astro-ph.IM - 仪器仪表和天体物理学方法

    cond-mat.mtrl-sci - 材料科学 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.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.MS - 数学软件 cs.NE - 神经与进化计算 cs.PF - 计算性能 cs.RO - 机器人学 cs.SD - 声音处理 cs.SI - 社交网络与信息网络 econ.GN - 一般经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.DG - 微分几何 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 nlin.AO - 适应和自组织系统 physics.comp-ph - 计算物理学 q-bio.NC - 神经元与认知 q-bio.PE - 人口与发展 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.IM]Detection of asteroid trails in Hubble Space Telescope images using Deep Learning
    • [cond-mat.mtrl-sci]Polymer Informatics with Multi-Task Learning
    • [cs.AI]Fact or Factitious? Contextualized Opinion Spam Detection
    • [cs.AI]Model Minimization For Online Predictability
    • [cs.AI]Proceedings 9th International Workshop on Theorem Proving Components for Educational Software
    • [cs.AI]QBSUM: a Large-Scale Query-Based Document Summarization Dataset from Real-world Applications
    • [cs.CL]”where is this relationship going?”: Understanding Relationship Trajectories in Narrative Text
    • [cs.CL]A Visuospatial Dataset for Naturalistic Verb Learning
    • [cs.CL]Combining Self-Training and Self-Supervised Learning for Unsupervised Disfluency Detection
    • [cs.CL]Contextual BERT: Conditioning the Language Model Using a Global State
    • [cs.CL]Conversation Graph: Data Augmentation, Training and Evaluation for Non-Deterministic Dialogue Management
    • [cs.CL]CopyNext: Explicit Span Copying and Alignment in Sequence to Sequence Models
    • [cs.CL]DeSMOG: Detecting Stance in Media On Global Warming
    • [cs.CL]Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation
    • [cs.CL]Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
    • [cs.CL]May I Ask Who’s Calling? Named Entity Recognition on Call Center Transcripts for Privacy Law Compliance
    • [cs.CL]Memory Attentive Fusion: External Language Model Integration for Transformer-based Sequence-to-Sequence Model
    • [cs.CL]Multiple Sclerosis Severity Classification From Clinical Text
    • [cs.CL]Named Entity Recognition for Social Media Texts with Semantic Augmentation
    • [cs.CL]Tilde at WMT 2020: News Task Systems
    • [cs.CL]Unbabel’s Participation in the WMT20 Metrics Shared Task
    • [cs.CL]Uncovering Latent Biases in Text: Method and Application to Peer Review
    • [cs.CR]5W1H-based Expression for the Effective Sharing of Information in Digital Forensic Investigations
    • [cs.CR]Construction Payment Automation Using Blockchain-Enabled Smart Contracts and Reality Capture Technologies
    • [cs.CR]What can we learn from gradients?
    • [cs.CV]An End to End Network Architecture for Fundamental Matrix Estimation
    • [cs.CV]An Overview Of 3D Object Detection
    • [cs.CV]Asynchronous Corner Tracking Algorithm based on Lifetime of Events for DAVIS Cameras
    • [cs.CV]Automatic joint damage quantification using computer vision and deep learning
    • [cs.CV]Beyond cross-entropy: learning highly separable feature distributions for robust and accurate classification
    • [cs.CV]Black-Box Optimization of Object Detector Scales
    • [cs.CV]CNN Profiler on Polar Coordinate Images for Tropical Cyclone Structure Analysis
    • [cs.CV]Collaborative Method for Incremental Learning on Classification and Generation
    • [cs.CV]Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search
    • [cs.CV]Deep DA for Ordinal Regression of Pain Intensity Estimation Using Weakly-Labeled Videos
    • [cs.CV]Deep Shells: Unsupervised Shape Correspondence with Optimal Transport
    • [cs.CV]Dynamic Resource-aware Corner Detection for Bio-inspired Vision Sensors
    • [cs.CV]Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation
    • [cs.CV]Free-Form Image Inpainting via Contrastive Attention Network
    • [cs.CV]Fusion Models for Improved Visual Captioning
    • [cs.CV]Identifying safe intersection design through unsupervised feature extraction from satellite imagery
    • [cs.CV]Learning Deep Interleaved Networks with Asymmetric Co-Attention for Image Restoration
    • [cs.CV]Night vision obstacle detection and avoidance based on Bio-Inspired Vision Sensors
    • [cs.CV]Object sieving and morphological closing to reduce false detections in wide-area aerial imagery
    • [cs.CV]Panoster: End-to-end Panoptic Segmentation of LiDAR Point Clouds
    • [cs.CV]Passport-aware Normalization for Deep Model Protection
    • [cs.CV]Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks
    • [cs.CV]Point Cloud Attribute Compression via Successive Subspace Graph Transform
    • [cs.CV]Quantified Facial Temporal-Expressiveness Dynamics for Affect Analysis
    • [cs.CV]Recurrent Neural Networks for video object detection
    • [cs.CV]Recurrent neural circuits for contour detection
    • [cs.CV]RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder
    • [cs.CV]SAR-NAS: Skeleton-based Action Recognition via Neural Architecture Searching
    • [cs.CV]Sea-Net: Squeeze-And-Excitation Attention Net For Diabetic Retinopathy Grading
    • [cs.CV]Self-Supervised Video Representation Using Pretext-Contrastive Learning
    • [cs.CV]Semantic video segmentation for autonomous driving
    • [cs.CV]Suppressing Mislabeled Data via Grouping and Self-Attention
    • [cs.CV]Transferable Universal Adversarial Perturbations Using Generative Models
    • [cs.CV]WaveTransform: Crafting Adversarial Examples via Input Decomposition
    • [cs.CY]Away from Trolley Problems and Toward Risk Management
    • [cs.CY]CRICTRS: Embeddings based Statistical and Semi Supervised Cricket Team Recommendation System
    • [cs.CY]Design and Evaluation of Electric Bus Systems for Metropolitan Cities
    • [cs.CY]Designing learning experiences for online teaching and learning
    • [cs.CY]Detecting Individuals with Depressive Disorder fromPersonal Google Search and YouTube History Logs
    • [cs.CY]Developing Augmented Reality based Gaming Model to Teach Ethical Education in Primary Schools
    • [cs.CY]Import test questions into Moodle LMS
    • [cs.CY]Machine Ethics and Automated Vehicles
    • [cs.CY]Machine Learning Based Demand Modelling for On-Demand Transit Services: A Case Study of Belleville, Ontario
    • [cs.CY]PeopleXploit — A hybrid tool to collect public data
    • [cs.CY]Using Twitter to Analyze Political Polarization During National Crises
    • [cs.CY]Using a Binary Classification Model to Predict the Likelihood of Enrolment to the Undergraduate Program of a Philippine University
    • [cs.DC]Advanced Python Performance Monitoring with Score-P
    • [cs.DC]Benchmarking Parallelism in FaaS Platforms
    • [cs.DC]On Linearizability and the Termination of Randomized Algorithms
    • [cs.DC]Prediction-Based Power Oversubscription in Cloud Platforms
    • [cs.DC]Rosella: A Self-Driving Distributed Scheduler for Heterogeneous Clusters
    • [cs.DC]Sizeless: Predicting the optimal size of serverless functions
    • [cs.DC]StencilFlow: Mapping Large Stencil Programs to Distributed Spatial Computing Systems
    • [cs.DS]A Local Search Framework for Experimental Design
    • [cs.DS]A more Pragmatic Implementation of the Lock-free, Ordered, Linked List
    • [cs.HC]Learning Personalized Discretionary Lane-Change Initiation for Fully Autonomous Driving Based on Reinforcement Learning
    • [cs.HC]Speech-Based Emotion Recognition using Neural Networks and Information Visualization
    • [cs.IR]CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation
    • [cs.IR]Efficient Joinable Table Discovery in Data Lakes: A High-Dimensional Similarity-Based Approach
    • [cs.IR]Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System
    • [cs.IT]Capacity-achieving codes: a review on double transitivity
    • [cs.IT]Channel Estimation and Equalization for CP-OFDM-based OTFS in Fractional Doppler Channels
    • [cs.IT]Concatenated Codes for Recovery From Multiple Reads of DNA Sequences
    • [cs.IT]Constrained Online Learning to Mitigate Distortion Effects in Pulse-Agile Cognitive Radar
    • [cs.IT]Learning Centric Wireless Resource Allocation for Edge Computing: Algorithm and Experiment
    • [cs.IT]Reconfigurable Intelligent Surface Aided Secure Transmission: Outage-Constrained Energy-Efficiency Maximization
    • [cs.IT]Semi-Grant-Free NOMA: Ergodic Rates Analysis with Random Deployed Users
    • [cs.IT]Slicing a single wireless collision channel among throughput- and timeliness-sensitive services
    • [cs.LG]A Novel Anomaly Detection Algorithm for Hybrid Production Systems based on Deep Learning and Timed Automata
    • [cs.LG]A Study on Efficiency in Continual Learning Inspired by Human Learning
    • [cs.LG]Abstract Value Iteration for Hierarchical Reinforcement Learning
    • [cs.LG]Analyzing the tree-layer structure of Deep Forests
    • [cs.LG]Autoregressive Asymmetric Linear Gaussian Hidden Markov Models
    • [cs.LG]Bandit Policies for Reliable Cellular Network Handovers in Extreme Mobility
    • [cs.LG]Batch Reinforcement Learning with a Nonparametric Off-Policy Policy Gradient
    • [cs.LG]Causal variables from reinforcement learning using generalized Bellman equations
    • [cs.LG]Class-incremental learning: survey and performance evaluation
    • [cs.LG]Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
    • [cs.LG]Emergence of Spatial Coordinates via Exploration
    • [cs.LG]Estimating Multiplicative Relations in Neural Networks
    • [cs.LG]FiGLearn: Filter and Graph Learning using Optimal Transport
    • [cs.LG]Financial ticket intelligent recognition system based on deep learning
