astro-ph.IM - 仪器仪表和天体物理学方法
cond-mat.dis-nn - 无序系统与神经网络 cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.ET - 新兴技术 cs.GR - 计算机图形学 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 hep-ex - 高能物理实验 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.ao-ph - 大气和海洋物理 physics.comp-ph - 计算物理学 physics.med-ph - 医学物理学 physics.soc-ph - 物理学与社会 q-bio.GN - 基因组学 q-fin.RM - 风险管理 q-fin.ST - 统计金融学 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [astro-ph.IM]Machine Learning Pipeline for Pulsar Star Dataset
• [cond-mat.dis-nn]Teaching Recurrent Neural Networks to Modify Chaotic Memories by Example
• [cs.AI]A Multialternative Neural Decision Process
• [cs.AI]Bayesian Entailment Hypothesis: How Brains Implement Monotonic and Non-monotonic Reasoning
• [cs.AI]Computing With Words for Student Strategy Evaluation in an Examination
• [cs.AI]Construction and Elicitation of a Black Box Model in the Game of Bridge
• [cs.AI]Enhancing Text-based Reinforcement Learning Agents with Commonsense Knowledge
• [cs.AI]Navigating the Landscape of Games
• [cs.AI]SEEK: Segmented Embedding of Knowledge Graphs
• [cs.AI]The ILASP system for Inductive Learning of Answer Set Programs
• [cs.CL]A Benchmark for Structured Procedural Knowledge Extraction from Cooking Videos
• [cs.CL]A Girl Has A Name: Detecting Authorship Obfuscation
• [cs.CL]A New Data Normalization Method to Improve Dialogue Generation by Minimizing Long Tail Effect
• [cs.CL]A Position Aware Decay Weighted Network for Aspect based Sentiment Analysis
• [cs.CL]A Simple Language Model for Task-Oriented Dialogue
• [cs.CL]A Tale of a Probe and a Parser
• [cs.CL]A Two-Stage Masked LM Method for Term Set Expansion
• [cs.CL]A language score based output selection method for multilingual speech recognition
• [cs.CL]AVA: an Automatic eValuation Approach to Question Answering Systems
• [cs.CL]An Accurate Model for Predicting the (Graded) Effect of Context in Word Similarity Based on Bert
• [cs.CL]An Imitation Game for Learning Semantic Parsers from User Interaction
• [cs.CL]Are Emojis Emotional? A Study to Understand the Association between Emojis and Emotions
• [cs.CL]BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QA
• [cs.CL]Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-trained Language Models
• [cs.CL]Bootstrapping Techniques for Polysynthetic Morphological Analysis
• [cs.CL]Can BERT Reason? Logically Equivalent Probes for Evaluating the Inference Capabilities of Language Models
• [cs.CL]Clue: Cross-modal Coherence Modeling for Caption Generation
• [cs.CL]Code and Named Entity Recognition in StackOverflow
• [cs.CL]Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation
• [cs.CL]Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering
• [cs.CL]Correcting the Autocorrect: Context-Aware Typographical Error Correction via Training Data Augmentation
• [cs.CL]DQI: Measuring Data Quality in NLP
• [cs.CL]DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering
• [cs.CL]Design Challenges for Low-resource Cross-lingual Entity Linking
• [cs.CL]Distributional Discrepancy: A Metric for Unconditional Text Generation
• [cs.CL]DoQA — Accessing Domain-Specific FAQs via Conversational QA
• [cs.CL]Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation
• [cs.CL]ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation
• [cs.CL]ESPRIT: Explaining Solutions to Physical Reasoning Tasks
• [cs.CL]Efficient Second-Order TreeCRF for Neural Dependency Parsing
• [cs.CL]Emergence of Syntax Needs Minimal Supervision
• [cs.CL]Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction
• [cs.CL]Evaluating Explanation Methods for Neural Machine Translation
• [cs.CL]Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen
• [cs.CL]Exploring and Predicting Transferability across NLP Tasks
• [cs.CL]Fast and Robust Unsupervised Contextual Biasing for Speech Recognition
• [cs.CL]From Arguments to Key Points: Towards Automatic Argument Summarization
• [cs.CL]From SPMRL to NMRL: What Did We Learn (and Unlearn) in a Decade of Parsing Morphologically-Rich Languages (MRLs)?
• [cs.CL]Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer
• [cs.CL]Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing
• [cs.CL]GenericsKB: A Knowledge Base of Generic Statements
• [cs.CL]Hard-Coded Gaussian Attention for Neural Machine Translation
• [cs.CL]How Can We Accelerate Progress Towards Human-like Linguistic Generalization?
• [cs.CL]How Does Selective Mechanism Improve Self-Attention Networks?
• [cs.CL]Improving Adversarial Text Generation by Modeling the Distant Future
• [cs.CL]Improving Non-autoregressive Neural Machine Translation with Monolingual Data
• [cs.CL]Improving Truthfulness of Headline Generation
• [cs.CL]Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models
• [cs.CL]Introducing the VoicePrivacy Initiative
• [cs.CL]KinGDOM: Knowledge-Guided DOMain adaptation for sentiment analysis
• [cs.CL]Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward
• [cs.CL]Language Models as an Alternative Evaluator of Word Order Hypotheses: A Case Study in Japanese
• [cs.CL]Let Me Choose: From Verbal Context to Font Selection
• [cs.CL]Measuring and Reducing Non-Multifact Reasoning in Multi-hop Question Answering
• [cs.CL]MultiQT: Multimodal Learning for Real-Time Question Tracking in Speech
• [cs.CL]NLP in FinTech Applications: Past, Present and Future
• [cs.CL]Neural Data-to-Text Generation via Jointly Learning the Segmentation and Correspondence
• [cs.CL]Noise Pollution in Hospital Readmission Prediction: Long Document Classification with Reinforcement Learning
• [cs.CL]Obtaining Faithful Interpretations from Compositional Neural Networks
• [cs.CL]On the Inference Calibration of Neural Machine Translation
• [cs.CL]On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation
• [cs.CL]On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs
• [cs.CL]Out of the Echo Chamber: Detecting Countering Debate Speeches
• [cs.CL]Predicting Performance for Natural Language Processing Tasks
• [cs.CL]Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance?
• [cs.CL]ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning
• [cs.CL]RMM: A Recursive Mental Model for Dialog Navigation
• [cs.CL]Rationalizing Medical Relation Prediction from Corpus-level Statistics
• [cs.CL]Reward Constrained Interactive Recommendation with Natural Language Feedback
• [cs.CL]Robust Encodings: A Framework for Combating Adversarial Typos
• [cs.CL]Robust and Interpretable Grounding of Spatial References with Relation Networks
• [cs.CL]Similarity Analysis of Contextual Word Representation Models
• [cs.CL]Single Model Ensemble using Pseudo-Tags and Distinct Vectors
• [cs.CL]Social Biases in NLP Models as Barriers for Persons with Disabilities
• [cs.CL]Sources of Transfer in Multilingual Named Entity Recognition
• [cs.CL]Synthesizer: Rethinking Self-Attention in Transformer Models
• [cs.CL]Tailoring and Evaluating the Wikipedia for in-Domain Comparable Corpora Extraction
• [cs.CL]Teaching Machine Comprehension with Compositional Explanations
• [cs.CL]The Paradigm Discovery Problem
• [cs.CL]The Sensitivity of Language Models and Humans to Winograd Schema Perturbations
• [cs.CL]To Test Machine Comprehension, Start by Defining Comprehension
• [cs.CL]Towards A Sign Language Gloss Representation Of Modern Standard Arabic
• [cs.CL]Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints
• [cs.CL]Transformer-based End-to-End Question Generation
• [cs.CL]Treebank Embedding Vectors for Out-of-domain Dependency Parsing
• [cs.CL]UnifiedQA: Crossing Format Boundaries With a Single QA System
• [cs.CL]Unsupervised Alignment-based Iterative Evidence Retrieval for Multi-hop Question Answering
• [cs.CL]Unsupervised Morphological Paradigm Completion
• [cs.CL]Using Context in Neural Machine Translation Training Objectives
• [cs.CL]Visually Grounded Continual Learning of Compositional Semantics
• [cs.CL]What is Learned in Visually Grounded Neural Syntax Acquisition
• [cs.CL]What-if I ask you to explain: Explaining the effects of perturbations in procedural text
• [cs.CL]WikiUMLS: Aligning UMLS to Wikipedia via Cross-lingual Neural Ranking
• [cs.CL]Words aren’t enough, their order matters: On the Robustness of Grounding Visual Referring Expressions
• [cs.CL]Zero-Shot Transfer Learning with Synthesized Data for Multi-Domain Dialogue State Tracking
• [cs.CL]pyBART: Evidence-based Syntactic Transformations for IE
• [cs.CR]Customizable and Rigorous Location Privacy through Policy Graph
• [cs.CR]Enhancing network forensics with particle swarm and deep learning: The particle deep framework
• [cs.CV]AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results
• [cs.CV]Anchors based method for fingertips position from a monocular RGB image using Deep Neural Network
• [cs.CV]Automated eye disease classification method from anterior eye image using anatomical structure focused image classification technique
• [cs.CV]BeCAPTCHA-Mouse: Synthetic Mouse Trajectories and Improved Bot Detection
• [cs.CV]CARRADA Dataset: Camera and Automotive Radar with Range-Angle-Doppler Annotations
• [cs.CV]CoMoGCN: Coherent Motion Aware Trajectory Prediction with Graph Representation
• [cs.CV]Correlating Edge, Pose with Parsing
• [cs.CV]Cross-View Image Retrieval — Ground to Aerial Image Retrieval through Deep Learning
• [cs.CV]Deep Encoder-Decoder Neural Network for Fingerprint Image Denoising and Inpainting
• [cs.CV]Derivation of a Constant Velocity Motion Model for Visual Tracking
• [cs.CV]DroTrack: High-speed Drone-based Object Tracking Under Uncertainty
• [cs.CV]Ego-motion and Surrounding Vehicle State Estimation Using a Monocular Camera
• [cs.CV]Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences
• [cs.CV]Group Equivariant Generative Adversarial Networks
• [cs.CV]Heterogeneous Knowledge Distillation using Information Flow Modeling
• [cs.CV]How to Train Your Dragon: Tamed Warping Network for Semantic Video Segmentation
• [cs.CV]How to Train Your Energy-Based Model for Regression
• [cs.CV]Joint-SRVDNet: Joint Super Resolution and Vehicle Detection Network
• [cs.CV]Minor Privacy Protection Through Real-time Video Processing at the Edge
• [cs.CV]Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques
• [cs.CV]MorphoCluster: Efficient Annotation of Plankton images by Clustering
• [cs.CV]Multi-Modality Generative Adversarial Networks with Tumor Consistency Loss for Brain MR Image Synthesis
• [cs.CV]Multi-focus Image Fusion: A Benchmark
• [cs.CV]NTIRE 2020 Challenge on Image and Video Deblurring
• [cs.CV]On the Benefits of Models with Perceptually-Aligned Gradients
• [cs.CV]One-Shot Image Classification by Learning to Restore Prototypes
• [cs.CV]PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data
• [cs.CV]Projection Inpainting Using Partial Convolution for Metal Artifact Reduction
• [cs.CV]Quadtree Driven Lossy Event Compression
• [cs.CV]Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities
• [cs.CV]SAMP: Shape and Motion Priors for 4D Vehicle Reconstruction
• [cs.CV]Tensor optimal transport, distance between sets of measures and tensor scaling
• [cs.CV]Transforming and Projecting Images into Class-conditional Generative Networks
• [cs.CV]Using Artificial Intelligence to Analyze Fashion Trends
• [cs.CV]Visual Question Answering with Prior Class Semantics
• [cs.CV]VisualEchoes: Spatial Image Representation Learning through Echolocation
• [cs.CY]An Integrated Framework for Sensing Radio Frequency Spectrum Attacks on Medical Delivery Drones
• [cs.CY]Digital Sand: The Becoming of Digital Representations
• [cs.CY]Dimensions of Diversity in Human Perceptions of Algorithmic Fairness
• [cs.CY]Discussion of digital gaming’s impact on players’ well-being during the COVID-19 lockdown
• [cs.CY]Open Loop In Natura Economic Planning
• [cs.CY]Quantifying human mobility behavior changes in response to non-pharmaceutical interventions during the COVID-19 outbreak in the United States
• [cs.CY]Workshops on Extreme Scale Design Automation (ESDA) Challenges and Opportunities for 2025 and Beyond
• [cs.DB]Knowledge Graph Validation
• [cs.DB]SEPAR: A Privacy-Preserving Blockchain-based System for Regulating Multi-Platform Crowdworking Environments
• [cs.DC]An Extensible, Scalable Spark Platform for Alignment-free Genomic Analysis — Version 1
• [cs.DC]Binding of Endpoints to Identifiers by On-Chain Proofs
• [cs.DC]How deep the machine learning can be
• [cs.DC]MARS: Multi-Scalable Actor-Critic Reinforcement Learning Scheduler
• [cs.DC]On the Design of Co-operating Blockchains for IoT
• [cs.DL]Examining Citations of Natural Language Processing Literature
• [cs.DL]Gender Gap in Natural Language Processing Research: Disparities in Authorship and Citations
• [cs.DS]A Study of Performance of Optimal Transport
• [cs.DS]Online Learning and Optimization for Revenue Management Problems with Add-on Discounts
• [cs.ET]Electrically-Tunable Stochasticity for Spin-based Neuromorphic Circuits: Self-Adjusting to Variation
• [cs.GR]Lagrangian Neural Style Transfer for Fluids
• [cs.HC]Crafting, Communality, and Computing: Building on Existing Strengths To Support a Vulnerable Population
• [cs.HC]Deep ConvLSTM with self-attention for human activity decoding using wearables
• [cs.HC]Human Strategic Steering Improves Performance of Interactive Optimization
• [cs.HC]Investigating the Effects of Robot Engagement Communication on Learning from Demonstration
• [cs.IR]EngMeta — Metadata for Computational Engineering
• [cs.IR]Extracting Entities and Topics from News and Connecting Criminal Records
• [cs.IR]FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems
• [cs.IR]Ten Questions in Lifelog Mining and Information Recall
• [cs.IR]The Newspaper Navigator Dataset: Extracting And Analyzing Visual Content from 16 Million Historic Newspaper Pages in Chronicling America
• [cs.IR]Visualization of Diseases at Risk in the COVID-19 Literature
• [cs.IT]Can Terahertz Provide High-Rate Reliable Low Latency Communications for Wireless VR?
