cs.AI - 人工智能
    cs.CC - 计算复杂度
    cs.CG - 计算几何学
    cs.CL - 计算与语言
    cs.CR - 加密与安全
    cs.CV - 机器视觉与模式识别
    cs.CY - 计算与社会
    cs.DB - 数据库
    cs.DC - 分布式、并行与集群计算
    cs.DS - 数据结构与算法
    cs.GR - 计算机图形学
    cs.GT - 计算机科学与博弈论
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LO - 计算逻辑
    cs.MA - 多代理系统
    cs.NE - 神经与进化计算
    cs.PL - 编程语言
    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
    gr-qc - 广义相对论与量子宇宙学
    math-ph - 数学物理
    math.OC - 优化与控制
    math.PR - 概率
    math.ST - 统计理论
    physics.geo-ph - 地球物理学
    physics.optics - 光学
    physics.soc-ph - 物理学与社会
    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.CO - 统计计算
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cs.AI]A Data-Driven Method for Recognizing Automated Negotiation Strategies
    • [cs.AI]Creating Unbiased Public Benchmark Datasets with Data Leakage Prevention for Predictive Process Monitoring
    • [cs.AI]Efficient Explanations for Knowledge Compilation Languages
    • [cs.AI]Ethics Sheets for AI Tasks
    • [cs.AI]Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction
    • [cs.AI]Modeling Interactions of Multimodal Road Users in Shared Spaces
    • [cs.AI]Solving Infinite-Domain CSPs Using the Patchwork Property
    • [cs.AI]Winning at Any Cost — Infringing the Cartel Prohibition With Reinforcement Learning
    • [cs.CC]Average-Case Communication Complexity of Statistical Problems
    • [cs.CG]Learning Delaunay Triangulation using Self-attention and Domain Knowledge
    • [cs.CL]A Knowledge-based Approach for Answering Complex Questions in Persian
    • [cs.CL]Arabic Code-Switching Speech Recognition using Monolingual Data
    • [cs.CL]Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model
    • [cs.CL]Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN
    • [cs.CL]CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction
    • [cs.CL]Coarse-to-Careful: Seeking Semantic-related Knowledge for Open-domain Commonsense Question Answering
    • [cs.CL]Contradiction Detection in Persian Text
    • [cs.CL]Cross-Modal Transformer-Based Neural Correction Models for Automatic Speech Recognition
    • [cs.CL]Deep Learning Schema-based Event Extraction: Literature Review and Current Trends
    • [cs.CL]Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning Models
    • [cs.CL]Domain Adaptation for Sentiment Analysis Using Increased Intraclass Separation
    • [cs.CL]ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
    • [cs.CL]End-to-end Neural Coreference Resolution Revisited: A Simple yet Effective Baseline
    • [cs.CL]FaVIQ: FAct Verification from Information-seeking Questions
    • [cs.CL]IITP at WAT 2021: System description for English-Hindi Multimodal Translation Task
    • [cs.CL]Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence
    • [cs.CL]Neural-Symbolic Solver for Math Word Problems with Auxiliary Tasks
    • [cs.CL]Persian-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation
    • [cs.CL]Scarecrow: A Framework for Scrutinizing Machine Text
    • [cs.CL]The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task
    • [cs.CL]Training Adaptive Computation for Open-Domain Question Answering with Computational Constraints
    • [cs.CL]Unified Autoregressive Modeling for Joint End-to-End Multi-Talker Overlapped Speech Recognition and Speaker Attribute Estimation
    • [cs.CR]A Framework for Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems
    • [cs.CR]Android Malware Category and Family Detection and Identification using Machine Learning
    • [cs.CR]Auxiliary-Classifier GAN for Malware Analysis
    • [cs.CR]ETHTID: Deployable Threshold Information Disclosure on Ethereum
    • [cs.CR]Logic Locking at the Frontiers of Machine Learning: A Survey on Developments and Opportunities
    • [cs.CR]Machine Learning for Malware Evolution Detection
    • [cs.CR]Smoothed Differential Privacy
    • [cs.CR]Subset Privacy: Draw from an Obfuscated Urn
    • [cs.CR]Understanding the Security of Deepfake Detection
    • [cs.CV]6D Object Pose Estimation using Keypoints and Part Affinity Fields
    • [cs.CV]A Novel Disaster Image Dataset and Characteristics Analysis using Attention Model
    • [cs.CV]A topological solution to object segmentation and tracking
    • [cs.CV]Bag of Instances Aggregation Boosts Self-supervised Learning
    • [cs.CV]Cognitive Visual Commonsense Reasoning Using Dynamic Working Memory
    • [cs.CV]Conditional Identity Disentanglement for Differential Face Morph Detection
    • [cs.CV]Continual Contrastive Self-supervised Learning for Image Classification
    • [cs.CV]Data Uncertainty Guided Noise-aware Preprocessing Of Fingerprints
    • [cs.CV]Deep Edge-Aware Interactive Colorization against Color-Bleeding Effects
    • [cs.CV]Demiguise Attack: Crafting Invisible Semantic Adversarial Perturbations with Perceptual Similarity
    • [cs.CV]Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection
    • [cs.CV]Direct Measure Matching for Crowd Counting
    • [cs.CV]Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation
    • [cs.CV]Do Different Tracking Tasks Require Different Appearance Models?
    • [cs.CV]Drone Detection Using Convolutional Neural Networks
    • [cs.CV]Efficient Vision Transformers via Fine-Grained Manifold Distillation
    • [cs.CV]Exploring Data Pipelines through the Process Lens: a Reference Model forComputer Vision
    • [cs.CV]FFR_FD: Effective and Fast Detection of DeepFakes Based on Feature Point Defects
    • [cs.CV]Fast and Scalable Optimal Transport for Brain Tractograms
    • [cs.CV]Faster-LTN: a neuro-symbolic, end-to-end object detection architecture
    • [cs.CV]Gaze Estimation with an Ensemble of Four Architectures
    • [cs.CV]How Incomplete is Contrastive Learning? An Inter-intra Variant Dual Representation Method for Self-supervised Video Recognition
    • [cs.CV]Improving a neural network model by explanation-guided training for glioma classification based on MRI data
    • [cs.CV]Learning Hierarchical Graph Neural Networks for Image Clustering
    • [cs.CV]Learning a Model for Inferring a Spatial Road Lane Network Graph using Self-Supervision
    • [cs.CV]Learning from scarce information: using synthetic data to classify Roman fine ware pottery
    • [cs.CV]MixStyle Neural Networks for Domain Generalization and Adaptation
    • [cs.CV]Multi-View Correlation Distillation for Incremental Object Detection
    • [cs.CV]No-Reference Quality Assessment for Colored Point Cloud and Mesh Based on Natural Scene Statistics
    • [cs.CV]OPA: Object Placement Assessment Dataset
    • [cs.CV]On Model Calibration for Long-Tailed Object Detection and Instance Segmentation
    • [cs.CV]One-Cycle Pruning: Pruning ConvNets Under a Tight Training Budget
    • [cs.CV]Part2Word: Learning Joint Embedding of Point Clouds and Text by Matching Parts to Words
    • [cs.CV]RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting
    • [cs.CV]Ray-ONet: Efficient 3D Reconstruction From A Single RGB Image
    • [cs.CV]Recovering the Unbiased Scene Graphs from the Biased Ones
    • [cs.CV]Robust End-to-End Offline Chinese Handwriting Text Page Spotter with Text Kernel
    • [cs.CV]SM-SGE: A Self-Supervised Multi-Scale Skeleton Graph Encoding Framework for Person Re-Identification
    • [cs.CV]SPI-GAN: Towards Single-Pixel Imaging through Generative Adversarial Network
    • [cs.CV]SSPNet: Scale Selection Pyramid Network for Tiny Person Detection from UAV Images
    • [cs.CV]Scene-aware Learning Network for Radar Object Detection
    • [cs.CV]Self-Contrastive Learning with Hard Negative Sampling for Self-supervised Point Cloud Learning
    • [cs.CV]Semi-supervised Learning for Dense Object Detection in Retail Scenes
    • [cs.CV]Sensor-invariant Fingerprint ROI Segmentation Using Recurrent Adversarial Learning
    • [cs.CV]Similarity-Aware Fusion Network for 3D Semantic Segmentation
    • [cs.CV]Super Resolution in Human Pose Estimation: Pixelated Poses to a Resolution Result?
    • [cs.CV]Test-Time Personalization with a Transformer for Human Pose Estimation
    • [cs.CV]Towards Better Adversarial Synthesis of Human Images from Text
    • [cs.CV]Visual Time Series Forecasting: An Image-driven Approach
    • [cs.CV]Web-Scale Generic Object Detection at Microsoft Bing
    • [cs.CV]What Makes for Hierarchical Vision Transformer?
    • [cs.CY]A Systematic Literature Review of Empiricism and Norms of Reporting in Computing Education Research Literature
    • [cs.CY]DiSH-trend: Intervention Modeling Simulator That Accounts for Trend Influences
    • [cs.CY]Harnessing Context for Budget-Limited Crowdsensing with Massive Uncertain Workers
    • [cs.CY]Implicit Gender Bias in Computer Science — A Qualitative Study
    • [cs.CY]PyLUSAT: An open-source Python toolkit for GIS-based land use suitability analysis
    • [cs.CY]Security implications of digitalization: The dangers of data colonialism and the way towards sustainable and sovereign management of environmental data
    • [cs.DB]Pool of Experts: Realtime Querying Specialized Knowledge in Massive Neural Networks
    • [cs.DC]A Fuzzy Scheduling Strategy for Deadline-Based Workflow Applications in Uncertain Edge-Cloud Environments
    • [cs.DC]Cloud Versus Local Processing in Distributed Networks
    • [cs.DS]Polymorphic dynamic programming by algebraic shortcut fusion
    • [cs.DS]Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering
    • [cs.GR]An Analytical Survey on Recent Trends in High Dimensional Data Visualization
    • [cs.GT]Learning in nonatomic games, Part I: Finite action spaces and population games
    • [cs.HC]Here’s What I’ve Learned: Asking Questions that Reveal Reward Learning
    • [cs.IR]Attribute-aware Explainable Complementary Clothing Recommendation
    • [cs.IR]FINT: Field-aware INTeraction Neural Network For CTR Prediction
    • [cs.IR]FINT: Field-aware INTeraction Neural Network For CTR Prediction
    • [cs.IR]Improved Representation Learning for Session-based Recommendation
    • [cs.IR]Learning Complex Users’ Preferences for Recommender Systems
    • [cs.IR]NOTE: Solution for KDD-CUP 2021 WikiKG90M-LSC
    • [cs.IT]A precise bare simulation approach to the minimization of some distances. Foundations
    • [cs.IT]Age of Information in Relay-Assisted Status Updating Systems
    • [cs.IT]An Information-Theoretic Approach for Automatically Determining the Number of States when Aggregating Markov Chains
    • [cs.IT]Cell-Free Massive MIMO-OFDM Transmission over Frequency-Selective Fading Channels
    • [cs.IT]Erasures repair for decreasing monomial-Cartesian and augmented Reed-Muller codes of high rate
    • [cs.IT]Expanded Gabidulin Codes and Their Application to Cryptography
    • [cs.IT]Impact of Channel Aging on Zero-Forcing Precoding in Cell-Free Massive MIMO Systems
    • [cs.IT]Improved Asymptotic Bounds for Codes Correcting Insertions and Deletions
    • [cs.IT]MIMO Operations in Molecular Communications: Theory, Prototypes, and Open Challenges
    • [cs.IT]Optimum GSSK Transmission in Massive MIMO Systems Using the Box-LASSO Decoder
    • [cs.IT]Physical Layer Security for NOMA-Enabled Multi-Access Edge Computing Wireless Networks
    • [cs.IT]STAR-IOS Aided NOMA Networks: Channel Model Approximation and Performance Analysis
    • [cs.IT]The 今日学术视野(2021.7.7) - 图1-weight distribution for MDS codes
    • [cs.IT]The Curious Case of the Diamond Network
    • [cs.IT]The information loss of a stochastic map
    • [cs.LG]A Comparison of the Delta Method and the Bootstrap in Deep Learning Classification
    • [cs.LG]A Theoretical Analysis of Fine-tuning with Linear Teachers
    • [cs.LG]A Typology of Data Anomalies
    • [cs.LG]A contextual analysis of multi-layer perceptron models in classifying hand-written digits and letters: limited resources
    • [cs.LG]ARM-Net: Adaptive Relation Modeling Network for Structured Data
    • [cs.LG]AdaL: Adaptive Gradient Transformation Contributes to Convergences and Generalizations
    • [cs.LG]Adaptive calibration for binary classification
    • [cs.LG]An Explainable AI System for the Diagnosis of High Dimensional Biomedical Data
    • [cs.LG]Are standard Object Segmentation models sufficient for Learning Affordance Segmentation?
    • [cs.LG]Autoencoder based Randomized Learning of Feedforward Neural Networks for Regression
    • [cs.LG]Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities
    • [cs.LG]BAGUA: Scaling up Distributed Learning with System Relaxations
    • [cs.LG]Bayesian decision-making under misspecified priors with applications to meta-learning
    • [cs.LG]Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks
    • [cs.LG]Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates
    • [cs.LG]CInC Flow: Characterizable Invertible 3x3 Convolution
    • [cs.LG]Certifiably Robust Interpretation via Renyi Differential Privacy
    • [cs.LG]Class Introspection: A Novel Technique for Detecting Unlabeled Subclasses by Leveraging Classifier Explainability Methods
    • [cs.LG]Cluster Representatives Selection in Non-Metric Spaces for Nearest Prototype Classification
    • [cs.LG]Clustering of Time Series Data with Prior Geographical Information
    • [cs.LG]DPPIN: A Biological Dataset of Dynamic Protein-Protein Interaction Networks
    • [cs.LG]Data-Driven Learning of Feedforward Neural Networks with Different Activation Functions
    • [cs.LG]Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning
    • [cs.LG]Designing Machine Learning Pipeline Toolkit for AutoML Surrogate Modeling Optimization
    • [cs.LG]Detecting Concept Drift With Neural Network Model Uncertainty
    • [cs.LG]Detecting Faults during Automatic Screwdriving: A Dataset and Use Case of Anomaly Detection for Automatic Screwdriving
    • [cs.LG]Differentially Private Sliced Wasserstein Distance
    • [cs.LG]Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning
    • [cs.LG]Exact Backpropagation in Binary Weighted Networks with Group Weight Transformations
    • [cs.LG]Examining average and discounted reward optimality criteria in reinforcement learning
    • [cs.LG]Fair Decision Rules for Binary Classification
    • [cs.LG]Fast Rate Learning in Stochastic First Price Bidding
    • [cs.LG]Feature Cross Search via Submodular Optimization
    • [cs.LG]Implicit Greedy Rank Learning in Autoencoders via Overparameterized Linear Networks
    • [cs.LG]Imputation-Free Learning from Incomplete Observations
    • [cs.LG]Incorporating Reachability Knowledge into a Multi-Spatial Graph Convolution Based Seq2Seq Model for Traffic Forecasting
    • [cs.LG]Isotonic Data Augmentation for Knowledge Distillation
    • [cs.LG]KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks
    • [cs.LG]Learning Debiased Representation via Disentangled Feature Augmentation
    • [cs.LG]Learning ODEs via Diffeomorphisms for Fast and Robust Integration
    • [cs.LG]Leveraging Evidential Deep Learning Uncertainties with Graph-based Clustering to Detect Anomalies
    • [cs.LG]Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics
    • [cs.LG]Machine Learning for Fraud Detection in E-Commerce: A Research Agenda
    • [cs.LG]Mava: a research framework for distributed multi-agent reinforcement learning
    • [cs.LG]Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks
    • [cs.LG]Memory and attention in deep learning
    • [cs.LG]Multiple-criteria Based Active Learning with Fixed-size Determinantal Point Processes
    • [cs.LG]On Bi-gram Graph Attributes
    • [cs.LG]On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs
    • [cs.LG]On The Distribution of Penultimate Activations of Classification Networks
    • [cs.LG]Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy
    • [cs.LG]Partition and Code: learning how to compress graphs
    • [cs.LG]Poisoning Attack against Estimating from Pairwise Comparisons
    • [cs.LG]Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective
    • [cs.LG]Provable Convergence of Nesterov Accelerated Method for Over-Parameterized Neural Networks
    • [cs.LG]Randomized Neural Networks for Forecasting Time Series with Multiple Seasonality
    • [cs.LG]Robust Online Convex Optimization in the Presence of Outliers
    • [cs.LG]Robust Restless Bandits: Tackling Interval Uncertainty with Deep Reinforcement Learning
    • [cs.LG]SCOD: Active Object Detection for Embodied Agents using Sensory Commutativity of Action Sequences
    • [cs.LG]SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing
    • [cs.LG]Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation
    • [cs.LG]Short-term probabilistic photovoltaic power forecast based on deep convolutional long short-term memory network and kernel density estimation
    • [cs.LG]Single Model for Influenza Forecasting of Multiple Countries by Multi-task Learning
    • [cs.LG]Spatiotemporal convolutional network for time-series prediction and causal inference
    • [cs.LG]Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network
    • [cs.LG]Subspace Clustering Based Analysis of Neural Networks
    • [cs.LG]Supervised Off-Policy Ranking
    • [cs.LG]Survey: Leakage and Privacy at Inference Time
    • [cs.LG]The Least Restriction for Offline Reinforcement Learning
    • [cs.LG]The MineRL BASALT Competition on Learning from Human Feedback
    • [cs.LG]Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning
    • [cs.LG]Universal Approximation of Functions on Sets
    • [cs.LG]Unsupervised Ensemble Selection for Multilayer Bootstrap Networks
    • [cs.LG]When and How to Fool Explainable Models (and Humans) with Adversarial Examples
    • [cs.LG]Where is the Grass Greener? Revisiting Generalized Policy Iteration for Offline Reinforcement Learning
    • [cs.LG]Why is Pruning at Initialization Immune to Reinitializing and Shuffling?
    • [cs.LO]The Semantics of Package Management via Event Structures
    • [cs.MA]Traffic Signal Control with Communicative Deep Reinforcement Learning Agents: a Case Study
    • [cs.NE]Multi-layer Hebbian networks with modern deep learning frameworks
    • [cs.NE]Q-SpiNN: A Framework for Quantizing Spiking Neural Networks
    • [cs.NE]Uso de GSO cooperativos com decaimentos de pesos para otimizacao de redes neurais
    • [cs.PL]The Composability of Intermediate Values in Composable Inductive Programming
    • [cs.RO]A System for Traded Control Teleoperation of Manipulation Tasks using Intent Prediction from Hand Gestures
    • [cs.RO]Accelerating Kinodynamic RRT* Through Dimensionality Reduction
    • [cs.RO]Advanced turning maneuver of a multi-legged robot using pitchfork bifurcation
    • [cs.RO]Biomimetic Tactile Receptors for 3d-printed Skin
    • [cs.RO]Breaking Barriers in Robotic Soft Tissue Surgery: Conditional Autonomous Intestinal Anastomosis
    • [cs.RO]Carnegie Mellon Team Tartan: Mission-level Robustness with Rapidly Deployed Autonomous Aerial Vehicles in the MBZIRC 2020
    • [cs.RO]Control of rough terrain vehicles using deep reinforcement learning
    • [cs.RO]GraspME — Grasp Manifold Estimator
    • [cs.RO]Hierarchical Policies for Cluttered-Scene Grasping with Latent Plans
    • [cs.RO]Hybrid and dynamic policy gradient optimization for bipedal robot locomotion
    • [cs.RO]Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces
    • [cs.RO]Online and Offline Robot Programming via Augmented Reality Workspaces
    • [cs.RO]Overcoming the Force Limitations of Magnetic Robotic Surgery: Impact-based Tetherless Suturing
    • [cs.RO]Prescient teleoperation of humanoid robots
    • [cs.RO]Row-sensing Templates: A Generic 3D Sensor-based Approach to Robot Localization with Respect to Orchard Row Centerlines
    • [cs.RO]Targeted Muscle Effort Distribution with Exercise Robots: Trajectory and Resistance Effects
    • [cs.RO]Toward Increased Airspace Safety: Quadrotor Guidance for Targeting Aerial Objects
    • [cs.RO]Towards safe human-to-robot handovers of unknown containers
    • [cs.RO]Unified Identification and Tuning Approach Using Deep Neural Networks For Visual Servoing Applications
    • [cs.RO]Using Probabilistic Movement Primitives in Analyzing Human Motion Difference under Transcranial Current Stimulation
    • [cs.SD]A Lottery Ticket Hypothesis Framework for Low-Complexity Device-Robust Neural Acoustic Scene Classification
    • [cs.SD]DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling
    • [cs.SD]Development of a Conversation State Recognition System
    • [cs.SE]Automated Recovery of Issue-Commit Links Leveraging Both Textual and Non-textual Data
    • [cs.SI]A Multilayer Network Model of the Coevolution of the Spread of a Disease and Competing Opinions
    • [cs.SI]Adversarial Robustness of Probabilistic Network Embedding for Link Prediction
    • [cs.SI]Ranking Online Social Users by their Influence
    • [eess.AS]Relaxed Attention: A Simple Method to Boost Performance of End-to-End Automatic Speech Recognition
    • [eess.AS]Towards Neural Diarization for Unlimited Numbers of Speakers Using Global and Local Attractors
    • [eess.IV]A study of CNN capacity applied to Left Venticle Segmentation in Cardiac MRI
    • [eess.IV]COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans
    • [eess.IV]COVID-VIT: Classification of COVID-19 from CT chest images based on vision transformer models
    • [eess.IV]CT Image Harmonization for Enhancing Radiomics Studies
    • [eess.IV]Controllable cardiac synthesis via disentangled anatomy arithmetic
    • [eess.IV]Custom Deep Neural Network for 3D Covid Chest CT-scan Classification
    • [eess.IV]EAR-NET: Error Attention Refining Network For Retinal Vessel Segmentation
    • [eess.IV]Pulmonary Vessel Segmentation based on Orthogonal Fused U-Net++ of Chest CT Images
    • [eess.IV]VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays
    • [eess.IV]WisdomNet: Prognosis of COVID-19 with Slender Prospect of False Negative Cases and Vaticinating the Probability of Maturation to ARDS using Posteroanterior Chest X-Rays
    • [eess.SP]Unbiasing Procedures for Scale-invariant Multi-reference Alignment
    • [gr-qc]On the Efficiency of Various Deep Transfer Learning Models in Glitch Waveform Detection in Gravitational-Wave Data
    • [math-ph]Cleaning large-dimensional covariance matrices for correlated samples
    • [math.OC]The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities
    • [math.OC]Third Party Risk Modelling and Assessment for Safe UAV Path Planning in Metropolitan Environments
    • [math.PR]Random Neural Networks in the Infinite Width Limit as Gaussian Processes
    • [math.ST]Accounting for Uncertainty When Estimating Counts Through an Average Rounded to the Nearest Integer
    • [math.ST]Anisotropic spectral cut-off estimation under multiplicative measurement errors
    • [math.ST]Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing Algorithm
    • [math.ST]Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM
    • [math.ST]Neyman-Pearson Hypothesis Testing, Epistemic Reliability and Pragmatic Value-Laden Asymmetric Error Risks
    • [math.ST]On the symmetric and skew-symmetric K-distributions
    • [math.ST]Rates of Es
    3000
    timation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections
    • [math.ST]Statistical Theory for Imbalanced Binary Classification
    • [physics.geo-ph]A convolutional neural network for prestack fracture detection
    • [physics.optics]Imaging dynamics beneath turbid media via parallelized single-photon detection
    • [physics.soc-ph]Become a better you: correlation between the change of research direction and the change of scientific performance
    • [physics.soc-ph]Directed Percolation in Temporal Networks
    • [physics.soc-ph]Quantifying agent impacts on contact sequences in social interactions
    • [physics.soc-ph]The hidden dependence of spreading vulnerability on topological complexity
    • [q-bio.NC]Data-driven mapping between functional connectomes using optimal transport
    • [q-bio.NC]Lonely individuals process the world in idiosyncratic ways
    • [q-bio.PE]Principled, practical, flexible, fast: a new approach to phylogenetic factor analysis
    • [quant-ph]QKSA: Quantum Knowledge Seeking Agent
    • [quant-ph]Quantum Error Mitigation Relying on Permutation Filtering
    • [quant-ph]Sets of Marginals and Pearson-Correlation-based CHSH Inequalities for a Two-Qubit System
    • [stat.AP]An extended watershed-based zonal statistical AHP model for flood risk estimation: Constraining runoff converging related indicators by sub-watersheds
    • [stat.AP]Uncertainty in Lung Cancer Stage for Outcome Estimation via Set-Valued Classification
    • [stat.CO]Variational Bayesian Inference for the Polytomous-Attribute Saturated Diagnostic Classification Model with Parallel Computing
    • [stat.ME]Analyzing Relevance Vector Machines using a single penalty approach
    • [stat.ME]Assessing contribution of treatment phases through tipping point analyses via counterfactual elicitation using rank preserving structural failure time models
    • [stat.ME]Bayesian two-interval test
    • [stat.ME]Blind source separation for non-stationary random fields
    • [stat.ME]Calibrating generalized predictive distributions
    • [stat.ME]Discussion of the manuscript: Spatial+ a novel approach to spatial confounding
    • [stat.ME]Extending Latent Basis Growth Model to Explore Joint Development in the Framework of Individual Measurement Occasions
    • [stat.ME]Matching a Desired Causal State via Shift Interventions
    • [stat.ME]Multivariate functional group sparse regression: functional predictor selection
    • [stat.ME]Nonparametric Detection of Multiple Location-Scale Change Points via Wild Binary Segmentation
    • [stat.ME]Nonparametric quantile regression for time series with replicated observations and its application to climate data
    • [stat.ME]Novel Semi-parametric Tobit Additive Regression Models
    • [stat.ME]On the Estimation of Bivariate Return Curves for Extreme Values
    • [stat.ME]One-step TMLE to target cause-specific absolute risks and survival curves
    • [stat.ME]Proportional mean model for panel count data with multiple modes of recurrence
    • [stat.ME]Selection of invalid instruments can improve estimation in Mendelian randomization
    • [stat.ME]Sibling Regression for Generalized Linear Models
    • [stat.ME]Sufficient principal component regression for pattern discovery in transcriptomic data
    • [stat.ME]The Effect of the Prior and the Experimental Design on the Inference of the Precision Matrix in Gaussian Chain Graph Models
    • [stat.ME]Zero-modified Count Time Series with Markovian Intensities
    • [stat.ML]A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the k-Triangle-Faithfulness Assumption
    • [stat.ML]Antithetic Riemannian Manifold And Quantum-Inspired Hamiltonian Monte Carlo
    • [stat.ML]Causally Invariant Predictor with Shift-Robustness
    • [stat.ML]Deep Gaussian Process Emulation using Stochastic Imputation
    • [stat.ML]Latent structure blockmodels for Bayesian spectral graph clustering
    • [stat.ML]Learning Bayesian Networks through Birkhoff Polytope: A Relaxation Method
    • [stat.ML]Minimum Wasserstein Distance Estimator under Finite Location-scale Mixtures
    • [stat.ML]Optimizing ROC Curves with a Sort-Based Surrogate Loss Function for Binary Classification and Changepoint Detection
    • [stat.ML]Scale Mixtures of Neural Network Gaussian Processes
    • [stat.ML]Slope and generalization properties of neural networks
    • [stat.ML]Template-Based Graph Clustering
    • [stat.ML]The Role of “Live” in Livestreaming Markets: Evidence Using Orthogonal Random Forest
    • [stat.ML]Tiled Squeeze-and-Excite: Channel Attention With Local Spatial Context
    • [stat.ML]UCSL : A Machine Learning Expectation-Maximization framework for Unsupervised Clustering driven by Supervised Learning

