cs.AI - 人工智能
    cs.AR - 硬件体系结构
    cs.CE - 计算工程、 金融和科学
    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.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.MM - 多媒体
    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
    math.CT - 范畴论
    math.DS - 动力系统
    math.NA - 数值分析
    math.OC - 优化与控制
    math.PR - 概率
    math.ST - 统计理论
    physics.ao-ph - 大气和海洋物理
    q-bio.GN - 基因组学
    q-bio.PE - 人口与发展
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cs.AI]Communicating Natural Programs to Humans and Machines
    • [cs.AI]Counterfactual Explanations as Interventions in Latent Space
    • [cs.AI]Diagnosing the Impact of AI on Radiology in China
    • [cs.AI]Improving Search by Utilizing State Information in OPTIC Planners Compilation to LP
    • [cs.AI]Medical Code Prediction from Discharge Summary: Document to Sequence BERT using Sequence Attention
    • [cs.AI]Physion: Evaluating Physical Prediction from Vision in Humans and Machines
    • [cs.AI]Population-coding and Dynamic-neurons improved Spiking Actor Network for Reinforcement Learning
    • [cs.AI]Pre-Trained Models: Past, Present and Future
    • [cs.AI]Query Embedding on Hyper-relational Knowledge Graphs
    • [cs.AI]Targeted Data Acquisition for Evolving Negotiation Agents
    • [cs.AI]Zero-shot Node Classification with Decomposed Graph Prototype Network
    • [cs.AR]S2Engine: A Novel Systolic Architecture for Sparse Convolutional Neural Networks
    • [cs.CE]CatBoost model with synthetic features in application to loan risk assessment of small businesses
    • [cs.CE]Graphical Gaussian Process Regression Model for Aqueous Solvation Free Energy Prediction of Organic Molecules in Redox Flow Battery
    • [cs.CL]ARTA: Collection and Classification of Ambiguous Requests and Thoughtful Actions
    • [cs.CL]An Automated Quality Evaluation Framework of Psychotherapy Conversations with Local Quality Estimates
    • [cs.CL]Assessing the Use of Prosody in Constituency Parsing of Imperfect Transcripts
    • [cs.CL]Bilateral Personalized Dialogue Generation with Dynamic Persona-Aware Fusion
    • [cs.CL]Biomedical Entity Linking with Contrastive Context Matching
    • [cs.CL]CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
    • [cs.CL]CausalNLP: A Practical Toolkit for Causal Inference with Text
    • [cs.CL]Challenges and Considerations with Code-Mixed NLP for Multilingual Societies
    • [cs.CL]CoDERT: Distilling Encoder Representations with Co-learning for Transducer-based Speech Recognition
    • [cs.CL]Consistency Regularization for Cross-Lingual Fine-Tuning
    • [cs.CL]Cross-sentence Neural Language Models for Conversational Speech Recognition
    • [cs.CL]Deriving Word Vectors from Contextualized Language Models using Topic-Aware Mention Selection
    • [cs.CL]Determinantal Beam Search
    • [cs.CL]Direction is what you need: Improving Word Embedding Compression in Large Language Models
    • [cs.CL]Improving Paraphrase Detection with the Adversarial Paraphrasing Task
    • [cs.CL]Incorporating Word Sense Disambiguation in Neural Language Models
    • [cs.CL]Knowledge-Rich BERT Embeddings for Readability Assessment
    • [cs.CL]Language Tags Matter for Zero-Shot Neural Machine Translation
    • [cs.CL]Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python
    • [cs.CL]Maximum Spanning Trees Are Invariant to Temperature Scaling in Graph-based Dependency Parsing
    • [cs.CL]Modeling morphology with Linear Discriminative Learning: considerations and design choices
    • [cs.CL]Overcoming Domain Mismatch in Low Resource Sequence-to-Sequence ASR Models using Hybrid Generated Pseudotranscripts
    • [cs.CL]Question Answering Infused Pre-training of General-Purpose Contextualized Representations
    • [cs.CL]SSMix: Saliency-Based Span Mixup for Text Classification
    • [cs.CL]Semantic Representation and Inference for NLP
    • [cs.CL]Sequence-Level Training for Non-Autoregressive Neural Machine Translation
    • [cs.CL]Text Generation with Efficient (Soft) Q-Learning
    • [cs.CL]The Possible, the Plausible, and the Desirable: Event-Based Modality Detection for Language Processing
    • [cs.CL]Three-part diachronic semantic change dataset for Russian
    • [cs.CL]Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance
    • [cs.CL]Using heterogeneity in semi-supervised transcription hypotheses to improve code-switched speech recognition
    • [cs.CR]CAN-LOC: Spoofing Detection and Physical Intrusion Localization on an In-Vehicle CAN Bus Based on Deep Features of Voltage Signals
    • [cs.CR]Code Integrity Attestation for PLCs using Black Box Neural Network Predictions
    • [cs.CR]Defending Touch-based Continuous Authentication Systems from Active Adversaries Using Generative Adversarial Networks
    • [cs.CR]Efficient Asynchronous Byzantine Agreement without Private Setups
    • [cs.CR]Evading Malware Classifiers via Monte Carlo Mutant Feature Discovery
    • [cs.CR]Multivariate Public Key Cryptosystemfrom Sidon Spaces
    • [cs.CR]On the Evaluation of Sequential Machine Learning for Network Intrusion Detection
    • [cs.CR]Privacy Assessment of Federated Learning using Private Personalized Layers
    • [cs.CR]Snail Mail Beats Email Any Day: On Effective Operator Security Notifications in the Internet
    • [cs.CR]Temporal Consistency Checks to Detect LiDAR Spoofing Attacks on Autonomous Vehicle Perception
    • [cs.CR]The Reliability and Acceptance of Biometric System in Bangladesh: Users Perspective
    • [cs.CV]A Clinically Inspired Approach for Melanoma classification
    • [cs.CV]A Hybrid mmWave and Camera System for Long-Range Depth Imaging
    • [cs.CV]A Spacecraft Dataset for Detection, Segmentation and Parts Recognition
    • [cs.CV]BEiT: BERT Pre-Training of Image Transformers
    • [cs.CV]Canonical Face Embeddings
    • [cs.CV]Cascading Convolutional Temporal Colour Constancy
    • [cs.CV]Cluster-guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification
    • [cs.CV]Color2Style: Real-Time Exemplar-Based Image Colorization with Self-Reference Learning and Deep Feature Modulation
    • [cs.CV]Compositional Sketch Search
    • [cs.CV]Computer-aided Interpretable Features for Leaf Image Classification
    • [cs.CV]DFM: A Performance Baseline for Deep Feature Matching
    • [cs.CV]Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification
    • [cs.CV]Demographic Fairness in Face Identification: The Watchlist Imbalance Effect
    • [cs.CV]Direction-aware Feature-level Frequency Decomposition for Single Image Deraining
    • [cs.CV]Domain Adaptive SiamRPN++ for Object Tracking in the Wild
    • [cs.CV]Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data
    • [cs.CV]Dynamic Head: Unifying Object Detection Heads with Attentions
    • [cs.CV]Efficient Facial Expression Analysis For Dimensional Affect Recognition Using Geometric Features
    • [cs.CV]Encouraging Intra-Class Diversity Through a Reverse Contrastive Loss for Better Single-Source Domain Generalization
    • [cs.CV]Face Age Progression With Attribute Manipulation
    • [cs.CV]Flow Guided Transformable Bottleneck Networks for Motion Retargeting
    • [cs.CV]G今日学术视野(2021.6.17) - 图1DA: Geometry-Guided Dual-Alignment Learning for RGB-Infrared Person Re-Identification
    • [cs.CV]Generating Data Augmentation samples for Semantic Segmentation of Salt Bodies in a Synthetic Seismic Image Dataset
    • [cs.CV]Generating Thermal Human Faces for Physiological Assessment Using Thermal Sensor Auxiliary Labels
    • [cs.CV]Gradient Forward-Propagation for Large-Scale Temporal Video Modelling
    • [cs.CV]Hotel Recognition via Latent Image Embedding
    • [cs.CV]Image Feature Information Extraction for Interest Point Detection: A Comprehensive Review
    • [cs.CV]Is this Harmful? Learning to Predict Harmfulness Ratings from Video
    • [cs.CV]Keep CALM and Improve Visual Feature Attribution
    • [cs.CV]Learning Deep Morphological Networks with Neural Architecture Search
    • [cs.CV]Learning to Aggregate and Personalize 3D Face from In-the-Wild Photo Collection
    • [cs.CV]Mixed Model OCR Training on Historical Latin Script for Out-of-the-Box Recognition and Finetuning
    • [cs.CV]Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
    • [cs.CV]Multi-script Handwritten Digit Recognition Using Multi-task Learning
    • [cs.CV]Mutation Sensitive Correlation Filter for Real-Time UAV Tracking with Adaptive Hybrid Label
    • [cs.CV]Object detection and Autoencoder-based 6D pose estimation for highly cluttered Bin Picking
    • [cs.CV]Potato Crop Stress Identification in Aerial Images using Deep Learning-based Object Detection
    • [cs.CV]ReS2tAC — UAV-Borne Real-Time SGM Stereo Optimized for Embedded ARM and CUDA Devices
    • [cs.CV]Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera
    • [cs.CV]Relation Modeling in Spatio-Temporal Action Localization
    • [cs.CV]Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images
    • [cs.CV]SAR Image Classification Based on Spiking Neural Network through Spike-Time Dependent Plasticity and Gradient Descent
    • [cs.CV]Towards Total Recall in Industrial Anomaly Detection
    • [cs.CV]Vision-Language Navigation with Random Environmental Mixup
    • [cs.CV]Weakly-Supervised Photo-realistic Texture Generation for 3D Face Reconstruction
    • [cs.CV]Zero-sample surface defect detection and classification based on semantic feedback neural network
    • [cs.CY]Achieving digital-driven patient agility in the era of big data
    • [cs.CY]Fairness as Equality of Opportunity: Normative Guidance from Political Philosophy
    • [cs.CY]Identifying Roles, Requirements and Responsibilities in Trustworthy AI Systems
    • [cs.DB]A Survey on Mining and Analysis of Uncertain Graphs
    • [cs.DC]Don’t Count on One to Carry the Ball: Scaling BFT without Sacrifing Efficiency
    • [cs.DC]Modeling memory bandwidth patterns on NUMA machines with performance counters
    • [cs.DC]ShortcutFusion: From Tensorflow to FPGA-based accelerator with reuse-aware memory allocation for shortcut data
    • [cs.GT]Learning Revenue-Maximizing Auctions With Differentiable Matching
    • [cs.GT]Optimization-friendly generic mechanisms without money
    • [cs.HC]StockBabble: A Conversational Financial Agent to support Stock Market Investors
    • [cs.IR]Can BERT Dig It? — Named Entity Recognition for Information Retrieval in the Archaeology Domain
    • [cs.IR]Does your robot know? Enhancing children’s information retrieval through spoken conversation with responsible robots
    • [cs.IR]Incorporating Domain Knowledge into Health Recommender Systems using Hyperbolic Embeddings
    • [cs.IR]Interpretable Self-supervised Multi-task Learning for COVID-19 Information Retrieval and Extraction
    • [cs.IR]To Infinity and Beyond! Accessibility is the Future for Kids’ Search Engines
    • [cs.IR]Towards Axiomatic Explanations for Neural Ranking Models
    • [cs.IR]User-specific Adaptive Fine-tuning for Cross-domain Recommendations
    • [cs.IT]A Monte-Carlo Based Construction of Polarization-Adjusted Convolutional (PAC) Codes
    • [cs.IT]Bivariate Polynomial Codes for Secure Distributed Matrix Multiplication
    • [cs.IT]Coded Privacy-Preserving Computation at Edge Networks
    • [cs.IT]Cyclic codes over a non-chain ring 今日学术视野(2021.6.17) - 图2 and their application to LCD codes
    • [cs.IT]Eavesdropper and Jammer Selection in Wireless Source Localization Networks
    • [cs.IT]Enforcing Statistical Orthogonality in Massive MIMO Systems via Covariance Shaping
    • [cs.IT]Heterogeneous Multi-sensor Fusion with Random Finite Set Multi-object Densities
    • [cs.IT]Improving the List Decoding Version of the Cyclically Equivariant Neural Decoder