    • [cs.LG]Forecasting Hamiltonian dynamics without canonical coordinates
    • [cs.LG]GENs: Generative Encoding Networks
    • [cs.LG]Gaussian Process Bandit Optimization of theThermodynamic Variational Objective
    • [cs.LG]How do Offline Measures for Exploration in Reinforcement Learning behave?
    • [cs.LG]LSTM for Model-Based Anomaly Detection in Cyber-Physical Systems
    • [cs.LG]Learning to Actively Learn: A Robust Approach
    • [cs.LG]Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions
    • [cs.LG]Measuring and Harnessing Transference in Multi-Task Learning
    • [cs.LG]Memory Optimization for Deep Networks
    • [cs.LG]Multilayer Clustered Graph Learning
    • [cs.LG]Multitask Bandit Learning through Heterogeneous Feedback Aggregation
    • [cs.LG]Off-Policy Interval Estimation with Lipschitz Value Iteration
    • [cs.LG]Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments
    • [cs.LG]Reliable Graph Neural Networks via Robust Aggregation
    • [cs.LG]Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
    • [cs.LG]Robustifying Binary Classification to Adversarial Perturbation
    • [cs.LG]Scalable Graph Neural Networks via Bidirectional Propagation
    • [cs.LG]Self-awareness in intelligent vehicles: Feature based dynamic Bayesian models for abnormality detection
    • [cs.LG]Self-paced Data Augmentation for Training Neural Networks
    • [cs.LG]Semi-Supervised Speech Recognition via Graph-based Temporal Classification
    • [cs.LG]Speech-Image Semantic Alignment Does Not Depend on Any Prior Classification Tasks
    • [cs.LG]Supervised sequential pattern mining of event sequences in sport to identify important patterns of play: an application to rugby union
    • [cs.LG]Test Set Optimization by Machine Learning Algorithms
    • [cs.LG]Understanding the Failure Modes of Out-of-Distribution Generalization
    • [cs.LG]Understanding the Pathologies of Approximate Policy Evaluation when Combined with Greedification in Reinforcement Learning
    • [cs.MS]Generalized eigen, singular value, and partial least squares decompositions: The GSVD package
    • [cs.NE]A brief overview of swarm intelligence-based algorithms for numerical association rule mining
    • [cs.NE]Measuring non-trivial compositionality in emergent communication
    • [cs.NE]Overcoming The Limitations of Neural Networks in Composite-Pattern Learning with Architopes
    • [cs.PF]Poster: Benchmarking Financial Data Feed Systems
    • [cs.RO]”What, not how” — Solving an under-actuated insertion task from scratch
    • [cs.RO]A Framework for Learning Predator-prey Agents from Simulation to Real World
    • [cs.RO]A Hybrid Position/Force Controller for Joint Robots
    • [cs.RO]Affordance-Aware Handovers with Human Arm Mobility Constraints
    • [cs.RO]Dynamic Formation Reshaping Based on Point Set Registration in a Swarm of Drones
    • [cs.RO]Gaussian Processes Model-based Control of Underactuated Balance Robots
    • [cs.RO]Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions
    • [cs.RO]Online State-Time Trajectory Planning Using Timed-ESDF in Highly Dynamic Environments
    • [cs.RO]Optimization Fabrics for Behavioral Design
    • [cs.SD]DNSMOS: A Non-Intrusive Perceptual Objective Speech Quality metric to evaluate Noise Suppressors
    • [cs.SD]GANs & Reels: Creating Irish Music using a Generative Adversarial Network
    • [cs.SD]Improving Perceptual Quality by Phone-Fortified Perceptual Loss for Speech Enhancement
    • [cs.SD]Raw Audio for Depression Detection Can Be More Robust Against Gender Imbalance than Mel-Spectrogram Features
    • [cs.SD]Self-supervised Pre-training Reduces Label Permutation Instability of Speech Separation
    • [cs.SI]Analyzing Societal Impact of COVID-19: A Study During the Early Days of the Pandemic
    • [cs.SI]Discovery and classification of Twitter bots
    • [cs.SI]Down the bot hole: actionable insights from a 1-year analysis of bots activity on Twitter
    • [cs.SI]Exploring complex networks with the ICON R package
    • [cs.SI]Micromobility in Smart Cities: A Closer Look at Shared Dockless E-Scooters via Big Social Data
    • [econ.GN]Preventing COVID-19 Fatalities: State versus Federal Policies
    • [eess.AS]Progressive Voice Trigger Detection: Accuracy vs Latency
    • [eess.IV]A Novel Fast 3D Single Image Super-Resolution Algorithm
    • [eess.IV]A comparison of automatic multi-tissue segmentation methods of the human fetal brain using the FeTA Dataset
    • [eess.IV]Accurate Prostate Cancer Detection and Segmentation on Biparametric MRI using Non-local Mask R-CNN with Histopathological Ground Truth
    • [eess.IV]An automated and multi-parametric algorithm for objective analysis of meibography images
    • [eess.IV]Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint
    • [eess.IV]Deep Autofocus for Synthetic Aperture Sonar
    • [eess.IV]FlatNet: Towards Photorealistic Scene Reconstruction from Lensless Measurements
    • [eess.IV]Genetic U-Net: Automatically Designing Lightweight U-shaped CNN Architectures Using the Genetic Algorithm for Retinal Vessel Segmentation
    • [eess.IV]GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video
    • [eess.IV]Ground Roll Suppression using Convolutional Neural Networks
    • [eess.IV]Maximum a posteriori signal recovery for optical coherence tomography angiography image generation and denoising
    • [eess.IV]ProCAN: Progressive Growing Channel Attentive Non-Local Network for Lung Nodule Classification
    • [eess.SP]Distance Invariant Sparse Autoencoder for Wireless Signal Strength Mapping
    • [eess.SP]FD Cell-Free mMIMO: Analysis and Optimization
    • [eess.SP]Identification of complex mixtures for Raman spectroscopy using a novel scheme based on a new multi-label deep neural network
    • [eess.SP]Sampling and Reconstruction of Sparse Signals in Shift-Invariant Spaces: Generalized Shannon’s Theorem Meets Compressive Sensing
    • [eess.SP]Solving Sparse Linear Inverse Problems in Communication Systems: A Deep Learning Approach With Adaptive Depth
    • [eess.SY]Cloud-Based Dynamic Programming for an Electric City Bus Energy Management Considering Real-Time Passenger Load Prediction
    • [eess.SY]Continuous Chaotic Nonlinear System and Lyapunov controller Optimization using Deep Learning
    • [eess.SY]Probabilistic interval predictor based on dissimilarity functions
    • [math.DG]Geometric Sampling of Networks
    • [math.NA]Identifying Transition States of Chemical Kinetic Systems using Network Embedding Techniques
    • [math.OC]A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
    • [math.OC]Sparse Signal Reconstruction for Nonlinear Models via Piecewise Rational Optimization
    • [math.PR]Rates of convergence for Gibbs sampling in the analysis of almost exchangeable data
    • [math.ST]Generalization bounds for deep thresholding networks
    • [math.ST]Nonparametric estimation of copulas and copula densities by orthogonal projections
    • [math.ST]Post-selection inference with HSIC-Lasso
    • [math.ST]Staged trees are curved exponential families
    • [nlin.AO]Link inference of noisy delay-coupled networks: Machine learning and opto-electronic experimental tests
    • [physics.comp-ph]A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound
    • [physics.comp-ph]Diagnostic data integration using deep neural networks for real-time plasma analysis
    • [q-bio.NC]The distribution of inhibitory neurons in the C. elegans connectome facilitates self-optimization of coordinated neural activity
    • [q-bio.PE]The fundamental equations of change in statistical ensembles and biological populations
    • [quant-ph]Fundamental limitations to key distillation from Gaussian states with Gaussian operations
    • [stat.AP]A statistical model to assess risk for supporting SARS-CoV-2 quarantine decisions
    • [stat.AP]COVID-19 incidences and its association with environmental quality: A country-level assessment in India
    • [stat.AP]Space-Time Covid-19 Bayesian SIR modeling in South Carolina
    • [stat.AP]Spatiotemporal effects of the causal factors on COVID-19 incidences in the contiguous United States
    • [stat.ME]An Exact Solution Path Algorithm for SLOPE and Quasi-Spherical OSCAR
    • [stat.ME]CONQ: CONtinuous Quantile Treatment Effects for Large-Scale Online Controlled Experiments
    • [stat.ME]Classification Accuracy and Parameter Estimation in Multilevel Contexts: A Study of Conditional Nonparametric Multilevel Latent Class Analysis
    • [stat.ME]Group-regularized ridge regression via empirical Bayes noise level cross-validation
    • [stat.ME]Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and Graphs
    • [stat.ME]Learning Bayesian Networks from Ordinal Data
    • [stat.ME]Modelling and simulation of dependence structures in nonlife insurance with Bernstein copulas
    • [stat.ML]Attentive Clustering Processes
    • [stat.ML]Domain adaptation under structural causal models
    • [stat.ML]Independence Tests Without Ground Truth for Noisy Learners
    • [stat.ML]Learning interaction kernels in mean-field equations of 1st-order systems of interacting particles
    • [stat.ML]Low-Variance Policy Gradient Estimation with World Models
    • [stat.ML]Matern Gaussian Processes on Graphs
    • [stat.ML]On the robustness of kernel-based pairwise learning
    • [stat.ML]Teaching a GAN What Not to Learn
    • [stat.ML]Tensor Completion via Tensor Networks with a Tucker Wrapper
    • [stat.ML]The Performance Analysis of Generalized Margin Maximizer (GMM) on Separable Data

