cs.AI - 人工智能
    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.DC - 分布式、并行与集群计算
    cs.DL - 数字图书馆
    cs.DS - 数据结构与算法
    cs.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.MA - 多代理系统
    cs.NE - 神经与进化计算
    cs.NI - 网络和互联网体系结构
    cs.RO - 机器人学
    cs.SD - 声音处理
    cs.SI - 社交网络与信息网络
    econ.EM - 计量经济学
    eess.AS - 语音处理
    eess.IV - 图像与视频处理
    eess.SY - 系统和控制
    math.OC - 优化与控制
    math.PR - 概率
    math.ST - 统计理论
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cs.AI]Don’t Get Yourself into Trouble! Risk-aware Decision-Making for Autonomous Vehicles
    • [cs.AI]Geospatial Reasoning with Shapefiles for Supporting Policy Decisions
    • [cs.AI]Information Avoidance and Overvaluation in Sequential Decision Making under Epistemic Constraints
    • [cs.AI]Measurable Monte Carlo Search Error Bounds
    • [cs.AI]Non-Parametric Stochastic Sequential Assignment With Random Arrival Times
    • [cs.AI]Planning for Novelty: Width-Based Algorithms for Common Problems in Control, Planning and Reinforcement Learning
    • [cs.CG]Relative Clustering Coefficient
    • [cs.CL]A Comparative Study on Neural Architectures and Training Methods for Japanese Speech Recognition
    • [cs.CL]A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021
    • [cs.CL]A Review of Human Evaluation for Style Transfer
    • [cs.CL]AUGVIC: Exploiting BiText Vicinity for Low-Resource NMT
    • [cs.CL]Auto-tagging of Short Conversational Sentences using Natural Language Processing Methods
    • [cs.CL]Automatic Sexism Detection with Multilingual Transformer Models
    • [cs.CL]CLTR: An End-to-End, Transformer-Based System for Cell Level Table Retrieval and Table Question Answering
    • [cs.CL]Case Studies on using Natural Language Processing Techniques in Customer Relationship Management Software
    • [cs.CL]Catchphrase: Automatic Detection of Cultural References
    • [cs.CL]Compacter: Efficient Low-Rank Hypercomplex Adapter Layers
    • [cs.CL]Comprehension Based Question Answering using Bloom’s Taxonomy
    • [cs.CL]Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study
    • [cs.CL]DGA-Net Dynamic Gaussian Attention Network for Sentence Semantic Matching
    • [cs.CL]DravidianMultiModality: A Dataset for Multi-modal Sentiment Analysis in Tamil and Malayalam
    • [cs.CL]Exploiting Language Relatedness for Low Web-Resource Language Model Adaptation: An Indic Languages Study
    • [cs.CL]FastSeq: Make Sequence Generation Faster
    • [cs.CL]Fragmented and Valuable: Following Sentiment Changes in Food Tweets
    • [cs.CL]Instantaneous Grammatical Error Correction with Shallow Aggressive Decoding
    • [cs.CL]Joint System-Wise Optimization for Pipeline Goal-Oriented Dialog System
    • [cs.CL]Learning Multilingual Representation for Natural Language Understanding with Enhanced Cross-Lingual Supervision
    • [cs.CL]MICE: A Crosslinguistic Emotion Corpus in Malay, Indonesian, Chinese and English
    • [cs.CL]Making Better Use of Bilingual Information for Cross-Lingual AMR Parsing
    • [cs.CL]Multi-hop Graph Convolutional Network with High-order Chebyshev Approximation for Text Reasoning
    • [cs.CL]Neural Extractive Search
    • [cs.CL]Neural Supervised Domain Adaptation by Augmenting Pre-trained Models with Random Units
    • [cs.CL]On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness, and Semantic Evaluation
    • [cs.CL]On the Lack of Robust Interpretability of Neural Text Classifiers
    • [cs.CL]Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation
    • [cs.CL]Phraseformer: Multimodal Key-phrase Extraction using Transformer and Graph Embedding
    • [cs.CL]Predicting the Success of Domain Adaptation in Text Similarity
    • [cs.CL]Probing Multilingual Language Models for Discourse
    • [cs.CL]Psycholinguistic Tripartite Graph Network for Personality Detection
    • [cs.CL]RealTranS: End-to-End Simultaneous Speech Translation with Convolutional Weighted-Shrinking Transformer
    • [cs.CL]Sentence Embeddings using Supervised Contrastive Learning
    • [cs.CL]Sequential End-to-End Intent and Slot Label Classification and Localization
    • [cs.CL]Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data
    • [cs.CL]UniKeyphrase: A Unified Extraction and Generation Framework for Keyphrase Prediction
    • [cs.CL]Unsupervised Automatic Speech Recognition: A Review
    • [cs.CL]What Would a Teacher Do? Predicting Future Talk Moves
    • [cs.CR]A Blockchain-Based Trust Management Framework with Verifiable Interactions
