834v1

    • [cs.CV]Hebbian Semi-Supervised Learning in a Sample Efficiency Setting
    Gabriele Lagani, Fabrizio Falchi, Claudio Gennaro, Giuseppe Amato
    http://arxiv.org/abs/2103.09002v1

    • [cs.CV]Is it Enough to Optimize CNN Architectures on ImageNet?
    Lukas Tuggener, Jürgen Schmidhuber, Thilo Stadelmann
    http://arxiv.org/abs/2103.09108v1

    • [cs.CV]LRGNet: Learnable Region Growing for Class-Agnostic Point Cloud Segmentation
    Jingdao Chen, Zsolt Kira, Yong K. Cho
    http://arxiv.org/abs/2103.09160v1

    • [cs.CV]Leveraging Recent Advances in Deep Learning for Audio-Visual Emotion Recognition
    Liam Schoneveld, Alice Othmani, Hazem Abdelkawy
    http://arxiv.org/abs/2103.09154v1

    • [cs.CV]Lite-HDSeg: LiDAR Semantic Segmentation Using Lite Harmonic Dense Convolutions
    Ryan Razani, Ran Cheng, Ehsan Taghavi, Liu Bingbing
    http://arxiv.org/abs/2103.08852v1

    • [cs.CV]Modulating Localization and Classification for Harmonized Object Detection
    Taiheng Zhang, Qiaoyong Zhong, Shiliang Pu, Di Xie
    http://arxiv.org/abs/2103.08958v1

    • [cs.CV]Multilingual Multimodal Pre-training for Zero-Shot Cross-Lingual Transfer of Vision-Language Models
    Po-Yao Huang, Mandela Patrick, Junjie Hu, Graham Neubig, Florian Metze, Alexander Hauptmann
    http://arxiv.org/abs/2103.08849v1

    • [cs.CV]PC-HMR: Pose Calibration for 3D Human Mesh Recovery from 2D Images/Videos
    Tianyu Luan, Yali Wang, Junhao Zhang, Zhe Wang, Zhipeng Zhou, Yu Qiao
    http://arxiv.org/abs/2103.09009v1

    • [cs.CV]QueryDet: Cascaded Sparse Query for Accelerating High-Resolution Small Object Detection
    Chenhongyi Yang, Zehao Huang, Naiyan Wang
    http://arxiv.org/abs/2103.09136v1

    • [cs.CV]RackLay: Multi-Layer Layout Estimation for Warehouse Racks
    Meher Shashwat Nigam, Avinash Prabhu, Anurag Sahu, Puru Gupta, Tanvi Karandikar, N. Sai Shankar, Ravi Kiran Sarvadevabhatla, K. Madhava Krishna
    http://arxiv.org/abs/2103.09174v1

    • [cs.CV]Revisiting Dynamic Convolution via Matrix Decomposition
    Yunsheng Li, Yinpeng Chen, Xiyang Dai, Mengchen Liu, Dongdong Chen, Ye Yu, Lu Yuan, Zicheng Liu, Mei Chen, Nuno Vasconcelos
    http://arxiv.org/abs/2103.08756v1

    • [cs.CV]Rotation Coordinate Descent for Fast Globally Optimal Rotation Averaging
    Álvaro Parra, Shin-Fang Chng, Tat-Jun Chin, Anders Eriksson, Ian Reid
    http://arxiv.org/abs/2103.08292v2

    • [cs.CV]S3Net: 3D LiDAR Sparse Semantic Segmentation Network
    Ran Cheng, Ryan Razani, Yuan Ren, Liu Bingbing
    http://arxiv.org/abs/2103.08745v1

    • [cs.CV]Simultaneous Multi-View Camera Pose Estimation and Object Tracking with Square Planar Markers
    Hamid Sarmadi, Rafael Muñoz-Salinas, M. A. Berbís, R. Medina-Carnicer
    http://arxiv.org/abs/2103.09141v1

    • [cs.CV]Skeleton Based Sign Language Recognition Using Whole-body Keypoints
    Songyao Jiang, Bin Sun, Lichen Wang, Yue Bai, Kunpeng Li, Yun Fu
    http://arxiv.org/abs/2103.08833v1

    • [cs.CV]Spatial Dependency Networks: Neural Layers for Improved Generative Image Modeling
    Đorđe Miladinović, Aleksandar Stanić, Stefan Bauer, Jürgen Schmidhuber, Joachim M. Buhmann
    http://arxiv.org/abs/2103.08877v1