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

    • [cs.AI]A Data-Driven Method for Recognizing Automated Negotiation Strategies
    Ming Li, Pradeep K. Murukannaiah, Catholijn M. Jonker
    http://arxiv.org/abs/2107.01496v1

    • [cs.AI]Creating Unbiased Public Benchmark Datasets with Data Leakage Prevention for Predictive Process Monitoring
    Hans Weytjens, Jochen De Weerdt
    http://arxiv.org/abs/2107.01905v1

    • [cs.AI]Efficient Explanations for Knowledge Compilation Languages
    Xuanxiang Huang, Yacine Izza, Alexey Ignatiev, Martin C. Cooper, Nicholas Asher, Joao Marques-Silva
    http://arxiv.org/abs/2107.01654v1

    • [cs.AI]Ethics Sheets for AI Tasks
    Saif M. Mohammad
    http://arxiv.org/abs/2107.01183v2

    • [cs.AI]Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction
    Assaf Hallak, Gal Dalal, Steven Dalton, Iuri Frosio, Shie Mannor, Gal Chechik
    http://arxiv.org/abs/2107.01715v1

    • [cs.AI]Modeling Interactions of Multimodal Road Users in Shared Spaces
    Fatema T. Johora, Jörg P. Müller
    http://arxiv.org/abs/2107.02083v1

    • [cs.AI]Solving Infinite-Domain CSPs Using the Patchwork Property
    Konrad K. Dabrowski, Peter Jonsson, Sebastian Ordyniak, George Osipov
    http://arxiv.org/abs/2107.01428v1

    • [cs.AI]Winning at Any Cost — Infringing the Cartel Prohibition With Reinforcement Learning
    Michael Schlechtinger, Damaris Kosack, Heiko Paulheim, Thomas Fetzer
    http://arxiv.org/abs/2107.01856v1

    • [cs.CC]Average-Case Communication Complexity of Statistical Problems
    Cyrus Rashtchian, David P. Woodruff, Peng Ye, Hanlin Zhu
    http://arxiv.org/abs/2107.01335v1

    • [cs.CG]Learning Delaunay Triangulation using Self-attention and Domain Knowledge
    Jaeseung Lee, Woojin Choi, Jibum Kim
    http://arxiv.org/abs/2107.01759v1

    • [cs.CL]A Knowledge-based Approach for Answering Complex Questions in Persian
    Romina Etezadi, Mehrnoush Shamsfard
    http://arxiv.org/abs/2107.02040v1

    • [cs.CL]Arabic Code-Switching Speech Recognition using Monolingual Data
    Ahmed Ali, Shammur Chowdhury, Amir Hussein, Yasser Hifny
    http://arxiv.org/abs/2107.01573v1

    • [cs.CL]Audio-Oriented Multimodal Machine Comprehension: Task, Dataset and Model
    Zhiqi Huang, Fenglin Liu, Xian Wu, Shen Ge, Helin Wang, Wei Fan, Yuexian Zou
    http://arxiv.org/abs/2107.01571v1

    • [cs.CL]Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN
    Rahma Chaabouni, Roberto Dessì, Eugene Kharitonov
    http://arxiv.org/abs/2107.01366v1

    • [cs.CL]CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction
    Jiawei Sheng, Shu Guo, Bowen Yu, Qian Li, Yiming Hei, Lihong Wang, Tingwen Liu, Hongbo Xu
    http://arxiv.org/abs/2107.01583v1

    • [cs.CL]Coarse-to-Careful: Seeking Semantic-related Knowledge for Open-domain Commonsense Question Answering
    Luxi Xing, Yue Hu, Jing Yu, Yuqiang Xie, Wei Peng
    http://arxiv.org/abs/2107.01592v1

    • [cs.CL]Contradiction Detection in Persian Text
    Zeinab Rahimi, Mehrnoush ShamsFard
    http://arxiv.org/abs/2107.01987v1

    • [cs.CL]Cross-Modal Transformer-Based Neural Correction Models for Automatic Speech Recognition
    Tomohiro Tanaka, Ryo Masumura, Mana Ihori, Akihiko Takashima, Takafumi Moriya, Takanori Ashihara, Shota Orihashi, Naoki Makishima
    http://arxiv.org/abs/2107.01569v1

    • [cs.CL]Deep Learning Schema-based Event Extraction: Literature Review and Current Trends
    Qian Li, Hao Peng, Jianxin Li, Yiming Hei, Rui Sun, Jiawei Sheng, Shu Guo, Lihong Wang, Philip S. Yu
    http://arxiv.org/abs/2107.02126v1

    • [cs.CL]Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning Models
    Mingyue Han, Yinglin Wang
    http://arxiv.org/abs/2107.01791v1

    • [cs.CL]Domain Adaptation for Sentiment Analysis Using Increased Intraclass Separation
    Mohammad Rostami, Aram Galstyan
    http://arxiv.org/abs/2107.01598v1

    • [cs.CL]ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation
    Yu Sun, Shuohuan Wang, Shikun Feng, Siyu Ding, Chao Pang, Junyuan Shang, Jiaxiang Liu, Xuyi Chen, Yanbin Zhao, Yuxiang Lu, Weixin Liu, Zhihua Wu, Weibao Gong, Jianzhong Liang, Zhizhou Shang, Peng Sun, Wei Liu, Xuan Ouyang, Dianhai Yu, Hao Tian, Hua Wu, Haifeng Wang
    http://arxiv.org/abs/2107.02137v1

    • [cs.CL]End-to-end Neural Coreference Resolution Revisited: A Simple yet Effective Baseline
    Tuan Manh Lai, Trung Bui, Doo Soon Kim
    http://arxiv.org/abs/2107.01700v1

    • [cs.CL]FaVIQ: FAct Verification from Information-seeking Questions
    Jungsoo Park, Sewon Min, Jaewoo Kang, Luke Zettlemoyer, Hannaneh Hajishirzi
    http://arxiv.org/abs/2107.02153v1

    • [cs.CL]IITP at WAT 2021: System description for English-Hindi Multimodal Translation Task
    Baban Gain, Dibyanayan Bandyopadhyay, Asif Ekbal
    http://arxiv.org/abs/2107.01656v1

    • [cs.CL]Is Automated Topic Model Evaluation Broken?: The Incoherence of Coherence
    Alexander Hoyle, Pranav Goel, Denis Peskov, Andrew Hian-Cheong, Jordan Boyd-Graber, Philip Resnik
    http://arxiv.org/abs/2107.02173v1

    • [cs.CL]Neural-Symbolic Solver for Math Word Problems with Auxiliary Tasks
    Jinghui Qin, Xiaodan Liang, Yining Hong, Jianheng Tang, Liang Lin
    http://arxiv.org/abs/2107.01431v1

    • [cs.CL]Persian-WSD-Corpus: A Sense Annotated Corpus for Persian All-words Word Sense Disambiguation
    Hossein Rouhizadeh, Mehrnoush Shamsfard, Vahideh Tajalli, Masoud Rouhziadeh
    http://arxiv.org/abs/2107.01540v1

    • [cs.CL]Scarecrow: A Framework for Scrutinizing Machine Text
    Yao Dou, Maxwell Forbes, Rik Koncel-Kedziorski, Noah A. Smith, Yejin Choi
    http://arxiv.org/abs/2107.01294v1

    • [cs.CL]The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task
    James Barry, Alireza Mohammadshahi, Joachim Wagner, Jennifer Foster, James Henderson
    http://arxiv.org/abs/2107.01982v1

    • [cs.CL]Training Adaptive Computation for Open-Domain Question Answering with Computational Constraints
    Yuxiang Wu, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel
    http://arxiv.org/abs/2107.02102v1

    • [cs.CL]Unified Autoregressive Modeling for Joint End-to-End Multi-Talker Overlapped Speech Recognition and Speaker Attribute Estimation
    Ryo Masumura, Daiki Okamura, Naoki Makishima, Mana Ihori, Akihiko Takashima, Tomohiro Tanaka, Shota Orihashi
    http://arxiv.org/abs/2107.01549v1

    • [cs.CR]A Framework for Evaluating the Cybersecurity Risk of Real World, Machine Learning Production Systems
    Ron Bitton, Nadav Maman, Inderjeet Singh, Satoru Momiyama, Yuval Elovici, Asaf Shabtai
    http://arxiv.org/abs/2107.01806v1

    • [cs.CR]Android Malware Category and Family Detection and Identification using Machine Learning
    Ahmed Hashem El Fiky, Ayman El Shenawy, Mohamed Ashraf Madkour
    http://arxiv.org/abs/2107.01927v1

    • [cs.CR]Auxiliary-Classifier GAN for Malware Analysis
    Rakesh Nagaraju, Mark Stamp
    http://arxiv.org/abs/2107.01620v1

    • [cs.CR]ETHTID: Deployable Threshold Information Disclosure on Ethereum
    Oliver Stengele, Markus Raiber, Jörn Müller-Quade, Hannes Hartenstein
    http://arxiv.org/abs/2107.01600v1

    • [cs.CR]Logic Locking at the Frontiers of Machine Learning: A Survey on Developments and Opportunities
    Dominik Sisejkovic, Lennart M. Reimann, Elmira Moussavi, Farhad Merchant, Rainer Leupers
    http://arxiv.org/abs/2107.01915v1

    • [cs.CR]Machine Learning for Malware Evolution Detection
    Lolitha Sresta Tupadha, Mark Stamp
    http://arxiv.org/abs/2107.01627v1

    • [cs.CR]Smoothed Differential Privacy
    Ao Liu, Lirong Xia
    http://arxiv.org/abs/2107.01559v1

    • [cs.CR]Subset Privacy: Draw from an Obfuscated Urn
    Ganghua Wang, Jie Ding
    http://arxiv.org/abs/2107.02013v1

    • [cs.CR]Understanding the Security of Deepfake Detection
    Xiaoyu Cao, Neil Zhenqiang Gong
    http://arxiv.org/abs/2107.02045v1

    • [cs.CV]6D Object Pose Estimation using Keypoints and Part Affinity Fields
    Moritz Zappel, Simon Bultmann, Sven Behnke
    http://arxiv.org/abs/2107.02057v1

    • [cs.CV]A Novel Disaster Image Dataset and Characteristics Analysis using Attention Model
    Fahim Faisal Niloy, Arif, Abu Bakar Siddik Nayem, Anis Sarker, Ovi Paul, M. Ashraful Amin, Amin Ahsan Ali, Moinul Islam Zaber, AKM Mahbubur Rahman
    http://arxiv.org/abs/2107.01284v1