    • [cs.IT]Intelligent Reflecting Surface Aided Wireless Energy and Information Transmission: An Overview
    • [cs.IT]Learning Autonomy in Management of Wireless Random Networks
    • [cs.IT]Over-the-Air Decentralized Federated Learning
    • [cs.IT]QoE Driven VR 360 Video Massive MIMO Transmission
    • [cs.IT]The subfield codes and subfield subcodes of a family of MDS codes
    • [cs.IT]User Pairing and Power Allocation for IRS-Assisted NOMA Systems with Imperfect Phase Compensation
    • [cs.LG]A White Paper on Neural Network Quantization
    • [cs.LG]An Analytical Theory of Curriculum Learning in Teacher-Student Networks
    • [cs.LG]An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks
    • [cs.LG]Awardee Solution of KDD Cup 2021 OGB Large-Scale Challenge Graph-Level Track
    • [cs.LG]Boosting in the Presence of Massart Noise
    • [cs.LG]CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
    • [cs.LG]CathAI: Fully Automated Interpretation of Coronary Angiograms Using Neural Networks
    • [cs.LG]Causal Navigation by Continuous-time Neural Networks
    • [cs.LG]Compression Implies Generalization
    • [cs.LG]Constraining Linear-chain CRFs to Regular Languages
    • [cs.LG]Contextualizing Multiple Tasks via Learning to Decompose
    • [cs.LG]Control Variates for Slate Off-Policy Evaluation
    • [cs.LG]Controlling Neural Networks with Rule Representations
    • [cs.LG]Counterfactual Explanations for Machine Learning: Challenges Revisited
    • [cs.LG]Coupled Gradient Estimators for Discrete Latent Variables
    • [cs.LG]Credit Assignment in Neural Networks through Deep Feedback Control
    • [cs.LG]Deep Reinforcement Learning for Conservation Decisions
    • [cs.LG]Efficient Micro-Structured Weight Unification for Neural Network Compression
    • [cs.LG]End-to-End Learning of Keypoint Representations for Continuous Control from Images
    • [cs.LG]Evaluating Modules in Graph Contrastive Learning
    • [cs.LG]Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection
    • [cs.LG]GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning
    • [cs.LG]Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach
    • [cs.LG]HUMAP: Hierarchical Uniform Manifold Approximation and Projection
    • [cs.LG]How Modular Should Neural Module Networks Be for Systematic Generalization?
    • [cs.LG]Hypergraph Dissimilarity Measures
    • [cs.LG]Improved Regret Bounds for Online Submodular Maximization
    • [cs.LG]Improving Robustness of Graph Neural Networks with Heterophily-Inspired Designs
    • [cs.LG]Improving the compromise between accuracy, interpretability and personalization of rule-based machine learning in medical problems
    • [cs.LG]KL Guided Domain Adaptation
    • [cs.LG]Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent
    • [cs.LG]Learning Incident Prediction Models Over Large Geographical Areas for Emergency Response Systems
    • [cs.LG]Learning Stable Classifiers by Transferring Unstable Features
    • [cs.LG]Machine Learning with Electronic Health Records is vulnerable to Backdoor Trigger Attacks
    • [cs.LG]Machine learning-based conditional mean filter: a generalization of the ensemble Kalman filter for nonlinear data assimilation
    • [cs.LG]Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations
    • [cs.LG]Model Extraction and Adversarial Attacks on Neural Networks using Switching Power Information
    • [cs.LG]Multivariate Business Process Representation Learning utilizing Gramian Angular Fields and Convolutional Neural Networks
    • [cs.LG]Natural continual learning: success is a journey, not (just) a destination
    • [cs.LG]Next Generation Reservoir Computing
    • [cs.LG]Non-Gradient Manifold Neural Network
    • [cs.LG]On Large-Cohort Training for Federated Learning
    • [cs.LG]On Multi-objective Policy Optimization as a Tool for Reinforcement Learning
    • [cs.LG]On the Convergence of Deep Learning with Differential Privacy
    • [cs.LG]On the Power of Multitask Representation Learning in Linear MDP
    • [cs.LG]Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation
    • [cs.LG]PairConnect: A Compute-Efficient MLP Alternative to Attention
    • [cs.LG]Phase Transitions, Distance Functions, and Implicit Neural Representations
    • [cs.LG]Pitfalls of Explainable ML: An Industry Perspective
    • [cs.LG]Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting
    • [cs.LG]Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers
    • [cs.LG]Probabilistic Margins for Instance Reweighting in Adversarial Training
    • [cs.LG]RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning
    • [cs.LG]Randomized Exploration for Reinforcement Learning with General Value Function Approximation
    • [cs.LG]Residual Reinforcement Learning from Demonstrations
    • [cs.LG]Revisiting Model Stitching to Compare Neural Representations
    • [cs.LG]Revisiting the Calibration of Modern Neural Networks
    • [cs.LG]Robust Out-of-Distribution Detection on Deep Probabilistic Generative Models
    • [cs.LG]Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
    • [cs.LG]Scaling Neural Tangent Kernels via Sketching and Random Features
    • [cs.LG]Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation
    • [cs.LG]Site-Agnostic 3D Dose Distribution Prediction with Deep Learning Neural Networks
    • [cs.LG]SynthASR: Unlocking Synthetic Data for Speech Recognition
    • [cs.LG]The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization
    • [cs.LG]Thompson Sampling for Unimodal Bandits
    • [cs.LG]Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering
    • [cs.LG]Very Deep Graph Neural Networks Via Noise Regularisation
    • [cs.LG]Voting for the right answer: Adversarial defense for speaker verification
    • [cs.MM]Detect and remove watermark in deep neural networks via generative adversarial networks
    • [cs.RO]Constrained Motion Planning of A Cable-Driven Soft Robot With Compressible Curvature Modeling
    • [cs.RO]Force-Sensing Tensegrity for Investigating Physical Human-Robot Interaction in Compliant Robotic Systems
    • [cs.RO]Human movement augmentation and how to make it a reality
    • [cs.RO]NeuroBEM: Hybrid Aerodynamic Quadrotor Model
    • [cs.RO]Simplifying Robot Programming using Augmented Reality and End-User Development
    • [cs.RO]Task Allocation and Coordinated Motion Planning for Autonomous Multi-Robot Optical Inspection Systems
    • [cs.RO]Towards Safe Control of Continuum Manipulator Using Shielded Multiagent Reinforcement Learning
    • [cs.SD]Adaptive Margin Circle Loss for Speaker Verification
    • [cs.SD]Graph-based Label Propagation for Semi-Supervised Speaker Identification
    • [cs.SD]Learning Audio-Visual Dereverberation
    • [cs.SD]Teacher-Student MixIT for Unsupervised and Semi-supervised Speech Separation
    • [cs.SD]Tracing Back Music Emotion Predictions to Sound Sources and Intuitive Perceptual Qualities
    • [cs.SE]A Syntax-Guided Edit Decoder for Neural Program Repair
    • [cs.SI]Evaluating the Effect of the Financial Status to the Mobility Customs
    • [cs.SI]Full Bitcoin Blockchain Data Made Easy
    • [eess.AS]Dialectal Speech Recognition and Translation of Swiss German Speech to Standard German Text: Microsoft’s Submission to SwissText 2021
    • [eess.AS]Kaizen: Continuously improving teacher using Exponential Moving Average for semi-supervised speech recognition
    • [eess.IV]A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification
    • [eess.IV]Automated triaging of head MRI examinations using convolutional neural networks
    • [eess.IV]Automatic linear measurements of the fetal brain on MRI with deep neural networks
    • [eess.IV]Cine-MRI detection of abdominal adhesions with spatio-temporal deep learning
    • [eess.IV]EuroCrops: A Pan-European Dataset for Time Series Crop Type Classification
    • [eess.IV]Highdicom: A Python library for standardized encoding of image annotations and machine learning model outputs in pathology and radiology
    • [eess.IV]Perceptually-inspired super-resolution of compressed videos
    • [eess.IV]ResDepth: A Deep Prior For 3D Reconstruction From High-resolution Satellite Images
    • [eess.IV]Wavelength-based Attributed Deep Neural Network for Underwater Image Restoration
    • [eess.SP]A stochastic metapopulation state-space approach to modeling and estimating Covid-19 spread
    • [eess.SP]Jamming Detection With Subcarrier Blanking for 5G and Beyond in Industry 4.0 Scenarios
    • [eess.SP]Learning to Compensate: A Deep Neural Network Framework for 5G Power Amplifier Compensation
    • [eess.SP]Towards Long-term Non-invasive Monitoring for Epilepsy via Wearable EEG Devices
    • [math.CT]An enriched category theory of language: from syntax to semantics
    • [math.DS]Extracting Global Dynamics of Loss Landscape in Deep Learning Models
    • [math.NA]Augmented Tensor Decomposition with Stochastic Optimization
    • [math.OC]A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization
    • [math.OC]Decentralized Local Stochastic Extra-Gradient for Variational Inequalities
    • [math.OC]Non-asymptotic convergence bounds for Wasserstein approximation using point clouds
    • [math.OC]SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients
    • [math.OC]Unique sparse decomposition of low rank matrices
    • [math.PR]Diagonal sections of copulas, multivariate conditional hazard rates and distributions of order statistics for minimally stable lifetimes
    • [math.ST]Generalized kernel distance covariance in high dimensions: non-null CLTs and power universality
    • [math.ST]Markov Equivalence of Max-Linear Bayesian Networks
    • [physics.ao-ph]Capabilities of Deep Learning Models on Learning Physical Relationships: Case of Rainfall-Runoff Modeling with LSTM
    • [q-bio.GN]Active feature selection discovers minimal gene-sets for classifying cell-types and disease states in single-cell mRNA-seq data
    • [q-bio.GN]MetaCache-GPU: Ultra-Fast Metagenomic Classification
    • [q-bio.PE]Epidemic modelling of multiple virus strains:a case study of SARS-CoV-2 B.1.1.7 in Moscow
    • [stat.AP]A Non-ergodic Effective Amplitude Ground-Motion Model for California
    • [stat.AP]Embracing Uncertainty in “Small Data” Problems: Estimating Earthquakes from Historical Anecdotes
    • [stat.ME]A Bayesian adaptive design for dual-agent phase I-II cancer clinical trials combining efficacy data across stages
    • [stat.ME]A Horseshoe Pit mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging
    • [stat.ME]A Phylogenetic Trees Analysis of SARS-CoV-2
    • [stat.ME]Adaptive normalization for IPW estimation
    • [stat.ME]Bootstrapping Clustered Data in R using lmeresampler
    • [stat.ME]Inference for treatment-specific survival curves using machine learning
    • [stat.ME]Robust Inference for High-Dimensional Linear Models via Residual Randomization
    • [stat.ME]Tree-Values: selective inference for regression trees
    • [stat.ML]Canonical-Correlation-Based Fast Feature Selection
    • [stat.ML]Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
    • [stat.ML]Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT)
    • [stat.ML]Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral
    • [stat.ML]Employing an Adjusted Stability Measure for Multi-Criteria Model Fitting on Data Sets with Similar Features
    • [stat.ML]Kernel Identification Through Transformers
    • [stat.ML]Linear-Time Probabilistic Solutions of Boundary Value Problems
    • [stat.ML]RFpredInterval: An R Package for Prediction Intervals with Random Forests and Boosted Forests
    • [stat.ML]S-LIME: Stabilized-LIME for Model Explanation
    • [stat.ML]Self-Supervised Learning with Kernel Dependence Maximization