• [cs.IT]Conditional Rényi entropy and the relationships between Rényi capacities
• [cs.IT]Effect of Correlation between Information and Energy Links in Secure Wireless Powered Communications
• [cs.IT]FDMA with Layers-based Optimized Mobile Relays Subsets Algorithm in B5G/6G Cognitive IoT Networks
• [cs.IT]Intelligent Reflecting Surface Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design
• [cs.IT]Intelligent Reflecting Surface Enhanced Millimeter-Wave NOMA Systems
• [cs.IT]Intra-Channel Nonlinearity Compensation Based on Second-Order Perturbation Theory
• [cs.IT]Millimeter-Wave Beam Search with Iterative Deactivation and Beam Shifting
• [cs.IT]New families of self-dual codes
• [cs.IT]On Secure Coded Caching via Combinatorial Method
• [cs.IT]Optimal Detection Interval for Absorbing Receivers in Molecular Communication Systems with Interference
• [cs.IT]Towards Reconfigurable Intelligent Surfaces Powered Green Wireless Networks
• [cs.LG]A Causal View on Robustness of Neural Networks
• [cs.LG]A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label Learning
• [cs.LG]A Dynamical Mean-Field Theory for Learning in Restricted Boltzmann Machines
• [cs.LG]A Finite Time Analysis of Two Time-Scale Actor Critic Methods
• [cs.LG]A Probabilistic Generative Model for Typographical Analysis of Early Modern Printing
• [cs.LG]A Solution for Large Scale Nonlinear Regression with High Rank and Degree at Constant Memory Complexity via Latent Tensor Reconstruction
• [cs.LG]A survey on modern trainable activation functions
• [cs.LG]Adaptive Learning of the Optimal Mini-Batch Size of SGD
• [cs.LG]An empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs
• [cs.LG]Autoencoders for strategic decision support
• [cs.LG]Ball k-means
• [cs.LG]Categorized Bandits
• [cs.LG]Cost Effective Optimization for Cost-related Hyperparameters
• [cs.LG]Decision Support for Intoxication Prediction Using Graph Convolutional Networks
• [cs.LG]Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey
• [cs.LG]Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development
• [cs.LG]Differentially Private Generation of Small Images
• [cs.LG]Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware?
• [cs.LG]Evaluating and Aggregating Feature-based Model Explanations
• [cs.LG]Explaining AI-based Decision Support Systems using Concept Localization Maps
• [cs.LG]Explaining How Deep Neural Networks Forget by Deep Visualization
• [cs.LG]ForecastQA: Machine Comprehension of Temporal Text for Answering Forecasting Questions
• [cs.LG]Generalized Reinforcement Meta Learning for Few-Shot Optimization
• [cs.LG]Graph Homomorphism Convolution
• [cs.LG]Guarantees on learning depth-2 neural networks under a data-poisoning attack
• [cs.LG]Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation
• [cs.LG]High-Dimensional Robust Mean Estimation via Gradient Descent
• [cs.LG]If You Like It, GAN It. Probabilistic Multivariate Times Series Forecast With GAN
• [cs.LG]Knowledge Base Completion: Baseline strikes back (Again)
• [cs.LG]LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees
• [cs.LG]Large-scale Uncertainty Estimation and Its Application in Revenue Forecast of SMEs
• [cs.LG]Learning Model Predictive Control for Competitive Autonomous Racing
• [cs.LG]Lecture notes: Efficient approximation of kernel functions
• [cs.LG]Multi-Center Federated Learning
• [cs.LG]Multi-consensus Decentralized Accelerated Gradient Descent
• [cs.LG]Multivariate Time Series Forecasting Based on Causal Inference with Transfer Entropy and Graph Neural Network
• [cs.LG]Neural Lyapunov Control
• [cs.LG]Off-Policy Adversarial Inverse Reinforcement Learning
• [cs.LG]Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
• [cs.LG]On the Generalization Effects of Linear Transformations in Data Augmentation
• [cs.LG]Open Graph Benchmark: Datasets for Machine Learning on Graphs
• [cs.LG]PowerPlanningDL: Reliability-Aware Framework for On-Chip Power Grid Design using Deep Learning
• [cs.LG]Quantifying Attention Flow in Transformers
• [cs.LG]Reinforcement Learning for Decentralized Stable Matching
• [cs.LG]Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering
• [cs.LG]StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics
• [cs.LG]Stochastic Neighbor Embedding of Multimodal Relational Data for Image-Text Simultaneous Visualization
• [cs.LG]Stochastic Sparse Subspace Clustering
• [cs.LG]TIMELY: Pushing Data Movements and Interfaces in PIM Accelerators Towards Local and in Time Domain
• [cs.LG]Understanding and Improving Information Transfer in Multi-Task Learning
• [cs.LG]wisardpkg — A library for WiSARD-based models
• [cs.MM]Towards Deep Learning Methods for Quality Assessment of Computer-Generated Imagery
• [cs.NE]It is Time for New Perspectives on How to Fight Bloat in GP
• [cs.NE]Lower Bounds for Non-Elitist Evolutionary Algorithms Via Negative Multiplicative Drift
• [cs.NE]Obtaining Basic Algebra Formulas with Genetic Programming and Functional Rewriting
• [cs.NE]Perfect Edge-Transmitting Recombination of Permutations
• [cs.NE]Spiking Neural Networks Hardware Implementations and Challenges: a Survey
• [cs.NE]System Metamodel Formalism
• [cs.NE]Towards Efficient Processing and Learning with Spikes: New Approaches for Multi-Spike Learning
• [cs.NE]Type-2 fuzzy reliability redundancy allocation problem and its solution using particle swarm optimization algorithm
• [cs.NI]A Machine Learning based Framework for KPI Maximization in Emerging Networks using Mobility Parameters
• [cs.NI]Neuromorphic AI Empowered Root Cause Analysis of Faults in Emerging Networks
• [cs.RO]”Can you do this?” Self-Assessment Dialogues with Autonomous Robots Before, During, and After a Mission
• [cs.RO]Design-Informed Kinematic Control for Improved Dexterous Teleoperation of a Bilateral Manipulator System
• [cs.RO]Haptic Sequential Monte Carlo Localization for Quadrupedal Locomotion in Vision-Denied Scenarios
• [cs.RO]Probabilistic Analysis of RRT Trees
• [cs.RO]Proceedings of the 2020 Workshop on Assessing, Explaining, and Conveying Robot Proficiency for Human-Robot Teaming
• [cs.RO]Robotic Self-Assessment of Competence
• [cs.RO]SIGVerse: A cloud-based VR platform for research on social and embodied human-robot interaction
• [cs.RO]Supportive Actions for Manipulation in Human-Robot Coworker Teams
• [cs.RO]TEX-CUP: The University of Texas Challenge for Urban Positioning
• [cs.SD]Addressing Missing Labels in Large-scale Sound Event Recognition using a Teacher-student Framework with Loss Masking
• [cs.SE]A Transformer-based Approach for Source Code Summarization
• [cs.SE]Minerva: A Portable Machine Learning Microservice Framework for Traditional Enterprise SaaS Applications
• [cs.SE]On Systematically Building a Controlled Natural Language for Functional Requirements
• [cs.SE]Pandemic Programming: How COVID-19 affects software developers and how their organizations can help
• [cs.SE]Storing, preprocessing and analyzing Tweets: Finding the suitable NoSQL system
• [cs.SI]Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection
• [cs.SI]Blind Estimation of Eigenvector Centrality from Graph Signals: Beyond Low-pass Filtering
• [cs.SI]Information Propagation in Stochastic Networks
• [cs.SI]Sentiment Paradoxes in Social Networks: Why Your Friends Are More Positive Than You?
• [eess.AS]Does Visual Self-Supervision Improve Learning of Speech Representations?
• [eess.AS]Noise2Weight: On Detecting Payload Weight from Drones Acoustic Emissions
• [eess.IV]A Comparative Study of Image Quality Assessment Models through Perceptual Optimization
• [eess.IV]A Little Bit More: Bitplane-Wise Bit-Depth Recovery
• [eess.IV]A Model-driven Deep Neural Network for Single Image Rain Removal
• [eess.IV]Boundary-aware Context Neural Network for Medical Image Segmentation
• [eess.IV]Deep Convolutional Neural Networks to Diagnose COVID-19 and other Pneumonia Diseases from Posteroanterior Chest X-Rays
• [eess.IV]Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution
• [eess.IV]Fusion of visible and infrared images via complex function
• [eess.IV]NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
• [eess.IV]Neural Differential Equations for Single Image Super-resolution
• [eess.IV]Towards Occlusion-Aware Multifocal Displays
• [eess.SP]Automotive-Radar-Based 50-cm Urban Positioning
• [eess.SP]Compressed-Sensing based Beam Detection in 5G NR Initial Access
• [eess.SP]Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition
• [eess.SP]Lupulus: A Flexible Hardware Accelerator for Neural Networks
• [eess.SP]PPG2ABP: Translating Photoplethysmogram (PPG) Signals to Arterial Blood Pressure (ABP) Waveforms using Fully Convolutional Neural Networks
• [eess.SP]Predicting the Path Loss of Wireless Channel Models Using Machine Learning Techniques in MmWave Urban Communications
• [eess.SP]Robust Adaptive Beam Tracking for Mobile Millimetre Wave Communications
• [eess.SP]Robust M-Estimation Based Bayesian Cluster Enumeration for Real Elliptically Symmetric Distributions
• [eess.SP]The Bussgang Decomposition of Non-Linear Systems: Basic Theory and MIMO Extensions
• [eess.SY]Formal Policy Synthesis for Continuous-Space Systems via Reinforcement Learning
• [hep-ex]Adversarially Learned Anomaly Detection on CMS Open Data: re-discovering the top quark
• [math.OC]Accelerated Learning with Robustness to Adversarial Regressors
• [math.OC]Multiagent Value Iteration Algorithms in Dynamic Programming and Reinforcement Learning
• [math.OC]On the Convergence Rate of Projected Gradient Descent for a Back-Projection based Objective
• [math.OC]Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold
• [math.PR]Linear spectral statistics of eigenvectors of anisotropic sample covariance matrices
• [math.ST]A Powerful Portmanteau Test for Detecting Nonlinearity in Time Series
• [math.ST]Bootstrapping Persistent Betti Numbers and Other Stabilizing Statistics
• [math.ST]Constraint-Based Causal Discovery In The Presence Of Cycles
• [math.ST]Gaussian linear model selection in a dependent context
• [math.ST]How many modes can a constrained Gaussian mixture have?