    • [cs.CV]Super-Resolving Cross-Domain Face Miniatures by Peeking at One-Shot Exemplar
    Peike Li, Xin Yu, Yi Yang
    http://arxiv.org/abs/2103.08863v1

    • [cs.CV]Towards Indirect Top-Down Road Transport Emissions Estimation
    Ryan Mukherjee, Derek Rollend, Gordon Christie, Armin Hadzic, Sally Matson, Anshu Saksena, Marisa Hughes
    http://arxiv.org/abs/2103.08829v1

    • [cs.CV]Track to Detect and Segment: An Online Multi-Object Tracker
    Jialian Wu, Jiale Cao, Liangchen Song, Yu Wang, Ming Yang, Junsong Yuan
    http://arxiv.org/abs/2103.08808v1

    • [cs.CV]UPANets: Learning from the Universal Pixel Attention Networks
    Ching-Hsun Tseng, Shin-Jye Lee, Jia-Nan Feng, Shengzhong Mao, Yu-Ping Wu, Jia-Yu Shang, Mou-Chung Tseng, Xiao-Jun Zeng
    http://arxiv.org/abs/2103.08640v1

    • [cs.CY]Data Mining and Visualization to Understand Accident-prone Areas
    Md Mashfiq Rizvee, Md Amiruzzaman, Md Rajibul Islam
    http://arxiv.org/abs/2103.09062v1

    • [cs.CY]OmniFair: A Declarative System for Model-Agnostic Group Fairness in Machine Learning
    Hantian Zhang, Xu Chu, Abolfazl Asudeh, Shamkant B. Navathe
    http://arxiv.org/abs/2103.09055v1

    • [cs.DC]An Efficient Vectorization Scheme for Stencil Computation
    Kun Li, Liang Yuan, Yunquan Zhang, Yue Yue, Hang Cao, Pengqi Lu
    http://arxiv.org/abs/2103.08825v1

    • [cs.DC]Autotuning Benchmarking Techniques: A Roofline Model Case Study
    Jacob Odgård Tørring, Jan Christian Meyer, Anne C. Elster
    http://arxiv.org/abs/2103.08716v1

    • [cs.DC]Byzantine-tolerant Distributed Grow-only Sets: Specification and Applications
    Vicent Cholvi, Antonio Fernández Anta, Chryssis Georgiou, Nicolas Nicolaou, Michel Raynal, Antonio Russo
    http://arxiv.org/abs/2103.08936v1

    • [cs.DC]Distributed Deep Learning Using Volunteer Computing-Like Paradigm
    Medha Atre, Birendra Jha, Ashwini Rao
    http://arxiv.org/abs/2103.08894v1

    • [cs.DC]Improving scalability and reliability of MPI-agnostic transparent checkpointing for production workloads at NERSC
    Prashant Singh Chouhan, Harsh Khetawat, Neil Resnik, Twinkle Jain, Rohan Garg, Gene Cooperman, Rebecca Hartman-Baker, Zhengji Zhao
    http://arxiv.org/abs/2103.08546v2

    • [cs.DC]Intelligent colocation of HPC workloads
    Felippe V. Zacarias, Vinicius Petrucci, Rajiv Nishtala, Paul Carpenter, Daniel Mossé
    http://arxiv.org/abs/2103.09019v1

    • [cs.DC]PerfSim: A Performance Simulator for Cloud Native Computing
    Michel Gokan Khan, Javid Taheri, Auday Al-Dulaimy, Andreas Kassler
    http://arxiv.org/abs/2103.08983v1

    • [cs.DC]Wait-free approximate agreement on graphs
    Dan Alistarh, Faith Ellen, Joel Rybicki
    http://arxiv.org/abs/2103.08949v1

    • [cs.DC]Workflows Community Summit: Bringing the Scientific Workflows Community Together
    Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Dan Laney, Dong Ahn, Shantenu Jha, Carole Goble, Lavanya Ramakrishnan, Luc Peterson, Bjoern Enders, Douglas Thain, Ilkay Altintas, Yadu Babuji, Rosa M. Badia, Vivien Bonazzi, Taina Coleman, Michael Crusoe, Ewa Deelman, Frank Di Natale, Paolo Di Tommaso, Thomas Fahringer, Rosa Filgueira, Grigori Fursin, Alex Ganose, Bjorn Gruning, Daniel S. Katz, Olga Kuchar, Ana Kupresanin, Bertram Ludascher, Ketan Maheshwari, Marta Mattoso, Kshitij Mehta, Todd Munson, Jonathan Ozik, Tom Peterka, Loic Pottier, Tim Randles, Stian Soiland-Reyes, Benjamin Tovar, Matteo Turilli, Thomas Uram, Karan Vahi, Michael Wilde, Matthew Wolf, Justin Wozniak
    http://arxiv.org/abs/2103.09181v1