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

    • [cs.AI]Communicating Natural Programs to Humans and Machines
    Samuel Acquaviva, Yewen Pu, Marta Kryven, Catherine Wong, Gabrielle E Ecanow, Maxwell Nye, Theodoros Sechopoulos, Michael Henry Tessler, Joshua B. Tenenbaum
    http://arxiv.org/abs/2106.07824v1

    • [cs.AI]Counterfactual Explanations as Interventions in Latent Space
    Riccardo Crupi, Alessandro Castelnovo, Daniele Regoli, Beatriz San Miguel Gonzalez
    http://arxiv.org/abs/2106.07754v1

    • [cs.AI]Diagnosing the Impact of AI on Radiology in China
    Niklas Muennighoff
    http://arxiv.org/abs/2106.07921v1

    • [cs.AI]Improving Search by Utilizing State Information in OPTIC Planners Compilation to LP
    Elad Denenberg, Amanda Coles, Derek Long
    http://arxiv.org/abs/2106.07924v1

    • [cs.AI]Medical Code Prediction from Discharge Summary: Document to Sequence BERT using Sequence Attention
    Tak-Sung Heo, Yongmin Yoo, Yeongjoon Park, Byeong-Cheol Jo
    http://arxiv.org/abs/2106.07932v1

    • [cs.AI]Physion: Evaluating Physical Prediction from Vision in Humans and Machines
    Daniel M. Bear, Elias Wang, Damian Mrowca, Felix J. Binder, Hsiau-Yu Fish Tung, R. T. Pramod, Cameron Holdaway, Sirui Tao, Kevin Smith, Li Fei-Fei, Nancy Kanwisher, Joshua B. Tenenbaum, Daniel L. K. Yamins, Judith E. Fan
    http://arxiv.org/abs/2106.08261v1

    • [cs.AI]Population-coding and Dynamic-neurons improved Spiking Actor Network for Reinforcement Learning
    Duzhen Zhang, Tielin Zhang, Shuncheng Jia, Xiang Cheng, Bo Xu
    http://arxiv.org/abs/2106.07854v1

    • [cs.AI]Pre-Trained Models: Past, Present and Future
    Xu Han, Zhengyan Zhang, Ning Ding, Yuxian Gu, Xiao Liu, Yuqi Huo, Jiezhong Qiu, Liang Zhang, Wentao Han, Minlie Huang, Qin Jin, Yanyan Lan, Yang Liu, Zhiyuan Liu, Zhiwu Lu, Xipeng Qiu, Ruihua Song, Jie Tang, Ji-Rong Wen, Jinhui Yuan, Wayne Xin Zhao, Jun Zhu
    http://arxiv.org/abs/2106.07139v2

    • [cs.AI]Query Embedding on Hyper-relational Knowledge Graphs
    Dimitrios Alivanistos, Max Berrendorf, Michael Cochez, Mikhail Galkin
    http://arxiv.org/abs/2106.08166v1

    • [cs.AI]Targeted Data Acquisition for Evolving Negotiation Agents
    Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh
    http://arxiv.org/abs/2106.07728v1

    • [cs.AI]Zero-shot Node Classification with Decomposed Graph Prototype Network
    Zheng Wang, Jialong Wang, Yuchen Guo, Zhiguo Gong
    http://arxiv.org/abs/2106.08022v1

    • [cs.AR]S2Engine: A Novel Systolic Architecture for Sparse Convolutional Neural Networks
    Jianlei Yang, Wenzhi Fu, Xingzhou Cheng, Xucheng Ye, Pengcheng Dai, Weisheng Zhao
    http://arxiv.org/abs/2106.07894v1

    • [cs.CE]CatBoost model with synthetic features in application to loan risk assessment of small businesses
    Liexing Cheng, Haoxue Wang
    http://arxiv.org/abs/2106.07954v1

    • [cs.CE]Graphical Gaussian Process Regression Model for Aqueous Solvation Free Energy Prediction of Organic Molecules in Redox Flow Battery
    Peiyuan Gao, Xiu Yang, Yu-Hang Tang, Muqing Zheng, Amity Anderson, Vijayakumar Murugesan, Aaron Hollas, Wei Wang
    http://arxiv.org/abs/2106.08146v1

    • [cs.CL]ARTA: Collection and Classification of Ambiguous Requests and Thoughtful Actions
    Shohei Tanaka, Koichiro Yoshino, Katsuhito Sudoh, Satoshi Nakamura
    http://arxiv.org/abs/2106.07999v1

    • [cs.CL]An Automated Quality Evaluation Framework of Psychotherapy Conversations with Local Quality Estimates
    Zhuohao Chen, Nikolaos Flemotomos, Karan Singla, Torrey A. Creed, David C. Atkins, Shrikanth Narayanan
    http://arxiv.org/abs/2106.07922v1

    • [cs.CL]Assessing the Use of Prosody in Constituency Parsing of Imperfect Transcripts
    Trang Tran, Mari Ostendorf
    http://arxiv.org/abs/2106.07794v1

    • [cs.CL]Bilateral Personalized Dialogue Generation with Dynamic Persona-Aware Fusion
    Bin Li, Bin Sun, Shutao Li
    http://arxiv.org/abs/2106.07857v1

    • [cs.CL]Biomedical Entity Linking with Contrastive Context Matching
    Shogo Ujiie, Hayate Iso, Eiji Aramaki
    http://arxiv.org/abs/2106.07583v2

    • [cs.CL]CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
    Ningyu Zhang, Zhen Bi, Xiaozhuan Liang, Lei Li, Xiang Chen, Shumin Deng, Luoqiu Li, Xin Xie, Hongbin Ye, Xin Shang, Kangping Yin, Chuanqi Tan, Jian Xu, Mosha Chen, Fei Huang, Luo Si, Yuan Ni, Guotong Xie, Zhifang Sui, Baobao Chang, Hui Zong, Zheng Yuan, Linfeng Li, Jun Yan, Hongying Zan, Kunli Zhang, Huajun Chen, Buzhou Tang, Qingcai Chen
    http://arxiv.org/abs/2106.08087v1

    • [cs.CL]CausalNLP: A Practical Toolkit for Causal Inference with Text
    Arun S. Maiya
    http://arxiv.org/abs/2106.08043v1

    • [cs.CL]Challenges and Considerations with Code-Mixed NLP for Multilingual Societies
    Vivek Srivastava, Mayank Singh
    http://arxiv.org/abs/2106.07823v1

    • [cs.CL]CoDERT: Distilling Encoder Representations with Co-learning for Transducer-based Speech Recognition
    Rupak Vignesh Swaminathan, Brian King, Grant P. Strimel, Jasha Droppo, Athanasios Mouchtaris
    http://arxiv.org/abs/2106.07734v1

    • [cs.CL]Consistency Regularization for Cross-Lingual Fine-Tuning
    Bo Zheng, Li Dong, Shaohan Huang, Wenhui Wang, Zewen Chi, Saksham Singhal, Wanxiang Che, Ting Liu, Xia Song, Furu Wei
    http://arxiv.org/abs/2106.08226v1

    • [cs.CL]Cross-sentence Neural Language Models for Conversational Speech Recognition
    Shih-Hsuan Chiu, Tien-Hong Lo, Berlin Chen
    http://arxiv.org/abs/2106.06922v2

    • [cs.CL]Deriving Word Vectors from Contextualized Language Models using Topic-Aware Mention Selection
    Yixiao Wang, Zied Bouraoui, Luis Espinosa Anke, Steven Schockaert
    http://arxiv.org/abs/2106.07947v1

    • [cs.CL]Determinantal Beam Search
    Clara Meister, Martina Forster, Ryan Cotterell
    http://arxiv.org/abs/2106.07400v2

    • [cs.CL]Direction is what you need: Improving Word Embedding Compression in Large Language Models
    Klaudia Bałazy, Mohammadreza Banaei, Rémi Lebret, Jacek Tabor, Karl Aberer
    http://arxiv.org/abs/2106.08181v1

    • [cs.CL]Improving Paraphrase Detection with the Adversarial Paraphrasing Task
    Animesh Nighojkar, John Licato
    http://arxiv.org/abs/2106.07691v1

    • [cs.CL]Incorporating Word Sense Disambiguation in Neural Language Models
    Jan Philip Wahle, Terry Ruas, Norman Meuschke, Bela Gipp
    http://arxiv.org/abs/2106.07967v1

    • [cs.CL]Knowledge-Rich BERT Embeddings for Readability Assessment
    Joseph Marvin Imperial
    http://arxiv.org/abs/2106.07935v1

    • [cs.CL]Language Tags Matter for Zero-Shot Neural Machine Translation
    Liwei Wu, Shanbo Cheng, Mingxuan Wang, Lei Li
    http://arxiv.org/abs/2106.07930v1

    • [cs.CL]Launching into clinical space with medspaCy: a new clinical text processing toolkit in Python
    Hannah Eyre, Alec B Chapman, Kelly S Peterson, Jianlin Shi, Patrick R Alba, Makoto M Jones, Tamara L Box, Scott L DuVall, Olga V Patterson
    http://arxiv.org/abs/2106.07799v1

    • [cs.CL]Maximum Spanning Trees Are Invariant to Temperature Scaling in Graph-based Dependency Parsing
    Stefan Grünewald
    http://arxiv.org/abs/2106.08159v1

    • [cs.CL]Modeling morphology with Linear Discriminative Learning: considerations and design choices
    Maria Heitmeier, Yu-Ying Chuang, R. Harald Baayen
    http://arxiv.org/abs/2106.07936v1

    • [cs.CL]Overcoming Domain Mismatch in Low Resource Sequence-to-Sequence ASR Models using Hybrid Generated Pseudotranscripts
    Chak-Fai Li, Francis Keith, William Hartmann, Matthew Snover, Owen Kimball
    http://arxiv.org/abs/2106.07716v1

    • [cs.CL]Question Answering Infused Pre-training of General-Purpose Contextualized Representations
    Robin Jia, Mike Lewis, Luke Zettlemoyer
    http://arxiv.org/abs/2106.08190v1

    • [cs.CL]SSMix: Saliency-Based Span Mixup for Text Classification
    Soyoung Yoon, Gyuwan Kim, Kyumin Park
    http://arxiv.org/abs/2106.08062v1

    • [cs.CL]Semantic Representation and Inference for NLP
    Dongsheng Wang
    http://arxiv.org/abs/2106.08117v1

