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