    • [cs.CV]A topological solution to object segmentation and tracking
    Thomas Tsao, Doris Y. Tsao
    http://arxiv.org/abs/2107.02036v1

    • [cs.CV]Bag of Instances Aggregation Boosts Self-supervised Learning
    Haohang Xu, Jiemin Fang, Xiaopeng Zhang, Lingxi Xie, Xinggang Wang, Wenrui Dai, Hongkai Xiong, Qi Tian
    http://arxiv.org/abs/2107.01691v1

    • [cs.CV]Cognitive Visual Commonsense Reasoning Using Dynamic Working Memory
    Xuejiao Tang
    http://arxiv.org/abs/2107.01671v1

    • [cs.CV]Conditional Identity Disentanglement for Differential Face Morph Detection
    Sudipta Banerjee, Arun Ross
    http://arxiv.org/abs/2107.02162v1

    • [cs.CV]Continual Contrastive Self-supervised Learning for Image Classification
    Zhiwei Lin, Yongtao Wang, Hongxiang Lin
    http://arxiv.org/abs/2107.01776v1

    • [cs.CV]Data Uncertainty Guided Noise-aware Preprocessing Of Fingerprints
    Indu Joshi, Ayush Utkarsh, Riya Kothari, Vinod K Kurmi, Antitza Dantcheva, Sumantra Dutta Roy, Prem Kumar Kalra
    http://arxiv.org/abs/2107.01248v1

    • [cs.CV]Deep Edge-Aware Interactive Colorization against Color-Bleeding Effects
    Eungyeup Kim, Sanghyeon Lee, Jeonghoon Park, Somi Choi, Choonghyun Seo, Jaegul Choo
    http://arxiv.org/abs/2107.01619v1

    • [cs.CV]Demiguise Attack: Crafting Invisible Semantic Adversarial Perturbations with Perceptual Similarity
    Yajie Wang, Shangbo Wu, Wenyi Jiang, Shengang Hao, Yu-an Tan, Quanxin Zhang
    http://arxiv.org/abs/2107.01396v1

    • [cs.CV]Depth Quality-Inspired Feature Manipulation for Efficient RGB-D Salient Object Detection
    Wenbo Zhang, Ge-Peng Ji, Zhuo Wang, Keren Fu, Qijun Zhao
    http://arxiv.org/abs/2107.01779v1

    • [cs.CV]Direct Measure Matching for Crowd Counting
    Hui Lin, Xiaopeng Hong, Zhiheng Ma, Xing Wei, Yunfeng Qiu, Yaowei Wang, Yihong Gong
    http://arxiv.org/abs/2107.01558v1

    • [cs.CV]Distance-based Hyperspherical Classification for Multi-source Open-Set Domain Adaptation
    Silvia Bucci, Francesco Cappio Borlino, Barbara Caputo, Tatiana Tommasi
    http://arxiv.org/abs/2107.02067v1

    • [cs.CV]Do Different Tracking Tasks Require Different Appearance Models?
    Zhongdao Wang, Hengshuang Zhao, Ya-Li Li, Shengjin Wang, Philip H. S. Torr, Luca Bertinetto
    http://arxiv.org/abs/2107.02156v1

    • [cs.CV]Drone Detection Using Convolutional Neural Networks
    Fatemeh Mahdavi, Roozbeh Rajabi
    http://arxiv.org/abs/2107.01435v1

    • [cs.CV]Efficient Vision Transformers via Fine-Grained Manifold Distillation
    Ding Jia, Kai Han, Yunhe Wang, Yehui Tang, Jianyuan Guo, Chao Zhang, Dacheng Tao
    http://arxiv.org/abs/2107.01378v1

    • [cs.CV]Exploring Data Pipelines through the Process Lens: a Reference Model forComputer Vision
    Agathe Balayn, Bogdan Kulynych, Seda Guerses
    http://arxiv.org/abs/2107.01824v1

    • [cs.CV]FFR_FD: Effective and Fast Detection of DeepFakes Based on Feature Point Defects
    Gaojian Wang, Qian Jiang, Xin Jin, Xiaohui Cui
    http://arxiv.org/abs/2107.02016v1

    • [cs.CV]Fast and Scalable Optimal Transport for Brain Tractograms
    Jean Feydy, Pierre Roussillon, Alain Trouvé, Pietro Gori
    http://arxiv.org/abs/2107.02010v1

    • [cs.CV]Faster-LTN: a neuro-symbolic, end-to-end object detection architecture
    Francesco Manigrasso, Filomeno Davide Miro, Lia Morra, Fabrizio Lamberti
    http://arxiv.org/abs/2107.01877v1

    • [cs.CV]Gaze Estimation with an Ensemble of Four Architectures
    Xin Cai, Boyu Chen, Jiabei Zeng, Jiajun Zhang, Yunjia Sun, Xiao Wang, Zhilong Ji, Xiao Liu, Xilin Chen, Shiguang Shan
    http://arxiv.org/abs/2107.01980v1

    • [cs.CV]How Incomplete is Contrastive Learning? An Inter-intra Variant Dual Representation Method for Self-supervised Video Recognition
    Lin Zhang, Qi She, Zhengyang Shen, Changhu Wang
    http://arxiv.org/abs/2107.01194v2

    • [cs.CV]Improving a neural network model by explanation-guided training for glioma classification based on MRI data
    Frantisek Sefcik, Wanda Benesova
    http://arxiv.org/abs/2107.02008v1

    • [cs.CV]Learning Hierarchical Graph Neural Networks for Image Clustering
    Yifan Xing, Tong He, Tianjun Xiao, Yongxin Wang, Yuanjun Xiong, Wei Xia, David Wipf Paul, Zheng Zhang, Stefano Soatto
    http://arxiv.org/abs/2107.01319v1

    • [cs.CV]Learning a Model for Inferring a Spatial Road Lane Network Graph using Self-Supervision
    Robin Karlsson, David Robert Wong, Simon Thompson, Kazuya Takeda
    http://arxiv.org/abs/2107.01784v1

    • [cs.CV]Learning from scarce information: using synthetic data to classify Roman fine ware pottery
    Santos J. Núñez Jareño, Daniël P. van Helden, Evgeny M. Mirkes, Ivan Y. Tyukin, Penelope M. Allison
    http://arxiv.org/abs/2107.01401v1

    • [cs.CV]MixStyle Neural Networks for Domain Generalization and Adaptation
    Kaiyang Zhou, Yongxin Yang, Yu Qiao, Tao Xiang
    http://arxiv.org/abs/2107.02053v1

    • [cs.CV]Multi-View Correlation Distillation for Incremental Object Detection
    Dongbao Yang, Yu Zhou, Weiping Wang
    http://arxiv.org/abs/2107.01787v1

    • [cs.CV]No-Reference Quality Assessment for Colored Point Cloud and Mesh Based on Natural Scene Statistics
    Zicheng Zhang
    http://arxiv.org/abs/2107.02041v1

    • [cs.CV]OPA: Object Placement Assessment Dataset
    Liu Liu, Bo Zhang, Jiangtong Li, Li Niu, Qingyang Liu, Liqing Zhang
    http://arxiv.org/abs/2107.01889v1

    • [cs.CV]On Model Calibration for Long-Tailed Object Detection and Instance Segmentation
    Tai-Yu Pan, Cheng Zhang, Yandong Li, Hexiang Hu, Dong Xuan, Soravit Changpinyo, Boqing Gong, Wei-Lun Chao
    http://arxiv.org/abs/2107.02170v1

    • [cs.CV]One-Cycle Pruning: Pruning ConvNets Under a Tight Training Budget
    Nathan Hubens, Matei Mancas, Bernard Gosselin, Marius Preda, Titus Zaharia
    http://arxiv.org/abs/2107.02086v1

    • [cs.CV]Part2Word: Learning Joint Embedding of Point Clouds and Text by Matching Parts to Words
    Chuan Tang, Xi Yang, Bojian Wu, Zhizhong Han, Yi Chang
    http://arxiv.org/abs/2107.01872v1

    • [cs.CV]RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting
    Benjamin Hou, Georgios Kaissis, Ronald Summers, Bernhard Kainz
    http://arxiv.org/abs/2107.02104v1

    • [cs.CV]Ray-ONet: Efficient 3D Reconstruction From A Single RGB Image
    Wenjing Bian, Zirui Wang, Kejie Li, Victor Adrian Prisacariu
    http://arxiv.org/abs/2107.01899v1

    • [cs.CV]Recovering the Unbiased Scene Graphs from the Biased Ones
    Meng-Jiun Chiou, Henghui Ding, Hanshu Yan, Changhu Wang, Roger Zimmermann, Jiashi Feng
    http://arxiv.org/abs/2107.02112v1

    • [cs.CV]Robust End-to-End Offline Chinese Handwriting Text Page Spotter with Text Kernel
    Zhihao Wang, Yanwei Yu, Yibo Wang, Haixu Long, Fazheng Wang
    http://arxiv.org/abs/2107.01547v1

    • [cs.CV]SM-SGE: A Self-Supervised Multi-Scale Skeleton Graph Encoding Framework for Person Re-Identification
    Haocong Rao, Xiping Hu, Jun Cheng, Bin Hu
    http://arxiv.org/abs/2107.01903v1

    • [cs.CV]SPI-GAN: Towards Single-Pixel Imaging through Generative Adversarial Network
    Nazmul Karim, Nazanin Rahnavard
    http://arxiv.org/abs/2107.01330v1

    • [cs.CV]SSPNet: Scale Selection Pyramid Network for Tiny Person Detection from UAV Images
    Mingbo Hong, Shuiwang Li, Yuchao Yang, Feiyu Zhu, Qijun Zhao, Li Lu
    http://arxiv.org/abs/2107.01548v1

    • [cs.CV]Scene-aware Learning Network for Radar Object Detection
    Zangwei Zheng, Xiangyu Yue, Kurt Keutzer, Alberto Sangiovanni Vincentelli
    http://arxiv.org/abs/2107.01469v1

    • [cs.CV]Self-Contrastive Learning with Hard Negative Sampling for Self-supervised Point Cloud Learning
    Bi’an Du, Xiang Gao, Wei Hu, Xin Li
    http://arxiv.org/abs/2107.01886v1

    • [cs.CV]Semi-supervised Learning for Dense Object Detection in Retail Scenes
    Jaydeep Chauhan, Srikrishna Varadarajan, Muktabh Mayank Srivastava
    http://arxiv.org/abs/2107.02114v1

    • [cs.CV]Sensor-invariant Fingerprint ROI Segmentation Using Recurrent Adversarial Learning
    Indu Joshi, Ayush Utkarsh, Riya Kothari, Vinod K Kurmi, Antitza Dantcheva, Sumantra Dutta Roy, Prem Kumar Kalra
    http://arxiv.org/abs/2107.01361v1

    • [cs.CV]Similarity-Aware Fusion Network for 3D Semantic Segmentation
    Linqing Zhao, Jiwen Lu, Jie Zhou
    http://arxiv.org/abs/2107.01579v1

    • [cs.CV]Super Resolution in Human Pose Estimation: Pixelated Poses to a Resolution Result?
    Peter Hardy, Srinandan Dasmahapatra, Hansung Kim
    http://arxiv.org/abs/2107.02108v1

    • [cs.CV]Test-Time Personalization with a Transformer for Human Pose Estimation
    Miao Hao, Yizhuo Li, Zonglin Di, Nitesh B. Gundavarapu, Xiaolong Wang
    http://arxiv.org/abs/2107.02133v1

    • [cs.CV]Towards Better Adversarial Synthesis of Human Images from Text
    Rania Briq, Pratika Kochar, Juergen Gall
    http://arxiv.org/abs/2107.01869v1

    • [cs.CV]Visual Time Series Forecasting: An Image-driven Approach
    Naftali Cohen, Srijan Sood, Zhen Zeng, Tucker Balch, Manuela Veloso
    http://arxiv.org/abs/2107.01273v1

    • [cs.CV]Web-Scale Generic Object Detection at Microsoft Bing
    Stephen Xi Chen, Saurajit Mukherjee, Unmesh Phadke, Tingting Wang, Junwon Park, Ravi Theja Yada
    http://arxiv.org/abs/2107.01814v1

    • [cs.CV]What Makes for Hierarchical Vision Transformer?
    Yuxin Fang, Xinggang Wang, Rui Wu, Jianwei Niu, Wenyu Liu
    http://arxiv.org/abs/2107.02174v1

    • [cs.CY]A Systematic Literature Review of Empiricism and Norms of Reporting in Computing Education Research Literature
    Sarah Heckman, Jeffrey C. Carver, Mark Sherriff, Ahmed Al-Zubidy
    http://arxiv.org/abs/2107.01984v1