    • [cs.CL]Sequence-Level Training for Non-Autoregressive Neural Machine Translation
    Chenze Shao, Yang Feng, Jinchao Zhang, Fandong Meng, Jie Zhou
    http://arxiv.org/abs/2106.08122v1

    • [cs.CL]Text Generation with Efficient (Soft) Q-Learning
    Han Guo, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu
    http://arxiv.org/abs/2106.07704v1

    • [cs.CL]The Possible, the Plausible, and the Desirable: Event-Based Modality Detection for Language Processing
    Valentina Pyatkin, Shoval Sadde, Aynat Rubinstein, Paul Portner, Reut Tsarfaty
    http://arxiv.org/abs/2106.08037v1

    • [cs.CL]Three-part diachronic semantic change dataset for Russian
    Andrey Kutuzov, Lidia Pivovarova
    http://arxiv.org/abs/2106.08294v1

    • [cs.CL]Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance
    Masaru Isonuma, Junichiro Mori, Danushka Bollegala, Ichiro Sakata
    http://arxiv.org/abs/2106.08007v1

    • [cs.CL]Using heterogeneity in semi-supervised transcription hypotheses to improve code-switched speech recognition
    Andrew Slottje, Shannon Wotherspoon, William Hartmann, Matthew Snover, Owen Kimball
    http://arxiv.org/abs/2106.07699v1

    • [cs.CR]CAN-LOC: Spoofing Detection and Physical Intrusion Localization on an In-Vehicle CAN Bus Based on Deep Features of Voltage Signals
    Efrat Levy, Asaf Shabtai, Bogdan Groza, Pal-Stefan Murvay, Yuval Elovici
    http://arxiv.org/abs/2106.07895v1

    • [cs.CR]Code Integrity Attestation for PLCs using Black Box Neural Network Predictions
    Yuqi Chen, Christopher M. Poskitt, Jun Sun
    http://arxiv.org/abs/2106.07851v1

    • [cs.CR]Defending Touch-based Continuous Authentication Systems from Active Adversaries Using Generative Adversarial Networks
    Mohit Agrawal, Pragyan Mehrotra, Rajesh Kumar, Rajiv Ratn Shah
    http://arxiv.org/abs/2106.07867v1

    • [cs.CR]Efficient Asynchronous Byzantine Agreement without Private Setups
    Yingzi Gao, Yuan Lu, Zhenliang Lu, Qiang Tang, Jing Xu, Zhenfeng Zhang
    http://arxiv.org/abs/2106.07831v1

    • [cs.CR]Evading Malware Classifiers via Monte Carlo Mutant Feature Discovery
    John Boutsikas, Maksim E. Eren, Charles Varga, Edward Raff, Cynthia Matuszek, Charles Nicholas
    http://arxiv.org/abs/2106.07860v1

    • [cs.CR]Multivariate Public Key Cryptosystemfrom Sidon Spaces
    Netanel Raviv, Ben Langton, Itzhak Tamo
    http://arxiv.org/abs/2106.07785v1

    • [cs.CR]On the Evaluation of Sequential Machine Learning for Network Intrusion Detection
    Andrea Corsini, Shanchieh Jay Yang, Giovanni Apruzzese
    http://arxiv.org/abs/2106.07961v1

    • [cs.CR]Privacy Assessment of Federated Learning using Private Personalized Layers
    Théo Jourdan, Antoine Boutet, Carole Frindel
    http://arxiv.org/abs/2106.08060v1

    • [cs.CR]Snail Mail Beats Email Any Day: On Effective Operator Security Notifications in the Internet
    Max Maass, Marc-Pascal Clement, Matthias Hollick
    http://arxiv.org/abs/2106.08024v1

    • [cs.CR]Temporal Consistency Checks to Detect LiDAR Spoofing Attacks on Autonomous Vehicle Perception
    Zhongyuan Hau, Soteris Demetriou
    http://arxiv.org/abs/2106.07833v1

    • [cs.CR]The Reliability and Acceptance of Biometric System in Bangladesh: Users Perspective
    Shaykh Siddique, Monica Yasmin, Tasnova Bintee Taher, Mushfiqul Alam
    http://arxiv.org/abs/2106.08177v1

    • [cs.CV]A Clinically Inspired Approach for Melanoma classification
    Prathyusha Akundi, Soumyasis Gun, Jayanthi Sivaswamy
    http://arxiv.org/abs/2106.08021v1

    • [cs.CV]A Hybrid mmWave and Camera System for Long-Range Depth Imaging
    Diana Zhang, Akarsh Prabhakara, Sirajum Munir, Aswin Sankaranarayanan, Swarun Kumar
    http://arxiv.org/abs/2106.07856v1

    • [cs.CV]A Spacecraft Dataset for Detection, Segmentation and Parts Recognition
    Dung Anh Hoang, Bo Chen, Tat-Jun Chin
    http://arxiv.org/abs/2106.08186v1

    • [cs.CV]BEiT: BERT Pre-Training of Image Transformers
    Hangbo Bao, Li Dong, Furu Wei
    http://arxiv.org/abs/2106.08254v1

    • [cs.CV]Canonical Face Embeddings
    David McNeely-White, Ben Sattelberg, Nathaniel Blanchard, Ross Beveridge
    http://arxiv.org/abs/2106.07822v1

    • [cs.CV]Cascading Convolutional Temporal Colour Constancy
    Matteo Rizzo, Cristina Conati, Daesik Jang, Hui Hu
    http://arxiv.org/abs/2106.07955v1

    • [cs.CV]Cluster-guided Asymmetric Contrastive Learning for Unsupervised Person Re-Identification
    Mingkun Li, Chun-Guang Li, Jun Guo
    http://arxiv.org/abs/2106.07846v1

    • [cs.CV]Color2Style: Real-Time Exemplar-Based Image Colorization with Self-Reference Learning and Deep Feature Modulation
    Hengyuan Zhao, Wenhao Wu, Yihao Liu, Dongliang He
    http://arxiv.org/abs/2106.08017v1

    • [cs.CV]Compositional Sketch Search
    Alexander Black, Tu Bui, Long Mai, Hailin Jin, John Collomosse
    http://arxiv.org/abs/2106.08009v1

    • [cs.CV]Computer-aided Interpretable Features for Leaf Image Classification
    Jayani P. G. Lakshika, Thiyanga S. Talagala
    http://arxiv.org/abs/2106.08077v1

    • [cs.CV]DFM: A Performance Baseline for Deep Feature Matching
    Ufuk Efe, Kutalmis Gokalp Ince, A. Aydin Alatan
    http://arxiv.org/abs/2106.07791v1

    • [cs.CV]Deep Transfer Learning for Brain Magnetic Resonance Image Multi-class Classification
    Yusuf Brima, Mossadek Hossain Kamal Tushar, Upama Kabir, Tariqul Islam
    http://arxiv.org/abs/2106.07333v2

    • [cs.CV]Demographic Fairness in Face Identification: The Watchlist Imbalance Effect
    Pawel Drozdowski, Christian Rathgeb, Christoph Busch
    http://arxiv.org/abs/2106.08049v1

    • [cs.CV]Direction-aware Feature-level Frequency Decomposition for Single Image Deraining
    Sen Deng, Yidan Feng, Mingqiang Wei, Haoran Xie, Yiping Chen, Jonathan Li, Xiao-Ping Zhang, Jing Qin
    http://arxiv.org/abs/2106.07941v1

    • [cs.CV]Domain Adaptive SiamRPN++ for Object Tracking in the Wild
    Zhongzhou Zhang, Lei Zhang
    http://arxiv.org/abs/2106.07862v1

    • [cs.CV]Dynamic Distillation Network for Cross-Domain Few-Shot Recognition with Unlabeled Data
    Ashraful Islam, Chun-Fu Chen, Rameswar Panda, Leonid Karlinsky, Rogerio Feris, Richard J. Radke
    http://arxiv.org/abs/2106.07807v1

    • [cs.CV]Dynamic Head: Unifying Object Detection Heads with Attentions
    Xiyang Dai, Yinpeng Chen, Bin Xiao, Dongdong Chen, Mengchen Liu, Lu Yuan, Lei Zhang
    http://arxiv.org/abs/2106.08322v1

    • [cs.CV]Efficient Facial Expression Analysis For Dimensional Affect Recognition Using Geometric Features
    Vassilios Vonikakis, Stefan Winkler
    http://arxiv.org/abs/2106.07817v1

    • [cs.CV]Encouraging Intra-Class Diversity Through a Reverse Contrastive Loss for Better Single-Source Domain Generalization
    Thomas Duboudin, Emmanuel
    d4c
    Dellandréa, Corentin Abgrall, Gilles Hénaff, Liming Chen
    http://arxiv.org/abs/2106.07916v1

    • [cs.CV]Face Age Progression With Attribute Manipulation
    Sinzith Tatikonda, Athira Nambiar, Anurag Mittal
    http://arxiv.org/abs/2106.07696v1

    • [cs.CV]Flow Guided Transformable Bottleneck Networks for Motion Retargeting
    Jian Ren, Menglei Chai, Oliver J. Woodford, Kyle Olszewski, Sergey Tulyakov
    http://arxiv.org/abs/2106.07771v1

    • [cs.CV]G今日学术视野(2021.6.17) - 图3DA: Geometry-Guided Dual-Alignment Learning for RGB-Infrared Person Re-Identification
    Lin Wan, Zongyuan Sun, Qianyan Jing, Yehansen Chen, Lijing Lu, Zhihang Li
    http://arxiv.org/abs/2106.07853v1

    • [cs.CV]Generating Data Augmentation samples for Semantic Segmentation of Salt Bodies in a Synthetic Seismic Image Dataset
    Luis Felipe Henriques, Sérgio Colcher, Ruy Luiz Milidiú, André Bulcão, Pablo Barros
    http://arxiv.org/abs/2106.08269v1

    • [cs.CV]Generating Thermal Human Faces for Physiological Assessment Using Thermal Sensor Auxiliary Labels
    Catherine Ordun, Edward Raff, Sanjay Purushotham
    http://arxiv.org/abs/2106.08091v1

    • [cs.CV]Gradient Forward-Propagation for Large-Scale Temporal Video Modelling
    Mateusz Malinowski, Dimitrios Vytiniotis, Grzegorz Swirszcz, Viorica Patraucean, Joao Carreira
    http://arxiv.org/abs/2106.08318v1

    • [cs.CV]Hotel Recognition via Latent Image Embedding
    Boris Tseytlin, Ilya Makarov
    http://arxiv.org/abs/2106.08042v1

    • [cs.CV]Image Feature Information Extraction for Interest Point Detection: A Comprehensive Review
    Junfeng Jing, Tian Gao, Weichuan Zhang, Yongsheng Gao, Changming Sun
    http://arxiv.org/abs/2106.07929v1

    • [cs.CV]Is this Harmful? Learning to Predict Harmfulness Ratings from Video
    Johan Edstedt, Johan Karlsson, Francisca Benavente, Anette Novak, Amanda Berg, Michael Felsberg
    http://arxiv.org/abs/2106.08323v1

    • [cs.CV]Keep CALM and Improve Visual Feature Attribution
    Jae Myung Kim, Junsuk Choe, Zeynep Akata, Seong Joon Oh
    http://arxiv.org/abs/2106.07861v1

    • [cs.CV]Learning Deep Morphological Networks with Neural Architecture Search
    Yufei Hu, Nacim Belkhir, Jesus Angulo, Angela Yao, Gianni Franchi
    http://arxiv.org/abs/2106.07714v1