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

    • [astro-ph.IM]Detection of asteroid trails in Hubble Space Telescope images using Deep Learning
    Andrei A. Parfeni, Laurentiu I. Caramete, Andreea M. Dobre, Nguyen Tran Bach
    http://arxiv.org/abs/2010.15425v1

    • [cond-mat.mtrl-sci]Polymer Informatics with Multi-Task Learning
    Christopher Künneth, Arunkumar Chitteth Rajan, Huan Tran, Lihua Chen, Chiho Kim, Rampi Ramprasad
    http://arxiv.org/abs/2010.15166v1

    • [cs.AI]Fact or Factitious? Contextualized Opinion Spam Detection
    Stefan Kennedy, Niall Walsh, Kirils Sloka, Jennifer Foster, Andrew McCarren
    http://arxiv.org/abs/2010.15296v1

    • [cs.AI]Model Minimization For Online Predictability
    Sriram Gopalakrishnan, Subbarao Kambhampati
    http://arxiv.org/abs/2010.15255v1

    • [cs.AI]Proceedings 9th International Workshop on Theorem Proving Components for Educational Software
    Pedro Quaresma, Walther Neuper, João Marcos
    http://arxiv.org/abs/2010.15832v1

    • [cs.AI]QBSUM: a Large-Scale Query-Based Document Summarization Dataset from Real-world Applications
    Mingjun Zhao, Shengli Yan, Bang Liu, Xinwang Zhong, Qian Hao, Haolan Chen, Di Niu, Bowei Long, Weidong Guo
    http://arxiv.org/abs/2010.14108v2

    • [cs.CL]“where is this relationship going?”: Understanding Relationship Trajectories in Narrative Text
    Keen You, Dan Goldwasser
    http://arxiv.org/abs/2010.15313v1

    • [cs.CL]A Visuospatial Dataset for Naturalistic Verb Learning
    Dylan Ebert, Ellie Pavlick
    http://arxiv.org/abs/2010.15225v1

    • [cs.CL]Combining Self-Training and Self-Supervised Learning for Unsupervised Disfluency Detection
    Shaolei Wang, Zhongyuan Wang, Wanxiang Che, Ting Liu
    http://arxiv.org/abs/2010.15360v1

    • [cs.CL]Contextual BERT: Conditioning the Language Model Using a Global State
    Timo I. Denk, Ana Peleteiro Ramallo
    http://arxiv.org/abs/2010.15778v1

    • [cs.CL]Conversation Graph: Data Augmentation, Training and Evaluation for Non-Deterministic Dialogue Management
    Milan Gritta, Gerasimos Lampouras, Ignacio Iacobacci
    http://arxiv.org/abs/2010.15411v1

    • [cs.CL]CopyNext: Explicit Span Copying and Alignment in Sequence to Sequence Models
    Abhinav Singh, Patrick Xia, Guanghui Qin, Mahsa Yarmohammadi, Benjamin Van Durme
    http://arxiv.org/abs/2010.15266v1

    • [cs.CL]DeSMOG: Detecting Stance in Media On Global Warming
    Yiwei Luo, Dallas Card, Dan Jurafsky
    http://arxiv.org/abs/2010.15149v1

    • [cs.CL]Explainable Automated Coding of Clinical Notes using Hierarchical Label-wise Attention Networks and Label Embedding Initialisation
    Hang Dong, Víctor Suárez-Paniagua, William Whiteley, Honghan Wu
    http://arxiv.org/abs/2010.15728v1

    • [cs.CL]Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
    Yuyang Nie, Yuanhe Tian, Yan Song, Xiang Ao, Xiang Wan
    http://arxiv.org/abs/2010.15466v1

    • [cs.CL]May I Ask Who’s Calling? Named Entity Recognition on Call Center Transcripts for Privacy Law Compliance
    Micaela Kaplan
    http://arxiv.org/abs/2010.15598v1

    • [cs.CL]Memory Attentive Fusion: External Language Model Integration for Transformer-based Sequence-to-Sequence Model
    Mana Ihori, Ryo Masumura, Naoki Makishima, Tomohiro Tanaka, Akihiko Takashima, Shota Orihashi
    http://arxiv.org/abs/2010.15437v1

    • [cs.CL]Multiple Sclerosis Severity Classification From Clinical Text
    Alister D Costa, Stefan Denkovski, Michal Malyska, Sae Young Moon, Brandon Rufino, Zhen Yang, Taylor Killian, Marzyeh Ghassemi
    http://arxiv.org/abs/2010.15316v1

    • [cs.CL]Named Entity Recognition for Social Media Texts with Semantic Augmentation
    Yuyang Nie, Yuanhe Tian, Xiang Wan, Yan Song, Bo Dai
    http://arxiv.org/abs/2010.15458v1

    • [cs.CL]Tilde at WMT 2020: News Task Systems
    Rihards Krišlauks, Mārcis Pinnis
    http://arxiv.org/abs/2010.15423v1

    • [cs.CL]Unbabel’s Participation in the WMT20 Metrics Shared Task
    Ricardo Rei, Craig Stewart, Catarina Farinha, Alon Lavie
    http://arxiv.org/abs/2010.15535v1

    • [cs.CL]Uncovering Latent Biases in Text: Method and Application to Peer Review
    Emaad Manzoor, Nihar B. Shah
    http://arxiv.org/abs/2010.15300v1

    • [cs.CR]5W1H-based Expression for the Effective Sharing of Information in Digital Forensic Investigations
    Jaehyeok Han, Jieon Kim, Sangjin Lee
    http://arxiv.org/abs/2010.15711v1

    • [cs.CR]Construction Payment Automation Using Blockchain-Enabled Smart Contracts and Reality Capture Technologies
    Hesam Hamledari, Martin Fischer
    http://arxiv.org/abs/2010.15232v1

    • [cs.CR]What can we learn from gradients?
    Jia Qian, Lars Kai Hansen
    http://arxiv.org/abs/2010.15718v1

    • [cs.CV]An End to End Network Architecture for Fundamental Matrix Estimation
    Yesheng Zhang, Xu Zhao, Dahong Qian
    http://arxiv.org/abs/2010.15528v1

    • [cs.CV]An Overview Of 3D Object Detection
    Yilin Wang, Jiayi Ye
    http://arxiv.org/abs/2010.15614v1

    • [cs.CV]Asynchronous Corner Tracking Algorithm based on Lifetime of Events for DAVIS Cameras
    Sherif A. S. Mohamed, Jawad N. Yasin, Mohammad-Hashem Haghbayan, Antonio Miele, Jukka Heikkonen, Hannu Tenhunen, Juha Plosila
    http://arxiv.org/abs/2010.15510v1

    • [cs.CV]Automatic joint damage quantification using computer vision and deep learning
    Quang Tran, Jeffery R. Roesler
    http://arxiv.org/abs/2010.15303v1

    • [cs.CV]Beyond cross-entropy: learning highly separable feature distributions for robust and accurate classification
    Arslan Ali, Andrea Migliorati, Tiziano Bianchi, Enrico Magli
    http://arxiv.org/abs/2010.15487v1

    • [cs.CV]Black-Box Optimization of Object Detector Scales
    Mohandass Muthuraja, Octavio Arriaga, Paul Plöger, Frank Kirchner, Matias Valdenegro-Toro
    http://arxiv.org/abs/2010.15823v1

    • [cs.CV]CNN Profiler on Polar Coordinate Images for Tropical Cyclone Structure Analysis
    Boyo Chen, Buo-Fu Chen, Chun-Min Hsiao
    http://arxiv.org/abs/2010.15158v1