• [math.ST]Inference for nonstationary time series of counts with application to change-point problems
• [math.ST]Limit theorem associated with Wishart matrices with application to hypothesis testing for common principal components
• [math.ST]Reduced Rank Multivariate Kernel Ridge Regression
• [math.ST]Uncertainty quantification in the stochastic block model with an unknown number of classes
• [nlin.AO]Physical reservoir computing — An introductory perspective
• [physics.ao-ph]Filtering Internal Tides From Wide-Swath Altimeter Data Using Convolutional Neural Networks
• [physics.comp-ph]Dynamic Compressed Sensing for Real-Time Tomographic Reconstruction
• [physics.med-ph]Monte Carlo modeling photon-tissue interaction using on-demand cloud infrastructure
• [physics.soc-ph]A study of the U.S. domestic air transportation network: Temporal evolution of network topology and robustness from 2001 to 2016
• [physics.soc-ph]Complex social contagion induces bistability on multiplex networks
• [physics.soc-ph]Interplay between $k$-core and community structure in complex networks
• [physics.soc-ph]Learning Geo-Contextual Embeddings for Commuting Flow Prediction
• [physics.soc-ph]Lived population density and the spread of COVID-19
• [q-bio.GN]Computational modelling in single-cell cancer genomics: methods and future directions
• [q-fin.RM]Neural Networks and Value at Risk
• [q-fin.RM]Tail Granger causalities and where to find them: extreme risk spillovers vs. spurious linkages
• [q-fin.ST]Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories
• [quant-ph]Setting up experimental Bell test with reinforcement learning
• [stat.AP]Data-Driven Modeling Reveals the Impact of Stay-at-Home Orders on Human Mobility during the COVID-19 Pandemic in the U.S
• [stat.AP]Estimation of COVID-19 spread curves integrating global data and borrowing information
• [stat.AP]Generalized Knowledge Tracing: A Constrained Framework for Learner Modeling
• [stat.AP]How Large is too Large? A Review of the Issues related to Sample Size Requirements of Regional Household Travel Surveys with a Case Study on the Greater Toronto and Hamilton Area (GTHA)
• [stat.AP]Integrated Time Series Summarization and Prediction Algorithm and its Application to COVID-19 Data Mining
• [stat.AP]Nonparametric Time Series Summary Statistics for High-Frequency Actigraphy Data from Individuals with Advanced Dementia
• [stat.AP]Survival Analysis of Organizational Networks — An Exploratory Study
• [stat.CO]Connecting the Dots: Towards Continuous Time Hamiltonian Monte Carlo
• [stat.CO]Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models
• [stat.ME]A Linear Mixed Model Formulation for Spatio-Temporal Random Processes with Computational Advances for the Separable and Product-Sum Covariances
• [stat.ME]An efficient and accurate approximation to the distribution of quadratic forms of Gaussian variables
• [stat.ME]Confidence intervals of prediction accuracy measures for multivariable prediction models based on the bootstrap-based optimism correction methods
• [stat.ME]Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise
• [stat.ME]Exact computation of projection regression depth and fast computation of its induced median and other estimators
• [stat.ME]High Dimensional Classification for Spatially Dependent Data with Application to Neuroimaging
• [stat.ME]Nonparametric testing of the dependence structure among points-marks-covariates in spatial point patterns
• [stat.ME]Pattern-Based Analysis of Time Series: Estimation
• [stat.ME]Point process models for sweat gland activation observed with noise
• [stat.ME]ProgPermute: Progressive permutation for a dynamic representation of the robustness of microbiome discoveries
• [stat.ME]Rejoinder for the discussion of the paper “A novel algorithmic approach to Bayesian Logic Regression”
• [stat.ME]Response-adaptive randomization in clinical trials: from myths to practical considerations
• [stat.ME]Simultaneous Non-Gaussian Component Analysis (SING) for Data Integration in Neuroimaging
• [stat.ML]Mutual Information Gradient Estimation for Representation Learning
• [stat.ML]Simulation free reliability analysis: A physics-informed deep learning based approach
• [stat.ML]Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations
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• [astro-ph.IM]Machine Learning Pipeline for Pulsar Star Dataset
Alexander Ylnner Choquenaira Florez, Braulio Valentin Sanchez Vinces, Diana Carolina Roca Arroyo, Josimar Edinson Chire Saire, Patrıcia Batista Franco
http://arxiv.org/abs/2005.01208v1
• [cond-mat.dis-nn]Teaching Recurrent Neural Networks to Modify Chaotic Memories by Example
Jason Z. Kim, Zhixin Lu, Erfan Nozari, George J. Pappas, Danielle S. Bassett
http://arxiv.org/abs/2005.01186v1
• [cs.AI]A Multialternative Neural Decision Process
Simone Cerreia-Vioglio, Fabio Maccheroni, Massimo Marinacci
http://arxiv.org/abs/2005.01081v1
• [cs.AI]Bayesian Entailment Hypothesis: How Brains Implement Monotonic and Non-monotonic Reasoning
Hiroyuki Kido
http://arxiv.org/abs/2005.00961v1
• [cs.AI]Computing With Words for Student Strategy Evaluation in an Examination
Prashant K Gupta, Pranab K. Muhuri
http://arxiv.org/abs/2005.00868v1
• [cs.AI]Construction and Elicitation of a Black Box Model in the Game of Bridge
Véronique Ventos, Daniel Braun, Colin Deheeger, Jean Pierre Desmoulins, Jean Baptiste Fantun, Swann Legras, Alexis Rimbaud, Céline Rouveirol, Henry Soldano
http://arxiv.org/abs/2005.01633v1
• [cs.AI]Enhancing Text-based Reinforcement Learning Agents with Commonsense Knowledge
Keerthiram Murugesan, Mattia Atzeni, Pushkar Shukla, Mrinmaya Sachan, Pavan Kapanipathi, Kartik Talamadupula
http://arxiv.org/abs/2005.00811v1
• [cs.AI]Navigating the Landscape of Games
Shayegan Omidshafiei, Karl Tuyls, Wojciech M. Czarnecki, Francisco C. Santos, Mark Rowland, Jerome Connor, Daniel Hennes, Paul Muller, Julien Perolat, Bart De Vylder, Audrunas Gruslys, Remi Munos
http://arxiv.org/abs/2005.01642v1
• [cs.AI]SEEK: Segmented Embedding of Knowledge Graphs
Wentao Xu, Shun Zheng, Liang He, Bin Shao, Jian Yin, Tie-Yan Liu
http://arxiv.org/abs/2005.00856v1
• [cs.AI]The ILASP system for Inductive Learning of Answer Set Programs
Mark Law, Alessandra Russo, Krysia Broda
http://arxiv.org/abs/2005.00904v1
• [cs.CL]A Benchmark for Structured Procedural Knowledge Extraction from Cooking Videos
Frank F. Xu, Lei Ji, Botian Shi, Junyi Du, Graham Neubig, Yonatan Bisk, Nan Duan
http://arxiv.org/abs/2005.00706v1
• [cs.CL]A Girl Has A Name: Detecting Authorship Obfuscation
Asad Mahmood, Zubair Shafiq, Padmini Srinivasan
http://arxiv.org/abs/2005.00702v1
• [cs.CL]A New Data Normalization Method to Improve Dialogue Generation by Minimizing Long Tail Effect
Zhiqiang Zhan, Zifeng Hou, Yang Zhang
http://arxiv.org/abs/2005.01278v1
• [cs.CL]A Position Aware Decay Weighted Network for Aspect based Sentiment Analysis
Avinash Madasu, Vijjini Anvesh Rao
http://arxiv.org/abs/2005.01027v1
• [cs.CL]A Simple Language Model for Task-Oriented Dialogue
Ehsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, Semih Yavuz, Richard Socher
http://arxiv.org/abs/2005.00796v1
• [cs.CL]A Tale of a Probe and a Parser
Rowan Hall Maudslay, Josef Valvoda, Tiago Pimentel, Adina Williams, Ryan Cotterell
http://arxiv.org/abs/2005.01641v1
• [cs.CL]A Two-Stage Masked LM Method for Term Set Expansion
Guy Kushilevitz, Shaul Markovitch, Yoav Goldberg
http://arxiv.org/abs/2005.01063v1
• [cs.CL]A language score based output selection method for multilingual speech recognition
Van Huy Nguyen, Thi Quynh Khanh Dinh, Truong Thinh Nguyen, Dang Khoa Mac
http://arxiv.org/abs/2005.00851v1
• [cs.CL]AVA: an Automatic eValuation Approach to Question Answering Systems
Thuy Vu, Alessandro Moschitti
http://arxiv.org/abs/2005.00705v1
• [cs.CL]An Accurate Model for Predicting the (Graded) Effect of Context in Word Similarity Based on Bert
Wei Bao, Hongshu Che, Jiandong Zhang
http://arxiv.org/abs/2005.01006v1
• [cs.CL]An Imitation Game for Learning Semantic Parsers from User Interaction
Ziyu Yao, Yiqi Tang, Wen-tau Yih, Huan Sun, Yu Su
http://arxiv.org/abs/2005.00689v1
• [cs.CL]Are Emojis Emotional? A Study to Understand the Association between Emojis and Emotions
Abu Shoeb, Gerard de Melo
http://arxiv.org/abs/2005.00693v1
• [cs.CL]BERT-kNN: Adding a kNN Search Component to Pretrained Language Models for Better QA
Nora Kassner, Hinrich Schütze
http://arxiv.org/abs/2005.00766v1
• [cs.CL]Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-trained Language Models
Bill Yuchen Lin, Seyeon Lee, Rahul Khanna, Xiang Ren
http://arxiv.org/abs/2005.00683v1
• [cs.CL]Bootstrapping Techniques for Polysynthetic Morphological Analysis
William Lane, Steven Bird
http://arxiv.org/abs/2005.00956v1
• [cs.CL]Can BERT Reason? Logically Equivalent Probes for Evaluating the Inference Capabilities of Language Models
Pei Zhou, Rahul Khanna, Bill Yuchen Lin, Daniel Ho, Xiang Ren, Jay Pujara
http://arxiv.org/abs/2005.00782v1
• [cs.CL]Clue: Cross-modal Coherence Modeling for Caption Generation
Malihe Alikhani, Piyush Sharma, Shengjie Li, Radu Soricut, Matthew Stone
http://arxiv.org/abs/2005.00908v1
• [cs.CL]Code and Named Entity Recognition in StackOverflow
Jeniya Tabassum, Mounica Maddela, Wei Xu, Alan Ritter
http://arxiv.org/abs/2005.01634v1
• [cs.CL]Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation
Lei Shen, Xiaoyu Guo, Meng Chen
http://arxiv.org/abs/2005.01556v1
• [cs.CL]Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering
Peifeng Wang, Nanyun Peng, Pedro Szekely, Xiang Ren
http://arxiv.org/abs/2005.00691v1
• [cs.CL]Correcting the Autocorrect: Context-Aware Typographical Error Correction via Training Data Augmentation
Kshitij Shah, Gerard de Melo
http://arxiv.org/abs/2005.01158v1
• [cs.CL]DQI: Measuring Data Quality in NLP
Swaroop Mishra, Anjana Arunkumar, Bhavdeep Sachdeva, Chris Bryan, Chitta Baral
http://arxiv.org/abs/2005.00816v1
• [cs.CL]DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering
Qingqing Cao, Harsh Trivedi, Aruna Balasubramanian, Niranjan Balasubramanian
http://arxiv.org/abs/2005.00697v1
• [cs.CL]Design Challenges for Low-resource Cross-lingual Entity Linking
Xingyu Fu, Weijia Shi, Zian Zhao, Xiaodong Yu, Dan Roth
http://arxiv.org/abs/2005.00692v1
• [cs.CL]Distributional Discrepancy: A Metric for Unconditional Text Generation
Ping Cai, Xingyuan Chen, Peng Jin, Hongjun Wang, Tianrui Li
http://arxiv.org/abs/2005.01282v1
• [cs.CL]DoQA — Accessing Domain-Specific FAQs via Conversational QA
Jon Ander Campos, Arantxa Otegi, Aitor Soroa, Jan Deriu, Mark Cieliebak, Eneko Agirre
http://arxiv.org/abs/2005.01328v1
• [cs.CL]Double-Hard Debias: Tailoring Word Embeddings for Gender Bias Mitigation
Tianlu Wang, Xi Victoria Lin, Nazneen Fatema Rajani, Bryan McCann, Vicente Ordonez, Caiming Xiong
http://arxiv.org/abs/2005.00965v1
• [cs.CL]ENGINE: Energy-Based Inference Networks for Non-Autoregressive Machine Translation
Lifu Tu, Richard Yuanzhe Pang, Sam Wiseman, Kevin Gimpel
http://arxiv.org/abs/2005.00850v1
• [cs.CL]ESPRIT: Explaining Solutions to Physical Reasoning Tasks
Nazneen Fatema Rajani, Rui Zhang, Yi Chern Tan, Stephan Zheng, Jeremy Weiss, Aadit Vyas, Abhijit Gupta, Abhijit Gupta, Richard Socher, Dragomir Radev
http://arxiv.org/abs/2005.00730v1
• [cs.CL]Efficient Second-Order TreeCRF for Neural Dependency Parsing
Yu Zhang, Zhenghua Li, Min Zhang
http://arxiv.org/abs/2005.00975v1
• [cs.CL]Emergence of Syntax Needs Minimal Supervision
Raphaël Bailly, Kata Gábor
http://arxiv.org/abs/2005.01119v1
• [cs.CL]Encoder-Decoder Models Can Benefit from Pre-trained Masked Language Models in Grammatical Error Correction
Masahiro Kaneko, Masato Mita, Shun Kiyono, Jun Suzuki, Kentaro Inui
http://arxiv.org/abs/2005.00987v1
• [cs.CL]Evaluating Explanation Methods for Neural Machine Translation
Jierui Li, Lemao Liu, Huayang Li, Guanlin Li, Guoping Huang, Shuming Shi
http://arxiv.org/abs/2005.01672v1
• [cs.CL]Expertise Style Transfer: A New Task Towards Better Communication between Experts and Laymen
Yixin Cao, Ruihao Shui, Liangming Pan, Min-Yen Kan, Zhiyuan Liu, Tat-Seng Chua
http://arxiv.org/abs/2005.00701v1
• [cs.CL]Exploring and Predicting Transferability across NLP Tasks
Tu Vu, Tong Wang, Tsendsuren Munkhdalai, Alessandro Sordoni, Adam Trischler, Andrew Mattarella-Micke, Subhransu Maji, Mohit Iyyer
http://arxiv.org/abs/2005.00770v1
• [cs.CL]Fast and Robust Unsupervised Contextual Biasing for Speech Recognition
Young Mo Kang, Yingbo Zhou
http://arxiv.org/abs/2005.01677v1
• [cs.CL]From Arguments to Key Points: Towards Automatic Argument Summarization
Roy Bar-Haim, Lilach Eden, Roni Friedman, Yoav Kantor, Dan Lahav, Noam Slonim
http://arxiv.org/abs/2005.01619v1
• [cs.CL]From SPMRL to NMRL: What Did We Learn (and Unlearn) in a Decade of Parsing Morphologically-Rich Languages (MRLs)?