    • [cs.CV]Learning to Aggregate and Personalize 3D Face from In-the-Wild Photo Collection
    Zhenyu Zhang, Yanhao Ge, Renwang Chen, Ying Tai, Yan Yan, Jian Yang, Chengjie Wang, Jilin Li, Feiyue Huang
    http://arxiv.org/abs/2106.07852v1

    • [cs.CV]Mixed Model OCR Training on Historical Latin Script for Out-of-the-Box Recognition and Finetuning
    Christian Reul, Christoph Wick, Maximilian Nöth, Andreas Büttner, Maximilian Wehner, Uwe Springmann
    http://arxiv.org/abs/2106.07881v1

    • [cs.CV]Multi-StyleGAN: Towards Image-Based Simulation of Time-Lapse Live-Cell Microscopy
    Tim Prangemeier, Christoph Reich, Christian Wildner, Heinz Koeppl
    http://arxiv.org/abs/2106.08285v1

    • [cs.CV]Multi-script Handwritten Digit Recognition Using Multi-task Learning
    Mesay Samuel Gondere, Lars Schmidt-Thieme, Durga Prasad Sharma, Randolf Scholz
    http://arxiv.org/abs/2106.08267v1

    • [cs.CV]Mutation Sensitive Correlation Filter for Real-Time UAV Tracking with Adaptive Hybrid Label
    Guangze Zheng, Changhong Fu, Junjie Ye, Fuling Lin, Fangqiang Ding
    http://arxiv.org/abs/2106.08073v1

    • [cs.CV]Object detection and Autoencoder-based 6D pose estimation for highly cluttered Bin Picking
    Timon Höfer, Faranak Shamsafar, Nuri Benbarka, Andreas Zell
    http://arxiv.org/abs/2106.08045v1

    • [cs.CV]Potato Crop Stress Identification in Aerial Images using Deep Learning-based Object Detection
    Sujata Butte, Aleksandar Vakanski, Kasia Duellman, Haotian Wang, Amin Mirkouei
    http://arxiv.org/abs/2106.07770v1

    • [cs.CV]ReS2tAC — UAV-Borne Real-Time SGM Stereo Optimized for Embedded ARM and CUDA Devices
    Boitumelo Ruf, Jonas Mohrs, Martin Weinmann, Stefan Hinz, Jürgen Beyerer
    http://arxiv.org/abs/2106.07927v1

    • [cs.CV]Real-time Pose and Shape Reconstruction of Two Interacting Hands With a Single Depth Camera
    Franziska Mueller, Micah Davis, Florian Bernard, Oleksandr Sotnychenko, Mickeal Verschoor, Miguel A. Otaduy, Dan Casas, Christian Theobalt
    http://arxiv.org/abs/2106.08059v1

    • [cs.CV]Relation Modeling in Spatio-Temporal Action Localization
    Yutong Feng, Jianwen Jiang, Ziyuan Huang, Zhiwu Qing, Xiang Wang, Shiwei Zhang, Mingqian Tang, Yue Gao
    http://arxiv.org/abs/2106.08061v1

    • [cs.CV]Reverse Engineering of Generative Models: Inferring Model Hyperparameters from Generated Images
    Vishal Asnani, Xi Yin, Tal Hassner, Xiaoming Liu
    http://arxiv.org/abs/2106.07873v1

    • [cs.CV]SAR Image Classification Based on Spiking Neural Network through Spike-Time Dependent Plasticity and Gradient Descent
    Jiankun Chen, Xiaolan Qiu, Chibiao Ding, Yirong Wu
    http://arxiv.org/abs/2106.08005v1

    • [cs.CV]Towards Total Recall in Industrial Anomaly Detection
    Karsten Roth, Latha Pemula, Joaquin Zepeda, Bernhard Schölkopf, Thomas Brox, Peter Gehler
    http://arxiv.org/abs/2106.08265v1

    • [cs.CV]Vision-Language Navigation with Random Environmental Mixup
    Chong Liu, Fengda Zhu, Xiaojun Chang, Xiaodan Liang, Yi-Dong Shen
    http://arxiv.org/abs/2106.07876v1

    • [cs.CV]Weakly-Supervised Photo-realistic Texture Generation for 3D Face Reconstruction
    Xiangnan Yin, Di Huang, Zehua Fu, Yunhong Wang, Liming Chen
    http://arxiv.org/abs/2106.08148v1

    • [cs.CV]Zero-sample surface defect detection and classification based on semantic feedback neural network
    Yibo Guo, Yiming Fan, Zhiyang Xiang, Haidi Wang, Wenhua Meng, Mingliang Xu
    http://arxiv.org/abs/2106.07959v1

    • [cs.CY]Achieving digital-driven patient agility in the era of big data
    Rogier van de Wetering
    http://arxiv.org/abs/2106.08204v1

    • [cs.CY]Fairness as Equality of Opportunity: Normative Guidance from Political Philosophy
    Falaah Arif Khan, Eleni Manis, Julia Stoyanovich
    http://arxiv.org/abs/2106.08259v1

    • [cs.CY]Identifying Roles, Requirements and Responsibilities in Trustworthy AI Systems
    Iain Barclay, Will Abramson
    http://arxiv.org/abs/2106.08258v1

    • [cs.DB]A Survey on Mining and Analysis of Uncertain Graphs
    Suman Banerjee
    http://arxiv.org/abs/2106.07837v1

    • [cs.DC]Don’t Count on One to Carry the Ball: Scaling BFT without Sacrifing Efficiency
    Kexin Hu, Kaiwen Guo, Qiang Tang, Zhenfeng Zhang, Hao Cheng, Zhiyang Zhao
    http://arxiv.org/abs/2106.08114v1

    • [cs.DC]Modeling memory bandwidth patterns on NUMA machines with performance counters
    Daniel Goodman, Roni Haecki, Tim Harris
    http://arxiv.org/abs/2106.08026v1

    • [cs.DC]ShortcutFusion: From Tensorflow to FPGA-based accelerator with reuse-aware memory allocation for shortcut data
    Duy Thanh Nguyen, Hyeonseung Je, Tuan Nghia Nguyen, Soojung Ryu, Kyujung Lee, Hyuk-Jae Lee
    http://arxiv.org/abs/2106.08167v1

    • [cs.GT]Learning Revenue-Maximizing Auctions With Differentiable Matching
    Michael J. Curry, Uro Lyi, Tom Goldstein, John Dickerson
    http://arxiv.org/abs/2106.07877v1

    • [cs.GT]Optimization-friendly generic mechanisms without money
    Mark Braverman
    http://arxiv.org/abs/2106.07752v1

    • [cs.HC]StockBabble: A Conversational Financial Agent to support Stock Market Investors
    Suraj Sharma, Joseph Brennan, Jason R. C. Nurse
    http://arxiv.org/abs/2106.08298v1

    • [cs.IR]Can BERT Dig It? — Named Entity Recognition for Information Retrieval in the Archaeology Domain
    Alex Brandsen, Suzan Verberne, Karsten Lambers, Milco Wansleeben
    http://arxiv.org/abs/2106.07742v1

    • [cs.IR]Does your robot know? Enhancing children’s information retrieval through spoken conversation with responsible robots
    T. Beelen, E. Velner, R. Ordelman, K. P. Truong, V. Evers, T. Huibers
    http://arxiv.org/abs/2106.07931v1

    • [cs.IR]Incorporating Domain Knowledge into Health Recommender Systems using Hyperbolic Embeddings
    Joel Peito, Qiwei Han
    http://arxiv.org/abs/2106.07720v1

    • [cs.IR]Interpretable Self-supervised Multi-task Learning for COVID-19 Information Retrieval and Extraction
    Nima Ebadi, Peyman Najafirad
    http://arxiv.org/abs/2106.08252v1

    • [cs.IR]To Infinity and Beyond! Accessibility is the Future for Kids’ Search Engines
    Ashlee Milton, Garrett Allen, Maria Soledad Pera
    http://arxiv.org/abs/2106.07813v1

    • [cs.IR]Towards Axiomatic Explanations for Neural Ranking Models
    Michael Völske, Alexander Bondarenko, Maik Fröbe, Matthias Hagen, Benno Stein, Jaspreet Singh, Avishek Anand
    http://arxiv.org/abs/2106.08019v1

    • [cs.IR]User-specific Adaptive Fine-tuning for Cross-domain Recommendations
    Lei Chen, Fajie Yuan, Jiaxi Yang, Xiangnan He, Chengming Li, Min Yang
    http://arxiv.org/abs/2106.07864v1

    • [cs.IT]A Monte-Carlo Based Construction of Polarization-Adjusted Convolutional (PAC) Codes
    Mohsen Moradi, Amir Mozammel
    http://arxiv.org/abs/2106.08118v1

    • [cs.IT]Bivariate Polynomial Codes for Secure Distributed Matrix Multiplication
    Burak Hasircioglu, Jesus Gomez-Vilardebo, Deniz Gunduz
    http://arxiv.org/abs/2106.07731v1

    • [cs.IT]Coded Privacy-Preserving Computation at Edge Networks
    Elahe Vedadi - Yasaman Keshtkarjahromi - Hulya Seferoglu
    http://arxiv.org/abs/2106.08290v1

    • [cs.IT]Cyclic codes over a non-chain ring 今日学术视野(2021.6.17) - 图4 and their application to LCD codes
    Habibul Islam, Edgar Martínez-Moro, Om Prakash
    http://arxiv.org/abs/2106.07962v1

    • [cs.IT]Eavesdropper and Jammer Selection in Wireless Source Localization Networks
    Cuneyd Ozturk, Sinan Gezici
    http://arxiv.org/abs/2106.07709v1

    • [cs.IT]Enforcing Statistical Orthogonality in Massive MIMO Systems via Covariance Shaping
    Placido Mursia, Italo Atzeni, Laura Cottatellucci, David Gesbert
    http://arxiv.org/abs/2106.07952v1

    • [cs.IT]Heterogeneous Multi-sensor Fusion with Random Finite Set Multi-object Densities
    Wei Yi, Lei Chai
    http://arxiv.org/abs/2106.08088v1

    • [cs.IT]Improving the List Decoding Version of the Cyclically Equivariant Neural Decoder
    Xiangyu Chen, Min Ye
    http://arxiv.org/abs/2106.07964v1

    • [cs.IT]Intelligent Reflecting Surface Aided Wireless Energy and Information Transmission: An Overview
    Qingqing Wu, Xinrong Guan, Rui Zhang
    http://arxiv.org/abs/2106.07997v1

    • [cs.IT]Learning Autonomy in Management of Wireless Random Networks
    Hoon Lee, Sang Hyun Lee, Tony Q. S. Quek
    http://arxiv.org/abs/2106.07984v1

    • [cs.IT]Over-the-Air Decentralized Federated Learning
    Yandong Shi, Yong Zhou, Yuanming Shi
    http://arxiv.org/abs/2106.08011v1

    • [cs.IT]QoE Driven VR 360 Video Massive MIMO Transmission
    Long Teng, Guangtao Zhai, Yongpeng Wu, Xiongkuo Min, Wenjun Zhang, Zhi Ding, Chengshang Xiao
    http://arxiv.org/abs/2106.08165v1

    • [cs.IT]The subfield codes and subfield subcodes of a family of MDS codes
    Chunming Tang, Qi Wang, Cunsheng Ding
    http://arxiv.org/abs/2106.07840v1