    • [cs.CV]Collaborative Method for Incremental Learning on Classification and Generation
    Byungju Kim, Jaeyoung Lee, Kyungsu Kim, Sungjin Kim, Junmo Kim
    http://arxiv.org/abs/2010.15378v1

    • [cs.CV]Cream of the Crop: Distilling Prioritized Paths For One-Shot Neural Architecture Search
    Houwen Peng, Hao Du, Hongyuan Yu, Qi Li, Jing Liao, Jianlong Fu
    http://arxiv.org/abs/2010.15821v1

    • [cs.CV]Deep DA for Ordinal Regression of Pain Intensity Estimation Using Weakly-Labeled Videos
    Gnana Praveen R, Eric Granger, Patrick Cardinal
    http://arxiv.org/abs/2010.15675v1

    • [cs.CV]Deep Shells: Unsupervised Shape Correspondence with Optimal Transport
    Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé, Daniel Cremers
    http://arxiv.org/abs/2010.15261v1

    • [cs.CV]Dynamic Resource-aware Corner Detection for Bio-inspired Vision Sensors
    Sherif A. S. Mohamed, Jawad N. Yasin, Mohammad-hashem Haghbayan, Antonio Miele, Jukka Heikkonen, Hannu Tenhunen, Juha Plosila
    http://arxiv.org/abs/2010.15507v1

    • [cs.CV]Exploring Generative Adversarial Networks for Image-to-Image Translation in STEM Simulation
    Nick Lawrence, Mingren Shen, Ruiqi Yin, Cloris Feng, Dane Morgan
    http://arxiv.org/abs/2010.15315v1

    • [cs.CV]Free-Form Image Inpainting via Contrastive Attention Network
    Xin Ma, Xiaoqiang Zhou, Huaibo Huang, Zhenhua Chai, Xiaolin Wei, Ran He
    http://arxiv.org/abs/2010.15643v1

    • [cs.CV]Fusion Models for Improved Visual Captioning
    Marimuthu Kalimuthu, Aditya Mogadala, Marius Mosbach, Dietrich Klakow
    http://arxiv.org/abs/2010.15251v1

    • [cs.CV]Identifying safe intersection design through unsupervised feature extraction from satellite imagery
    Jasper S. Wijnands, Haifeng Zhao, Kerry A. Nice, Jason Thompson, Katherine Scully, Jingqiu Guo, Mark Stevenson
    http://arxiv.org/abs/2010.15343v1

    • [cs.CV]Learning Deep Interleaved Networks with Asymmetric Co-Attention for Image Restoration
    Feng Li, Runmin Cong, Huihui Bai, Yifan He, Yao Zhao, Ce Zhu
    http://arxiv.org/abs/2010.15689v1

    • [cs.CV]Night vision obstacle detection and avoidance based on Bio-Inspired Vision Sensors
    Jawad N. Yasin, Sherif A. S. Mohamed, Mohammad-hashem Haghbayan, Jukka Heikkonen, Hannu Tenhunen, Muhammad Mehboob Yasin, Juha Plosila
    http://arxiv.org/abs/2010.15509v1

    • [cs.CV]Object sieving and morphological closing to reduce false detections in wide-area aerial imagery
    Xin Gao, Sundaresh Ram, Jeffrey J. Rodriguez
    http://arxiv.org/abs/2010.15260v1

    • [cs.CV]Panoster: End-to-end Panoptic Segmentation of LiDAR Point Clouds
    Stefano Gasperini, Mohammad-Ali Nikouei Mahani, Alvaro Marcos-Ramiro, Nassir Navab, Federico Tombari
    http://arxiv.org/abs/2010.15157v1

    • [cs.CV]Passport-aware Normalization for Deep Model Protection
    Jie Zhang, Dongdong Chen, Jing Liao, Weiming Zhang, Gang Hua, Nenghai Yu
    http://arxiv.org/abs/2010.15824v1

    • [cs.CV]Permute, Quantize, and Fine-tune: Efficient Compression of Neural Networks
    Julieta Martinez, Jashan Shewakramani, Ting Wei Liu, Ioan Andrei Bârsan, Wenyuan Zeng, Raquel Urtasun
    http://arxiv.org/abs/2010.15703v1

    • [cs.CV]Point Cloud Attribute Compression via Successive Subspace Graph Transform
    Yueru Chen, Yiting Shao, Jing Wang, Ge Li, C. -C. Jay Kuo
    http://arxiv.org/abs/2010.15302v1

    • [cs.CV]Quantified Facial Temporal-Expressiveness Dynamics for Affect Analysis
    Md Taufeeq Uddin, Shaun Canavan
    http://arxiv.org/abs/2010.14705v1

    • [cs.CV]Recurrent Neural Networks for video object detection
    Ahmad B Qasim, Arnd Pettirsch
    http://arxiv.org/abs/2010.15740v1

    • [cs.CV]Recurrent neural circuits for contour detection
    Drew Linsley, Junkyung Kim, Alekh Ashok, Thomas Serre
    http://arxiv.org/abs/2010.15314v1

    • [cs.CV]RelationNet++: Bridging Visual Representations for Object Detection via Transformer Decoder
    Cheng Chi, Fangyun Wei, Han Hu
    http://arxiv.org/abs/2010.15831v1

    • [cs.CV]SAR-NAS: Skeleton-based Action Recognition via Neural Architecture Searching
    Haoyuan Zhang, Yonghong Hou, Pichao Wang, Zihui Guo, Wanqing Li
    http://arxiv.org/abs/2010.15336v1

    • [cs.CV]Sea-Net: Squeeze-And-Excitation Attention Net For Diabetic Retinopathy Grading
    Ziyuan Zhao, Kartik Chopra, Zeng Zeng, Xiaoli Li
    http://arxiv.org/abs/2010.15344v1

    • [cs.CV]Self-Supervised Video Representation Using Pretext-Contrastive Learning
    Li Tao, Xueting Wang, Toshihiko Yamasaki
    http://arxiv.org/abs/2010.15464v1

    • [cs.CV]Semantic video segmentation for autonomous driving
    Minh Triet Chau
    http://arxiv.org/abs/2010.15250v1

    • [cs.CV]Suppressing Mislabeled Data via Grouping and Self-Attention
    Xiaojiang Peng, Kai Wang, Zhaoyang Zeng, Qing Li, Jianfei Yang, Yu Qiao
    http://arxiv.org/abs/2010.15603v1

    • [cs.CV]Transferable Universal Adversarial Perturbations Using Generative Models
    Atiye Sadat Hashemi, Andreas Bär, Saeed Mozaffari, Tim Fingscheidt
    http://arxiv.org/abs/2010.14919v2

    • [cs.CV]WaveTransform: Crafting Adversarial Examples via Input Decomposition
    Divyam Anshumaan, Akshay Agarwal, Mayank Vatsa, Richa Singh
    http://arxiv.org/abs/2010.15773v1

    • [cs.CY]Away from Trolley Problems and Toward Risk Management
    Noah J. Goodall
    http://arxiv.org/abs/2010.15217v1

    • [cs.CY]CRICTRS: Embeddings based Statistical and Semi Supervised Cricket Team Recommendation System
    Prazwal Chhabra, Rizwan Ali, Vikram Pudi
    http://arxiv.org/abs/2010.15607v1

    • [cs.CY]Design and Evaluation of Electric Bus Systems for Metropolitan Cities
    Unnikrishnan Menon, Divyani Panda
    http://arxiv.org/abs/2010.15606v1

    • [cs.CY]Designing learning experiences for online teaching and learning
    Nachamma Sockalingam, Junhua Liu
    http://arxiv.org/abs/2010.15602v1

    • [cs.CY]Detecting Individuals with Depressive Disorder fromPersonal Google Search and YouTube History Logs
    Boyu Zhang, Anis Zaman, Rupam Acharyya, Ehsan Hoque, Vincent Silenzio, Henry Kautz
    http://arxiv.org/abs/2010.15670v1

    • [cs.CY]Developing Augmented Reality based Gaming Model to Teach Ethical Education in Primary Schools
    Mohammad Ali
    http://arxiv.org/abs/2010.15346v1

    • [cs.CY]Import test questions into Moodle LMS
    Iryna S. Mintii, Svitlana V. Shokaliuk, Tetiana A. Vakaliuk, Mykhailo M. Mintii, Vladimir N. Soloviev
    http://arxiv.org/abs/2010.15577v1

    • [cs.CY]Machine Ethics and Automated Vehicles
    Noah J. Goodall
    http://arxiv.org/abs/2010.15665v1

    • [cs.CY]Machine Learning Based Demand Modelling for On-Demand Transit Services: A Case Study of Belleville, Ontario
    Nael Alsaleh, Bilal Farooq
    http://arxiv.org/abs/2010.15673v1

    • [cs.CY]PeopleXploit — A hybrid tool to collect public data
    Arjun Anand V, Buvanasri A K, Meenakshi R, Dr. Karthika S, Ashok Kumar Mohan
    http://arxiv.org/abs/2010.15668v1