    • [cs.CY]DiSH-trend: Intervention Modeling Simulator That Accounts for Trend Influences
    Stefan Andjelkovic, Natasa Miskov-Zivanov
    http://arxiv.org/abs/2107.01302v1

    • [cs.CY]Harnessing Context for Budget-Limited Crowdsensing with Massive Uncertain Workers
    Feng Li, Jichao Zhao, Dongxiao Yu, Xiuzhen Cheng, Weifeng Lv
    http://arxiv.org/abs/2107.01385v1

    • [cs.CY]Implicit Gender Bias in Computer Science — A Qualitative Study
    Aurélie Breidenbach, Caroline Mahlow, Andreas Schreiber
    http://arxiv.org/abs/2107.01624v1

    • [cs.CY]PyLUSAT: An open-source Python toolkit for GIS-based land use suitability analysis
    Changjie Chen, Jasmeet Judge, David Hulse
    http://arxiv.org/abs/2107.01674v1

    • [cs.CY]Security implications of digitalization: The dangers of data colonialism and the way towards sustainable and sovereign management of environmental data
    Matthias Stürmer, Jasmin Nussbaumer, Pascal Stöckli
    http://arxiv.org/abs/2107.01662v1

    • [cs.DB]Pool of Experts: Realtime Querying Specialized Knowledge in Massive Neural Networks
    Hakbin Kim, Dong-Wan Choi
    http://arxiv.org/abs/2107.01354v1

    • [cs.DC]A Fuzzy Scheduling Strategy for Deadline-Based Workflow Applications in Uncertain Edge-Cloud Environments
    Bing Lin, Chaowei Lin, Xing Chen, Neal N. Xiong, Peisong Hua, Qiang Shen
    http://arxiv.org/abs/2107.01405v1

    • [cs.DC]Cloud Versus Local Processing in Distributed Networks
    Abdulaziz M. Alqarni, Thomas G. Robertazzi
    http://arxiv.org/abs/2107.01735v1

    • [cs.DS]Polymorphic dynamic programming by algebraic shortcut fusion
    Max A. Little, Ugur Kayas
    http://arxiv.org/abs/2107.01752v1

    • [cs.DS]Randomized Dimensionality Reduction for Facility Location and Single-Linkage Clustering
    Shyam Narayanan, Sandeep Silwal, Piotr Indyk, Or Zamir
    http://arxiv.org/abs/2107.01804v1

    • [cs.GR]An Analytical Survey on Recent Trends in High Dimensional Data Visualization
    Alexander Kiefer, Md. Khaledur Rahman
    http://arxiv.org/abs/2107.01887v1

    • [cs.GT]Learning in nonatomic games, Part I: Finite action spaces and population games
    Saeed Hadikhanloo, Rida Laraki, Panayotis Mertikopoulos, Sylvain Sorin
    http://arxiv.org/abs/2107.01595v1

    • [cs.HC]Here’s What I’ve Learned: Asking Questions that Reveal Reward Learning
    Soheil Habibian, Ananth Jonnavittula, Dylan P. Losey
    http://arxiv.org/abs/2107.01995v1

    • [cs.IR]Attribute-aware Explainable Complementary Clothing Recommendation
    Yang Li, Tong Chen, Zi Huang
    http://arxiv.org/abs/2107.01655v1

    • [cs.IR]FINT: Field-aware INTeraction Neural Network For CTR Prediction
    Zhishan Zhao, Sen Yang, Guohui Liu, Dawei Feng, Kele Xu
    http://arxiv.org/abs/org/abs/2107.01999v1

    • [cs.IR]FINT: Field-aware INTeraction Neural Network For CTR Prediction
    Zhishan Zhao, Sen Yang, Guohui Liu, Dawei Feng, Kele Xu
    http://arxiv.org/abs/2107.01999v1

    • [cs.IR]Improved Representation Learning for Session-based Recommendation
    Sai Mitheran, Abhinav Java, Abhinav Java, Arshad Shaikh
    http://arxiv.org/abs/2107.01516v1

    • [cs.IR]Learning Complex Users’ Preferences for Recommender Systems
    Shahpar Yakhchi
    http://arxiv.org/abs/2107.01529v1

    • [cs.IR]NOTE: Solution for KDD-CUP 2021 WikiKG90M-LSC
    Weiyue Su, Zeyang Fang, Hui Zhong, Huijuan Wang, Siming Dai, Zhengjie Huang, Yunsheng Shi, Shikun Feng, Zeyu Chen
    http://arxiv.org/abs/2107.01892v1

    • [cs.IT]A precise bare simulation approach to the minimization of some distances. Foundations
    Michel Broniatowski, Wolfgang Stummer
    http://arxiv.org/abs/2107.01693v1

    • [cs.IT]Age of Information in Relay-Assisted Status Updating Systems
    Jixiang Zhang, Yinfei Xu
    http://arxiv.org/abs/2107.01833v1

    • [cs.IT]An Information-Theoretic Approach for Automatically Determining the Number of States when Aggregating Markov Chains
    Isaac J. Sledge, Jose C. Principe
    http://arxiv.org/abs/2107.01799v1

    • [cs.IT]Cell-Free Massive MIMO-OFDM Transmission over Frequency-Selective Fading Channels
    Wei Jiang, Hans Dieter Schotten
    http://arxiv.org/abs/2107.01402v1

    • [cs.IT]Erasures repair for decreasing monomial-Cartesian and augmented Reed-Muller codes of high rate
    Hiram H. López, Gretchen L. Matthews, Daniel Valvo
    http://arxiv.org/abs/2107.01534v1

    • [cs.IT]Expanded Gabidulin Codes and Their Application to Cryptography
    Wenshuo Guo, Fang-Wei Fu
    http://arxiv.org/abs/2107.01610v1

    • [cs.IT]Impact of Channel Aging on Zero-Forcing Precoding in Cell-Free Massive MIMO Systems
    Wei Jiang, Hans Dieter Schotten
    http://arxiv.org/abs/2107.01404v1

    • [cs.IT]Improved Asymptotic Bounds for Codes Correcting Insertions and Deletions
    Kenji Yasunaga
    http://arxiv.org/abs/2107.01785v1

    • [cs.IT]MIMO Operations in Molecular Communications: Theory, Prototypes, and Open Challenges
    Bon-Hong Koo, Changmin Lee, Ali E. Pusane, Tuna Tugcu, Chan-Byoung Chae
    http://arxiv.org/abs/2107.01793v1

    • [cs.IT]Optimum GSSK Transmission in Massive MIMO Systems Using the Box-LASSO Decoder
    Ayed M. Alrashdi, Abdullah E. Alrashdi, Mohamed A. H. Eleiwa
    http://arxiv.org/abs/2107.01870v1

    • [cs.IT]Physical Layer Security for NOMA-Enabled Multi-Access Edge Computing Wireless Networks
    Yating Wen, Tong-Xing Zheng, Yongxia Tong, Hao-Wen Liu, Xin Chen, Pengcheng Mu, Hui-Ming Wang
    http://arxiv.org/abs/2107.01322v1

    • [cs.IT]STAR-IOS Aided NOMA Networks: Channel Model Approximation and Performance Analysis
    Chao Zhang, Wenqiang Yi, Yuanwei Liu, Zhiguo Ding, Lingyang Song
    http://arxiv.org/abs/2107.01543v1

    • [cs.IT]The 今日学术视野(2021.7.7) - 图2-weight distribution for MDS codes
    Canze Zhu, Qunying Liao
    http://arxiv.org/abs/2107.01717v1

    • [cs.IT]The Curious Case of the Diamond Network
    Allison Beemer, Alberto Ravagnani
    http://arxiv.org/abs/2107.02144v1

    • [cs.IT]The information loss of a stochastic map
    James Fullwood, Arthur J. Parzygnat
    http://arxiv.org/abs/2107.01975v1

    • [cs.LG]A Comparison of the Delta Method and the Bootstrap in Deep Learning Classification
    Geir K. Nilsen, Antonella Z. Munthe-Kaas, Hans J. Skaug, Morten Brun
    http://arxiv.org/abs/2107.01606v1

    • [cs.LG]A Theoretical Analysis of Fine-tuning with Linear Teachers
    Gal Shachaf, Alon Brutzkus, Amir Globerson
    http://arxiv.org/abs/2107.01641v1

    • [cs.LG]A Typology of Data Anomalies
    Ralph Foorthuis
    http://arxiv.org/abs/2107.01615v1

    • [cs.LG]A contextual analysis of multi-layer perceptron models in classifying hand-written digits and letters: limited resources
    Tidor-Vlad Pricope
    http://arxiv.org/abs/2107.01782v1

    • [cs.LG]ARM-Net: Adaptive Relation Modeling Network for Structured Data
    Shaofeng Cai, Kaiping Zheng, Gang Chen, H. V. Jagadish, Beng Chin Ooi, Meihui Zhang
    http://arxiv.org/abs/2107.01830v1

    • [cs.LG]AdaL: Adaptive Gradient Transformation Contributes to Convergences and Generalizations
    Hongwei Zhang, Weidong Zou, Hongbo Zhao, Qi Ming, Tijin Yan, Yuanqing Xia, Weipeng Cao
    http://arxiv.org/abs/2107.01525v1

    • [cs.LG]Adaptive calibration for binary classification
    Vladimir Vovk, Ivan Petej, Alex Gammerman
    http://arxiv.org/abs/2107.01726v1

    • [cs.LG]An Explainable AI System for the Diagnosis of High Dimensional Biomedical Data
    Alfred Ultsch, Jörg Hoffmann, Maximilian Röhnert, Malte Von Bonin, Uta Oelschlägel, Cornelia Brendel, Michael C. Thrun
    http://arxiv.org/abs/2107.01820v1

    • [cs.LG]Are standard Object Segmentation models sufficient for Learning Affordance Segmentation?
    Hugo Caselles-Dupré, Michael Garcia-Ortiz, David Filliat
    http://arxiv.org/abs/2107.02095v1

    • [cs.LG]Autoencoder based Randomized Learning of Feedforward Neural Networks for Regression
    Grzegorz Dudek
    http://arxiv.org/abs/2107.01711v1

    • [cs.LG]Automating Generative Deep Learning for Artistic Purposes: Challenges and Opportunities
    Sebastian Berns, Terence Broad, Christian Guckelsberger, Simon Colton
    http://arxiv.org/abs/2107.01858v1

    • [cs.LG]BAGUA: Scaling up Distributed Learning with System Relaxations
    Shaoduo Gan, Xiangru Lian, Rui Wang, Jianbin Chang, Chengjun Liu, Hongmei Shi, Shengzhuo Zhang, Xianghong Li, Tengxu Sun, Jiawei Jiang, Binhang Yuan, Sen Yang, Ji Liu, Ce Zhang
    http://arxiv.org/abs/2107.01499v1

    • [cs.LG]Bayesian decision-making under misspecified priors with applications to meta-learning
    Max Simchowitz, Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu, Thodoris Lykouris, Miroslav Dudík, Robert E. Schapire
    http://arxiv.org/abs/2107.01509v1

    • [cs.LG]Boosting Transferability of Targeted Adversarial Examples via Hierarchical Generative Networks
    Xiao Yang, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu
    http://arxiv.org/abs/2107.01809v1

    • [cs.LG]Byzantine-robust Federated Learning through Spatial-temporal Analysis of Local Model Updates
    Zhuohang Li, Luyang Liu, Jiaxin Zhang, Jian Liu
    http://arxiv.org/abs/2107.01477v1

    • [cs.LG]CInC Flow: Characterizable Invertible 3x3 Convolution
    Sandeep Nagar, Marius Dufraisse, Girish Varma
    http://arxiv.org/abs/2107.01358v1

    • [cs.LG]Certifiably Robust Interpretation via Renyi Differential Privacy
    Ao Liu, Xiaoyu Chen, Sijia Liu, Lirong Xia, Chuang Gan
    http://arxiv.org/abs/2107.01561v1

    • [cs.LG]Class Introspection: A Novel Technique for Detecting Unlabeled Subclasses by Leveraging Classifier Explainability Methods
    Patrick Kage, Pavlos Andreadis
    http://arxiv.org/abs/2107.01657v1

    • [cs.LG]Cluster Representatives Selection in Non-Metric Spaces for Nearest Prototype Classification
    Jaroslav Hlaváč, Martin Kopp, Jan Kohout
    http://arxiv.org/abs/2107.01345v1

    • [cs.LG]Clustering of Time Series Data with Prior Geographical Information
    Reza Asadi, Amelia Regan
    http://arxiv.org/abs/2107.01310v1

    • [cs.LG]DPPIN: A Biological Dataset of Dynamic Protein-Protein Interaction Networks
    Dongqi Fu, Jingrui He
    http://arxiv.org/abs/2107.02168v1

    • [cs.LG]Data-Driven Learning of Feedforward Neural Networks with Different Activation Functions
    Grzegorz Dudek
    http://arxiv.org/abs/2107.01702v1