    • [cs.IT]User Pairing and Power Allocation for IRS-Assisted NOMA Systems with Imperfect Phase Compensation
    Pavan Reddy M., Abhinav Kumar
    http://arxiv.org/abs/2106.07938v1

    • [cs.LG]A White Paper on Neural Network Quantization
    Markus Nagel, Marios Fournarakis, Rana Ali Amjad, Yelysei Bondarenko, Mart van Baalen, Tijmen Blankevoort
    http://arxiv.org/abs/2106.08295v1

    • [cs.LG]An Analytical Theory of Curriculum Learning in Teacher-Student Networks
    Luca Saglietti, Stefano Sarao Mannelli, Andrew Saxe
    http://arxiv.org/abs/2106.08068v1

    • [cs.LG]An Exponential Improvement on the Memorization Capacity of Deep Threshold Networks
    Shashank Rajput, Kartik Sreenivasan, Dimitris Papailiopoulos, Amin Karbasi
    http://arxiv.org/abs/2106.07724v1

    • [cs.LG]Awardee Solution of KDD Cup 2021 OGB Large-Scale Challenge Graph-Level Track
    Chengxuan Ying, Mingqi Yang, Shuxin Zheng, Guolin Ke, Shengjie Luo, Tianle Cai, Chenglin Wu, Yuxin Wang, Yanming Shen, Di He
    http://arxiv.org/abs/2106.08279v1

    • [cs.LG]Boosting in the Presence of Massart Noise
    Ilias Diakonikolas, Russell Impagliazzo, Daniel Kane, Rex Lei, Jessica Sorrell, Christos Tzamos
    http://arxiv.org/abs/2106.07779v1

    • [cs.LG]CRFL: Certifiably Robust Federated Learning against Backdoor Attacks
    Chulin Xie, Minghao Chen, Pin-Yu Chen, Bo Li
    http://arxiv.org/abs/2106.08283v1

    • [cs.LG]CathAI: Fully Automated Interpretation of Coronary Angiograms Using Neural Networks
    Robert Avram, Jeffrey E. Olgin, Alvin Wan, Zeeshan Ahmed, Louis Verreault-Julien, Sean Abreau, Derek Wan, Joseph E. Gonzalez, Derek Y. So, Krishan Soni, Geoffrey H. Tison
    http://arxiv.org/abs/2106.07708v1

    • [cs.LG]Causal Navigation by Continuous-time Neural Networks
    Charles Vorbach, Ramin Hasani, Alexander Amini, Mathias Lechner, Daniela Rus
    http://arxiv.org/abs/2106.08314v1

    • [cs.LG]Compression Implies Generalization
    Allan Grønlund, Mikael Høgsgaard, Lior Kamma, Kasper Green Larsen
    http://arxiv.org/abs/2106.07989v1

    • [cs.LG]Constraining Linear-chain CRFs to Regular Languages
    Sean Papay, Roman Klinger, Sebastian Padó
    http://arxiv.org/abs/2106.07306v2

    • [cs.LG]Contextualizing Multiple Tasks via Learning to Decompose
    Han-Jia Ye, Da-Wei Zhou, Lanqing Hong, Zhenguo Li, Xiu-Shen Wei, De-Chuan Zhan
    http://arxiv.org/abs/2106.08112v1

    • [cs.LG]Control Variates for Slate Off-Policy Evaluation
    Nikos Vlassis, Ashok Chandrashekar, Fernando Amat Gil, Nathan Kallus
    http://arxiv.org/abs/2106.07914v1

    • [cs.LG]Controlling Neural Networks with Rule Representations
    Sungyong Seo, Sercan O. Arik, Jinsung Yoon, Xiang Zhang, Kihyuk Sohn, Tomas Pfister
    http://arxiv.org/abs/2106.07804v1

    • [cs.LG]Counterfactual Explanations for Machine Learning: Challenges Revisited
    Sahil Verma, John Dickerson, Keegan Hines
    http://arxiv.org/abs/2106.07756v1

    • [cs.LG]Coupled Gradient Estimators for Discrete Latent Variables
    Zhe Dong, Andriy Mnih, George Tucker
    http://arxiv.org/abs/2106.08056v1

    • [cs.LG]Credit Assignment in Neural Networks through Deep Feedback Control
    Alexander Meulemans, Matilde Tristany Farinha, Javier García Ordóñez, Pau Vilimelis Aceituno, João Sacramento, Benjamin F. Grewe
    http://arxiv.org/abs/2106.07887v1

    • [cs.LG]Deep Reinforcement Learning for Conservation Decisions
    Marcus Lapeyrolerie, Melissa S. Chapman, Kari E. A. Norman, Carl Boettiger
    http://arxiv.org/abs/2106.08272v1

    • [cs.LG]Efficient Micro-Structured Weight Unification for Neural Network Compression
    Sheng Lin, Wei Jiang, Wei Wang, Kaidi Xu, Yanzhi Wang, Shan Liu, Songnan Li
    http://arxiv.org/abs/2106.08301v1

    • [cs.LG]End-to-End Learning of Keypoint Representations for Continuous Control from Images
    Rinu Boney, Alexander Ilin, Juho Kannala
    http://arxiv.org/abs/2106.07995v1

    • [cs.LG]Evaluating Modules in Graph Contrastive Learning
    Ganqu Cui, Yufeng Du, Cheng Yang, Jie Zhou, Liang Xu, Lifeng Wang, Zhiyuan Liu
    http://arxiv.org/abs/2106.08171v1

    • [cs.LG]Federated Learning for Internet of Things: A Federated Learning Framework for On-device Anomaly Data Detection
    Tuo Zhang, Chaoyang He, Tianhao Ma, Mark Ma, Salman Avestimehr
    http://arxiv.org/abs/2106.07976v1

    • [cs.LG]GDI: Rethinking What Makes Reinforcement Learning Different From Supervised Learning
    Jiajun Fan, Changnan Xiao, Yue Huang
    http://arxiv.org/abs/2106.06232v2

    • [cs.LG]Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach
    Johannes Rabold, Michael Siebers, Ute Schmid
    http://arxiv.org/abs/2106.08064v1

    • [cs.LG]HUMAP: Hierarchical Uniform Manifold Approximation and Projection
    Wilson E. Marcílio-Jr, Danilo M. Eler, Fernando V. Paulovich, Rafael M. Martins
    http://arxiv.org/abs/2106.07718v1

    • [cs.LG]How Modular Should Neural Module Networks Be for Systematic Generalization?
    Vanessa D’Amario, Tomotake Sasaki, Xavier Boix
    http://arxiv.org/abs/2106.08170v1

    • [cs.LG]Hypergraph Dissimilarity Measures
    Amit Surana, Can Chen, Indika Rajapakse
    http://arxiv.org/abs/2106.08206v1

    • [cs.LG]Improved Regret Bounds for Online Submodular Maximization
    Omid Sadeghi, Prasanna Raut, Maryam Fazel
    http://arxiv.org/abs/2106.07836v1

    • [cs.LG]Improving Robustness of Graph Neural Networks with Heterophily-Inspired Designs
    Jiong Zhu, Junchen Jin, Michael T. Schaub, Danai Koutra
    http://arxiv.org/abs/2106.07767v1

    • [cs.LG]Improving the compromise between accuracy, interpretability and personalization of rule-based machine learning in medical problems
    Francisco Valente, Simao Paredes, Jorge Henriques
    http://arxiv.org/abs/2106.07827v1

    • [cs.LG]KL Guided Domain Adaptation
    A. Tuan Nguyen, Toan Tran, Yarin Gal, Philip H. S. Torr, Atılım Güneş Baydin
    http://arxiv.org/abs/2106.07780v1

    • [cs.LG]Learning Equivariant Energy Based Models with Equivariant Stein Variational Gradient Descent
    Priyank Jaini, Lars Holdijk, Max Welling
    http://arxiv.org/abs/2106.07832v1

    • [cs.LG]Learning Incident Prediction Models Over Large Geographical Areas for Emergency Response Systems
    Sayyed Mohsen Vazirizade, Ayan Mukhopadhyay, Geoffrey Pettet, Said El Said, Hiba Baroud, Abhishek Dubey
    http://arxiv.org/abs/2106.08307v1

    • [cs.LG]Learning Stable Classifiers by Transferring Unstable Features
    Yujia Bao, Shiyu Chang, Regina Barzilay
    http://arxiv.org/abs/2106.07847v1

    • [cs.LG]Machine Learning with Electronic Health Records is vulnerable to Backdoor Trigger Attacks
    Byunggill Joe, Akshay Mehra, Insik Shin, Jihun Hamm
    http://arxiv.org/abs/2106.07925v1

    • [cs.LG]Machine learning-based conditional mean filter: a generalization of the ensemble Kalman filter for nonlinear data assimilation
    Truong-Vinh Hoang, Sebastian Krumscheid, Hermann G. Matthies, Raúl Tempone
    http://arxiv.org/abs/2106.07908v1

    • [cs.LG]Mean Embeddings with Test-Time Data Augmentation for Ensembling of Representations
    Arsenii Ashukha, Andrei Atanov, Dmitry Vetrov
    http://arxiv.org/abs/2106.08038v1

    • [cs.LG]Model Extraction and Adversarial Attacks on Neural Networks using Switching Power Information
    Tommy Li, Cory Merkel
    http://arxiv.org/abs/2106.08299v1

    • [cs.LG]Multivariate Business Process Representation Learning utilizing Gramian Angular Fields and Convolutional Neural Networks
    Peter Pfeiffer, Johannes Lahann, Peter Fettke
    http://arxiv.org/abs/2106.08027v1

    • [cs.LG]Natural continual learning: success is a journey, not (just) a destination
    Ta-Chu Kao, Kristopher T. Jensen, Alberto Bernacchia, Guillaume Hennequin
    http://arxiv.org/abs/2106.08085v1

    • [cs.LG]Next Generation Reservoir Computing
    Daniel J. Gauthier, Erik Bollt, Aaron Griffith, Wendson A. S. Barbosa
    http://arxiv.org/abs/2106.07688v1

    • [cs.LG]Non-Gradient Manifold Neural Network
    Rui Zhang, Ziheng Jiao, Hongyuan Zhang, Xuelong Li
    http://arxiv.org/abs/2106.07905v1

    • [cs.LG]On Large-Cohort Training for Federated Learning
    Zachary Charles, Zachary Garrett, Zhouyuan Huo, Sergei Shmulyian, Virginia Smith
    http://arxiv.org/abs/2106.07820v1

    • [cs.LG]On Multi-objective Policy Optimization as a Tool for Reinforcement Learning
    Abbas Abdolmaleki, Sandy H. Huang, Giulia Vezzani, Bobak Shahriari, Jost Tobias Springenberg, Shruti Mishra, Dhruva TB, Arunkumar Byravan, Konstantinos Bousmalis, Andras Gyorgy, Csaba Szepesvari, Raia Hadsell, Nicolas Heess, Martin Riedmiller
    http://arxiv.org/abs/2106.08199v1

    • [cs.LG]On the Convergence of Deep Learning with Differential Privacy
    Zhiqi Bu, Hua Wang, Qi Long, Weijie J. Su
    http://arxiv.org/abs/2106.07830v1

    • [cs.LG]On the Power of Multitask Representation Learning in Linear MDP
    Rui Lu, Gao Huang, Simon S. Du
    http://arxiv.org/abs/2106.08053v1