    • [cs.CY]Using Twitter to Analyze Political Polarization During National Crises
    Parth Shisode
    http://arxiv.org/abs/2010.15669v1

    • [cs.CY]Using a Binary Classification Model to Predict the Likelihood of Enrolment to the Undergraduate Program of a Philippine University
    Dr. Joseph A. Esquivel, Dr. James A. Esquivel
    http://arxiv.org/abs/2010.15601v1

    • [cs.DC]Advanced Python Performance Monitoring with Score-P
    Andreas Gocht, Robert Schöne, Jan Frenzel
    http://arxiv.org/abs/2010.15444v1

    • [cs.DC]Benchmarking Parallelism in FaaS Platforms
    Daniel Barcelona-Pons, Pedro García-López
    http://arxiv.org/abs/2010.15032v2

    • [cs.DC]On Linearizability and the Termination of Randomized Algorithms
    Vassos Hadzilacos, Xing Hu, Sam Toueg
    http://arxiv.org/abs/2010.15210v1

    • [cs.DC]Prediction-Based Power Oversubscription in Cloud Platforms
    Alok Kumbhare, Reza Azimi, Ioannis Manousakis, Anand Bonde, Felipe Frujeri, Nithish Mahalingam, Pulkit Misra, Seyyed Ahmad Javadi, Bianca Schroeder, Marcus Fontoura, Ricardo Bianchini
    http://arxiv.org/abs/2010.15388v1

    • [cs.DC]Rosella: A Self-Driving Distributed Scheduler for Heterogeneous Clusters
    Qiong Wu, Sunil Manandhar, Zhenming Liu
    http://arxiv.org/abs/2010.15206v1

    • [cs.DC]Sizeless: Predicting the optimal size of serverless functions
    Simon Eismann, Long Bui, Johannes Grohmann, Cristina L. Abad, Nikolas Herbst, Samuel Kounev
    http://arxiv.org/abs/2010.15162v1

    • [cs.DC]StencilFlow: Mapping Large Stencil Programs to Distributed Spatial Computing Systems
    Johannes de Fine Licht, Andreas Kuster, Tiziano De Matteis, Tal Ben-Nun, Dominic Hofer, Torsten Hoefler
    http://arxiv.org/abs/2010.15218v1

    • [cs.DS]A Local Search Framework for Experimental Design
    Lap Chi Lau, Hong Zhou
    http://arxiv.org/abs/2010.15805v1

    • [cs.DS]A more Pragmatic Implementation of the Lock-free, Ordered, Linked List
    Jesper Larsson Träff, Manuel Pöter
    http://arxiv.org/abs/2010.15755v1

    • [cs.HC]Learning Personalized Discretionary Lane-Change Initiation for Fully Autonomous Driving Based on Reinforcement Learning
    Zhuoxi Liu, Zheng Wang, Bo Yang, Kimihiko Nakano
    http://arxiv.org/abs/2010.15372v1

    • [cs.HC]Speech-Based Emotion Recognition using Neural Networks and Information Visualization
    Jumana Almahmoud, Kruthika Kikkeri
    http://arxiv.org/abs/2010.15229v1

    • [cs.IR]CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation
    Yikun Xian, Zuohui Fu, Handong Zhao, Yingqiang Ge, Xu Chen, Qiaoying Huang, Shijie Geng, Zhou Qin, Gerard de Melo, S. Muthukrishnan, Yongfeng Zhang
    http://arxiv.org/abs/2010.15620v1

    • [cs.IR]Efficient Joinable Table Discovery in Data Lakes: A High-Dimensional Similarity-Based Approach
    Yuyang Dong, Kunihiro Takeoka, Chuan Xiao, Masafumi Oyamada
    http://arxiv.org/abs/2010.13273v2

    • [cs.IR]Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System
    Tianxin Wei, Fuli Feng, Jiawei Chen, Chufeng Shi, Ziwei Wu, Jinfeng Yi, Xiangnan He
    http://arxiv.org/abs/2010.15363v1

    • [cs.IT]Capacity-achieving codes: a review on double transitivity
    Kirill Ivanov, Rüdiger L. Urbanke
    http://arxiv.org/abs/2010.15453v1

    • [cs.IT]Channel Estimation and Equalization for CP-OFDM-based OTFS in Fractional Doppler Channels
    Noriyuki Hashimoto, Noboru Osawa, Kosuke Yamazaki, Shinsuke Ibi
    http://arxiv.org/abs/2010.15396v1

    • [cs.IT]Concatenated Codes for Recovery From Multiple Reads of DNA Sequences
    Andreas Lenz, Issam Maarouf, Lorenz Welter, Antonia Wachter-Zeh, Eirik Rosnes, Alexandre Graell i Amat
    http://arxiv.org/abs/2010.15461v1

    • [cs.IT]Constrained Online Learning to Mitigate Distortion Effects in Pulse-Agile Cognitive Radar
    Charles E. Thornton, R. Michael Buehrer, Anthony F. Martone
    http://arxiv.org/abs/2010.15698v1

    • [cs.IT]Learning Centric Wireless Resource Allocation for Edge Computing: Algorithm and Experiment
    Liangkai Zhou, Yuncong Hong, Shuai Wang, Ruihua Han, Dachuan Li, Rui Wang, Qi Hao
    http://arxiv.org/abs/2010.15371v1

    • [cs.IT]Reconfigurable Intelligent Surface Aided Secure Transmission: Outage-Constrained Energy-Efficiency Maximization
    Zongze Li, Shuai Wang, Miaowen Wen, Yik-Chung Wu
    http://arxiv.org/abs/2010.15354v1

    • [cs.IT]Semi-Grant-Free NOMA: Ergodic Rates Analysis with Random Deployed Users
    Chao Zhang, Yuanwei Liu, Wenqiang Yi, Zhijin Qin, Zhiguo Ding
    http://arxiv.org/abs/2010.15169v1

    • [cs.IT]Slicing a single wireless collision channel among throughput- and timeliness-sensitive services
    Israel Leyva-Mayorga, Federico Chiariotti, Čedomir Stefanović, Anders E. Kalør, Petar Popovski
    http://arxiv.org/abs/2010.15171v1

    • [cs.LG]A Novel Anomaly Detection Algorithm for Hybrid Production Systems based on Deep Learning and Timed Automata
    Nemanja Hranisavljevic, Oliver Niggemann, Alexander Maier
    http://arxiv.org/abs/2010.15415v1

    • [cs.LG]A Study on Efficiency in Continual Learning Inspired by Human Learning
    Philip J. Ball, Yingzhen Li, Angus Lamb, Cheng Zhang
    http://arxiv.org/abs/2010.15187v1

    • [cs.LG]Abstract Value Iteration for Hierarchical Reinforcement Learning
    Kishor Jothimurugan, Osbert Bastani, Rajeev Alur
    http://arxiv.org/abs/2010.15638v1

    • [cs.LG]Analyzing the tree-layer structure of Deep Forests
    Ludovic Arnould, Claire Boyer, Erwan Scornet
    http://arxiv.org/abs/2010.15690v1

    • [cs.LG]Autoregressive Asymmetric Linear Gaussian Hidden Markov Models
    Carlos Puerto-Santana, Pedro Larrañaga, Concha Bielza
    http://arxiv.org/abs/2010.15604v1

    • [cs.LG]Bandit Policies for Reliable Cellular Network Handovers in Extreme Mobility
    Yuanjie Li, Esha Datta, Jiaxin Ding, Ness Shroff, Xin Liu
    http://arxiv.org/abs/2010.15237v1

    • [cs.LG]Batch Reinforcement Learning with a Nonparametric Off-Policy Policy Gradient
    Samuele Tosatto, João Carvalho, Jan Peters
    http://arxiv.org/abs/2010.14771v2

    • [cs.LG]Causal variables from reinforcement learning using generalized Bellman equations
    Tue Herlau
    http://arxiv.org/abs/2010.15745v1

    • [cs.LG]Class-incremental learning: survey and performance evaluation
    Marc Masana, Xialei Liu, Bartlomiej Twardowski, Mikel Menta, Andrew D. Bagdanov, Joost van de Weijer
    http://arxiv.org/abs/2010.15277v1

    • [cs.LG]Do Wide and Deep Networks Learn the Same Things? Uncovering How Neural Network Representations Vary with Width and Depth
    Thao Nguyen, Maithra Raghu, Simon Kornblith
    http://arxiv.org/abs/2010.15327v1

    • [cs.LG]Emergence of Spatial Coordinates via Exploration
    Alban Laflaquière
    http://arxiv.org/abs/2010.15469v1

    • [cs.LG]Estimating Multiplicative Relations in Neural Networks
    Bhaavan Goel
    http://arxiv.org/abs/2010.15003v2

    • [cs.LG]FiGLearn: Filter and Graph Learning using Optimal Transport
    Matthias Minder, Zahra Farsijani, Dhruti Shah, Mireille El Gheche, Pascal Frossard
    http://arxiv.org/abs/2010.15457v1