    • [cs.LG]Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning
    Mathias Löwe, Jennifer Villareale, Evan Freed, Aleksanteri Sladek, Jichen Zhu, Sebastian Risi
    http://arxiv.org/abs/2107.02052v1

    • [cs.LG]Designing Machine Learning Pipeline Toolkit for AutoML Surrogate Modeling Optimization
    Paulito P. Palmes, Akihiro Kishimoto, Radu Marinescu, Parikshit Ram, Elizabeth Daly
    http://arxiv.org/abs/2107.01253v1

    • [cs.LG]Detecting Concept Drift With Neural Network Model Uncertainty
    Lucas Baier, Tim Schlör, Jakob Schöffer, Niklas Kühl
    http://arxiv.org/abs/2107.01873v1

    • [cs.LG]Detecting Faults during Automatic Screwdriving: A Dataset and Use Case of Anomaly Detection for Automatic Screwdriving
    Błażej Leporowski, Daniella Tola, Casper Hansen, Alexandros Iosifidis
    http://arxiv.org/abs/2107.01955v1

    • [cs.LG]Differentially Private Sliced Wasserstein Distance
    Alain Rakotomamonjy, Liva Ralaivola
    http://arxiv.org/abs/2107.01848v1

    • [cs.LG]Ensemble and Auxiliary Tasks for Data-Efficient Deep Reinforcement Learning
    Muhammad Rizki Maulana, Wee Sun Lee
    http://arxiv.org/abs/2107.01904v1

    • [cs.LG]Exact Backpropagation in Binary Weighted Networks with Group Weight Transformations
    Yaniv Shulman
    http://arxiv.org/abs/2107.01400v1

    • [cs.LG]Examining average and discounted reward optimality criteria in reinforcement learning
    Vektor Dewanto, Marcus Gallagher
    http://arxiv.org/abs/2107.01348v1

    • [cs.LG]Fair Decision Rules for Binary Classification
    Connor Lawless, Oktay Gunluk
    http://arxiv.org/abs/2107.01325v1

    • [cs.LG]Fast Rate Learning in Stochastic First Price Bidding
    Juliette Achddou, Olivier Cappé, Aurélien Garivier
    http://arxiv.org/abs/2107.01835v1

    • [cs.LG]Feature Cross Search via Submodular Optimization
    Lin Chen, Hossein Esfandiari, Gang Fu, Vahab S. Mirrokni, Qian Yu
    http://arxiv.org/abs/2107.02139v1

    • [cs.LG]Implicit Greedy Rank Learning in Autoencoders via Overparameterized Linear Networks
    Shih-Yu Sun, Vimal Thilak, Etai Littwin, Omid Saremi, Joshua M. Susskind
    http://arxiv.org/abs/2107.01301v1

    • [cs.LG]Imputation-Free Learning from Incomplete Observations
    Qitong Gao, Dong Wang, Joshua D. Amason, Siyang Yuan, Chenyang Tao, Ricardo Henao, Majda Hadziahmetovic, Lawrence Carin, Miroslav Pajic
    http://arxiv.org/abs/2107.01983v1

    • [cs.LG]Incorporating Reachability Knowledge into a Multi-Spatial Graph Convolution Based Seq2Seq Model for Traffic Forecasting
    Jiexia Ye, Furong Zheng, Juanjuan Zhao, Kejiang Ye, Chengzhong Xu
    http://arxiv.org/abs/2107.01528v1

    • [cs.LG]Isotonic Data Augmentation for Knowledge Distillation
    Wanyun Cui, Sen Yan
    http://arxiv.org/abs/2107.01412v1

    • [cs.LG]KAISA: An Adaptive Second-order Optimizer Framework for Deep Neural Networks
    J. Gregory Pauloski, Qi Huang, Lei Huang, Shivaram Venkataraman, Kyle Chard, Ian Foster, Zhao Zhang
    http://arxiv.org/abs/2107.01739v1

    • [cs.LG]Learning Debiased Representation via Disentangled Feature Augmentation
    Eungyeup Kim, Jungsoo Lee, Juyoung Lee, Jihyeon Lee, Jaegul Choo
    http://arxiv.org/abs/2107.01372v1

    • [cs.LG]Learning ODEs via Diffeomorphisms for Fast and Robust Integration
    Weiming Zhi, Tin Lai, Lionel Ott, Edwin V. Bonilla, Fabio Ramos
    http://arxiv.org/abs/2107.01650v1

    • [cs.LG]Leveraging Evidential Deep Learning Uncertainties with Graph-based Clustering to Detect Anomalies
    Sandeep Kumar Singh, Jaya Shradha Fowdur, Jakob Gawlikowski, Daniel Medina
    http://arxiv.org/abs/2107.01557v1

    • [cs.LG]Low-Dimensional State and Action Representation Learning with MDP Homomorphism Metrics
    Nicolò Botteghi, Mannes Poel, Beril Sirmacek, Christoph Brune
    http://arxiv.org/abs/2107.01677v1

    • [cs.LG]Machine Learning for Fraud Detection in E-Commerce: A Research Agenda
    Niek Tax, Kees Jan de Vries, Mathijs de Jong, Nikoleta Dosoula, Bram van den Akker, Jon Smith, Olivier Thuong, Lucas Bernardi
    http://arxiv.org/abs/2107.01979v1

    • [cs.LG]Mava: a research framework for distributed multi-agent reinforcement learning
    Arnu Pretorius, Kale-ab Tessera, Andries P. Smit, Claude Formanek, St John Grimbly, Kevin Eloff, Siphelele Danisa, Lawrence Francis, Jonathan Shock, Herman Kamper, Willie Brink, Herman Engelbrecht, Alexandre Laterre, Karim Beguir
    http://arxiv.org/abs/2107.01460v1

    • [cs.LG]Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks
    Amirhossein Nouranizadeh, Mohammadjavad Matinkia, Mohammad Rahmati, Reza Safabakhsh
    http://arxiv.org/abs/2107.01410v1

    • [cs.LG]Memory and attention in deep learning
    Hung Le
    http://arxiv.org/abs/2107.01390v1

    • [cs.LG]Multiple-criteria Based Active Learning with Fixed-size Determinantal Point Processes
    Xueying Zhan, Qing Li, Antoni B. Chan
    http://arxiv.org/abs/2107.01622v1

    • [cs.LG]On Bi-gram Graph Attributes
    Thomas Konstantinovsky, Matan Mizrachi
    http://arxiv.org/abs/2107.02128v1

    • [cs.LG]On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs
    Hejie Cui, Zijie Lu, Pan Li, Carl Yang
    http://arxiv.org/abs/2107.01495v1

    • [cs.LG]On The Distribution of Penultimate Activations of Classification Networks
    Minkyo Seo, Yoonho Lee, Suha Kwak
    http://arxiv.org/abs/2107.01900v1

    • [cs.LG]Optimizing the Numbers of Queries and Replies in Federated Learning with Differential Privacy
    Yipeng Zhou, Xuezheng Liu, Yao Fu, Di Wu, Chao Li, Shui Yu
    http://arxiv.org/abs/2107.01895v1

    • [cs.LG]Partition and Code: learning how to compress graphs
    Giorgos Bouritsas, Andreas Loukas, Nikolaos Karalias, Michael M. Bronstein
    http://arxiv.org/abs/2107.01952v1

    • [cs.LG]Poisoning Attack against Estimating from Pairwise Comparisons
    Ke Ma, Qianqian Xu, Jinshan Zeng, Xiaochun Cao, Qingming Huang
    http://arxiv.org/abs/2107.01854v1

    • [cs.LG]Privacy-Preserving Representation Learning on Graphs: A Mutual Information Perspective
    Binghui Wang, Jiayi Guo, Ang Li, Yiran Chen, Hai Li
    http://arxiv.org/abs/2107.01475v1

    • [cs.LG]Provable Convergence of Nesterov Accelerated Method for Over-Parameterized Neural Networks
    Xin Liu, Zhisong Pan
    http://arxiv.org/abs/2107.01832v1

    • [cs.LG]Randomized Neural Networks for Forecasting Time Series with Multiple Seasonality
    Grzegorz Dudek
    http://arxiv.org/abs/2107.01705v1

    • [cs.LG]Robust Online Convex Optimization in the Presence of Outliers
    Tim van Erven, Sarah Sachs, Wouter M. Koolen, Wojciech Kotłowski
    http://arxiv.org/abs/2107.01881v1

    • [cs.LG]Robust Restless Bandits: Tackling Interval Uncertainty with Deep Reinforcement Learning
    Jackson A. Killian, Lily Xu, Arpita Biswas, Milind Tambe
    http://arxiv.org/abs/2107.01689v1

    • [cs.LG]SCOD: Active Object Detection for Embodied Agents using Sensory Commutativity of Action Sequences
    Hugo Caselles-Dupré, Michael Garcia-Ortiz, David Filliat
    http://arxiv.org/abs/2107.02069v1

    • [cs.LG]SHORING: Design Provable Conditional High-Order Interaction Network via Symbolic Testing
    Hui Li, Xing Fu, Ruofan Wu, Jinyu Xu, Kai Xiao, Xiaofu Chang, Weiqiang Wang, Shuai Chen, Leilei Shi, Tao Xiong, Yuan Qi
    http://arxiv.org/abs/2107.01326v1

    • [cs.LG]Sample Efficient Reinforcement Learning via Model-Ensemble Exploration and Exploitation
    Yao Yao, Li Xiao, Zhicheng An, Wanpeng Zhang, Dijun Luo
    http://arxiv.org/abs/2107.01825v1

    • [cs.LG]Short-term probabilistic photovoltaic power forecast based on deep convolutional long short-term memory network and kernel density estimation
    Mingliang Bai, Xinyu Zhao, Zhenhua Long, Jinfu Liu, Daren Yu
    http://arxiv.org/abs/2107.01343v1

    • [cs.LG]Single Model for Influenza Forecasting of Multiple Countries by Multi-task Learning
    Taichi Murayama, Shoko Wakamiya, Eiji Aramaki
    http://arxiv.org/abs/2107.01760v1

    • [cs.LG]Spatiotemporal convolutional network for time-series prediction and causal inference
    Hao Peng, Pei Chen, Rui Liu, Luonan Chen
    http://arxiv.org/abs/2107.01353v1

    • [cs.LG]Split-and-Bridge: Adaptable Class Incremental Learning within a Single Neural Network
    Jong-Yeong Kim, Dong-Wan Choi
    http://arxiv.org/abs/2107.01349v1

    • [cs.LG]Subspace Clustering Based Analysis of Neural Networks
    Uday Singh Saini, Pravallika Devineni, Evangelos E. Papalexakis
    http://arxiv.org/abs/2107.01296v1

    • [cs.LG]Supervised Off-Policy Ranking
    Yue Jin, Yue Zhang, Tao Qin, Xudong Zhang, Jian Yuan, Houqiang Li, Tie-Yan Liu
    http://arxiv.org/abs/2107.01360v1

    • [cs.LG]Survey: Leakage and Privacy at Inference Time
    Marija Jegorova, Chaitanya Kaul, Charlie Mayor, Alison Q. O’Neil, Alexander Weir, Roderick Murray-Smith, Sotirios A. Tsaftaris
    http://arxiv.org/abs/2107.01614v1

    • [cs.LG]The Least Restriction for Offline Reinforcement Learning
    Zizhou Su
    http://arxiv.org/abs/2107.01757v1

    • [cs.LG]The MineRL BASALT Competition on Learning from Human Feedback
    Rohin Shah, Cody Wild, Steven H. Wang, Neel Alex, Brandon Houghton, William Guss, Sharada Mohanty, Anssi Kanervisto, Stephanie Milani, Nicholay Topin, Pieter Abbeel, Stuart Russell, Anca Dragan
    http://arxiv.org/abs/2107.01969v1

    • [cs.LG]Towards Scheduling Federated Deep Learning using Meta-Gradients for Inter-Hospital Learning
    Rasheed el-Bouri, Tingting Zhu, David A. Clifton
    http://arxiv.org/abs/2107.01707v1

    • [cs.LG]Universal Approximation of Functions on Sets
    Edward Wagstaff, Fabian B. Fuchs, Martin Engelcke, Michael A. Osborne, Ingmar Posner
    http://arxiv.org/abs/2107.01959v1

    • [cs.LG]Unsupervised Ensemble Selection for Multilayer Bootstrap Networks
    Xiao-Lei Zhang
    http://arxiv.org/abs/2107.02071v1

    • [cs.LG]When and How to Fool Explainable Models (and Humans) with Adversarial Examples
    Jon Vadillo, Roberto Santana, Jose A. Lozano
    http://arxiv.org/abs/2107.01943v1

    • [cs.LG]Where is the Grass Greener? Revisiting Generalized Policy Iteration for Offline Reinforcement Learning
    Lionel Blondé, Alexandros Kalousis
    http://arxiv.org/abs/2107.01407v1