    • [cs.DL]Two tales of science technology linkage: Patent in-text versus front-page references
    Jian Wang, Suzan Verberne
    http://arxiv.org/abs/2103.08931v1

    • [cs.ET]ARXON: A Framework for Approximate Communication over Photonic Networks-on-Chip
    Febin Sunny, Asif Mirza, Ishan Thakkar, Mahdi Nikdast, Sudeep Pasricha
    http://arxiv.org/abs/2103.08828v1

    • [cs.IR]A Novel Paper Recommendation Method Empowered by Knowledge Graph: for Research Beginners
    Bangchao Wang, Ziyang Weng, Yanping Wang
    http://arxiv.org/abs/2103.08819v1

    • [cs.IR]Dual Side Deep Context-aware Modulation for Social Recommendation
    Bairan Fu, Wenming Zhang, Guangneng Hu, Xinyu Dai, Shujian Huang, Jiajun Chen
    http://arxiv.org/abs/2103.08976v1

    • [cs.IR]Fairness and Transparency in Recommendation: The Users’ Perspective
    Nasim Sonboli, Jessie J. Smith, Florencia Cabral Berenfus, Robin Burke, Casey Fiesler
    http://arxiv.org/abs/2103.08786v1

    • [cs.IR]TLSAN: Time-aware Long- and Short-term Attention Network for Next-item Recommendation
    Jianqing Zhang, Dongjing Wang, Dongjin Yu
    http://arxiv.org/abs/2103.08971v1

    • [cs.IT]A Semiclassical Proof of Duality Between the Classical BSC and the Quantum PSC
    Narayanan Rengaswamy, Henry D. Pfister
    http://arxiv.org/abs/2103.09225v1

    • [cs.IT]Channel Estimation for Intelligent Reflecting Surface Assisted Backscatter Communication
    Samith Abeywickrama, Changsheng You, Rui Zhang, Chau Yuen
    http://arxiv.org/abs/2103.08836v1

    • [cs.IT]Decoding of Variable Length PLH Codes
    Marco Morini, Alessandro Ugolini, Giulio Colavolpe
    http://arxiv.org/abs/2103.08991v1

    • [cs.IT]Large System Achievable Rate Analysis of RIS-Assisted MIMO Wireless Communication with Statistical CSIT
    Jun Zhang, Jie Liu, Shaodan Ma, Chao-Kai Wen, Shi Jin
    http://arxiv.org/abs/2103.09161v1

    • [cs.IT]On Bounds for Ring-Based Coding Theory
    Niklas Gassner, Marcus Greferath, Joachim Rosenthal, Violetta Weger
    http://arxiv.org/abs/2103.07749v2

    • [cs.IT]Reconfigurable Intelligent Surface aided Massive MIMO Systems with Low-Resolution DACs
    Jianxin Dai, Yuanyuan Wang, Cunhua Pan, Kangda Zhi, Hong Ren, Kezhi Wang
    http://arxiv.org/abs/2103.08871v1

    • [cs.IT]STAR: Simultaneous Transmission And Reflection for 360° Coverage by Intelligent Surfaces
    Yuanwei Liu, Xidong Mu, Jiaqi Xu, Robert Schober, Yang Hao, H. Vincent Poor, Lajos Hanzo
    http://arxiv.org/abs/2103.09104v1

    • [cs.IT]Vertical Beamforming in Reconfigurable Intelligent Surface-aided Cognitive Radio Networks
    S. Fatemeh Zamanian, S. Mohammad Razavizadeh, Qingqing Wu
    http://arxiv.org/abs/2103.08900v1

    • [cs.LG]A Hybrid Gradient Method to Designing Bayesian Experiments for Implicit Models
    Jiaxin Zhang, Sirui Bi, Guannan Zhang
    http://arxiv.org/abs/2103.08594v1

    • [cs.LG]EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry
    Yingqi Liu, Guangyu Shen, Guanhong Tao, Zhenting Wang, Shiqing Ma, Xiangyu Zhang
    http://arxiv.org/abs/2103.08820v1