    • [cs.LG]Financial ticket intelligent recognition system based on deep learning
    Fukang Tian, Haiyu Wu, Bo Xu
    http://arxiv.org/abs/2010.15356v1

    • [cs.LG]Forecasting Hamiltonian dynamics without canonical coordinates
    Anshul Choudhary, John F. Lindner, Elliott G. Holliday, Scott T. Miller, Sudeshna Sinha, William L. Ditto
    http://arxiv.org/abs/2010.15201v1

    • [cs.LG]GENs: Generative Encoding Networks
    Surojit Saha, Shireen Elhabian, Ross T. Whitaker
    http://arxiv.org/abs/2010.15283v1

    • [cs.LG]Gaussian Process Bandit Optimization of theThermodynamic Variational Objective
    Vu Nguyen, Vaden Masrani, Rob Brekelmans, Michael A. Osborne, Frank Wood
    http://arxiv.org/abs/2010.15750v1

    • [cs.LG]How do Offline Measures for Exploration in Reinforcement Learning behave?
    Jakob J. Hollenstein, Sayantan Auddy, Matteo Saveriano, Erwan Renaudo, Justus Piater
    http://arxiv.org/abs/2010.15533v1

    • [cs.LG]LSTM for Model-Based Anomaly Detection in Cyber-Physical Systems
    Benedikt Eiteneuer, Oliver Niggemann
    http://arxiv.org/abs/2010.15680v1

    • [cs.LG]Learning to Actively Learn: A Robust Approach
    Jifan Zhang, Kevin Jamieson
    http://arxiv.org/abs/2010.15382v1

    • [cs.LG]Linear Regression Games: Convergence Guarantees to Approximate Out-of-Distribution Solutions
    Kartik Ahuja, Karthikeyan Shanmugam, Amit Dhurandhar
    http://arxiv.org/abs/2010.15234v1

    • [cs.LG]Measuring and Harnessing Transference in Multi-Task Learning
    Christopher Fifty, Ehsan Amid, Zhe Zhao, Tianhe Yu, Rohan Anil, Chelsea Finn
    http://arxiv.org/abs/2010.15413v1

    • [cs.LG]Memory Optimization for Deep Networks
    Aashaka Shah, Chao-Yuan Wu, Jayashree Mohan, Vijay Chidambaram, Philipp Krähenbühl
    http://arxiv.org/abs/2010.14501v2

    • [cs.LG]Multilayer Clustered Graph Learning
    Mireille El Gheche, Pascal Frossard
    http://arxiv.org/abs/2010.15456v1

    • [cs.LG]Multitask Bandit Learning through Heterogeneous Feedback Aggregation
    Zhi Wang, Chicheng Zhang, Manish Kumar Singh, Laurel D. Riek, Kamalika Chaudhuri
    http://arxiv.org/abs/2010.15390v1

    • [cs.LG]Off-Policy Interval Estimation with Lipschitz Value Iteration
    Ziyang Tang, Yihao Feng, Na Zhang, Jian Peng, Qiang Liu
    http://arxiv.org/abs/2010.15392v1

    • [cs.LG]Reinforcement Learning for Sparse-Reward Object-Interaction Tasks in First-person Simulated 3D Environments
    Wilka Carvalho, Anthony Liang, Kimin Lee, Sungryull Sohn, Honglak Lee, Richard L. Lewis, Satinder Singh
    http://arxiv.org/abs/2010.15195v1

    • [cs.LG]Reliable Graph Neural Networks via Robust Aggregation
    Simon Geisler, Daniel Zügner, Stephan Günnemann
    http://arxiv.org/abs/2010.15651v1

    • [cs.LG]Representation learning for improved interpretability and classification accuracy of clinical factors from EEG
    Garrett Honke, Irina Higgins, Nina Thigpen, Vladimir Miskovic, Katie Link, Pramod Gupta, Julia Klawohn, Greg Hajcak
    http://arxiv.org/abs/2010.15274v1

    • [cs.LG]Robustifying Binary Classification to Adversarial Perturbation
    Fariborz Salehi, Babak Hassibi
    http://arxiv.org/abs/2010.15391v1

    • [cs.LG]Scalable Graph Neural Networks via Bidirectional Propagation
    Ming Chen, Zhewei Wei, Bolin Ding, Yaliang Li, Ye Yuan, Xiaoyong Du, Ji-Rong Wen
    http://arxiv.org/abs/2010.15421v1

    • [cs.LG]Self-awareness in intelligent vehicles: Feature based dynamic Bayesian models for abnormality detection
    Divya Thekke Kanapram, Pablo Marin-Plaza, Lucio Marcenaro, David Martin, Arturo de la Escalera, Carlo Regazzoni
    http://arxiv.org/abs/2010.15441v1

    • [cs.LG]Self-paced Data Augmentation for Training Neural Networks
    Tomoumi Takase, Ryo Karakida, Hideki Asoh
    http://arxiv.org/abs/2010.15434v1

    • [cs.LG]Semi-Supervised Speech Recognition via Graph-based Temporal Classification
    Niko Moritz, Takaaki Hori, Jonathan Le Roux
    http://arxiv.org/abs/2010.15653v1

    • [cs.LG]Speech-Image Semantic Alignment Does Not Depend on Any Prior Classification Tasks
    Masood S. Mortazavi
    http://arxiv.org/abs/2010.15288v1

    • [cs.LG]Supervised sequential pattern mining of event sequences in sport to identify important patterns of play: an application to rugby union
    Rory Bunker, Keisuke Fujii, Hiroyuki Hanada, Ichiro Takeuchi
    http://arxiv.org/abs/2010.15377v1

    • [cs.LG]Test Set Optimization by Machine Learning Algorithms
    Kaiming Fu, Yulu Jin, Zhousheng Chen
    http://arxiv.org/abs/2010.15240v1

    • [cs.LG]Understanding the Failure Modes of Out-of-Distribution Generalization
    Vaishnavh Nagarajan, Anders Andreassen, Behnam Neyshabur
    http://arxiv.org/abs/2010.15775v1

    • [cs.LG]Understanding the Pathologies of Approximate Policy Evaluation when Combined with Greedification in Reinforcement Learning
    Kenny Young, Richard S. Sutton
    http://arxiv.org/abs/2010.15268v1

    • [cs.MS]Generalized eigen, singular value, and partial least squares decompositions: The GSVD package
    Derek Beaton
    http://arxiv.org/abs/2010.14734v2

    • [cs.NE]A brief overview of swarm intelligence-based algorithms for numerical association rule mining
    Iztok Fister Jr., Iztok Fister
    http://arxiv.org/abs/2010.15524v1

    • [cs.NE]Measuring non-trivial compositionality in emergent communication
    Tomasz Korbak, Julian Zubek, Joanna Rączaszek-Leonardi
    http://arxiv.org/abs/2010.15058v2

    • [cs.NE]Overcoming The Limitations of Neural Networks in Composite-Pattern Learning with Architopes
    Anastasis Kratsios, Behnoosh Zamanlooy
    http://arxiv.org/abs/2010.15571v1

    • [cs.PF]Poster: Benchmarking Financial Data Feed Systems
    Manuel Coenen, Christoph Wagner, Alexander Echler, Sebastian Frischbier
    http://arxiv.org/abs/2010.15534v1

    • [cs.RO]“What, not how” — Solving an under-actuated insertion task from scratch
    Giulia Vezzani, Michael Neunert, Markus Wulfmeier, Rae Jeong, Thomas Lampe, Noah Siegel, Roland Hafner, Abbas Abdolmaleki, Martin Riedmiller, Francesco Nori
    http://arxiv.org/abs/2010.15492v1

    • [cs.RO]A Framework for Learning Predator-prey Agents from Simulation to Real World
    Jiunhan Chen, Zhenyu Gao
    http://arxiv.org/abs/2010.15792v1

    • [cs.RO]A Hybrid Position/Force Controller for Joint Robots
    Shengwen Xie, Juan Ren
    http://arxiv.org/abs/2010.15350v1

    • [cs.RO]Affordance-Aware Handovers with Human Arm Mobility Constraints
    Paola Ardón, Maria E. Cabrera, Èric Pairet, Ronald P. A. Petrick, Subramanian Ramamoorthy, Katrin S. Lohan, Maya Cakmak
    http://arxiv.org/abs/2010.15436v1

    • [cs.RO]Dynamic Formation Reshaping Based on Point Set Registration in a Swarm of Drones
    Jawad N. Yasin, Sherif A. S. Mohamed, Mohammad-Hashem Haghbayan, Jukka Heikkonen, Hannu Tenhunen, Muhammad Mehboob Yasin, Juha Plosila
    http://arxiv.org/abs/2010.15506v1

    • [cs.RO]Gaussian Processes Model-based Control of Underactuated Balance Robots
    Kuo Chen, Jingang Yi, Dezhen Song
    http://arxiv.org/abs/2010.15320v1

    • [cs.RO]Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions
    Constantinos Chamzas, Zachary Kingston, Carlos Quintero-Peña, Anshumali Shrivastava, Lydia E. Kavraki
    http://arxiv.org/abs/2010.15335v1