Reut Tsarfaty, Dan Bareket, Stav Klein, Amit Seker
http://arxiv.org/abs/2005.01330v1
• [cs.CL]Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer
Jieyu Zhao, Subhabrata Mukherjee, Saghar Hosseini, Kai-Wei Chang, Ahmed Hassan Awadallah
http://arxiv.org/abs/2005.00699v1
• [cs.CL]Generalized Entropy Regularization or: There’s Nothing Special about Label Smoothing
Clara Meister, Elizabeth Salesky, Ryan Cotterell
http://arxiv.org/abs/2005.00820v1
• [cs.CL]GenericsKB: A Knowledge Base of Generic Statements
Sumithra Bhakthavatsalam, Chloe Anastasiades, Peter Clark
http://arxiv.org/abs/2005.00660v1
• [cs.CL]Hard-Coded Gaussian Attention for Neural Machine Translation
Weiqiu You, Simeng Sun, Mohit Iyyer
http://arxiv.org/abs/2005.00742v1
• [cs.CL]How Can We Accelerate Progress Towards Human-like Linguistic Generalization?
Tal Linzen
http://arxiv.org/abs/2005.00955v1
• [cs.CL]How Does Selective Mechanism Improve Self-Attention Networks?
Xinwei Geng, Longyue Wang, Xing Wang, Bing Qin, Ting Liu, Zhaopeng Tu
http://arxiv.org/abs/2005.00979v1
• [cs.CL]Improving Adversarial Text Generation by Modeling the Distant Future
Ruiyi Zhang, Changyou Chen, Zhe Gan, Wenlin Wang, Dinghan Shen, Guoyin Wang, Zheng Wen, Lawrence Carin
http://arxiv.org/abs/2005.01279v1
• [cs.CL]Improving Non-autoregressive Neural Machine Translation with Monolingual Data
Jiawei Zhou, Phillip Keung
http://arxiv.org/abs/2005.00932v1
• [cs.CL]Improving Truthfulness of Headline Generation
Kazuki Matsumaru, Sho Takase, Naoaki Okazaki
http://arxiv.org/abs/2005.00882v1
• [cs.CL]Influence Paths for Characterizing Subject-Verb Number Agreement in LSTM Language Models
Kaiji Lu, Piotr Mardziel, Klas Leino, Matt Fedrikson, Anupam Datta
http://arxiv.org/abs/2005.01190v1
• [cs.CL]Introducing the VoicePrivacy Initiative
Natalia Tomashenko, Brij Mohan Lal Srivastava, Xin Wang, Emmanuel Vincent, Andreas Nautsch, Junichi Yamagishi, Nicholas Evans, Jose Patino, Jean-François Bonastre, Paul-Gauthier Noé, Massimiliano Todisco
http://arxiv.org/abs/2005.01387v1
• [cs.CL]KinGDOM: Knowledge-Guided DOMain adaptation for sentiment analysis
Deepanway Ghosal, Devamanyu Hazarika, Navonil Majumder, Abhinaba Roy, Soujanya Poria, Rada Mihalcea
http://arxiv.org/abs/2005.00791v1
• [cs.CL]Knowledge Graph-Augmented Abstractive Summarization with Semantic-Driven Cloze Reward
Luyang Huang, Lingfei Wu, Lu Wang
http://arxiv.org/abs/2005.01159v1
• [cs.CL]Language Models as an Alternative Evaluator of Word Order Hypotheses: A Case Study in Japanese
Tatsuki Kuribayashi, Takumi Ito, Jun Suzuki, Kentaro Inui
http://arxiv.org/abs/2005.00842v1
• [cs.CL]Let Me Choose: From Verbal Context to Font Selection
Amirreza Shirani, Franck Dernoncourt, Jose Echevarria, Paul Asente, Nedim Lipka, Thamar Solorio
http://arxiv.org/abs/2005.01151v1
• [cs.CL]Measuring and Reducing Non-Multifact Reasoning in Multi-hop Question Answering
Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal
http://arxiv.org/abs/2005.00789v1
• [cs.CL]MultiQT: Multimodal Learning for Real-Time Question Tracking in Speech
Jakob Drachmann Havtorn, Jan Latko, Joakim Edin, Lasse Borgholt, Lars Maaløe, Lorenzo Belgrano, Nicolai Frost Jakobsen, Regitze Sdun, Željko Agić
http://arxiv.org/abs/2005.00812v1
• [cs.CL]NLP in FinTech Applications: Past, Present and Future
Chung-Chi Chen, Hen-Hsen Huang, Hsin-Hsi Chen
http://arxiv.org/abs/2005.01320v1
• [cs.CL]Neural Data-to-Text Generation via Jointly Learning the Segmentation and Correspondence
Xiaoyu Shen, Ernie Chang, Hui Su, Jie Zhou, Dietrich Klakow
http://arxiv.org/abs/2005.01096v1
• [cs.CL]Noise Pollution in Hospital Readmission Prediction: Long Document Classification with Reinforcement Learning
Liyan Xu, Julien Hogan, Rachel E. Patzer, Jinho D. Choi
http://arxiv.org/abs/2005.01259v1
• [cs.CL]Obtaining Faithful Interpretations from Compositional Neural Networks
Sanjay Subramanian, Ben Bogin, Nitish Gupta, Tomer Wolfson, Sameer Singh, Jonathan Berant, Matt Gardner
http://arxiv.org/abs/2005.00724v1
• [cs.CL]On the Inference Calibration of Neural Machine Translation
Shuo Wang, Zhaopeng Tu, Shuming Shi, Yang Liu
http://arxiv.org/abs/2005.00963v1
• [cs.CL]On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation
Wei Zhao, Goran Glavaš, Maxime Peyrard, Yang Gao, Robert West, Steffen Eger
http://arxiv.org/abs/2005.01196v1
• [cs.CL]On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs
Adina Williams, Ryan Cotterell, Lawrence Wolf-Sonkin, Damián Blasi, Hanna Wallach
http://arxiv.org/abs/2005.01204v1
• [cs.CL]Out of the Echo Chamber: Detecting Countering Debate Speeches
Matan Orbach, Yonatan Bilu, Assaf Toledo, Dan Lahav, Michal Jacovi, Ranit Aharonov, Noam Slonim
http://arxiv.org/abs/2005.01157v1
• [cs.CL]Predicting Performance for Natural Language Processing Tasks
Mengzhou Xia, Antonios Anastasopoulos, Ruochen Xu, Yiming Yang, Graham Neubig
http://arxiv.org/abs/2005.00870v1
• [cs.CL]Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance?
Abhilasha Ravichander, Yonatan Belinkov, Eduard Hovy
http://arxiv.org/abs/2005.00719v1
• [cs.CL]ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning
Michael Boratko, Xiang Lorraine Li, Rajarshi Das, Tim O’Gorman, Dan Le, Andrew McCallum
http://arxiv.org/abs/2005.00771v1
• [cs.CL]RMM: A Recursive Mental Model for Dialog Navigation
Homero Roman Roman, Yonatan Bisk, Jesse Thomason, Asli Celikyilmaz, Jianfeng Gao
http://arxiv.org/abs/2005.00728v1
• [cs.CL]Rationalizing Medical Relation Prediction from Corpus-level Statistics
Zhen Wang, Jennifer Lee, Simon Lin, Huan Sun
http://arxiv.org/abs/2005.00889v1
• [cs.CL]Reward Constrained Interactive Recommendation with Natural Language Feedback
Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin, Changyou Chen, Lawrence Carin
http://arxiv.org/abs/2005.01618v1
• [cs.CL]Robust Encodings: A Framework for Combating Adversarial Typos
Erik Jones, Robin Jia, Aditi Raghunathan, Percy Liang
http://arxiv.org/abs/2005.01229v1
• [cs.CL]Robust and Interpretable Grounding of Spatial References with Relation Networks
Tsung-Yen Yang, Karthik Narasimham
http://arxiv.org/abs/2005.00696v1
• [cs.CL]Similarity Analysis of Contextual Word Representation Models
John M. Wu, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, James Glass
http://arxiv.org/abs/2005.01172v1
• [cs.CL]Single Model Ensemble using Pseudo-Tags and Distinct Vectors
Ryosuke Kuwabara, Jun Suzuki, Hideki Nakayama
http://arxiv.org/abs/2005.00879v1
• [cs.CL]Social Biases in NLP Models as Barriers for Persons with Disabilities
Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, Stephen Denuyl
http://arxiv.org/abs/2005.00813v1
• [cs.CL]Sources of Transfer in Multilingual Named Entity Recognition
David Mueller, Nicholas Andrews, Mark Dredze
http://arxiv.org/abs/2005.00847v1
• [cs.CL]Synthesizer: Rethinking Self-Attention in Transformer Models
Yi Tay, Dara Bahri, Donald Metzler, Da-Cheng Juan, Zhe Zhao, Che Zheng
http://arxiv.org/abs/2005.00743v1
• [cs.CL]Tailoring and Evaluating the Wikipedia for in-Domain Comparable Corpora Extraction
Cristina España-Bonet, Alberto Barrón-Cedeño, Lluís Màrquez
http://arxiv.org/abs/2005.01177v1
• [cs.CL]Teaching Machine Comprehension with Compositional Explanations
Qinyuan Ye, Xiao Huang, Xiang Ren
http://arxiv.org/abs/2005.00806v1
• [cs.CL]The Paradigm Discovery Problem
Alexander Erdmann, Micha Elsner, Shijie Wu, Ryan Cotterell, Nizar Habash
http://arxiv.org/abs/2005.01630v1
• [cs.CL]The Sensitivity of Language Models and Humans to Winograd Schema Perturbations
Mostafa Abdou, Vinit Ravishankar, Maria Barrett, Yonatan Belinkov, Desmond Elliott, Anders Søgaard
http://arxiv.org/abs/2005.01348v1
• [cs.CL]To Test Machine Comprehension, Start by Defining Comprehension
Jesse Dunietz, Gregory Burnham, Akash Bharadwaj, Jennifer Chu-Carroll, Owen Rambow, David Ferrucci
http://arxiv.org/abs/2005.01525v1
• [cs.CL]Towards A Sign Language Gloss Representation Of Modern Standard Arabic
Salma El Anigri, Mohammed Majid Himmi, Abdelhak Mahmoudi
http://arxiv.org/abs/2005.01497v1
• [cs.CL]Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints
Zhenyi Wang, Xiaoyang Wang, Bang An, Dong Yu, Changyou Chen
http://arxiv.org/abs/2005.00969v1
• [cs.CL]Transformer-based End-to-End Question Generation
Luis Enrico Lopez, Diane Kathryn Cruz, Jan Christian Blaise Cruz, Charibeth Cheng
http://arxiv.org/abs/2005.01107v1
• [cs.CL]Treebank Embedding Vectors for Out-of-domain Dependency Parsing
Joachim Wagner, James Barry, Jennifer Foster
http://arxiv.org/abs/2005.00800v1
• [cs.CL]UnifiedQA: Crossing Format Boundaries With a Single QA System
Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, Hannaneh Hajishirzi
http://arxiv.org/abs/2005.00700v1
• [cs.CL]Unsupervised Alignment-based Iterative Evidence Retrieval for Multi-hop Question Answering
Vikas Yadav, Steven Bethard, Mihai Surdeanu
http://arxiv.org/abs/2005.01218v1
• [cs.CL]Unsupervised Morphological Paradigm Completion
Huiming Jin, Liwei Cai, Yihui Peng, Chen Xia, Arya D. McCarthy, Katharina Kann
http://arxiv.org/abs/2005.00970v1
• [cs.CL]Using Context in Neural Machine Translation Training Objectives
Danielle Saunders, Felix Stahlberg, Bill Byrne
http://arxiv.org/abs/2005.01483v1
• [cs.CL]Visually Grounded Continual Learning of Compositional Semantics
Xisen Jin, Junyi Du, Xiang Ren
http://arxiv.org/abs/2005.00785v1
• [cs.CL]What is Learned in Visually Grounded Neural Syntax Acquisition
Noriyuki Kojima, Hadar Averbuch-Elor, Alexander M. Rush, Yoav Artzi
http://arxiv.org/abs/2005.01678v1
• [cs.CL]What-if I ask you to explain: Explaining the effects of perturbations in procedural text
Dheeraj Rajagopal, Niket Tandon, Peter Clarke, Bhavana Dalvi, Eduard Hovy
http://arxiv.org/abs/2005.01526v1
• [cs.CL]WikiUMLS: Aligning UMLS to Wikipedia via Cross-lingual Neural Ranking
Afshin Rahimi, Timothy Baldwin, Karin Verspoor
http://arxiv.org/abs/2005.01281v1
• [cs.CL]Words aren’t enough, their order matters: On the Robustness of Grounding Visual Referring Expressions
Arjun R Akula, Spandana Gella, Yaser Al-Onaizan, Song-Chun Zhu, Siva Reddy
http://arxiv.org/abs/2005.01655v1
• [cs.CL]Zero-Shot Transfer Learning with Synthesized Data for Multi-Domain Dialogue State Tracking
Giovanni Campagna, Agata Foryciarz, Mehrad Moradshahi, Monica S. Lam
http://arxiv.org/abs/2005.00891v1
• [cs.CL]pyBART: Evidence-based Syntactic Transformations for IE
Aryeh Tiktinsky, Yoav Goldberg, Reut Tsarfaty
http://arxiv.org/abs/2005.01306v1
• [cs.CR]Customizable and Rigorous Location Privacy through Policy Graph
Yang Cao, Yonghui Xiao, Shun Takagi, Li Xiong, Masatoshi Yoshikawa, Yilin Shen, Jinfei Liu, Hongxia Jin, Xiaofeng Xu
http://arxiv.org/abs/2005.01263v1
• [cs.CR]Enhancing network forensics with particle swarm and deep learning: The particle deep framework
Nickolaos Koroniotis, Nour Moustafa
http://arxiv.org/abs/2005.00722v1
• [cs.CV]AIM 2019 Challenge on Video Temporal Super-Resolution: Methods and Results
Seungjun Nah, Sanghyun Son, Radu Timofte, Kyoung Mu Lee
http://arxiv.org/abs/2005.01233v1