    • [cs.LG]Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties
    Lisa Schut, Oscar Key, Rory McGrath, Luca Costabello, Bogdan Sacaleanu, Medb Corcoran, Yarin Gal
    http://arxiv.org/abs/2103.08951v1

    • [cs.LG]GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks
    Tianxiang Zhao, Xiang Zhang, Suhang Wang
    http://arxiv.org/abs/2103.08826v1

    • [cs.LG]Growing 3D Artefacts and Functional Machines with Neural Cellular Automata
    Shyam Sudhakaran, Djordje Grbic, Siyan Li, Adam Katona, Elias Najarro, Claire Glanois, Sebastian Risi
    http://arxiv.org/abs/2103.08737v1

    • [cs.LG]Hierarchical Reinforcement Learning Framework for Stochastic Spaceflight Campaign Design
    Yuji Takubo, Hao Chen, Koki Ho
    http://arxiv.org/abs/2103.08981v1

    • [cs.LG]Interpretable Deep Learning for the Remote Characterisation of Ambulation in Multiple Sclerosis using Smartphones
    Andrew P. Creagh, Florian Lipsmeier, Michael Lindemann, Maarten De Vos
    http://arxiv.org/abs/2103.09171v1

    • [cs.LG]Learned Gradient Compression for Distributed Deep Learning
    Lusine Abrahamyan, Yiming Chen, Giannis Bekoulis, Nikos Deligiannis
    http://arxiv.org/abs/2103.08870v1

    • [cs.LG]Learning to Shape Rewards using a Game of Switching Controls
    David Mguni, Jianhong Wang, Taher Jafferjee, Nicolas Perez-Nieves, Wenbin Song, Yaodong Yang, Feifei Tong, Hui Chen, Jiangcheng Zhu, Yali Du, Jun Wang
    http://arxiv.org/abs/2103.09159v1

    • [cs.LG]Learning with Feature-Dependent Label Noise: A Progressive Approach
    Yikai Zhang, Songzhu Zheng, Pengxiang Wu, Mayank Goswami, Chao Chen
    http://arxiv.org/abs/2103.07756v2

    • [cs.LG]Learning without gradient descent encoded by the dynamics of a neurobiological model
    Vivek Kurien George, Vikash Morar, Weiwei Yang, Jonathan Larson, Bryan Tower, Shweti Mahajan, Arkin Gupta, Christopher White, Gabriel A. Silva
    http://arxiv.org/abs/2103.08878v1

    • [cs.LG]Lyapunov Barrier Policy Optimization
    Harshit Sikchi, Wenxuan Zhou, David Held
    http://arxiv.org/abs/2103.09230v1

    • [cs.LG]Multi-task learning for virtual flow metering
    Anders T. Sandnes, Bjarne Grimstad, Odd Kolbjørnsen
    http://arxiv.org/abs/2103.08713v1

    • [cs.LG]Predicting Early Dropout: Calibration and Algorithmic Fairness Considerations
    Marzieh Karimi-Haghighi, Carlos Castillo, Davinia Hernandez-Leo, Veronica Moreno Oliver
    http://arxiv.org/abs/2103.09068v1

    • [cs.LG]Predicting Opioid Use Disorder from Longitudinal Healthcare Data using Multi-stream Transformer
    Sajjad Fouladvand, Jeffery Talbert, Linda P. Dwoskin, Heather Bush, Amy Lynn Meadows, Lars E. Peterson, Ramakanth Kavuluru, Jin Chen
    http://arxiv.org/abs/2103.08800v1

    • [cs.LG]Repurposing Pretrained Models for Robust Out-of-domain Few-Shot Learning
    Namyeong Kwon, Hwidong Na, Gabriel Huang, Simon Lacoste-Julien
    http://arxiv.org/abs/2103.09027v1

    • [cs.LG]Reweighting Augmented Samples by Minimizing the Maximal Expected Loss
    Mingyang Yi, Lu Hou, Lifeng Shang, Xin Jiang, Qun Liu, Zhi-Ming Ma
    http://arxiv.org/abs/2103.08933v1

    • [cs.LG]Sampling-free Variational Inference for Neural Networks with Multiplicative Activation Noise
    Jannik Schmitt, Stefan Roth
    http://arxiv.org/abs/2103.08497v2

    • [cs.LG]Semi-Supervised Graph-to-Graph Translation
    Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang
    http://arxiv.org/abs/2103.08827v1