    • [cs.RO]Online State-Time Trajectory Planning Using Timed-ESDF in Highly Dynamic Environments
    Delong Zhu, Tong Zhou, Jiahui Lin, Yuqi Fang, Max Q. -H. Meng
    http://arxiv.org/abs/2010.15364v1

    • [cs.RO]Optimization Fabrics for Behavioral Design
    Nathan D. Ratliff, Karl Van Wyk, Mandy Xie, Anqi Li, Asif Muhammad Rana
    http://arxiv.org/abs/2010.15676v1

    • [cs.SD]DNSMOS: A Non-Intrusive Perceptual Objective Speech Quality metric to evaluate Noise Suppressors
    Chandan K A Reddy, Vishak Gopal, Ross Cutler
    http://arxiv.org/abs/2010.15258v1

    • [cs.SD]GANs & Reels: Creating Irish Music using a Generative Adversarial Network
    Antonina Kolokolova, Mitchell Billard, Robert Bishop, Moustafa Elsisy, Zachary Northcott, Laura Graves, Vineel Nagisetty, Heather Patey
    http://arxiv.org/abs/2010.15772v1

    • [cs.SD]Improving Perceptual Quality by Phone-Fortified Perceptual Loss for Speech Enhancement
    Tsun-An Hsieh, Cheng Yu, Szu-Wei Fu, Xugang Lu, Yu Tsao
    http://arxiv.org/abs/2010.15174v1

    • [cs.SD]Raw Audio for Depression Detection Can Be More Robust Against Gender Imbalance than Mel-Spectrogram Features
    Andrew Bailey, Mark D. Plumbley
    http://arxiv.org/abs/2010.15120v1

    • [cs.SD]Self-supervised Pre-training Reduces Label Permutation Instability of Speech Separation
    Sung-Feng Huang, Shun-Po Chuang, Da-Rong Liu, Yi-Chen Chen, Gene-Ping Yang, Hung-yi Lee
    http://arxiv.org/abs/2010.15366v1

    • [cs.SI]Analyzing Societal Impact of COVID-19: A Study During the Early Days of the Pandemic
    Swaroop Gowdra Shanthakumar, Anand Seetharam, Arti Ramesh
    http://arxiv.org/abs/2010.15674v1

    • [cs.SI]Discovery and classification of Twitter bots
    Alexander Shevtsov Alexander Shevtsov, Maria Oikonomidou, Despoina Antonakaki, Polyvios Pratikakis, Alexandros Kanterakis, Sotiris Ioannidis, Paraskevi Fragopoulou
    http://arxiv.org/abs/2010.15393v1

    • [cs.SI]Down the bot hole: actionable insights from a 1-year analysis of bots activity on Twitter
    Luca Luceri, Felipe Cardoso, Silvia Giordano
    http://arxiv.org/abs/2010.15820v1

    • [cs.SI]Exploring complex networks with the ICON R package
    Raoul R. Wadhwa, Jacob G. Scott
    http://arxiv.org/abs/2010.15222v1

    • [cs.SI]Micromobility in Smart Cities: A Closer Look at Shared Dockless E-Scooters via Big Social Data
    Yunhe Feng, Dong Zhong, Peng Sun, Weijian Zheng, Qinglei Cao, Xi Luo, Zheng Lu
    http://arxiv.org/abs/2010.15203v1

    • [econ.GN]Preventing COVID-19 Fatalities: State versus Federal Policies
    Jean-Paul Renne, Guillaume Roussellet, Gustavo Schwenkler
    http://arxiv.org/abs/2010.15263v1

    • [eess.AS]Progressive Voice Trigger Detection: Accuracy vs Latency
    Siddharth Sigtia, John Bridle, Hywel Richards, Pascal Clark, Erik Marchi, Vineet Garg
    http://arxiv.org/abs/2010.15446v1

    • [eess.IV]A Novel Fast 3D Single Image Super-Resolution Algorithm
    Nwigbo Kenule Tuador, Duong Hung Pham, Jérôme Michetti, Adrian Basarab, Denis Kouamé
    http://arxiv.org/abs/2010.15491v1

    • [eess.IV]A comparison of automatic multi-tissue segmentation methods of the human fetal brain using the FeTA Dataset
    Kelly Payette, Priscille de Dumast, Hamza Kebiri, Ivan Ezhov, Johannes C. Paetzold, Suprosanna Shit, Asim Iqbal, Romesa Khan, Raimund Kottke, Patrice Grehten, Hui Ji, Levente Lanczi, Marianna Nagy, Monika Beresova, Thi Dao Nguyen, Giancarlo Natalucci, Theofanis Karayannis, Bjoern Menze, Meritxell Bach Cuadra, Andras Jakab
    http://arxiv.org/abs/2010.15526v1

    • [eess.IV]Accurate Prostate Cancer Detection and Segmentation on Biparametric MRI using Non-local Mask R-CNN with Histopathological Ground Truth
    Zhenzhen Dai, Ivan Jambor, Pekka Taimen, Milan Pantelic, Mohamed Elshaikh, Craig Rogers, Otto Ettala, Peter Boström, Hannu Aronen, Harri Merisaari, Ning Wen
    http://arxiv.org/abs/2010.15233v1

    • [eess.IV]An automated and multi-parametric algorithm for objective analysis of meibography images
    Peng Xiao, Zhongzhou Luo, Yuqing Deng, Gengyuan Wang, Jin Yuan
    http://arxiv.org/abs/2010.15352v1

    • [eess.IV]Brain Tumor Segmentation Network Using Attention-based Fusion and Spatial Relationship Constraint
    Chenyu Liu, Wangbin Ding, Lei Li, Zhen Zhang, Chenhao Pei, Liqin Huang, Xiahai Zhuang
    http://arxiv.org/abs/2010.15647v1

    • [eess.IV]Deep Autofocus for Synthetic Aperture Sonar
    Isaac Gerg, Vishal Monga
    http://arxiv.org/abs/2010.15687v1

    • [eess.IV]FlatNet: Towards Photorealistic Scene Reconstruction from Lensless Measurements
    Salman S. Khan, Varun Sundar, Vivek Boominathan, Ashok Veeraraghavan, Kaushik Mitra
    http://arxiv.org/abs/2010.15440v1

    • [eess.IV]Genetic U-Net: Automatically Designing Lightweight U-shaped CNN Architectures Using the Genetic Algorithm for Retinal Vessel Segmentation
    Jiahong Wei, Zhun Fan
    http://arxiv.org/abs/2010.15560v1

    • [eess.IV]GloFlow: Global Image Alignment for Creation of Whole Slide Images for Pathology from Video
    Viswesh Krishna, Anirudh Joshi, Philip L. Bulterys, Eric Yang, Andrew Y. Ng, Pranav Rajpurkar
    http://arxiv.org/abs/2010.15269v1

    • [eess.IV]Ground Roll Suppression using Convolutional Neural Networks
    Dario Augusto Borges Oliveira, Daniil Semin, Semen Zaytsev
    http://arxiv.org/abs/2010.15209v1

    • [eess.IV]Maximum a posteriori signal recovery for optical coherence tomography angiography image generation and denoising
    Lennart Husvogt, Stefan B. Ploner, Siyu Chen, Daniel Stromer, Julia Schottenhamml, A. Yasin Alibhai, Eric Moult, Nadia K. Waheed, James G. Fujimoto, Andreas Maier
    http://arxiv.org/abs/2010.15682v1

    • [eess.IV]ProCAN: Progressive Growing Channel Attentive Non-Local Network for Lung Nodule Classification
    Mundher Al-Shabi, Kelvin Shak, Maxine Tan
    http://arxiv.org/abs/2010.15417v1

    • [eess.SP]Distance Invariant Sparse Autoencoder for Wireless Signal Strength Mapping
    Renato Miyagusuku, Koichi Ozaki
    http://arxiv.org/abs/2010.15347v1

    • [eess.SP]FD Cell-Free mMIMO: Analysis and Optimization
    Soumyadeep Datta, Ekant Sharma, Dheeraj Naidu Amudala, Rohit Budhiraja, Shivendra S. Panwar
    http://arxiv.org/abs/2010.15672v1

    • [eess.SP]Identification of complex mixtures for Raman spectroscopy using a novel scheme based on a new multi-label deep neural network
    Liangrui Pan, Pronthep Pipitsunthonsan, Chalongrat Daengngam, Mitchai Chongcheawchamnan
    http://arxiv.org/abs/2010.15654v1

    • [eess.SP]Sampling and Reconstruction of Sparse Signals in Shift-Invariant Spaces: Generalized Shannon’s Theorem Meets Compressive Sensing
    Tin Vlašić, Damir Seršić
    http://arxiv.org/abs/2010.15618v1

    • [eess.SP]Solving Sparse Linear Inverse Problems in Communication Systems: A Deep Learning Approach With Adaptive Depth
    Wei Chen, Bowen Zhang, Shi Jin, Bo Ai, Zhangdui Zhong
    http://arxiv.org/abs/2010.15376v1