• [cs.CV]Anchors based method for fingertips position from a monocular RGB image using Deep Neural Network
Purnendu Mishra, Kishor Sarawadekar
http://arxiv.org/abs/2005.01351v1
• [cs.CV]Automated eye disease classification method from anterior eye image using anatomical structure focused image classification technique
Masahiro Oda, Takefumi Yamaguchi, Hideki Fukuoka, Yuta Ueno, Kensaku Mori
http://arxiv.org/abs/2005.01433v1
• [cs.CV]BeCAPTCHA-Mouse: Synthetic Mouse Trajectories and Improved Bot Detection
Alejandro Acien, Aythami Morales, Julian Fierrez, Ruben Vera-Rodriguez
http://arxiv.org/abs/2005.00890v1
• [cs.CV]CARRADA Dataset: Camera and Automotive Radar with Range-Angle-Doppler Annotations
A. Ouaknine, A. Newson, J. Rebut, F. Tupin, P. Pérez
http://arxiv.org/abs/2005.01456v1
• [cs.CV]CoMoGCN: Coherent Motion Aware Trajectory Prediction with Graph Representation
Yuying Chen, Congcong Liu, Bertram Shi, Ming Liu
http://arxiv.org/abs/2005.00754v1
• [cs.CV]Correlating Edge, Pose with Parsing
Ziwei Zhang, Chi Su, Liang Zheng, Xiaodong Xie
http://arxiv.org/abs/2005.01431v1
• [cs.CV]Cross-View Image Retrieval — Ground to Aerial Image Retrieval through Deep Learning
Numan Khurshid, Talha Hanif, Mohbat Tharani, Murtaza Taj
http://arxiv.org/abs/2005.00725v1
• [cs.CV]Deep Encoder-Decoder Neural Network for Fingerprint Image Denoising and Inpainting
Weiya Fan
http://arxiv.org/abs/2005.01115v1
• [cs.CV]Derivation of a Constant Velocity Motion Model for Visual Tracking
Nathanael L. Baisa
http://arxiv.org/abs/2005.00844v1
• [cs.CV]DroTrack: High-speed Drone-based Object Tracking Under Uncertainty
Ali Hamdi, Flora Salim, Du Yong Kim
http://arxiv.org/abs/2005.00828v1
• [cs.CV]Ego-motion and Surrounding Vehicle State Estimation Using a Monocular Camera
Jun Hayakawa, Behzad Dariush
http://arxiv.org/abs/2005.01632v1
• [cs.CV]Feature-metric Registration: A Fast Semi-supervised Approach for Robust Point Cloud Registration without Correspondences
Xiaoshui Huang, Guofeng Mei, Jian Zhang
http://arxiv.org/abs/2005.01014v1
• [cs.CV]Group Equivariant Generative Adversarial Networks
Neel Dey, Antong Chen, Soheil Ghafurian
http://arxiv.org/abs/2005.01683v1
• [cs.CV]Heterogeneous Knowledge Distillation using Information Flow Modeling
Nikolaos Passalis, Maria Tzelepi, Anastasios Tefas
http://arxiv.org/abs/2005.00727v1
• [cs.CV]How to Train Your Dragon: Tamed Warping Network for Semantic Video Segmentation
Junyi Feng, Songyuan Li, Yifeng Chen, Fuxian Huang, Jiabao Cui, Xi Li
http://arxiv.org/abs/2005.01344v1
• [cs.CV]How to Train Your Energy-Based Model for Regression
Fredrik K. Gustafsson, Martin Danelljan, Radu Timofte, Thomas B. Schön
http://arxiv.org/abs/2005.01698v1
• [cs.CV]Joint-SRVDNet: Joint Super Resolution and Vehicle Detection Network
Moktari Mostofa, Syeda Nyma Ferdous, Benjamin S. Riggan, Nasser M. Nasrabadi
http://arxiv.org/abs/2005.00983v1
• [cs.CV]Minor Privacy Protection Through Real-time Video Processing at the Edge
Meng Yuan, Seyed Yahya Nikouei, Alem Fitwi, Yu Chen, Yunxi Dong
http://arxiv.org/abs/2005.01178v1
• [cs.CV]Monitoring COVID-19 social distancing with person detection and tracking via fine-tuned YOLO v3 and Deepsort techniques
Narinder Singh Punn, Sanjay Kumar Sonbhadra, Sonali Agarwal
http://arxiv.org/abs/2005.01385v1
• [cs.CV]MorphoCluster: Efficient Annotation of Plankton images by Clustering
Simon-Martin Schröder, Rainer Kiko, Reinhard Koch
http://arxiv.org/abs/2005.01595v1
• [cs.CV]Multi-Modality Generative Adversarial Networks with Tumor Consistency Loss for Brain MR Image Synthesis
Bingyu Xin, Yifan Hu, Yefeng Zheng, Hongen Liao
http://arxiv.org/abs/2005.00925v1
• [cs.CV]Multi-focus Image Fusion: A Benchmark
Xingchen Zhang
http://arxiv.org/abs/2005.01116v1
• [cs.CV]NTIRE 2020 Challenge on Image and Video Deblurring
Seungjun Nah, Sanghyun Son, Radu Timofte, Kyoung Mu Lee
http://arxiv.org/abs/2005.01244v1
• [cs.CV]On the Benefits of Models with Perceptually-Aligned Gradients
Gunjan Aggarwal, Abhishek Sinha, Nupur Kumari, Mayank Singh
http://arxiv.org/abs/2005.01499v1
• [cs.CV]One-Shot Image Classification by Learning to Restore Prototypes
Wanqi Xue, Wei Wang
http://arxiv.org/abs/2005.01234v1
• [cs.CV]PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data
Zheng Tang, Milind Naphade, Stan Birchfield, Jonathan Tremblay, William Hodge, Ratnesh Kumar, Shuo Wang, Xiaodong Yang
http://arxiv.org/abs/2005.00673v1
• [cs.CV]Projection Inpainting Using Partial Convolution for Metal Artifact Reduction
Lin Yuan, Yixing Huang, Andreas Maier
http://arxiv.org/abs/2005.00762v1
• [cs.CV]Quadtree Driven Lossy Event Compression
Srutarshi Banerjee, Zihao W. Wang, Henry H. Chopp, Oliver Cossairt, Aggelos Katsaggelos
http://arxiv.org/abs/2005.00974v1
• [cs.CV]Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities
Gong Cheng, Xingxing Xie, Junwei Han, Lei Guo, Gui-Song Xia
http://arxiv.org/abs/2005.01094v1
• [cs.CV]SAMP: Shape and Motion Priors for 4D Vehicle Reconstruction
Francis Engelmann, Jörg Stückler, Bastian Leibe
http://arxiv.org/abs/2005.00922v1
• [cs.CV]Tensor optimal transport, distance between sets of measures and tensor scaling
Shmuel Friedland
http://arxiv.org/abs/2005.00945v1
• [cs.CV]Transforming and Projecting Images into Class-conditional Generative Networks
Minyoung Huh, Richard Zhang, Jun-Yan Zhu, Sylvain Paris, Aaron Hertzmann
http://arxiv.org/abs/2005.01703v1
• [cs.CV]Using Artificial Intelligence to Analyze Fashion Trends
Mengyun Shi, Van Dyk Lewis
http://arxiv.org/abs/2005.00986v1
• [cs.CV]Visual Question Answering with Prior Class Semantics
Violetta Shevchenko, Damien Teney, Anthony Dick, Anton van den Hengel
http://arxiv.org/abs/2005.01239v1
• [cs.CV]VisualEchoes: Spatial Image Representation Learning through Echolocation
Ruohan Gao, Changan Chen, Ziad Al-Halah, Carl Schissler, Kristen Grauman
http://arxiv.org/abs/2005.01616v1
• [cs.CY]An Integrated Framework for Sensing Radio Frequency Spectrum Attacks on Medical Delivery Drones
Philip H. Kulp, Nagi Mei
http://arxiv.org/abs/2005.01503v1
• [cs.CY]Digital Sand: The Becoming of Digital Representations
Thomas Østerlie, Eric Monteiro
http://arxiv.org/abs/2005.01121v1
• [cs.CY]Dimensions of Diversity in Human Perceptions of Algorithmic Fairness
Nina Grgić-Hlača, Adrian Weller, Elissa M. Redmiles
http://arxiv.org/abs/2005.00808v1
• [cs.CY]Discussion of digital gaming’s impact on players’ well-being during the COVID-19 lockdown
Hiroko Oe
http://arxiv.org/abs/2005.00594v1
• [cs.CY]Open Loop In Natura Economic Planning
Spyridon Samothrakis
http://arxiv.org/abs/2005.01539v1
• [cs.CY]Quantifying human mobility behavior changes in response to non-pharmaceutical interventions during the COVID-19 outbreak in the United States
Yixuan Pan, Aref Darzi, Aliakbar Kabiri, Guangchen Zhao, Weiyu Luo, Chenfeng Xiong, Lei Zhang
http://arxiv.org/abs/2005.01224v1
• [cs.CY]Workshops on Extreme Scale Design Automation (ESDA) Challenges and Opportunities for 2025 and Beyond
R. Iris Bahar, Alex K. Jones, Srinivas Katkoori, Patrick H. Madden, Diana Marculescu, Igor L. Markov
http://arxiv.org/abs/2005.01588v1
• [cs.DB]Knowledge Graph Validation
Elwin Huaman, Elias Kärle, Dieter Fensel
http://arxiv.org/abs/2005.01389v1
• [cs.DB]SEPAR: A Privacy-Preserving Blockchain-based System for Regulating Multi-Platform Crowdworking Environments
Mohammad Javad Amiri, Joris Duguépéroux, Tristan Allard, Divyakant Agrawal, Amr El Abbadi
http://arxiv.org/abs/2005.01038v1
• [cs.DC]An Extensible, Scalable Spark Platform for Alignment-free Genomic Analysis — Version 1
Umberto Ferraro Petrillo, Francesco Palini, Giuseppe Cattaneo, Raffaele Giancarlo
http://arxiv.org/abs/2005.00942v1
• [cs.DC]Binding of Endpoints to Identifiers by On-Chain Proofs
Diego Pennino, Maurizio Pizzonia, Andrea Vitaletti, Marco Zecchini
http://arxiv.org/abs/2005.00794v1
• [cs.DC]How deep the machine learning can be
János Végh
http://arxiv.org/abs/2005.00872v1
• [cs.DC]MARS: Multi-Scalable Actor-Critic Reinforcement Learning Scheduler
Betis Baheri, Qiang Guan
http://arxiv.org/abs/2005.01584v1
• [cs.DC]On the Design of Co-operating Blockchains for IoT
Gokhan Sagirlar, John D. Sheehan, Emanuele Ragnoli
http://arxiv.org/abs/2005.00658v1
• [cs.DL]Examining Citations of Natural Language Processing Literature
Saif M. Mohammad
http://arxiv.org/abs/2005.00912v1
• [cs.DL]Gender Gap in Natural Language Processing Research: Disparities in Authorship and Citations
Saif M. Mohammad
http://arxiv.org/abs/2005.00962v1
• [cs.DS]A Study of Performance of Optimal Transport
Yihe Dong, Yu Gao, Richard Peng, Ilya Razenshteyn, Saurabh Sawlani
http://arxiv.org/abs/2005.01182v1
• [cs.DS]Online Learning and Optimization for Revenue Management Problems with Add-on Discounts
David Simchi-Levi, Rui Sun, Huanan Zhang
http://arxiv.org/abs/2005.00947v1
• [cs.ET]Electrically-Tunable Stochasticity for Spin-based Neuromorphic Circuits: Self-Adjusting to Variation
Hossein Pourmeidani
http://arxiv.org/abs/2005.00923v1
• [cs.GR]Lagrangian Neural Style Transfer for Fluids
Byungsoo Kim, Vinicius C. Azevedo, Markus Gross, Barbara Solenthaler
http://arxiv.org/abs/2005.00803v1
• [cs.HC]Crafting, Communality, and Computing: Building on Existing Strengths To Support a Vulnerable Population
Aakash Gautam, Deborah Tatar, Steve Harrison
http://arxiv.org/abs/2005.01459v1
• [cs.HC]Deep ConvLSTM with self-attention for human activity decoding using wearables
Satya P. Singh, Aimé Lay-Ekuakille, Deepak Gangwar, Madan Kumar Sharma, Sukrit Gupta
http://arxiv.org/abs/2005.00698v1
• [cs.HC]Human Strategic Steering Improves Performance of Interactive Optimization
Fabio Colella, Pedram Daee, Jussi Jokinen, Antti Oulasvirta, Samuel Kaski
http://arxiv.org/abs/2005.01291v1
• [cs.HC]Investigating the Effects of Robot Engagement Communication on Learning from Demonstration
Mingfei Sun, Zhenhui Peng, Meng Xia, Xiaojuan Ma
http://arxiv.org/abs/2005.01020v1
• [cs.IR]EngMeta — Metadata for Computational Engineering
Björn Schembera, Dorothea Iglezakis
http://arxiv.org/abs/2005.01637v1
• [cs.IR]Extracting Entities and Topics from News and Connecting Criminal Records
Quang Pham, Marija Stanojevic, Zoran Obradovic
http://arxiv.org/abs/2005.00950v1
• [cs.IR]FairMatch: A Graph-based Approach for Improving Aggregate Diversity in Recommender Systems
Masoud Mansoury, Himan Abdollahpouri, Mykola Pechenizkiy, Bamshad Mobasher, Robin Burke
http://arxiv.org/abs/2005.01148v1
• [cs.IR]Ten Questions in Lifelog Mining and Information Recall
An-Zi Yen, Hen-Hsen Huang, Hsin-Hsi Chen
http://arxiv.org/abs/2005.01535v1
• [cs.IR]The Newspaper Navigator Dataset: Extracting And Analyzing Visual Content from 16 Million Historic Newspaper Pages in Chronicling America
Benjamin Charles Germain Lee, Jaime Mears, Eileen Jakeway, Meghan Ferriter, Chris Adams, Nathan Yarasavage, Deborah Thomas, Kate Zwaard, Daniel S. Weld
http://arxiv.org/abs/2005.01583v1
• [cs.IR]Visualization of Diseases at Risk in the COVID-19 Literature
Francis Wolinski
http://arxiv.org/abs/2005.00848v1
• [cs.IT]Can Terahertz Provide High-Rate Reliable Low Latency Communications for Wireless VR?