    • [cs.LG]TinyOL: TinyML with Online-Learning on Microcontrollers
    Haoyu Ren, Darko Anicic, Thomas Runkler
    http://arxiv.org/abs/2103.08295v2

    • [cs.LG]dNNsolve: an efficient NN-based PDE solver
    Veronica Guidetti, Francesco Muia, Yvette Welling, Alexander Westphal
    http://arxiv.org/abs/2103.08662v1

    • [cs.NE]HDTest: Differential Fuzz Testing of Brain-Inspired Hyperdimensional Computing
    Dongning Ma, Jianmin Guo, Yu Jiang, Xun Jiao
    http://arxiv.org/abs/2103.08668v1

    • [cs.NE]Training Dynamical Binary Neural Networks with Equilibrium Propagation
    Jérémie Laydevant, Maxence Ernoult, Damien Querlioz, Julie Grollier
    http://arxiv.org/abs/2103.08953v1

    • [cs.RO]A New Autoregressive Neural Network Model with Command Compensation for Imitation Learning Based on Bilateral Control
    Kazuki Hayashi, Ayumu Sasagawa, Sho Sakaino, Toshiaki Tsuji
    http://arxiv.org/abs/2103.08879v1

    • [cs.RO]A Normal Distribution Transform-Based Radar Odometry Designed For Scanning and Automotive Radars
    Pou-Chun Kung, Chieh-Chih Wang, Wen-Chieh Lin
    http://arxiv.org/abs/2103.07908v2

    • [cs.RO]Analysis of a 3-RUU Parallel Manipulator
    Thomas Stigger, Johannes Siegele, Daniel F. Scharler, Martin Pfurner, Manfred L. Husty
    http://arxiv.org/abs/2103.09037v1

    • [cs.RO]Autonomous Drone Racing with Deep Reinforcement Learning
    Yunlong Song, Mats Steinweg, Elia Kaufmann, Davide Scaramuzza
    http://arxiv.org/abs/2103.08624v1

    • [cs.RO]Behavior-Tree-Based Person Search for Symbiotic Autonomous Mobile Robot Tasks
    Marvin Stuede, Timo Lerche, Martin Alexander Petersen, Svenja Spindeldreier
    http://arxiv.org/abs/2103.09162v1

    • [cs.RO]Closed-Loop Error Learning Control for Uncertain Nonlinear Systems With Experimental Validation on a Mobile Robot
    Erkan Kayacan
    http://arxiv.org/abs/2103.08845v1

    • [cs.RO]Cognitive architecture aided by working-memory for self-supervised multi-modal humans recognition
    Jonas Gonzalez-Billandon, Giulia Belgiovine, Alessandra Sciutti, Giulio Sandini, Francesco Rea
    http://arxiv.org/abs/2103.09072v1

    • [cs.RO]Combining Planning and Learning of Behavior Trees for Robotic Assembly
    Jonathan Styrud, Matteo Iovino, Mikael Norrlöf, Mårten Björkman, Christian Smith
    http://arxiv.org/abs/2103.09036v1

    • [cs.RO]Design and Development of Autonomous Delivery Robot
    Aniket Gujarathi, Akshay Kulkarni, Unmesh Patil, Yogesh Phalak, Rajeshree Deotalu, Aman Jain, Navid Panchi, Ashwin Dhabale, Shital Chiddarwar
    http://arxiv.org/abs/2103.09229v1

    • [cs.RO]Distributed motion coordination for multi-robot systems under LTL specifications
    Pian Yu, Dimos V. Dimarogonas
    http://arxiv.org/abs/2103.09111v1

    • [cs.RO]Few Shot System Identification for Reinforcement Learning
    Karim Farid, Nourhan Sakr
    http://arxiv.org/abs/2103.08850v1

    • [cs.RO]Formation Control for UAVs Using a Flux Guided Approach
    John Hartley, Hubert P. H. Shum, Edmond S. L. Ho, He Wang, Subramanian Ramamoorthy
    http://arxiv.org/abs/2103.09184v1

    • [cs.RO]Human-Robot Motion Retargeting via Neural Latent Optimization
    Haodong Zhang, Weijie Li, Yuwei Liang, Zexi Chen, Yuxiang Cui, Yue Wang, Rong Xiong
    http://arxiv.org/abs/2103.08882v1

    • [cs.RO]Inclined Quadrotor Landing using Deep Reinforcement Learning
    Jacob E. Kooi, Robert Babuška
    http://arxiv.org/abs/2103.09043v1