    • [cs.LG]Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation
    Dawood Al Chanti, Diana Mateus
    http://arxiv.org/abs/2106.08188v1

    • [cs.LG]PairConnect: A Compute-Efficient MLP Alternative to Attention
    Zhaozhuo Xu, Minghao Yan, Junyan Zhang, Anshumali Shrivastava
    http://arxiv.org/abs/2106.08235v1

    • [cs.LG]Phase Transitions, Distance Functions, and Implicit Neural Representations
    Yaron Lipman
    http://arxiv.org/abs/2106.07689v1

    • [cs.LG]Pitfalls of Explainable ML: An Industry Perspective
    Sahil Verma, Aditya Lahiri, John P. Dickerson, Su-In Lee
    http://arxiv.org/abs/2106.07758v1

    • [cs.LG]Planning to Fairly Allocate: Probabilistic Fairness in the Restless Bandit Setting
    Christine Herlihy, Aviva Prins, Aravind Srinivasan, John Dickerson
    http://arxiv.org/abs/2106.07677v1

    • [cs.LG]Poisoning Deep Reinforcement Learning Agents with In-Distribution Triggers
    Chace Ashcraft, Kiran Karra
    http://arxiv.org/abs/2106.07798v1

    • [cs.LG]Probabilistic Margins for Instance Reweighting in Adversarial Training
    Qizhou Wang, Feng Liu, Bo Han, Tongliang Liu, Chen Gong, Gang Niu, Mingyuan Zhou, Masashi Sugiyama
    http://arxiv.org/abs/2106.07904v1

    • [cs.LG]RETRIEVE: Coreset Selection for Efficient and Robust Semi-Supervised Learning
    Krishnateja Killamsetty, Xujiang Zhao, Feng Chen, Rishabh Iyer
    http://arxiv.org/abs/2106.07760v1

    • [cs.LG]Randomized Exploration for Reinforcement Learning with General Value Function Approximation
    Haque Ishfaq, Qiwen Cui, Viet Nguyen, Alex Ayoub, Zhuoran Yang, Zhaoran Wang, Doina Precup, Lin F. Yang
    http://arxiv.org/abs/2106.07841v1

    • [cs.LG]Residual Reinforcement Learning from Demonstrations
    Minttu Alakuijala, Gabriel Dulac-Arnold, Julien Mairal, Jean Ponce, Cordelia Schmid
    http://arxiv.org/abs/2106.08050v1

    • [cs.LG]Revisiting Model Stitching to Compare Neural Representations
    Yamini Bansal, Preetum Nakkiran, Boaz Barak
    http://arxiv.org/abs/2106.07682v1

    • [cs.LG]Revisiting the Calibration of Modern Neural Networks
    Matthias Minderer, Josip Djolonga, Rob Romijnders, Frances Hubis, Xiaohua Zhai, Neil Houlsby, Dustin Tran, Mario Lucic
    http://arxiv.org/abs/2106.07998v1

    • [cs.LG]Robust Out-of-Distribution Detection on Deep Probabilistic Generative Models
    Jaemoo Choi, Changyeon Yoon, Jeongwoo Bae, Myungjoo Kang
    http://arxiv.org/abs/2106.07903v1

    • [cs.LG]Sample Efficient Reinforcement Learning In Continuous State Spaces: A Perspective Beyond Linearity
    Dhruv Malik, Aldo Pacchiano, Vishwak Srinivasan, Yuanzhi Li
    http://arxiv.org/abs/2106.07814v1

    • [cs.LG]Scaling Neural Tangent Kernels via Sketching and Random Features
    Amir Zandieh, Insu Han, Haim Avron, Neta Shoham, Chaewon Kim, Jinwoo Shin
    http://arxiv.org/abs/2106.07880v1

    • [cs.LG]Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation
    Cody Blakeney, Nathaniel Huish, Yan Yan, Ziliang Zong
    http://arxiv.org/abs/2106.07849v1

    • [cs.LG]Site-Agnostic 3D Dose Distribution Prediction with Deep Learning Neural Networks
    Maryam Mashayekhi, Itzel Ramirez Tapia, Anjali Balagopal, Xinran Zhong, Azar Sadeghnejad Barkousaraie, Rafe McBeth, Mu-Han Lin, Steve Jiang, Dan Nguyen
    http://arxiv.org/abs/2106.07825v1

    • [cs.LG]SynthASR: Unlocking Synthetic Data for Speech Recognition
    Amin Fazel, Wei Yang, Yulan Liu, Roberto Barra-Chicote, Yixiong Meng, Roland Maas, Jasha Droppo
    http://arxiv.org/abs/2106.07803v1

    • [cs.LG]The Flip Side of the Reweighted Coin: Duality of Adaptive Dropout and Regularization
    Daniel LeJeune, Hamid Javadi, Richard G. Baraniuk
    http://arxiv.org/abs/2106.07769v1

    • [cs.LG]Thompson Sampling for Unimodal Bandits
    Long Yang, Zhao Li, Zehong Hu, Shasha Ruan, Shijian Li, Gang Pan, Hongyang Chen
    http://arxiv.org/abs/2106.08187v1

    • [cs.LG]Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering
    Cheng Feng, Pengwei Tian
    http://arxiv.org/abs/2106.07992v1

    • [cs.LG]Very Deep Graph Neural Networks Via Noise Regularisation
    Jonathan Godwin, Michael Schaarschmidt, Alexander Gaunt, Alvaro Sanchez-Gonzalez, Yulia Rubanova, Petar Veličković, James Kirkpatrick, Peter Battaglia
    http://arxiv.org/abs/2106.07971v1

    • [cs.LG]Voting for the right answer: Adversarial defense for speaker verification
    Haibin Wu, Yang Zhang, Zhiyong Wu, Dong Wang, Hung-yi Lee
    http://arxiv.org/abs/2106.07868v1

    • [cs.MM]Detect and remove watermark in deep neural networks via generative adversarial networks
    Haoqi Wang, Mingfu Xue, Shichang Sun, Yushu Zhang, Jian Wang, Weiqiang Liu
    http://arxiv.org/abs/2106.08104v1

    • [cs.RO]Constrained Motion Planning of A Cable-Driven Soft Robot With Compressible Curvature Modeling
    Jiewen Lai, Bo Lu, Qingxiang Zhao, Henry K. Chu
    http://arxiv.org/abs/2106.08250v1

    • [cs.RO]Force-Sensing Tensegrity for Investigating Physical Human-Robot Interaction in Compliant Robotic Systems
    Andrew R. Barkan, Akhil Padmanabha, Sala R. Tiemann, Albert Lee, Matthew P. Kanter, Yash S. Agarwal, Alice M. Agogino
    http://arxiv.org/abs/2106.07838v1

    • [cs.RO]Human movement augmentation and how to make it a reality
    Jonathan Eden, Mario Bräcklein, Jaime Ibáñez Pereda, Deren Yusuf Barsakcioglu, Giovanni Di Pino, Dario Farina, Etienne Burdet, Carsten Mehring
    http://arxiv.org/abs/2106.08129v1

    • [cs.RO]NeuroBEM: Hybrid Aerodynamic Quadrotor Model
    Leonard Bauersfeld, Elia Kaufmann, Philipp Foehn, Sihao Sun, Davide Scaramuzza
    http://arxiv.org/abs/2106.08015v1

    • [cs.RO]Simplifying Robot Programming using Augmented Reality and End-User Development
    Enes Yigitbas, Ivan Jovanovikj, Gregor Engels
    http://arxiv.org/abs/2106.07944v1

    • [cs.RO]Task Allocation and Coordinated Motion Planning for Autonomous Multi-Robot Optical Inspection Systems
    Yinhua Liu, Wenzheng Zhao, Tim Lutz, Xiaowei Yue
    http://arxiv.org/abs/2106.08164v1

    • [cs.RO]Towards Safe Control of Continuum Manipulator Using Shielded Multiagent Reinforcement Learning
    Guanglin Ji, Junyan Yan, Jingxin Du, Wanquan Yan, Jibiao Chen, Yongkang Lu, Juan Rojas, Shing Shin Cheng
    http://arxiv.org/abs/2106.07892v1

    • [cs.SD]Adaptive Margin Circle Loss for Speaker Verification
    Runqiu Xiao
    http://arxiv.org/abs/2106.08004v1

    • [cs.SD]Graph-based Label Propagation for Semi-Supervised Speaker Identification
    Long Chen, Venkatesh Ravichandran, Andreas Stolcke
    http://arxiv.org/abs/2106.08207v1

    • [cs.SD]Learning Audio-Visual Dereverberation
    Changan Chen, Wei Sun, David Harwath, Kristen Grauman
    http://arxiv.org/abs/2106.07732v1

    • [cs.SD]Teacher-Student MixIT for Unsupervised and Semi-supervised Speech Separation
    Jisi Zhang, Catalin Zorila, Rama Doddipatla, Jon Barker
    http://arxiv.org/abs/2106.07843v1

    • [cs.SD]Tracing Back Music Emotion Predictions to Sound Sources and Intuitive Perceptual Qualities
    Shreyan Chowdhury, Verena Praher, Gerhard Widmer
    http://arxiv.org/abs/2106.07787v1

    • [cs.SE]A Syntax-Guided Edit Decoder for Neural Program Repair
    Qihao Zhu, Zeyu Sun, Yuan-an Xiao, Wenjie Zhang, Kang Yuan, Yingfei Xiong, Lu Zhang
    http://arxiv.org/abs/2106.08253v1

    • [cs.SI]Evaluating the Effect of the Financial Status to the Mobility Customs
    Gergő Pintér, Imre Felde
    http://arxiv.org/abs/2106.07909v1

    • [cs.SI]Full Bitcoin Blockchain Data Made Easy
    Jules Azad Emery, Matthieu Latapy
    http://arxiv.org/abs/2106.08072v1

    • [eess.AS]Dialectal Speech Recognition and Translation of Swiss German Speech to Standard German Text: Microsoft’s Submission to SwissText 2021
    Yuriy Arabskyy, Aashish Agarwal, Subhadeep Dey, Oscar Koller
    http://arxiv.org/abs/2106.08126v1

    • [eess.AS]Kaizen: Continuously improving teacher using Exponential Moving Average for semi-supervised speech recognition
    Vimal Manohar, Tatiana Likhomanenko, Qiantong Xu, Wei-Ning Hsu, Ronan Collobert, Yatharth Saraf, Geoffrey Zweig, Abdelrahman Mohamed
    http://arxiv.org/abs/2106.07759v1

    • [eess.IV]A Lightweight ReLU-Based Feature Fusion for Aerial Scene Classification
    Md Adnan Arefeen, Sumaiya Tabassum Nimi, Md Yusuf Sarwar Uddin, Zhu Li
    http://arxiv.org/abs/2106.07879v1

    • [eess.IV]Automated triaging of head MRI examinations using convolutional neural networks
    David A. Wood, Sina Kafiabadi, Ayisha Al Busaidi, Emily Guilhem, Antanas Montvila, Siddharth Agarwal, Jeremy Lynch, Matthew Townend, Gareth Barker, Sebastien Ourselin, James H. Cole, Thomas C. Booth
    http://arxiv.org/abs/2106.08176v1

    • [eess.IV]Automatic linear measurements of the fetal brain on MRI with deep neural networks
    Netanell Avisdris, Bossmat Yehuda, Ori Ben-Zvi, Daphna Link-Sourani, Liat Ben-Sira, Elka Miller, Elena Zharkov, Dafna Ben Bashat, Leo Joskowicz
    http://arxiv.org/abs/2106.08174v1