Christina Chaccour, Mehdi Naderi Soorki, Walid Saad, Mehdi Bennis, Petar Popovski
http://arxiv.org/abs/2005.00536v1
• [cs.IT]Conditional Rényi entropy and the relationships between Rényi capacities
Gautam Aishwarya, Mokshay Madiman
http://arxiv.org/abs/2005.00876v1
• [cs.IT]Effect of Correlation between Information and Energy Links in Secure Wireless Powered Communications
Antonio Tarrías-Muñoz, José Luis Matez-Bandera, Pablo Ramírez-Espinosa, F. Javier López-Martínez
http://arxiv.org/abs/2005.01648v1
• [cs.IT]FDMA with Layers-based Optimized Mobile Relays Subsets Algorithm in B5G/6G Cognitive IoT Networks
He Huang
http://arxiv.org/abs/2005.01384v1
• [cs.IT]Intelligent Reflecting Surface Assisted Multi-User MISO Communication: Channel Estimation and Beamforming Design
Qurrat-Ul-Ain Nadeem, Hibatallah Alwazani, Abla Kammoun, Anas Chaaban, Merouane Debbah, Mohamed-Slim Alouini
http://arxiv.org/abs/2005.01301v1
• [cs.IT]Intelligent Reflecting Surface Enhanced Millimeter-Wave NOMA Systems
Jiakuo Zuo, Yuanwei Liu, Ertugrul Basar, Octavia A. Dobre
http://arxiv.org/abs/2005.01562v1
• [cs.IT]Intra-Channel Nonlinearity Compensation Based on Second-Order Perturbation Theory
O. S. Sunish Kumar, A. Amari, O. A. Dobre, R. Venkatesan
http://arxiv.org/abs/2005.01191v1
• [cs.IT]Millimeter-Wave Beam Search with Iterative Deactivation and Beam Shifting
Chunshan Liu, Min Li, Lou Zhao, Philip Whiting, Stephen V. Hanly, Iain B. Collings
http://arxiv.org/abs/2005.00968v1
• [cs.IT]New families of self-dual codes
Lin Sok
http://arxiv.org/abs/2005.00726v1
• [cs.IT]On Secure Coded Caching via Combinatorial Method
Minquan Cheng, Dequan Liang, Ruizhong Wei
http://arxiv.org/abs/2005.01043v1
• [cs.IT]Optimal Detection Interval for Absorbing Receivers in Molecular Communication Systems with Interference
Trang Ngoc Cao, Nikola Zlatanov, Phee Lep Yeoh, Jamie S. Evans
http://arxiv.org/abs/2005.00948v1
• [cs.IT]Towards Reconfigurable Intelligent Surfaces Powered Green Wireless Networks
Siyuan Sun, Min Fu, Yuanming Shi, Yong Zhou
http://arxiv.org/abs/2005.01514v1
• [cs.LG]A Causal View on Robustness of Neural Networks
Cheng Zhang, Kun Zhang, Yingzhen Li
http://arxiv.org/abs/2005.01095v1
• [cs.LG]A Concise yet Effective model for Non-Aligned Incomplete Multi-view and Missing Multi-label Learning
Xiang Li, Songcan Chen
http://arxiv.org/abs/2005.00976v1
• [cs.LG]A Dynamical Mean-Field Theory for Learning in Restricted Boltzmann Machines
Burak Çakmak, Manfred Opper
http://arxiv.org/abs/2005.01560v1
• [cs.LG]A Finite Time Analysis of Two Time-Scale Actor Critic Methods
Yue Wu, Weitong Zhang, Pan Xu, Quanquan Gu
http://arxiv.org/abs/2005.01350v1
• [cs.LG]A Probabilistic Generative Model for Typographical Analysis of Early Modern Printing
Kartik Goyal, Chris Dyer, Christopher Warren, Max G’Sell, Taylor Berg-Kirkpatrick
http://arxiv.org/abs/2005.01646v1
• [cs.LG]A Solution for Large Scale Nonlinear Regression with High Rank and Degree at Constant Memory Complexity via Latent Tensor Reconstruction
Sandor Szedmak, Anna Cichonska, Heli Julkunen, Tapio Pahikkala, Juho Rousu
http://arxiv.org/abs/2005.01538v1
• [cs.LG]A survey on modern trainable activation functions
Andrea Apicella, Francesco Donnarumma, Francesco Isgrò, Roberto Prevete
http://arxiv.org/abs/2005.00817v1
• [cs.LG]Adaptive Learning of the Optimal Mini-Batch Size of SGD
Motasem Alfarra, Slavomir Hanzely, Alyazeed Albasyoni, Bernard Ghanem, Peter Richtarik
http://arxiv.org/abs/2005.01097v1
• [cs.LG]An empirical comparison of deep-neural-network architectures for next activity prediction using context-enriched process event logs
S. Weinzierl, S. Zilker, J. Brunk, K. Revoredo, A. Nguyen, M. Matzner, J. Becker, B. Eskofier
http://arxiv.org/abs/2005.01194v1
• [cs.LG]Autoencoders for strategic decision support
Sam Verboven, Jeroen Berrevoets, Chris Wuytens, Bart Baesens, Wouter Verbeke
http://arxiv.org/abs/2005.01075v1
• [cs.LG]Ball k-means
Shuyin Xia, Daowan Peng, Deyu Meng, Changqing Zhang, Guoyin Wang, Zizhong Chen, Wei Wei
http://arxiv.org/abs/2005.00784v1
• [cs.LG]Categorized Bandits
Matthieu Jedor, Jonathan Louedec, Vianney Perchet
http://arxiv.org/abs/2005.01656v1
• [cs.LG]Cost Effective Optimization for Cost-related Hyperparameters
Qingyun Wu, Chi Wang, Silu Huang
http://arxiv.org/abs/2005.01571v1
• [cs.LG]Decision Support for Intoxication Prediction Using Graph Convolutional Networks
Hendrik Burwinkel, Matthias Keicher, David Bani-Harouni, Tobias Zellner, Florian Eyer, Nassir Navab, Seyed-Ahmad Ahmadi
http://arxiv.org/abs/2005.00840v1
• [cs.LG]Deep Reinforcement Learning for Intelligent Transportation Systems: A Survey
Ammar Haydari, Yasin Yilmaz
http://arxiv.org/abs/2005.00935v1
• [cs.LG]Demystifying a Dark Art: Understanding Real-World Machine Learning Model Development
Angela Lee, Doris Xin, Doris Lee, Aditya Parameswaran
http://arxiv.org/abs/2005.01520v1
• [cs.LG]Differentially Private Generation of Small Images
Justus T. C. Schwabedal, Pascal Michel, Mario S. Riontino
http://arxiv.org/abs/2005.00783v1
• [cs.LG]Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware?
Marco Melis, Michele Scalas, Ambra Demontis, Davide Maiorca, Battista Biggio, Giorgio Giacinto, Fabio Roli
http://arxiv.org/abs/2005.01452v1
• [cs.LG]Evaluating and Aggregating Feature-based Model Explanations
Umang Bhatt, Adrian Weller, José M. F. Moura
http://arxiv.org/abs/2005.00631v1
• [cs.LG]Explaining AI-based Decision Support Systems using Concept Localization Maps
Adriano Lucieri, Muhammad Naseer Bajwa, Andreas Dengel, Sheraz Ahmed
http://arxiv.org/abs/2005.01399v1
• [cs.LG]Explaining How Deep Neural Networks Forget by Deep Visualization
Giang Nguyen, Shuan Chen, Tae Joon Jun, Daeyoung Kim
http://arxiv.org/abs/2005.01004v1
• [cs.LG]ForecastQA: Machine Comprehension of Temporal Text for Answering Forecasting Questions
Woojeong Jin, Suji Kim, Xiang Ren
http://arxiv.org/abs/2005.00792v1
• [cs.LG]Generalized Reinforcement Meta Learning for Few-Shot Optimization
Raviteja Anantha, Stephen Pulman, Srinivas Chappidi
http://arxiv.org/abs/2005.01246v1
• [cs.LG]Graph Homomorphism Convolution
Hoang NT, Takanori Maehara
http://arxiv.org/abs/2005.01214v1
• [cs.LG]Guarantees on learning depth-2 neural networks under a data-poisoning attack
Anirbit Mukherjee, Ramchandran Muthukumar
http://arxiv.org/abs/2005.01699v1
• [cs.LG]Hierarchical Decomposition of Nonlinear Dynamics and Control for System Identification and Policy Distillation
Hany Abdulsamad, Jan Peters
http://arxiv.org/abs/2005.01432v1
• [cs.LG]High-Dimensional Robust Mean Estimation via Gradient Descent
Yu Cheng, Ilias Diakonikolas, Rong Ge, Mahdi Soltanolkotabi
http://arxiv.org/abs/2005.01378v1
• [cs.LG]If You Like It, GAN It. Probabilistic Multivariate Times Series Forecast With GAN
Alireza Koochali, Andreas Dengel, Sheraz Ahmed
http://arxiv.org/abs/2005.01181v1
• [cs.LG]Knowledge Base Completion: Baseline strikes back (Again)
Prachi Jain, Sushant Rathi, Mausam, Soumen Chakrabarti
http://arxiv.org/abs/2005.00804v1
• [cs.LG]LIMEtree: Interactively Customisable Explanations Based on Local Surrogate Multi-output Regression Trees
Kacper Sokol, Peter Flach
http://arxiv.org/abs/2005.01427v1
• [cs.LG]Large-scale Uncertainty Estimation and Its Application in Revenue Forecast of SMEs
Zebang Zhang, Kui Zhao, Kai Huang, Quanhui Jia, Yanming Fang, Quan Yu
http://arxiv.org/abs/2005.00718v1
• [cs.LG]Learning Model Predictive Control for Competitive Autonomous Racing
Lukas Brunke
http://arxiv.org/abs/2005.00826v1
• [cs.LG]Lecture notes: Efficient approximation of kernel functions
Amitabha Bagchi
http://arxiv.org/abs/2005.01566v1
• [cs.LG]Multi-Center Federated Learning
Ming Xie, Guodong Long, Tao Shen, Tianyi Zhou, Xianzhi Wang, Jing Jiang
http://arxiv.org/abs/2005.01026v1
• [cs.LG]Multi-consensus Decentralized Accelerated Gradient Descent
Haishan Ye, Luo Luo, Ziang Zhou, Tong Zhang
http://arxiv.org/abs/2005.00797v1
• [cs.LG]Multivariate Time Series Forecasting Based on Causal Inference with Transfer Entropy and Graph Neural Network
Haoyan Xu, Yida Huang, Ziheng Duan, Jie Feng, Pengyu Song
http://arxiv.org/abs/2005.01185v1
• [cs.LG]Neural Lyapunov Control
Ya-Chien Chang, Nima Roohi, Sicun Gao
http://arxiv.org/abs/2005.00611v1
• [cs.LG]Off-Policy Adversarial Inverse Reinforcement Learning
Samin Yeasar Arnob
http://arxiv.org/abs/2005.01138v1
• [cs.LG]Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems
Sergey Levine, Aviral Kumar, George Tucker, Justin Fu
http://arxiv.org/abs/2005.01643v1
• [cs.LG]On the Generalization Effects of Linear Transformations in Data Augmentation
Sen Wu, Hongyang R. Zhang, Gregory Valiant, Christopher Ré
http://arxiv.org/abs/2005.00695v1
• [cs.LG]Open Graph Benchmark: Datasets for Machine Learning on Graphs
Weihua Hu, Matthias Fey, Marinka Zitnik, Yuxiao Dong, Hongyu Ren, Bowen Liu, Michele Catasta, Jure Leskovec
http://arxiv.org/abs/2005.00687v1
• [cs.LG]PowerPlanningDL: Reliability-Aware Framework for On-Chip Power Grid Design using Deep Learning
Sukanta Dey, Sukumar Nandi, Gaurav Trivedi
http://arxiv.org/abs/2005.01386v1
• [cs.LG]Quantifying Attention Flow in Transformers
Samira Abnar, Willem Zuidema
http://arxiv.org/abs/2005.00928v1
• [cs.LG]Reinforcement Learning for Decentralized Stable Matching
Kshitija Taywade, Judy Goldsmith, Brent Harrison
http://arxiv.org/abs/2005.01117v1
• [cs.LG]Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering
Jicong Fan, Chengrun Yang, Madeleine Udell
http://arxiv.org/abs/2005.01317v1
• [cs.LG]StackGenVis: Alignment of Data, Algorithms, and Models for Stacking Ensemble Learning Using Performance Metrics
Angelos Chatzimparmpas, Rafael M. Martins, Kostiantyn Kucher, Andreas Kerren
http://arxiv.org/abs/2005.01575v1
• [cs.LG]Stochastic Neighbor Embedding of Multimodal Relational Data for Image-Text Simultaneous Visualization
Morihiro Mizutani, Akifumi Okuno, Geewook Kim, Hidetoshi Shimodaira
http://arxiv.org/abs/2005.00670v1
• [cs.LG]Stochastic Sparse Subspace Clustering
Ying Chen, Chun-Guang Li, Chong You
http://arxiv.org/abs/2005.01449v1
• [cs.LG]TIMELY: Pushing Data Movements and Interfaces in PIM Accelerators Towards Local and in Time Domain
Weitao Li, Pengfei Xu, Yang Zhao, Haitong Li, Yuan Xie, Yingyan Lin
http://arxiv.org/abs/2005.01206v1
• [cs.LG]Understanding and Improving Information Transfer in Multi-Task Learning
Sen Wu, Hongyang R. Zhang, Christopher Ré
http://arxiv.org/abs/2005.00944v1
• [cs.LG]wisardpkg — A library for WiSARD-based models
Aluizio S. Lima Filho, Gabriel P. Guarisa, Leopoldo A. D. Lusquino Filho, Luiz F. R. Oliveira, Felipe M. G. Franca, Priscila M. V. Lima
http://arxiv.org/abs/2005.00887v1
• [cs.MM]Towards Deep Learning Methods for Quality Assessment of Computer-Generated Imagery
Markus Utke, Saman Zadtootaghaj, Steven Schmidt, Sebastian Möller
http://arxiv.org/abs/2005.00836v1
• [cs.NE]It is Time for New Perspectives on How to Fight Bloat in GP
Francisco Fernández de Vega, Gustavo Olague, Francisco Chávez, Daniel Lanza, Wolfgang Banzhaf, Erik Goodman
http://arxiv.org/abs/2005.00603v1
• [cs.NE]Lower Bounds for Non-Elitist Evolutionary Algorithms Via Negative Multiplicative Drift
Benjamin Doerr
http://arxiv.org/abs/2005.00853v1
• [cs.NE]Obtaining Basic Algebra Formulas with Genetic Programming and Functional Rewriting
Edwin Camilo Cubides, Jonatan Gomez
http://arxiv.org/abs/2005.01207v1