    • [cs.RO]Manipulator-Independent Representations for Visual Imitation
    Yuxiang Zhou, Yusuf Aytar, Konstantinos Bousmalis
    http://arxiv.org/abs/2103.09016v1

    • [cs.RO]Map completion from partial observation using the global structure of multiple environmental maps
    Yuki Katsumata, Akinori Kanechika, Akira Taniguchi, Lotfi El Hafi, Yoshinobu Hagiwara, Tadahiro Taniguchi
    http://arxiv.org/abs/2103.09071v1

    • [cs.RO]Mobile Teleoperation: Evaluation of Wireless Wearable Sensing of the Operator’s Arm Motion
    Guanhao Fu, Ehsan Azimi, Peter Kazanzides
    http://arxiv.org/abs/2103.08119v1

    • [cs.RO]Multi-Robot Routing with Time Windows: A Column Generation Approach
    Naveed Haghani, Jiaoyang Li, Sven Koenig, Gautam Kunapuli, Claudio Contardo, Amelia Regan, Julian Yarkony
    http://arxiv.org/abs/2103.08835v1

    • [cs.RO]Robotics During a Pandemic: The 2020 NSF CPS Virtual Challenge — SoilScope, Mars Edition
    Darwin Mick, K. Srikar Siddarth, Swastik Nandan, Harish Anand, Stephen A. Rees, Jnaneshwar Das
    http://arxiv.org/abs/2103.08684v1

    • [cs.RO]Sparse Curriculum Reinforcement Learning for End-to-End Driving
    Pranav Agarwal, Pierre de Beaucorps, Raoul de Charette
    http://arxiv.org/abs/2103.09189v1

    • [cs.RO]Variable compliance and geometry regulation of Soft-Bubble grippers with active pressure control
    Sihah Joonhigh, Naveen Kuppuswamy, Andrew Beaulieu, Alex Alspach, Russ Tedrake
    http://arxiv.org/abs/2103.08710v1

    • [cs.SD]Fast Development of ASR in African Languages using Self Supervised Speech Representation Learning
    Jama Hussein Mohamud, Lloyd Acquaye Thompson, Aissatou Ndoye, Laurent Besacier
    http://arxiv.org/abs/2103.08993v1

    • [cs.SE]Cost-aware Integration Process Modeling in Multiclouds
    Daniel Ritter
    http://arxiv.org/abs/2103.08675v1

    • [cs.SE]Embedding Code Contexts for Cryptographic API Suggestion:New Methodologies and Comparisons
    Ya Xiao, Salman Ahmed, Wenjia Song, Xinyang Ge, Bimal Viswanath, Danfeng, Yao
    http://arxiv.org/abs/2103.08747v1

    • [cs.SE]LabelGit: A Dataset for Software Repositories Classification using Attributed Dependency Graphs
    Cezar Sas, Andrea Capiluppi
    http://arxiv.org/abs/2103.08890v1

    • [cs.SE]Please Don’t Go — A Comprehensive Approach to Increase Women’s Participation in Open Source Software
    Bianca Trinkenreich
    http://arxiv.org/abs/2103.08763v1

    • [cs.SE]Software Architecture for ML-based Systems: What Exists and What Lies Ahead
    Henry Muccini, Karthik Vaidhyanathan
    http://arxiv.org/abs/2103.07950v2

    • [cs.SI]Clandestino or Rifugiato? Anti-immigration Facebook Ad Targeting in Italy
    Arthur Capozzi, Gianmarco De Francisci Morales, Yelena Mejova, Corrado Monti, André Panisson, Daniela Paolotti
    http://arxiv.org/abs/2103.09224v1

    • [cs.SI]Predicting hyperlinks via hypernetwork loop structure
    Liming Pan, Hui-Juan Shang, Peiyan Li, Haixing Dai, Wei Wang, Lixin Tian
    http://arxiv.org/abs/2103.08926v1

    • [eess.AS]Flow-based Self-supervised Density Estimation for Anomalous Sound Detection
    Kota Dohi, Takashi Endo, Harsh Purohit, Ryo Tanabe, Yohei Kawaguchi
    http://arxiv.org/abs/2103.08801v1

    • [eess.IV]Deep Learning for Chest X-ray Analysis: A Survey
    Ecem Sogancioglu, Erdi Çallı, Bram van Ginneken, Kicky G. van Leeuwen, Keelin Murphy
    http://arxiv.org/abs/2103.08700v1