    • [cs.LG]Why is Pruning at Initialization Immune to Reinitializing and Shuffling?
    Sahib Singh, Rosanne Liu
    http://arxiv.org/abs/2107.01808v1

    • [cs.LO]The Semantics of Package Management via Event Structures
    Gershom Bazerman
    http://arxiv.org/abs/2107.01542v1

    • [cs.MA]Traffic Signal Control with Communicative Deep Reinforcement Learning Agents: a Case Study
    Paolo Fazzini, Isaac Wheeler, Francesco Petracchini
    http://arxiv.org/abs/2107.01347v1

    • [cs.NE]Multi-layer Hebbian networks with modern deep learning frameworks
    Thomas Miconi
    http://arxiv.org/abs/2107.01729v1

    • [cs.NE]Q-SpiNN: A Framework for Quantizing Spiking Neural Networks
    Rachmad Vidya Wicaksana Putra, Muhammad Shafique
    http://arxiv.org/abs/2107.01807v1

    • [cs.NE]Uso de GSO cooperativos com decaimentos de pesos para otimizacao de redes neurais
    Danielle Silva, Teresa Ludermir
    http://arxiv.org/abs/2107.02080v1

    • [cs.PL]The Composability of Intermediate Values in Composable Inductive Programming
    Edward McDaid, Sarah McDaid
    http://arxiv.org/abs/2107.01621v1

    • [cs.RO]A System for Traded Control Teleoperation of Manipulation Tasks using Intent Prediction from Hand Gestures
    Yoojin Oh, Marc Toussaint, Jim Mainprice
    http://arxiv.org/abs/2107.01829v1

    • [cs.RO]**Accelerating Kinodynamic RRT Through Dimensionality Reduction
    Dongliang Zheng, Panagiotis Tsiotras
    http://arxiv.org/abs/2107.01259v1

    • [cs.RO]Advanced turning maneuver of a multi-legged robot using pitchfork bifurcation
    Shinya Aoi, Ryoe Tomatsu, Yuki Yabuuchi, Soichiro Fujiki, Kei Senda, Kazuo Tsuchiya
    http://arxiv.org/abs/2107.01837v1

    • [cs.RO]Biomimetic Tactile Receptors for 3d-printed Skin
    Nicholas Pestell, Thom Griffith, Nathan F. Lepora
    http://arxiv.org/abs/2107.02084v1

    • [cs.RO]Breaking Barriers in Robotic Soft Tissue Surgery: Conditional Autonomous Intestinal Anastomosis
    H. Saeidi, J. D. Opfermann, M. Kam, S. Wei, S. Leonard, M. H. Hsieh, J. U. Kang, A. Krieger
    http://arxiv.org/abs/2107.01288v1

    • [cs.RO]Carnegie Mellon Team Tartan: Mission-level Robustness with Rapidly Deployed Autonomous Aerial Vehicles in the MBZIRC 2020
    Anish Bhattacharya, Akshit Gandhi, Lukas Merkle, Rohan Tiwari, Karun Warrior, Stanley Winata, Andrew Saba, Kevin Zhang, Oliver Kroemer, Sebastian Scherer
    http://arxiv.org/abs/2107.01507v1

    • [cs.RO]Control of rough terrain vehicles using deep reinforcement learning
    Viktor Wiberg, Erik Wallin, Martin Servin, Tomas Nordfjell
    http://arxiv.org/abs/2107.01867v1

    • [cs.RO]GraspME — Grasp Manifold Estimator
    Janik Hager, Ruben Bauer, Marc Toussaint, Jim Mainprice
    http://arxiv.org/abs/2107.01836v1

    • [cs.RO]Hierarchical Policies for Cluttered-Scene Grasping with Latent Plans
    Lirui Wang, Yu Xiang, Dieter Fox
    http://arxiv.org/abs/2107.01518v1

    • [cs.RO]Hybrid and dynamic policy gradient optimization for bipedal robot locomotion
    Changxin Huang, Jiang Su, Zhihong Zhang, Dong Zhao, Liang Lin
    http://arxiv.org/abs/2107.01908v1

    • [cs.RO]Low Dimensional State Representation Learning with Robotics Priors in Continuous Action Spaces
    Nicolò Botteghi, Khaled Alaa, Mannes Poel, Beril Sirmacek, Christoph Brune, Abeje Mersha, Stefano Stramigioli
    http://arxiv.org/abs/2107.01667v1

    • [cs.RO]Online and Offline Robot Programming via Augmented Reality Workspaces
    Yong Joon Thoo, Jérémy Maceiras, Philip Abbet, Mattia Racca, Hakan Girgin, Sylvain Calinon
    http://arxiv.org/abs/2107.01884v1

    • [cs.RO]Overcoming the Force Limitations of Magnetic Robotic Surgery: Impact-based Tetherless Suturing
    Onder Erin, Xiaolong Liu, Jiawei Ge, Lamar Mair, Yotam Barnoy, Yancy Diaz-Mercado, Axel Krieger
    http://arxiv.org/abs/2107.01504v1

    • [cs.RO]Prescient teleoperation of humanoid robots
    Luigi Penco, Jean-Baptiste Mouret, Serena Ivaldi
    http://arxiv.org/abs/2107.01281v1

    • [cs.RO]Row-sensing Templates: A Generic 3D Sensor-based Approach to Robot Localization with Respect to Orchard Row Centerlines
    Zhenghao Fei, Stavros Vougioukas
    http://arxiv.org/abs/2107.01321v1

    • [cs.RO]Targeted Muscle Effort Distribution with Exercise Robots: Trajectory and Resistance Effects
    Humberto De las Casas, Santino Bianco, Hanz Richter
    http://arxiv.org/abs/2107.01280v1

    • [cs.RO]Toward Increased Airspace Safety: Quadrotor Guidance for Targeting Aerial Objects
    Anish Bhattacharya
    http://arxiv.org/abs/2107.01733v1

    • [cs.RO]Towards safe human-to-robot handovers of unknown containers
    Yik Lung Pang, Alessio Xompero, Changjae Oh, Andrea Cavallaro
    http://arxiv.org/abs/2107.01309v1

    • [cs.RO]Unified Identification and Tuning Approach Using Deep Neural Networks For Visual Servoing Applications
    Oussama Abdul Hay, Mohamad Chehadeh, Abdulla Ayyad, Mohamad Wahbah, Muhammad Humais, Yahya Zweiri
    http://arxiv.org/abs/2107.01581v1

    • [cs.RO]Using Probabilistic Movement Primitives in Analyzing Human Motion Difference under Transcranial Current Stimulation
    Honghu Xue, Rebecca Herzog, Till M Berger, Tobias Bäumer, Anne Weissbach, Elmar Rueckert
    http://arxiv.org/abs/2107.02063v1

    • [cs.SD]A Lottery Ticket Hypothesis Framework for Low-Complexity Device-Robust Neural Acoustic Scene Classification
    Chao-Han Huck Yang, Hu Hu, Sabato Marco Siniscalchi, Qing Wang, Yuyang Wang, Xianjun Xia, Yuanjun Zhao, Yuzhong Wu, Yannan Wang, Jun Du, Chin-Hui Lee
    http://arxiv.org/abs/2107.01461v1

    • [cs.SD]DeepRapper: Neural Rap Generation with Rhyme and Rhythm Modeling
    Lanqing Xue, Kaitao Song, Duocai Wu, Xu Tan, Nevin L. Zhang, Tao Qin, Wei-Qiang Zhang, Tie-Yan Liu
    http://arxiv.org/abs/2107.01875v1

    • [cs.SD]Development of a Conversation State Recognition System
    Sujay Uday Rittikar
    http://arxiv.org/abs/2107.01462v1

    • [cs.SE]Automated Recovery of Issue-Commit Links Leveraging Both Textual and Non-textual Data
    Pooya Rostami Mazrae, Maliheh Izadi, Abbas Heydarnoori
    http://arxiv.org/abs/2107.01894v1

    • [cs.SI]A Multilayer Network Model of the Coevolution of the Spread of a Disease and Competing Opinions
    Kaiyan Peng, Zheng Lu, Vanessa Lin, Michael R. Lindstrom, Christian Parkinson, Chuntian Wang, Andrea L. Bertozzi, Mason A. Porter
    http://arxiv.org/abs/2107.01713v1

    • [cs.SI]Adversarial Robustness of Probabilistic Network Embedding for Link Prediction
    Xi Chen, Bo Kang, Jefrey Lijffijt, Tijl De Bie
    http://arxiv.org/abs/2107.01936v1

    • [cs.SI]Ranking Online Social Users by their Influence
    Anastasios Giovanidis, Bruno Baynat, Clémence Magnien, Antoine Vendeville
    http://arxiv.org/abs/2107.01914v1

    • [eess.AS]Relaxed Attention: A Simple Method to Boost Performance of End-to-End Automatic Speech Recognition
    Timo Lohrenz, Patrick Schwarz, Zhengyang Li, Tim Fingscheidt
    http://arxiv.org/abs/2107.01275v1

    • [eess.AS]Towards Neural Diarization for Unlimited Numbers of Speakers Using Global and Local Attractors
    Shota Horiguchi, Shinji Watanabe, Paola Garcia, Yawen Xue, Yuki Takashima, Yohei Kawaguchi
    http://arxiv.org/abs/2107.01545v1

    • [eess.IV]A study of CNN capacity applied to Left Venticle Segmentation in Cardiac MRI
    Marcelo Toledo, Daniel Lima, José Krieger, Marco Gutierrez
    http://arxiv.org/abs/2107.01318v1

    • [eess.IV]COVID-Rate: An Automated Framework for Segmentation of COVID-19 Lesions from Chest CT Scans
    Nastaran Enshaei, Anastasia Oikonomou, Moezedin Javad Rafiee, Parnian Afshar, Shahin Heidarian, Arash Mohammadi, Konstantinos N. Plataniotis, Farnoosh Naderkhani
    http://arxiv.org/abs/2107.01527v1

    • [eess.IV]COVID-VIT: Classification of COVID-19 from CT chest images based on vision transformer models
    Xiaohong Gao, Yu Qian, Alice Gao
    http://arxiv.org/abs/2107.01682v1

    • [eess.IV]CT Image Harmonization for Enhancing Radiomics Studies
    Md Selim, Jie Zhang, Baowei Fei, Guo-Qiang Zhang, Jin Chen
    http://arxiv.org/abs/2107.01337v1

    • [eess.IV]Controllable cardiac synthesis via disentangled anatomy arithmetic
    Spyridon Thermos, Xiao Liu, Alison O’Neil, Sotirios A. Tsaftaris
    http://arxiv.org/abs/2107.01748v1

    • [eess.IV]Custom Deep Neural Network for 3D Covid Chest CT-scan Classification
    Quoc Huy Trinh, Minh Van Nguyen
    http://arxiv.org/abs/2107.01456v1

    • [eess.IV]EAR-NET: Error Attention Refining Network For Retinal Vessel Segmentation
    Jun Wang, Xiaohan Yu, Yongsheng Gao
    http://arxiv.org/abs/2107.01351v1

    • [eess.IV]Pulmonary Vessel Segmentation based on Orthogonal Fused U-Net++ of Chest CT Images
    Hejie Cui, Xinglong Liu, Ning Huang
    http://arxiv.org/abs/2107.01502v1

    • [eess.IV]VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays
    Hoang C. Nguyen, Tung T. Le, Hieu H. Pham, Ha Q. Nguyen
    http://arxiv.org/abs/2107.01327v1

    • [eess.IV]WisdomNet: Prognosis of COVID-19 with Slender Prospect of False Negative Cases and Vaticinating the Probability of Maturation to ARDS using Posteroanterior Chest X-Rays
    Peeyush Kumar, Ayushe Gangal, Sunita Kumari
    http://arxiv.org/abs/2107.01392v1

    • [eess.SP]Unbiasing Procedures for Scale-invariant Multi-reference Alignment
    Matthew Hirn, Anna Little
    http://arxiv.org/abs/2107.01274v1

    • [gr-qc]On the Efficiency of Various Deep Transfer Learning Models in Glitch Waveform Detection in Gravitational-Wave Data
    Reymond Mesuga, Brian James Bayanay
    http://arxiv.org/abs/2107.01863v1

    • [math-ph]Cleaning large-dimensional covariance matrices for correlated samples
    Zdzislaw Burda, Andrzej Jarosz
    http://arxiv.org/abs/2107.01352v1

    • [math.OC]The Last-Iterate Convergence Rate of Optimistic Mirror Descent in Stochastic Variational Inequalities
    Waïss Azizian, Franck Iutzeler, Jérôme Malick, Panayotis Mertikopoulos
    http://arxiv.org/abs/2107.01906v1

    • [math.OC]Third Party Risk Modelling and Assessment for Safe UAV Path Planning in Metropolitan Environments
    Bizhao Pang, Xinting Hu, Wei Dai, Kin Huat Low
    http://arxiv.org/abs/2107.01834v1