• [cs.NE]Perfect Edge-Transmitting Recombination of Permutations
Adriaan Merlevede, Carl Troein
http://arxiv.org/abs/2005.01113v1
• [cs.NE]Spiking Neural Networks Hardware Implementations and Challenges: a Survey
Maxence Bouvier, Alexandre Valentian, Thomas Mesquida, François Rummens, Marina Reyboz, Elisa Vianello, Edith Beigné
http://arxiv.org/abs/2005.01467v1
• [cs.NE]System Metamodel Formalism
Patrik Christen
http://arxiv.org/abs/2005.01192v1
• [cs.NE]Towards Efficient Processing and Learning with Spikes: New Approaches for Multi-Spike Learning
Qiang Yu, Shenglan Li, Huajin Tang, Longbiao Wang, Jianwu Dang, Kay Chen Tan
http://arxiv.org/abs/2005.00723v1
• [cs.NE]Type-2 fuzzy reliability redundancy allocation problem and its solution using particle swarm optimization algorithm
Zubair Ashraf, Pranab K. Muhuri, Q. M. Danish Lohani, Mukul L. Roy
http://arxiv.org/abs/2005.00863v1
• [cs.NI]A Machine Learning based Framework for KPI Maximization in Emerging Networks using Mobility Parameters
Joel Shodamola, Usama Masood, Marvin Manalastas, Ali Imran
http://arxiv.org/abs/2005.01474v1
• [cs.NI]Neuromorphic AI Empowered Root Cause Analysis of Faults in Emerging Networks
Shruti Bothe, Usama Masood, Hasan Farooq, Ali Imran
http://arxiv.org/abs/2005.01472v1
• [cs.RO]“Can you do this?” Self-Assessment Dialogues with Autonomous Robots Before, During, and After a Mission
Tyler Frasca, Evan Krause, Ravenna Thielstrom, Matthias Scheutz
http://arxiv.org/abs/2005.01544v1
• [cs.RO]Design-Informed Kinematic Control for Improved Dexterous Teleoperation of a Bilateral Manipulator System
Lasitha Wijayarathne, Juan Vallejo, Anthony Barnum, Zachary Cloutier, Frank L. Hammond III
http://arxiv.org/abs/2005.00739v1
• [cs.RO]Haptic Sequential Monte Carlo Localization for Quadrupedal Locomotion in Vision-Denied Scenarios
Russell Buchanan, Marco Camurri, Maurice Fallon
http://arxiv.org/abs/2005.01567v1
• [cs.RO]Probabilistic Analysis of RRT Trees
Konrad Anand, Luc Devroye
http://arxiv.org/abs/2005.01242v1
• [cs.RO]Proceedings of the 2020 Workshop on Assessing, Explaining, and Conveying Robot Proficiency for Human-Robot Teaming
Aaron Steinfeld, Michael Goodrich
http://arxiv.org/abs/2005.01527v1
• [cs.RO]Robotic Self-Assessment of Competence
Gertjan J. Burghouts, Albert Huizing, Mark A. Neerincx
http://arxiv.org/abs/2005.01546v1
• [cs.RO]SIGVerse: A cloud-based VR platform for research on social and embodied human-robot interaction
Tetsunari Inamura, Yoshiaki Mizuchi
http://arxiv.org/abs/2005.00825v1
• [cs.RO]Supportive Actions for Manipulation in Human-Robot Coworker Teams
Shray Bansal, Rhys Newbury, Wesley Chan, Akansel Cosgun, Aimee Allen, Dana Kulić, Tom Drummond, Charles Isbell
http://arxiv.org/abs/2005.00769v1
• [cs.RO]TEX-CUP: The University of Texas Challenge for Urban Positioning
Lakshay Narula, Daniel M. LaChapelle, Matthew J. Murrian, J. Michael Wooten, Todd E. Humphreys, Elliot de Toldi, Guirec Morvant, Jean-Baptiste Lacambre
http://arxiv.org/abs/2005.00709v1
• [cs.SD]Addressing Missing Labels in Large-scale Sound Event Recognition using a Teacher-student Framework with Loss Masking
Eduardo Fonseca, Shawn Hershey, Manoj Plakal, Daniel P. W. Ellis, Aren Jansen, R. Channing Moore, Xavier Serra
http://arxiv.org/abs/2005.00878v1
• [cs.SE]A Transformer-based Approach for Source Code Summarization
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, Kai-Wei Chang
http://arxiv.org/abs/2005.00653v1
• [cs.SE]Minerva: A Portable Machine Learning Microservice Framework for Traditional Enterprise SaaS Applications
Venkata Duvvuri
http://arxiv.org/abs/2005.00866v1
• [cs.SE]On Systematically Building a Controlled Natural Language for Functional Requirements
Alvaro Veizaga, Mauricio Alferez, Damiano Torre, Mehrdad Sabetzadeh, Lionel Briand
http://arxiv.org/abs/2005.01355v1
• [cs.SE]Pandemic Programming: How COVID-19 affects software developers and how their organizations can help
Paul Ralph, Sebastian Baltes, Gianisa Adisaputri, Richard Torkar, Vladimir Kovalenko, Marcos Kalinowski, Nicole Novielli, Shin Yoo, Xavier Devroey, Xin Tan, Minghui Zhou, Burak Turhan, Rashina Hoda, Hideaki Hata, Gregorio Robles, Amin Milani Fard, Rana Alkadhi
http://arxiv.org/abs/2005.01127v1
• [cs.SE]Storing, preprocessing and analyzing Tweets: Finding the suitable NoSQL system
Souad Amghar, Safae Cherdal, Salma Mouline
http://arxiv.org/abs/2005.01393v1
• [cs.SI]Alleviating the Inconsistency Problem of Applying Graph Neural Network to Fraud Detection
Zhiwei Liu, Yingtong Dou, Philip S. Yu, Yutong Deng, Hao Peng
http://arxiv.org/abs/2005.00625v1
• [cs.SI]Blind Estimation of Eigenvector Centrality from Graph Signals: Beyond Low-pass Filtering
T. Mitchell Roddenberry, Santiago Segarra
http://arxiv.org/abs/2005.00659v1
• [cs.SI]Information Propagation in Stochastic Networks
Peter Laszlo Juhasz
http://arxiv.org/abs/2005.00758v1
• [cs.SI]Sentiment Paradoxes in Social Networks: Why Your Friends Are More Positive Than You?
Xinyi Zhou, Shengmin Jin, Reza Zafarani
http://arxiv.org/abs/2005.00731v1
• [eess.AS]Does Visual Self-Supervision Improve Learning of Speech Representations?
Abhinav Shukla, Stavros Petridis, Maja Pantic
http://arxiv.org/abs/2005.01400v1
• [eess.AS]Noise2Weight: On Detecting Payload Weight from Drones Acoustic Emissions
Omar Adel Ibrahim, Savio Sciancalepore, Roberto Di Pietro
http://arxiv.org/abs/2005.01347v1
• [eess.IV]A Comparative Study of Image Quality Assessment Models through Perceptual Optimization
Keyan Ding, Kede Ma, Shiqi Wang, Eero P. Simoncelli
http://arxiv.org/abs/2005.01338v1
• [eess.IV]A Little Bit More: Bitplane-Wise Bit-Depth Recovery
Abhijith Punnappurath, Michael S. Brown
http://arxiv.org/abs/2005.01091v1
• [eess.IV]A Model-driven Deep Neural Network for Single Image Rain Removal
Hong Wang, Qi Xie, Qian Zhao, Deyu Meng
http://arxiv.org/abs/2005.01333v1
• [eess.IV]Boundary-aware Context Neural Network for Medical Image Segmentation
Ruxin Wang, Shuyuan Chen, Chaojie Ji, Jianping Fan, Ye Li
http://arxiv.org/abs/2005.00966v1
• [eess.IV]Deep Convolutional Neural Networks to Diagnose COVID-19 and other Pneumonia Diseases from Posteroanterior Chest X-Rays
Pierre G. B. Moutounet-Cartan
http://arxiv.org/abs/2005.00845v1
• [eess.IV]Deep Generative Adversarial Residual Convolutional Networks for Real-World Super-Resolution
Rao Muhammad Umer, Gian Luca Foresti, Christian Micheloni
http://arxiv.org/abs/2005.00953v1
• [eess.IV]Fusion of visible and infrared images via complex function
Ya. Ye. Khaustov, D. Ye, Ye. Ryzhov, E. Lychkovskyy, Yu. A. Nastishin
http://arxiv.org/abs/2005.01047v1
• [eess.IV]NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results
Kai Zhang, Shuhang Gu, Radu Timofte, Taizhang Shang, Qiuju Dai, Shengchen Zhu, Tong Yang, Yandong Guo, Younghyun Jo, Sejong Yang, Seon Joo Kim, Lin Zha, Jiande Jiang, Xinbo Gao, Wen Lu, Jing Liu, Kwangjin Yoon, Taegyun Jeon, Kazutoshi Akita, Takeru Ooba, Norimichi Ukita, Zhipeng Luo, Yuehan Yao, Zhenyu Xu, Dongliang He, Wenhao Wu, Yukang Ding, Chao Li, Fu Li, Shilei Wen, Jianwei Li, Fuzhi Yang, Huan Yang, Jianlong Fu, Byung-Hoon Kim, JaeHyun Baek, Jong Chul Ye, Yuchen Fan, Thomas S. Huang, Junyeop Lee, Bokyeung Lee, Jungki Min, Gwantae Kim, Kanghyu Lee, Jaihyun Park, Mykola Mykhailych, Haoyu Zhong, Yukai Shi, Xiaojun Yang, Zhijing Yang, Liang Lin, Tongtong Zhao, Jinjia Peng, Huibing Wang, Zhi Jin, Jiahao Wu, Yifu Chen, Chenming Shang, Huanrong Zhang, Jeongki Min, Hrishikesh P S, Densen Puthussery, Jiji C V
http://arxiv.org/abs/2005.01056v1
• [eess.IV]Neural Differential Equations for Single Image Super-resolution
Teven Le Scao
http://arxiv.org/abs/2005.00865v1
• [eess.IV]Towards Occlusion-Aware Multifocal Displays
Jen-Hao Rick Chang, Anat Levin, B. V. K. Vijaya Kumar, Aswin C. Sankaranarayanan
http://arxiv.org/abs/2005.00946v1
• [eess.SP]Automotive-Radar-Based 50-cm Urban Positioning
Lakshay Narula, Peter A. Iannucci, Todd E. Humphreys
http://arxiv.org/abs/2005.00704v1
• [eess.SP]Compressed-Sensing based Beam Detection in 5G NR Initial Access
Junmo Sung, Brian L. Evans
http://arxiv.org/abs/2005.00919v1
• [eess.SP]Deep Feature Mining via Attention-based BiLSTM-GCN for Human Motor Imagery Recognition
Yimin Hou, Shuyue Jia, Shu Zhang, Xiangmin Lun, Yan Shi, Yang Li, Hanrui Yang, Rui Zeng, Jinglei Lv
http://arxiv.org/abs/2005.00777v1
• [eess.SP]Lupulus: A Flexible Hardware Accelerator for Neural Networks
Andreas Toftegaard Kristensen, Robert Giterman, Alexios Balatsoukas-Stimming, Andreas Burg
http://arxiv.org/abs/2005.01016v1
• [eess.SP]PPG2ABP: Translating Photoplethysmogram (PPG) Signals to Arterial Blood Pressure (ABP) Waveforms using Fully Convolutional Neural Networks
Nabil Ibtehaz, M. Sohel Rahman
http://arxiv.org/abs/2005.01669v1
• [eess.SP]Predicting the Path Loss of Wireless Channel Models Using Machine Learning Techniques in MmWave Urban Communications
Saud Aldossari, Kwang-Cheng Chen
http://arxiv.org/abs/2005.00745v1
• [eess.SP]Robust Adaptive Beam Tracking for Mobile Millimetre Wave Communications
Chunshan Liu, Min Li, Lou Zhao, Philip Whiting, Stephen V. Hanly, Iain B. Collings, Minjian Zhao
http://arxiv.org/abs/2005.00980v1
• [eess.SP]Robust M-Estimation Based Bayesian Cluster Enumeration for Real Elliptically Symmetric Distributions
Christian A. Schroth, Michael Muma
http://arxiv.org/abs/2005.01404v1
• [eess.SP]The Bussgang Decomposition of Non-Linear Systems: Basic Theory and MIMO Extensions
Özlem Tuğfe Demir, Emil Björnson
http://arxiv.org/abs/2005.01597v1
• [eess.SY]Formal Policy Synthesis for Continuous-Space Systems via Reinforcement Learning
Milad Kazemi, Sadegh Soudjani
http://arxiv.org/abs/2005.01319v1
• [hep-ex]Adversarially Learned Anomaly Detection on CMS Open Data: re-discovering the top quark
Oliver Knapp, Guenther Dissertori, Olmo Cerri, Thong Q. Nguyen, Jean-Roch Vlimant, Maurizio Pierini
http://arxiv.org/abs/2005.01598v1
• [math.OC]Accelerated Learning with Robustness to Adversarial Regressors
Joseph E. Gaudio, Anuradha M. Annaswamy, José M. Moreu, Michael A. Bolender, Travis E. Gibson
http://arxiv.org/abs/2005.01529v1
• [math.OC]Multiagent Value Iteration Algorithms in Dynamic Programming and Reinforcement Learning
Dimitri Bertsekas
http://arxiv.org/abs/2005.01627v1
• [math.OC]On the Convergence Rate of Projected Gradient Descent for a Back-Projection based Objective
Tom Tirer, Raja Giryes
http://arxiv.org/abs/2005.00959v1
• [math.OC]Riemannian Stochastic Proximal Gradient Methods for Nonsmooth Optimization over the Stiefel Manifold
Bokun Wang, Shiqian Ma, Lingzhou Xue
http://arxiv.org/abs/2005.01209v1
• [math.PR]Linear spectral statistics of eigenvectors of anisotropic sample covariance matrices
Fan Yang
http://arxiv.org/abs/2005.00999v1
• [math.ST]A Powerful Portmanteau Test for Detecting Nonlinearity in Time Series
Esam Mahdi
http://arxiv.org/abs/2005.00971v1
• [math.ST]Bootstrapping Persistent Betti Numbers and Other Stabilizing Statistics
Benjamin Roycraft, Johannes Krebs, Wolfgang Polonik
http://arxiv.org/abs/2005.01417v1
• [math.ST]Constraint-Based Causal Discovery In The Presence Of Cycles
Joris M. Mooij, Tom Claassen
http://arxiv.org/abs/2005.00610v1
• [math.ST]Gaussian linear model selection in a dependent context
Emmanuel Caron, Jérôme Dedecker, Bertrand Michel
http://arxiv.org/abs/2005.01058v1
• [math.ST]How many modes can a constrained Gaussian mixture have?