    • [eess.IV]Deep Reinforcement Learning for Band Selection in Hyperspectral Image Classification
    Lichao Mou, Sudipan Saha, Yuansheng Hua, Francesca Bovolo, Lorenzo Bruzzone, Xiao Xiang Zhu
    http://arxiv.org/abs/2103.08741v1

    • [eess.IV]Invertible Residual Network with Regularization for Effective Medical Image Segmentation
    Kashu Yamazaki, Vidhiwar Singh Rathour, T. Hoang Ngan Le
    http://arxiv.org/abs/2103.09042v1

    • [eess.IV]ReconResNet: Regularised Residual Learning for MR Image Reconstruction of Undersampled Cartesian and Radial Data
    Soumick Chatterjee, Mario Breitkopf, Chompunuch Sarasaen, Hadya Yassin, Georg Rose, Andreas Nürnberger, Oliver Speck
    http://arxiv.org/abs/2103.09203v1

    • [eess.IV]Unsupervised Anomaly Segmentation using Image-Semantic Cycle Translation
    Chenxin Li, Yunlong Zhang, Jiongcheng Li, Yue Huang, Xinghao Ding
    http://arxiv.org/abs/2103.09094v1

    • [eess.IV]Unsupervised Missing Cone Deep Learning in Optical Diffraction Tomography
    Hyungjin Chung, Jaeyoung Huh, Geon Kim, Yong Keun Park, Jong Chul Ye
    http://arxiv.org/abs/2103.09022v1

    • [eess.IV]Unsupervised anomaly detection in digital pathology using GANs
    Milda Pocevičiūtė, Gabriel Eilertsen, Claes Lundström
    http://arxiv.org/abs/2103.08945v1

    • [eess.SP]Data Discover Using Lossless Compression-Based Sparse Representation
    Elyas Sabeti, Peter X. K. Song, Alfred O. Hero III
    http://arxiv.org/abs/2103.08765v1

    • [eess.SP]Graph-Based Multiobject Tracking with Embedded Particle Flow
    Wenyu Zhang, Florian Meyer
    http://arxiv.org/abs/2103.08968v1

    • [eess.SY]Data-driven Thermal Anomaly Detection for Batteries using Unsupervised Shape Clustering
    Xiaojun Li, Jianwei Li, Ali Abdollahi, Trevor Jones, Asif Habeebullah
    http://arxiv.org/abs/2103.08796v1

    • [hep-ex]Learning to increase matching efficiency in identifying additional b-jets in the 今日学术视野(2021.3.18) - 图5 process
    Cheongjae Jang, Sang-Kyun Ko, Yung-Kyun Noh, Jieun Choi, Jongwon Lim, Tae Jeong Kim
    http://arxiv.org/abs/2103.09129v1

    • [math.NA]Parareal Neural Networks Emulating a Parallel-in-time Algorithm
    Chang-Ock Lee, Youngkyu Lee, Jongho Park
    http://arxiv.org/abs/2103.08802v1

    • [math.ST]A refined continuity correction for the negative binomial distribution and asymptotics of the median
    Frédéric Ouimet
    http://arxiv.org/abs/2103.08846v1

    • [math.ST]Deep learning: a statistical viewpoint
    Peter L. Bartlett, Andrea Montanari, Alexander Rakhlin
    http://arxiv.org/abs/2103.09177v1

    • [math.ST]Extreme value analysis for mixture models with heavy-tailed impurity
    Vladimir Panov, Ekaterina Morozova
    http://arxiv.org/abs/2103.07689v2

    • [physics.data-an]Determining the maximum information gain and optimising experimental design in neutron reflectometry using the Fisher information
    James H. Durant, Lucas Wilkins, Keith Butler, Joshaniel F. K. Cooper
    http://arxiv.org/abs/2103.08973v1

    • [quant-ph]Tomography of time-dependent quantum spin networks with machine learning
    Chen-Di Han, Bryan Glaz, Mulugeta Haile, Ying-Cheng Lai
    http://arxiv.org/abs/2103.08645v1

    • [stat.AP]Effect of social isolation in dengue cases in the state of Sao Paulo, Brazil: an analysis during the COVID-19 pandemic
    Gleice Margarete de Souza Conceição, Gerson Laurindo Barbosa, Camila Lorenz, Ana Carolina Dias Bocewicz, Lidia Maria Reis Santana, Cristiano Corrêa de Azevedo Marques, Francisco Chiaravalloti-Neto
    http://arxiv.org/abs/2103.08669v1