    • [eess.SY]Cloud-Based Dynamic Programming for an Electric City Bus Energy Management Considering Real-Time Passenger Load Prediction
    Junzhe Shi, Bin Xu, Xingyu Zhou, Jun Hou
    http://arxiv.org/abs/2010.15239v1

    • [eess.SY]Continuous Chaotic Nonlinear System and Lyapunov controller Optimization using Deep Learning
    Amr Mahmoud, Youmna Ismaeil, Mohamed Zohdy
    http://arxiv.org/abs/2010.14746v1

    • [eess.SY]Probabilistic interval predictor based on dissimilarity functions
    A. Daniel Carnerero, Daniel R. Ramirez, Teodoro Alamo
    http://arxiv.org/abs/2010.15530v1

    • [math.DG]Geometric Sampling of Networks
    Vladislav Barkanass, Jürgen Jost, Emil Saucan
    http://arxiv.org/abs/2010.15221v1

    • [math.NA]Identifying Transition States of Chemical Kinetic Systems using Network Embedding Techniques
    Paula Mercurio, Di Liu
    http://arxiv.org/abs/2010.15760v1

    • [math.OC]A Single-Loop Smoothed Gradient Descent-Ascent Algorithm for Nonconvex-Concave Min-Max Problems
    Jiawei Zhang, Peijun Xiao, Ruoyu Sun, Zhi-Quan Luo
    http://arxiv.org/abs/2010.15768v1

    • [math.OC]Sparse Signal Reconstruction for Nonlinear Models via Piecewise Rational Optimization
    Arthur Marmin, Marc Castella, Jean-Christophe Pesquet, Laurent Duval
    http://arxiv.org/abs/2010.15427v1

    • [math.PR]Rates of convergence for Gibbs sampling in the analysis of almost exchangeable data
    Balázs Gerencsér, Andrea Ottolini
    http://arxiv.org/abs/2010.15539v1

    • [math.ST]Generalization bounds for deep thresholding networks
    Arash Behboodi, Holger Rauhut, Ekkehard Schnoor
    http://arxiv.org/abs/2010.15658v1

    • [math.ST]Nonparametric estimation of copulas and copula densities by orthogonal projections
    Yves I. Ngounou Bakam, Denys Pommeret
    http://arxiv.org/abs/2010.15351v1

    • [math.ST]Post-selection inference with HSIC-Lasso
    Tobias Freidling, Benjamin Poignard, Héctor Climente-González, Makoto Yamada
    http://arxiv.org/abs/2010.15659v1

    • [math.ST]Staged trees are curved exponential families
    Christiane Görgen, Manuele Leonelli, Orlando Marigliano
    http://arxiv.org/abs/2010.15515v1

    • [nlin.AO]Link inference of noisy delay-coupled networks: Machine learning and opto-electronic experimental tests
    Amitava Banerjee, Joseph D. Hart, Rajarshi Roy, Edward Ott
    http://arxiv.org/abs/2010.15289v1

    • [physics.comp-ph]A Helmholtz equation solver using unsupervised learning: Application to transcranial ultrasound
    Antonio Stanziola, Simon R. Arridge, Ben T. Cox, Bradley E. Treeby
    http://arxiv.org/abs/2010.15761v1

    • [physics.comp-ph]Diagnostic data integration using deep neural networks for real-time plasma analysis
    A. Rigoni Garola, R. Cavazzana, M. Gobbin, R. S. Delogu, G. Manduchi, C. Taliercio, A. Luchetta
    http://arxiv.org/abs/2010.15156v1

    • [q-bio.NC]The distribution of inhibitory neurons in the C. elegans connectome facilitates self-optimization of coordinated neural activity
    Alejandro Morales, Tom Froese
    http://arxiv.org/abs/2010.15272v1

    • [q-bio.PE]The fundamental equations of change in statistical ensembles and biological populations
    Steven A. Frank, Frank J. Bruggeman
    http://arxiv.org/abs/2010.14544v1

    • [quant-ph]Fundamental limitations to key distillation from Gaussian states with Gaussian operations
    Ludovico Lami, Ladislav Mišta, Jr., Gerardo Adesso
    http://arxiv.org/abs/2010.15729v1

    • [stat.AP]A statistical model to assess risk for supporting SARS-CoV-2 quarantine decisions
    Volker Dicken, Benjamin Geisler, Sonja Jäckle, Elias Röger, Jakob Schumacher, Max Westphal
    http://arxiv.org/abs/2010.15677v1

    • [stat.AP]COVID-19 incidences and its association with environmental quality: A country-level assessment in India
    Arabinda Maiti, Suman Chakraborti, Suvamoy Pramanik, Srikanta Sannigrahi
    http://arxiv.org/abs/2010.15777v1

    • [stat.AP]Space-Time Covid-19 Bayesian SIR modeling in South Carolina
    Andrew B. Lawson, Joanne Kim
    http://arxiv.org/abs/2010.15207v1

    • [stat.AP]Spatiotemporal effects of the causal factors on COVID-19 incidences in the contiguous United States
    Arabinda Maiti, Qi Zhang, Srikanta Sannigrahi, Suvamoy Pramanik, Suman Chakraborti, Francesco Pilla
    http://arxiv.org/abs/2010.15754v1

    • [stat.ME]An Exact Solution Path Algorithm for SLOPE and Quasi-Spherical OSCAR
    Shunichi Nomura
    http://arxiv.org/abs/2010.15511v1

    • [stat.ME]CONQ: CONtinuous Quantile Treatment Effects for Large-Scale Online Controlled Experiments
    Weinan Wang, Xi Zhang
    http://arxiv.org/abs/2010.15326v1

    • [stat.ME]Classification Accuracy and Parameter Estimation in Multilevel Contexts: A Study of Conditional Nonparametric Multilevel Latent Class Analysis
    Chi Chang, Kimberly Kelly, M. Lee Van Horn, Richard T. Houang, Joseph Gardiner, Laurie Van Egeren, Heng-Chieh Wu
    http://arxiv.org/abs/2010.15368v1

    • [stat.ME]Group-regularized ridge regression via empirical Bayes noise level cross-validation
    Nikolaos Ignatiadis, Panagiotis Lolas
    http://arxiv.org/abs/2010.15817v1

    • [stat.ME]Intrinsic Sliced Wasserstein Distances for Comparing Collections of Probability Distributions on Manifolds and Graphs
    Raif M. Rustamov, Subhabrata Majumdar
    http://arxiv.org/abs/2010.15285v1

    • [stat.ME]Learning Bayesian Networks from Ordinal Data
    Xiang Ge Luo, Giusi Moffa, Jack Kuipers
    http://arxiv.org/abs/2010.15808v1

    • [stat.ME]Modelling and simulation of dependence structures in nonlife insurance with Bernstein copulas
    Dietmar Pfeifer, Doreen Strassburger, Joerg Philipps
    http://arxiv.org/abs/2010.15709v1

    • [stat.ML]Attentive Clustering Processes
    Ari Pakman, Yueqi Wang, Yoonho Lee, Pallab Basu, Juho Lee, Yee Whye Teh, Liam Paninski
    http://arxiv.org/abs/2010.15727v1

    • [stat.ML]Domain adaptation under structural causal models
    Yuansi Chen, Peter Bühlmann
    http://arxiv.org/abs/2010.15764v1

    • [stat.ML]Independence Tests Without Ground Truth for Noisy Learners
    Andrés Corrada-Emmanuel, Edward Pantridge, Eddie Zahrebelski, Aditya Chaganti, Simeon Simeonov
    http://arxiv.org/abs/2010.15662v1

    • [stat.ML]Learning interaction kernels in mean-field equations of 1st-order systems of interacting particles
    Quanjun Lang, Fei Lu
    http://arxiv.org/abs/2010.15694v1

    • [stat.ML]Low-Variance Policy Gradient Estimation with World Models
    Michal Nauman, Floris Den Hengst
    http://arxiv.org/abs/2010.15622v1

    • [stat.ML]Matern Gaussian Processes on Graphs
    Viacheslav Borovitskiy, Iskander Azangulov, Alexander Terenin, Peter Mostowsky, Marc Peter Deisenroth, Nicolas Durrande
    http://arxiv.org/abs/2010.15538v1

    • [stat.ML]On the robustness of kernel-based pairwise learning
    Patrick Gensler, Andreas Christmann
    http://arxiv.org/abs/2010.15527v1

    • [stat.ML]Teaching a GAN What Not to Learn
    Siddarth Asokan, Chandra Sekhar Seelamantula
    http://arxiv.org/abs/2010.15639v1

    • [stat.ML]Tensor Completion via Tensor Networks with a Tucker Wrapper
    Yunfeng Cai, Ping Li
    http://arxiv.org/abs/2010.15819v1

    • [stat.ML]The Performance Analysis of Generalized Margin Maximizer (GMM) on Separable Data
    Fariborz Salehi, Ehsan Abbasi, Babak Hassibi
    http://arxiv.org/abs/2010.15379v1