Navin Kashyap, Manjunath Krishnapur
http://arxiv.org/abs/2005.01580v1
• [math.ST]Inference for nonstationary time series of counts with application to change-point problems
William Kengne, Isidore Séraphin Ngongo
http://arxiv.org/abs/2005.00934v1
• [math.ST]Limit theorem associated with Wishart matrices with application to hypothesis testing for common principal components
Koji Tsukuda, Shun Matsuura
http://arxiv.org/abs/2005.01316v1
• [math.ST]Reduced Rank Multivariate Kernel Ridge Regression
Wenjia Wang, Yi-Hui Zhou
http://arxiv.org/abs/2005.01559v1
• [math.ST]Uncertainty quantification in the stochastic block model with an unknown number of classes
J. van Waaij, B. J. K. Kleijn
http://arxiv.org/abs/2005.01362v1
• [nlin.AO]Physical reservoir computing — An introductory perspective
Kohei Nakajima
http://arxiv.org/abs/2005.00992v1
• [physics.ao-ph]Filtering Internal Tides From Wide-Swath Altimeter Data Using Convolutional Neural Networks
Redouane Lguensat, Ronan Fablet, Julien Le Sommer, Sammy Metref, Emmanuel Cosme, Kaouther Ouenniche, Lucas Drumetz, Jonathan Gula
http://arxiv.org/abs/2005.01090v1
• [physics.comp-ph]Dynamic Compressed Sensing for Real-Time Tomographic Reconstruction
Jonathan Schwartz, Huihuo Zheng, Marcus Hanwell, Yi Jiang, Robert Hovden
http://arxiv.org/abs/2005.01662v1
• [physics.med-ph]Monte Carlo modeling photon-tissue interaction using on-demand cloud infrastructure
Ethan P. M. LaRochelle, Pedro Arce, Brian W. Pogue
http://arxiv.org/abs/2005.01108v1
• [physics.soc-ph]A study of the U.S. domestic air transportation network: Temporal evolution of network topology and robustness from 2001 to 2016
Leonidas Siozos-Rousoulis, Dimitri Robert, Wouter Verbeke
http://arxiv.org/abs/2005.01101v1
• [physics.soc-ph]Complex social contagion induces bistability on multiplex networks
Longzhao Liu, Xin Wang, Shaoting Tang, Zhiming Zheng
http://arxiv.org/abs/2005.00664v1
• [physics.soc-ph]Interplay between $k$-core and community structure in complex networks
Irene Malvestio, Alessio Cardillo, Naoki Masuda
http://arxiv.org/abs/2005.01147v1
• [physics.soc-ph]Learning Geo-Contextual Embeddings for Commuting Flow Prediction
Zhicheng Liu, Fabio Miranda, Weiting Xiong, Junyan Yang, Qiao Wang, Claudio T. Silva
http://arxiv.org/abs/2005.01690v1
• [physics.soc-ph]Lived population density and the spread of COVID-19
Dave Babbitt, Patrick Garland, Oliver Johnson
http://arxiv.org/abs/2005.01167v1
• [q-bio.GN]Computational modelling in single-cell cancer genomics: methods and future directions
Allen W Zhang, Kieran R Campbell
http://arxiv.org/abs/2005.01549v1
• [q-fin.RM]Neural Networks and Value at Risk
Alexander Arimond, Damian Borth, Andreas Hoepner, Michael Klawunn, Stefan Weisheit
http://arxiv.org/abs/2005.01686v1
• [q-fin.RM]Tail Granger causalities and where to find them: extreme risk spillovers vs. spurious linkages
Piero Mazzarisi, Silvia Zaoli, Carlo Campajola, Fabrizio Lillo
http://arxiv.org/abs/2005.01160v1
• [q-fin.ST]Ensemble Forecasting for Intraday Electricity Prices: Simulating Trajectories
Michał Narajewski, Florian Ziel
http://arxiv.org/abs/2005.01365v1
• [quant-ph]Setting up experimental Bell test with reinforcement learning
Alexey A. Melnikov, Pavel Sekatski, Nicolas Sangouard
http://arxiv.org/abs/2005.01697v1
• [stat.AP]Data-Driven Modeling Reveals the Impact of Stay-at-Home Orders on Human Mobility during the COVID-19 Pandemic in the U.S
Chenfeng Xiong, Songhua Hu, Mofeng Yang, Hannah N Younes, Weiyu Luo, Sepehr Ghader, Lei Zhang
http://arxiv.org/abs/2005.00667v1
• [stat.AP]Estimation of COVID-19 spread curves integrating global data and borrowing information
Se Yoon Lee, Bowen Lei, Bani K. Mallick
http://arxiv.org/abs/2005.00662v1
• [stat.AP]Generalized Knowledge Tracing: A Constrained Framework for Learner Modeling
Philip I. Pavlik, Jr., Luke G. Eglington, Leigh M. Harrell-Williams
http://arxiv.org/abs/2005.00869v1
• [stat.AP]How Large is too Large? A Review of the Issues related to Sample Size Requirements of Regional Household Travel Surveys with a Case Study on the Greater Toronto and Hamilton Area (GTHA)
Khandker Nurul Habib, Wafic El-Assi, Tian Lin
http://arxiv.org/abs/2005.00563v1
• [stat.AP]Integrated Time Series Summarization and Prediction Algorithm and its Application to COVID-19 Data Mining
Mogens Graf Plessen
http://arxiv.org/abs/2005.00592v1
• [stat.AP]Nonparametric Time Series Summary Statistics for High-Frequency Actigraphy Data from Individuals with Advanced Dementia
Keerati Suibkitwanchai, Adam M. Sykulski, Guillermo Perez Algorta, Daniel Waller, Catherine Walshe
http://arxiv.org/abs/2005.01171v1
• [stat.AP]Survival Analysis of Organizational Networks — An Exploratory Study
Paula Lopes, Pedro Campos, Luis Meira-Machado
http://arxiv.org/abs/2005.01481v1
• [stat.CO]Connecting the Dots: Towards Continuous Time Hamiltonian Monte Carlo
Tore Selland Kleppe
http://arxiv.org/abs/2005.01285v1
• [stat.CO]Global sensitivity analysis for stochastic simulators based on generalized lambda surrogate models
X. Zhu, B. Sudret
http://arxiv.org/abs/2005.01309v1
• [stat.ME]A Linear Mixed Model Formulation for Spatio-Temporal Random Processes with Computational Advances for the Separable and Product-Sum Covariances
Michael Dumelle, Jay M. Ver Hoef, Claudio Fuentes, Alix Gitelman
http://arxiv.org/abs/2005.00952v1
• [stat.ME]An efficient and accurate approximation to the distribution of quadratic forms of Gaussian variables
Hong Zhang, Judong Shen, Zheyang Wu
http://arxiv.org/abs/2005.00905v1
• [stat.ME]Confidence intervals of prediction accuracy measures for multivariable prediction models based on the bootstrap-based optimism correction methods
Hisashi Noma, Tomohiro Shinozaki, Katsuhiro Iba, Satoshi Teramukai, Toshi A. Furukawa
http://arxiv.org/abs/2005.01457v1
• [stat.ME]Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise
Gaetano Romano, Guillem Rigaill, Vincent Runge, Paul Fearnhead
http://arxiv.org/abs/2005.01379v1
• [stat.ME]Exact computation of projection regression depth and fast computation of its induced median and other estimators
Yijun Zuo
http://arxiv.org/abs/2005.01262v1
• [stat.ME]High Dimensional Classification for Spatially Dependent Data with Application to Neuroimaging
Yingjie Li, Liangliang Zhang, Tapabrata Maiti
http://arxiv.org/abs/2005.01168v1
• [stat.ME]Nonparametric testing of the dependence structure among points-marks-covariates in spatial point patterns
Jiří Dvořák, Tomáš Mrkvička, Jorge Mateu, Jonatan González
http://arxiv.org/abs/2005.01019v1
• [stat.ME]Pattern-Based Analysis of Time Series: Estimation
Elyas Sabeti, Peter X. K. Song, Alfred O. Hero
http://arxiv.org/abs/2005.00926v1
• [stat.ME]Point process models for sweat gland activation observed with noise
Mikko Kuronen, Mari Myllymäki, Adam Loavenbruck, Aila Särkkä
http://arxiv.org/abs/2005.01517v1
• [stat.ME]ProgPermute: Progressive permutation for a dynamic representation of the robustness of microbiome discoveries
Liangliang Zhang, Yushu Shi, Kim-Anh Do, Christine B. Peterson, Robert R. Jenq
http://arxiv.org/abs/2005.01169v1
• [stat.ME]Rejoinder for the discussion of the paper “A novel algorithmic approach to Bayesian Logic Regression”
Aliaksandr Hubin, Geir Storvik, Florian Frommlet
http://arxiv.org/abs/2005.00605v1
• [stat.ME]Response-adaptive randomization in clinical trials: from myths to practical considerations
David S. Robertson, Kim May Lee, Boryana C. Lopez-Kolkovska, Sofia S. Villar
http://arxiv.org/abs/2005.00564v1
• [stat.ME]Simultaneous Non-Gaussian Component Analysis (SING) for Data Integration in Neuroimaging
Benjamin Risk, Irina Gaynanova
http://arxiv.org/abs/2005.00597v1
• [stat.ML]Mutual Information Gradient Estimation for Representation Learning
Liangjian Wen, Yiji Zhou, Lirong He, Mingyuan Zhou, Zenglin Xu
http://arxiv.org/abs/2005.01123v1
• [stat.ML]Simulation free reliability analysis: A physics-informed deep learning based approach
Souvik Chakraborty
http://arxiv.org/abs/2005.01302v1
• [stat.ML]Sum-Product-Transform Networks: Exploiting Symmetries using Invertible Transformations
Tomas Pevny, Vasek Smidl, Martin Trapp, Ondrej Polacek, Tomas Oberhuber
http://arxiv.org/abs/2005.01297v1