    • [stat.AP]Identification of COVID-19 mortality patterns in Brazil by a functional QR decomposition analysis
    Jorge C. Lucero
    http://arxiv.org/abs/2103.08794v1

    • [stat.AP]Modeling Weather-induced Home Insurance Risks with Support Vector Machine Regression
    Asim K. Dey, Vyacheslav Lyubchich, Yulia R. Gel
    http://arxiv.org/abs/2103.08761v1

    • [stat.AP]The role of mobility and sanitary measures on Covid-19 in Costa Rica, March through July 2020
    Luis A. Barboza, Paola Vásquez, Gustavo Mery, Fabio Sanchez, Yury E. García, Juan G. Calvo, Tania Rivas, Daniel Salas
    http://arxiv.org/abs/2103.08732v1

    • [stat.ME]A two-way factor model for high-dimensional matrix data
    Gao Zhigen, Yuan Chaofeng, Jing Bingyi, Huang Wei, Guo Jianhua
    http://arxiv.org/abs/2103.07920v2

    • [stat.ME]Estimation of parameters of the Gumbel type-II distribution under AT-II PHCS with an application of Covid-19 data
    Subhankar Dutta, Suchandan Kayal
    http://arxiv.org/abs/2103.08641v1

    • [stat.ME]Generalized Low-rank plus Sparse Tensor Estimation by Fast Riemannian Optimization
    Jian-Feng Cai, Jingyang Li, Dong Xia
    http://arxiv.org/abs/2103.08895v1

    • [stat.ME]Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-Differentiable Priors
    Jacob Vorstrup Goldman, Torben Sell, Sumeetpal Sidhu Singh
    http://arxiv.org/abs/2103.09017v1

    • [stat.ME]Incorporating External Data into the Analysis of Clinical Trials via Bayesian Additive Regression Trees
    Tianjian Zhou, Yuan Ji
    http://arxiv.org/abs/2103.08754v1

    • [stat.ME]Modeling proportion of success in high school leaving examination- A comparative study of Inflated Unit Lindley and Inflated Beta distribution
    Subrata Chakraborty, Sahana Bhattacharjee
    http://arxiv.org/abs/2103.08916v1

    • [stat.ME]Newcomb-Benford’s law as a fast ersatz of discrepancy measures
    Pamphile T. Roy
    http://arxiv.org/abs/2103.08705v1

    • [stat.ME]Rollage: Efficient Rolling Average Algorithm to Estimate ARMA Models for Big Time Series Data
    Ali Eshragh, Glen Livingston, Thomas McCarthy McCann, Luke Yerbury
    http://arxiv.org/abs/2103.09175v1

    • [stat.ME]Valid sequential inference on probability forecast performance
    Alexander Henzi, Johanna F. Ziegel
    http://arxiv.org/abs/2103.08402v2

    • [stat.ME]Visualizing Outliers in High Dimensional Functional Data for Task fMRI data exploration
    Yasser Aleman-Gomez, Ana Arribas-Gil, Manuel Desco, Antonio Elias-Fernandez, Juan Romo
    http://arxiv.org/abs/2103.08874v1

    • [stat.ME]Workflow Techniques for the Robust Use of Bayes Factors
    Daniel J. Schad, Bruno Nicenboim, Paul-Christian Bürkner, Michael Betancourt, Shravan Vasishth
    http://arxiv.org/abs/2103.08744v1

    • [stat.ML]A Central Limit Theorem for Differentially Private Query Answering
    Jinshuo Dong, Weijie J. Su, Linjun Zhang
    http://arxiv.org/abs/2103.08721v1

    • [stat.ML]Differentiable Learning Under Triage
    Nastaran Okati, Abir De, Manuel Gomez-Rodriguez
    http://arxiv.org/abs/2103.08902v1

    • [stat.ML]Function approximation by deep neural networks with parameters 今日学术视野(2021.3.18) - 图6
    Aleksandr Beknazaryan
    http://arxiv.org/abs/2103.08659v1

    • [stat.ML]Quick Learning Mechanism with Cross-Domain Adaptation for Intelligent Fault Diagnosis
    Arun K. Sharma, Nishchal K. Verma
    http://arxiv.org/abs/2103.08889v1

    • [stat.ML]Soft and subspace robust multivariate rank tests based on entropy regularized optimal transport
    Shoaib Bin Masud, Boyang Lyu, Shuchin Aeron
    http://arxiv.org/abs/2103.08811v1