    • [eess.IV]Cine-MRI detection of abdominal adhesions with spatio-temporal deep learning
    Bram de Wilde, Richard P. G. ten Broek, Henkjan Huisman
    http://arxiv.org/abs/2106.08094v1

    • [eess.IV]EuroCrops: A Pan-European Dataset for Time Series Crop Type Classification
    Maja Schneider, Amelie Broszeit, Marco Körner
    http://arxiv.org/abs/2106.08151v1

    • [eess.IV]Highdicom: A Python library for standardized encoding of image annotations and machine learning model outputs in pathology and radiology
    Christopher P. Bridge, Chris Gorman, Steven Pieper, Sean W. Doyle, Jochen K. Lennerz, Jayashree Kalpathy-Cramer, David A. Clunie, Andriy Y. Fedorov, Markus D. Herrmann
    http://arxiv.org/abs/2106.07806v1

    • [eess.IV]Perceptually-inspired super-resolution of compressed videos
    Di Ma, Mariana Afonso, Fan Zhang, David R. Bull
    http://arxiv.org/abs/2106.08147v1

    • [eess.IV]ResDepth: A Deep Prior For 3D Reconstruction From High-resolution Satellite Images
    Corinne Stucker, Konrad Schindler
    http://arxiv.org/abs/2106.08107v1

    • [eess.IV]Wavelength-based Attributed Deep Neural Network for Underwater Image Restoration
    Prasen Kumar Sharma, Ira Bisht, Arijit Sur
    http://arxiv.org/abs/2106.07910v1

    • [eess.SP]A stochastic metapopulation state-space approach to modeling and estimating Covid-19 spread
    Yukun Tan, Durward Cator III, Martial Ndeffo-Mbah, Ulisses Braga-Neto
    http://arxiv.org/abs/2106.07919v1

    • [eess.SP]Jamming Detection With Subcarrier Blanking for 5G and Beyond in Industry 4.0 Scenarios
    Leonardo Chiarello, Paolo Baracca, Karthik Upadhya, Saeed R. Khosravirad, Thorsten Wild
    http://arxiv.org/abs/2106.07970v1

    • [eess.SP]Learning to Compensate: A Deep Neural Network Framework for 5G Power Amplifier Compensation
    Po-Yu Chen, Hao Chen, Yi-Min Tsai, Hsien-Kai Kuo, Hantao Huang, Hsin-Hung Chen, Sheng-Hong Yan, Wei-Lun Ou, Chia-Ming Cheng
    http://arxiv.org/abs/2106.07953v1

    • [eess.SP]Towards Long-term Non-invasive Monitoring for Epilepsy via Wearable EEG Devices
    Thorir Mar Ingolfsson, Andrea Cossettini, Xiaying Wang, Enrico Tabanelli, Guiseppe Tagliavini, Philippe Ryvlin, Luca Benini
    http://arxiv.org/abs/2106.08008v1

    • [math.CT]An enriched category theory of language: from syntax to semantics
    Tai-Danae Bradley, John Terilla, Yiannis Vlassopoulos
    http://arxiv.org/abs/2106.07890v1

    • [math.DS]Extracting Global Dynamics of Loss Landscape in Deep Learning Models
    Mohammed Eslami, Hamed Eramian, Marcio Gameiro, William Kalies, Konstantin Mischaikow
    http://arxiv.org/abs/2106.07683v1

    • [math.NA]Augmented Tensor Decomposition with Stochastic Optimization
    Chaoqi Yang, Cheng Qian, Navjot Singh, Cao Xiao, M Brandon Westover, Edgar Solomonik, Jimeng Sun
    http://arxiv.org/abs/2106.07900v1

    • [math.OC]A Value-Function-based Interior-point Method for Non-convex Bi-level Optimization
    Risheng Liu, Xuan Liu, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang
    http://arxiv.org/abs/2106.07991v1

    • [math.OC]Decentralized Local Stochastic Extra-Gradient for Variational Inequalities
    Aleksandr Beznosikov, Pavel Dvurechensky, Anastasia Koloskova, Valentin Samokhin, Sebastian U Stich, Alexander Gasnikov
    http://arxiv.org/abs/2106.08315v1

    • [math.OC]Non-asymptotic convergence bounds for Wasserstein approximation using point clouds
    Quentin Merigot, Filippo Santambrogio, Clément Sarrazin
    http://arxiv.org/abs/2106.07911v1

    • [math.OC]SUPER-ADAM: Faster and Universal Framework of Adaptive Gradients
    Feihu Huang, Junyi Li, Heng Huang
    http://arxiv.org/abs/2106.08208v1

    • [math.OC]Unique sparse decomposition of low rank matrices
    Dian Jin, Xin Bing, Yuqian Zhang
    http://arxiv.org/abs/2106.07736v1

    • [math.PR]Diagonal sections of copulas, multivariate conditional hazard rates and distributions of order statistics for minimally stable lifetimes
    Rachele Foschi, Giovanna Nappo, Fabio L. Spizzichino
    http://arxiv.org/abs/2106.08297v1

    • [math.ST]Generalized kernel distance covariance in high dimensions: non-null CLTs and power universality
    Qiyang Han, Yandi Shen
    http://arxiv.org/abs/2106.07725v1

    • [math.ST]Markov Equivalence of Max-Linear Bayesian Networks
    Carlos Améndola, Ben Hollering, Seth Sullivant, Ngoc Tran
    http://arxiv.org/abs/2106.08305v1

    • [physics.ao-ph]Capabilities of Deep Learning Models on Learning Physical Relationships: Case of Rainfall-Runoff Modeling with LSTM
    Kazuki Yokoo, Kei Ishida, Ali Ercan, Tongbi Tu, Takeyoshi Nagasato, Masato Kiyama, Motoki Amagasaki
    http://arxiv.org/abs/2106.07963v1

    • [q-bio.GN]Active feature selection discovers minimal gene-sets for classifying cell-types and disease states in single-cell mRNA-seq data
    Xiaoqiao Chen, Sisi Chen, Matt Thomson
    http://arxiv.org/abs/2106.08317v1

    • [q-bio.GN]MetaCache-GPU: Ultra-Fast Metagenomic Classification
    Robin Kobus, André Müller, Daniel Jünger, Christian Hundt, Bertil Schmidt
    http://arxiv.org/abs/2106.08150v1

    • [q-bio.PE]Epidemic modelling of multiple virus strains:a case study of SARS-CoV-2 B.1.1.7 in Moscow
    Boris Tseytlin, Ilya Makarov
    http://arxiv.org/abs/2106.08048v1

    • [stat.AP]A Non-ergodic Effective Amplitude Ground-Motion Model for California
    Grigorios Lavrentiadis, Norman A. Abrahamson, Nicolas M. Kuehn
    http://arxiv.org/abs/2106.07834v1

    • [stat.AP]Embracing Uncertainty in “Small Data” Problems: Estimating Earthquakes from Historical Anecdotes
    Justin A. Krometis, Hayden Ringer, Jared P. Whitehead, Nathan E. Glatt-Holtz, Ronald A. Harris
    http://arxiv.org/abs/2106.07797v1

    • [stat.ME]A Bayesian adaptive design for dual-agent phase I-II cancer clinical trials combining efficacy data across stages
    José L. Jiménez, Haiyan Zheng
    http://arxiv.org/abs/2106.08277v1

    • [stat.ME]A Horseshoe Pit mixture model for Bayesian screening with an application to light sheet fluorescence microscopy in brain imaging
    Francesco Denti, Ricardo Azevedo, Chelsie Lo, Damian Wheeler, Sunil P. Gandhi, Michele Guindani, Babak Shahbaba
    http://arxiv.org/abs/2106.08281v1

    • [stat.ME]A Phylogenetic Trees Analysis of SARS-CoV-2
    Chen Shen, Vic Patrangenaru, Roland Moore
    http://arxiv.org/abs/2106.06918v2

    • [stat.ME]Adaptive normalization for IPW estimation
    Samir Khan, Johan Ugander
    http://arxiv.org/abs/2106.07695v1

    • [stat.ME]Bootstrapping Clustered Data in R using lmeresampler
    Adam Loy, Jenna Korobova
    http://arxiv.org/abs/2106.06568v1

    • [stat.ME]Inference for treatment-specific survival curves using machine learning
    Ted Westling, Alex Luedtke, Peter Gilbert, Marco Carone
    http://arxiv.org/abs/2106.06602v1

    • [stat.ME]Robust Inference for High-Dimensional Linear Models via Residual Randomization
    Y. Samuel Wang, Si Kai Lee, Panos Toulis, Mladen Kolar
    http://arxiv.org/abs/2106.07717v1

    • [stat.ME]Tree-Values: selective inference for regression trees
    Anna C. Neufeld, Lucy L. Gao, Daniela M. Witten
    http://arxiv.org/abs/2106.07816v1

    • [stat.ML]Canonical-Correlation-Based Fast Feature Selection
    Sikai Zhang, Tingna Wang, Keith Worden, Elizabeth J. Cross
    http://arxiv.org/abs/2106.08247v1

    • [stat.ML]Contrastive Mixture of Posteriors for Counterfactual Inference, Data Integration and Fairness
    Adam Foster, Árpi Vezér, Craig A Glastonbury, Páidí Creed, Sam Abujudeh, Aaron Sim
    http://arxiv.org/abs/2106.08161v1

    • [stat.ML]Decomposition of Global Feature Importance into Direct and Associative Components (DEDACT)
    Gunnar König, Timo Freiesleben, Bernd Bischl, Giuseppe Casalicchio, Moritz Grosse-Wentrup
    http://arxiv.org/abs/2106.08086v1

    • [stat.ML]Divergence Frontiers for Generative Models: Sample Complexity, Quantization Level, and Frontier Integral
    Lang Liu, Krishna Pillutla, Sean Welleck, Sewoong Oh, Yejin Choi, Zaid Harchaoui
    http://arxiv.org/abs/2106.07898v1

    • [stat.ML]Employing an Adjusted Stability Measure for Multi-Criteria Model Fitting on Data Sets with Similar Features
    Andrea Bommert, Jörg Rahnenführer, Michel Lang
    http://arxiv.org/abs/2106.08105v1

    • [stat.ML]Kernel Identification Through Transformers
    Fergus Simpson, Ian Davies, Vidhi Lalchand, Alessandro Vullo, Nicolas Durrande, Carl Rasmussen
    http://arxiv.org/abs/2106.08185v1

    • [stat.ML]Linear-Time Probabilistic Solutions of Boundary Value Problems
    Nicholas Krämer, Philipp Hennig
    http://arxiv.org/abs/2106.07761v1

    • [stat.ML]RFpredInterval: An R Package for Prediction Intervals with Random Forests and Boosted Forests
    Cansu Alakus, Denis Larocque, Aurelie Labbe
    http://arxiv.org/abs/2106.08217v1

    • [stat.ML]S-LIME: Stabilized-LIME for Model Explanation
    Zhengze Zhou, Giles Hooker, Fei Wang
    http://arxiv.org/abs/2106.07875v1

    • [stat.ML]Self-Supervised Learning with Kernel Dependence Maximization
    Yazhe Li, Roman Pogodin, Danica J. Sutherland, Arthur Gretton
    http://arxiv.org/abs/2106.08320v1