    • [math.PR]Random Neural Networks in the Infinite Width Limit as Gaussian Processes
    Boris Hanin
    http://arxiv.org/abs/2107.01562v1

    • [math.ST]Accounting for Uncertainty When Estimating Counts Through an Average Rounded to the Nearest Integer
    Roberto Rivera, Axel Cortes-Cubero, Roberto Reyes-Carranza, Wolfgang Rolke
    http://arxiv.org/abs/2107.01618v1

    • [math.ST]Anisotropic spectral cut-off estimation under multiplicative measurement errors
    Sergio Brenner Miguel
    http://arxiv.org/abs/2107.02120v1

    • [math.ST]Asymptotic Statistical Analysis of Sparse Group LASSO via Approximate Message Passing Algorithm
    Kan Chen, Zhiqi Bu, Shiyun Xu
    http://arxiv.org/abs/2107.01266v1

    • [math.ST]Maximum likelihood for high-noise group orbit estimation and single-particle cryo-EM
    Zhou Fan, Roy R. Lederman, Yi Sun, Tianhao Wang, Sheng Xu
    http://arxiv.org/abs/2107.01305v1

    • [math.ST]Neyman-Pearson Hypothesis Testing, Epistemic Reliability and Pragmatic Value-Laden Asymmetric Error Risks
    Adam P. Kubiak, Pawel Kawalec, Adam Kiersztyn
    http://arxiv.org/abs/2107.01944v1

    • [math.ST]On the symmetric and skew-symmetric K-distributions
    Stylianos E. Trevlakis, Nestor Chatzidiamantis, George K. Karagiannidis
    http://arxiv.org/abs/2107.02092v1

    • [math.ST]Rates of Es
    3000
    timation of Optimal Transport Maps using Plug-in Estimators via Barycentric Projections
    Nabarun Deb, Promit Ghosal, Bodhisattva Sen
    http://arxiv.org/abs/2107.01718v1

    • [math.ST]Statistical Theory for Imbalanced Binary Classification
    Shashank Singh, Justin Khim
    http://arxiv.org/abs/2107.01777v1

    • [physics.geo-ph]A convolutional neural network for prestack fracture detection
    Zhenyu Yuan, Yuxin Jiang, Jingjing Li, Handong Huang
    http://arxiv.org/abs/2107.01466v1

    • [physics.optics]Imaging dynamics beneath turbid media via parallelized single-photon detection
    Shiqi Xu, Xi Yang, Wenhui Liu, Joakim Jonsson, Ruobing Qian, Pavan Chandra Konda, Kevin C. Zhou, Qionghai Dai, Haoqian Wang, Edouard Berrocal, Roarke Horstmeyer
    http://arxiv.org/abs/2107.01422v1

    • [physics.soc-ph]Become a better you: correlation between the change of research direction and the change of scientific performance
    Xiaoyao Yu, Boleslaw K. Szymanski, Tao Jia
    http://arxiv.org/abs/2107.01232v1

    • [physics.soc-ph]Directed Percolation in Temporal Networks
    Arash Badie-Modiri, Abbas K. Rizi, Márton Karsai, Mikko Kivelä
    http://arxiv.org/abs/2107.01510v1

    • [physics.soc-ph]Quantifying agent impacts on contact sequences in social interactions
    Mark M. Dekker, Tessa F. Blanken, Fabian Dablander, Jiamin Ou, Denny Borsboom, Debabrata Panja
    http://arxiv.org/abs/2107.01443v1

    • [physics.soc-ph]The hidden dependence of spreading vulnerability on topological complexity
    Mark M. Dekker, Debabrata Panja
    http://arxiv.org/abs/2107.01651v1

    • [q-bio.NC]Data-driven mapping between functional connectomes using optimal transport
    Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost
    http://arxiv.org/abs/2107.01303v1

    • [q-bio.NC]Lonely individuals process the world in idiosyncratic ways
    Elisa C. Baek, Ryan Hyon, Karina López, Mason A. Porter, Carolyn Parkinson
    http://arxiv.org/abs/2107.01312v1

    • [q-bio.PE]Principled, practical, flexible, fast: a new approach to phylogenetic factor analysis
    Gabriel W. Hassler, Brigida Gallone, Leandro Aristide, William L. Allen, Max R. Tolkoff, Andrew J. Holbrook, Guy Baele, Philippe Lemey, Marc A. Suchard
    http://arxiv.org/abs/2107.01246v1

    • [quant-ph]QKSA: Quantum Knowledge Seeking Agent
    Aritra Sarkar
    http://arxiv.org/abs/2107.01429v1

    • [quant-ph]Quantum Error Mitigation Relying on Permutation Filtering
    Yifeng Xiong, Soon Xin Ng, Lajos Hanzo
    http://arxiv.org/abs/2107.01458v1

    • [quant-ph]Sets of Marginals and Pearson-Correlation-based CHSH Inequalities for a Two-Qubit System
    Yuwen Huang, Pascal O. Vontobel
    http://arxiv.org/abs/2107.01816v1

    • [stat.AP]An extended watershed-based zonal statistical AHP model for flood risk estimation: Constraining runoff converging related indicators by sub-watersheds
    Hongping Zhang, Zhenfeng Shao, Jinqi Zhao, Xiao Huang, Jie Yang, Bin Hu, Wenfu Wu
    http://arxiv.org/abs/2107.02043v1

    • [stat.AP]Uncertainty in Lung Cancer Stage for Outcome Estimation via Set-Valued Classification
    Savannah Bergquist, Gabriel Brooks, Mary Beth Landrum, Nancy Keating, Sherri Rose
    http://arxiv.org/abs/2107.01251v1

    • [stat.CO]Variational Bayesian Inference for the Polytomous-Attribute Saturated Diagnostic Classification Model with Parallel Computing
    Motonori Oka, Shun Saso, Kensuke Okada
    http://arxiv.org/abs/2107.01865v1

    • [stat.ME]Analyzing Relevance Vector Machines using a single penalty approach
    Anand Dixit, Vivekananda Roy
    http://arxiv.org/abs/2107.02085v1

    • [stat.ME]Assessing contribution of treatment phases through tipping point analyses via counterfactual elicitation using rank preserving structural failure time models
    Sudipta Bhattacharya, Jyotirmoy Dey
    http://arxiv.org/abs/2107.01480v1

    • [stat.ME]Bayesian two-interval test
    Nicolas Meyer, Erik-André Sauleau
    http://arxiv.org/abs/2107.01271v1

    • [stat.ME]Blind source separation for non-stationary random fields
    Christoph Muehlmann, François Bachoc, Klaus Nordhausen
    http://arxiv.org/abs/2107.01916v1

    • [stat.ME]Calibrating generalized predictive distributions
    Pei-Shien Wu, Ryan Martin
    http://arxiv.org/abs/2107.01688v1

    • [stat.ME]Discussion of the manuscript: Spatial+ a novel approach to spatial confounding
    Georgia Papadogeorgou
    http://arxiv.org/abs/2107.01644v1

    • [stat.ME]Extending Latent Basis Growth Model to Explore Joint Development in the Framework of Individual Measurement Occasions
    Jin Liu
    http://arxiv.org/abs/2107.01773v1

    • [stat.ME]Matching a Desired Causal State via Shift Interventions
    Jiaqi Zhang, Chandler Squires, Caroline Uhler
    http://arxiv.org/abs/2107.01850v1

    • [stat.ME]Multivariate functional group sparse regression: functional predictor selection
    Ali Mahzarnia, Jun Song
    http://arxiv.org/abs/2107.02146v1

    • [stat.ME]Nonparametric Detection of Multiple Location-Scale Change Points via Wild Binary Segmentation
    Gordon J. Ross
    http://arxiv.org/abs/2107.01742v1

    • [stat.ME]Nonparametric quantile regression for time series with replicated observations and its application to climate data
    Soudeep Deb, Kaushik Jana
    http://arxiv.org/abs/2107.02091v1

    • [stat.ME]Novel Semi-parametric Tobit Additive Regression Models
    Hailin Huang
    http://arxiv.org/abs/2107.01497v1

    • [stat.ME]On the Estimation of Bivariate Return Curves for Extreme Values
    C. J. R. Murphy-Barltrop, J. L. Wadsworth, E. F. Eastoe
    http://arxiv.org/abs/2107.01942v1

    • [stat.ME]One-step TMLE to target cause-specific absolute risks and survival curves
    Helene C. W. Rytgaard, Mark J. van der Laan
    http://arxiv.org/abs/2107.01537v1

    • [stat.ME]Proportional mean model for panel count data with multiple modes of recurrence
    Sreedevi E. P., Sankaran P. G.
    http://arxiv.org/abs/2107.01388v1

    • [stat.ME]Selection of invalid instruments can improve estimation in Mendelian randomization
    Ashish Patel, Francis J. Ditraglia, Verena Zuber, Stephen Burgess
    http://arxiv.org/abs/2107.01513v1

    • [stat.ME]Sibling Regression for Generalized Linear Models
    Shiv Shankar, Daniel Sheldon
    http://arxiv.org/abs/2107.01338v1

    • [stat.ME]Sufficient principal component regression for pattern discovery in transcriptomic data
    Lei Ding, Gabriel E. Zentner, Daniel J. McDonald
    http://arxiv.org/abs/2107.02150v1

    • [stat.ME]The Effect of the Prior and the Experimental Design on the Inference of the Precision Matrix in Gaussian Chain Graph Models
    Yunyi Shen, Claudia Solis-Lemus
    http://arxiv.org/abs/2107.01306v1

    • [stat.ME]Zero-modified Count Time Series with Markovian Intensities
    N. Balakrishna, Muhammed Anvar, Bovas Abraham
    http://arxiv.org/abs/2107.01813v1

    • [stat.ML]A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the k-Triangle-Faithfulness Assumption
    Shuyan Wang, Peter Spirtes
    http://arxiv.org/abs/2107.01333v1

    • [stat.ML]Antithetic Riemannian Manifold And Quantum-Inspired Hamiltonian Monte Carlo
    Wilson Tsakane Mongwe, Rendani Mbuvha, Tshilidzi Marwala
    http://arxiv.org/abs/2107.02070v1

    • [stat.ML]Causally Invariant Predictor with Shift-Robustness
    Xiangyu Zheng, Xinwei Sun, Wei Chen, Tie-Yan Liu
    http://arxiv.org/abs/2107.01876v1

    • [stat.ML]Deep Gaussian Process Emulation using Stochastic Imputation
    Deyu Ming, Daniel Williamson, Serge Guillas
    http://arxiv.org/abs/2107.01590v1

    • [stat.ML]Latent structure blockmodels for Bayesian spectral graph clustering
    Francesco Sanna Passino, Nicholas A. Heard
    http://arxiv.org/abs/2107.01734v1

    • [stat.ML]Learning Bayesian Networks through Birkhoff Polytope: A Relaxation Method
    Aramayis Dallakyan, Mohsen Pourahmadi
    http://arxiv.org/abs/2107.01658v1

    • [stat.ML]Minimum Wasserstein Distance Estimator under Finite Location-scale Mixtures
    Qiong Zhang, Jiahua Chen
    http://arxiv.org/abs/2107.01323v1

    • [stat.ML]Optimizing ROC Curves with a Sort-Based Surrogate Loss Function for Binary Classification and Changepoint Detection
    Jonathan Hillman, Toby Dylan Hocking
    http://arxiv.org/abs/2107.01285v1

    • [stat.ML]Scale Mixtures of Neural Network Gaussian Processes
    Hyungi Lee, Eunggu Yun, Hongseok Yang, Juho Lee
    http://arxiv.org/abs/2107.01408v1

    • [stat.ML]Slope and generalization properties of neural networks
    Anton Johansson, Niklas Engsner, Claes Strannegård, Petter Mostad
    http://arxiv.org/abs/2107.01473v1

    • [stat.ML]Template-Based Graph Clustering
    Mateus Riva, Florian Yger, Pietro Gori, Roberto M. Cesar Jr., Isabelle Bloch
    http://arxiv.org/abs/2107.01994v1

    • [stat.ML]The Role of “Live” in Livestreaming Markets: Evidence Using Orthogonal Random Forest
    Ziwei Cong, Jia Liu, Puneet Manchanda
    http://arxiv.org/abs/2107.01629v1

    • [stat.ML]Tiled Squeeze-and-Excite: Channel Attention With Local Spatial Context
    Niv Vosco, Alon Shenkler, Mark Grobman
    http://arxiv.org/abs/2107.02145v1

    • [stat.ML]UCSL : A Machine Learning Expectation-Maximization framework for Unsupervised Clustering driven by Supervised Learning
    Robin Louiset, Pietro Gori, Benoit Dufumier, Josselin Houenou, Antoine Grigis, Edouard Duchesnay
    http://arxiv.org/abs/2107.01988v1