    • [cs.CR]A reversible system based on hybrid toggle radius-4 cellular automata and its application as a block cipher
    • [cs.CR]Handcrafted Backdoors in Deep Neural Networks
    • [cs.CR]Recovering AES Keys with a Deep Cold Boot Attack
    • [cs.CR]Tackling spam in the era of end-to-end encryption: A case study of WhatsApp
    • [cs.CV]A machine learning pipeline for aiding school identification from child trafficking images
    • [cs.CV]Agile wide-field imaging with selective high resolution
    • [cs.CV]An Efficient Point of Gaze Estimator for Low-Resolution Imaging Systems Using Extracted Ocular Features Based Neural Architecture
    • [cs.CV]CLCC: Contrastive Learning for Color Constancy
    • [cs.CV]Cervical Cytology Classification Using PCA & GWO Enhanced Deep Features Selection
    • [cs.CV]Check It Again: Progressive Visual Question Answering via Visual Entailment
    • [cs.CV]CoAtNet: Marrying Convolution and Attention for All Data Sizes
    • [cs.CV]Deep Tiny Network for Recognition-Oriented Face Image Quality Assessment
    • [cs.CV]Distilling Image Classifiers in Object Detectors
    • [cs.CV]Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory Tracing
    • [cs.CV]Exploiting Learned Symmetries in Group Equivariant Convolutions
    • [cs.CV]Generative Models as a Data Source for Multiview Representation Learning
    • [cs.CV]Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields
    • [cs.CV]Grounding inductive biases in natural images:invariance stems from variations in data
    • [cs.CV]Knowledge distillation: A good teacher is patient and consistent
    • [cs.CV]Learning to Rank Words: Optimizing Ranking Metrics for Word Spotting
    • [cs.CV]More than meets the eye: Self-supervised depth reconstruction from brain activity
    • [cs.CV]NeRF in detail: Learning to sample for view synthesis
    • [cs.CV]PAM: Understanding Product Images in Cross Product Category Attribute Extraction
    • [cs.CV]PCNet: A Structure Similarity Enhancement Method for Multispectral and Multimodal Image Registration
    • [cs.CV]Point Cloud Upsampling via Disentangled Refinement
    • [cs.CV]Real Time Egocentric Object Segmentation: THU-READ Labeling and Benchmarking Results
    • [cs.CV]Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
    • [cs.CV]SDGMNet: Statistic-based Dynamic Gradient Modulation for Local Descriptor Learning
    • [cs.CV]SHARP: Shape-Aware Reconstruction of People In Loose Clothing
    • [cs.CV]ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation
    • [cs.CV]Salient Object Ranking with Position-Preserved Attention
    • [cs.CV]Salient Positions based Attention Network for Image Classification
    • [cs.CV]Self-supervised Feature Enhancement: Applying Internal Pretext Task to Supervised Learning
    • [cs.CV]Self-supervision of Feature Transformation for Further Improving Supervised Learning
    • [cs.CV]Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time
    • [cs.CV]Semi-supervised lane detection with Deep Hough Transform
    • [cs.CV]SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation
    • [cs.CV]Towards Defending against Adversarial Examples via Attack-Invariant Features
    • [cs.CV]Towards Explainable Abnormal Infant Movements Identification: A Body-part Based Prediction and Visualisation Framework
    • [cs.CV]Towards Training Stronger Video Vision Transformers for EPIC-KITCHENS-100 Action Recognition
    • [cs.CV]Tracking by Joint Local and Global Search: A Target-aware Attention based Approach
    • [cs.CV]VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation
    • [cs.CV]We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature
    • [cs.CY]Understanding Privacy Attitudes and Concerns Towards Remote Communications During the COVID-19 Pandemic
    • [cs.DC]Benchmarking NetBASILISK: a Network Security Project for Science
    • [cs.DC]Benchmarking the Nvidia GPU Lineage
    • [cs.DC]Blockchain for IoT Access Control: Recent Trends and Future Research Directions
    • [cs.DC]Communication-efficient SGD: From Local SGD to One-Shot Averaging
    • [cs.DC]IChannels: Exploiting Current Management Mechanisms to Create Covert Channels in Modern Processors
    • [cs.DC]LB4OMP: A Dynamic Load Balancing Library for Multithreaded Applications
    • [cs.DC]Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development
    • [cs.DL]Scientometric engineering: Revealing spatiotemporal citation dynamics via open eprints
    • [cs.DS]Boolean Matrix Factorization via Nonnegative Auxiliary Optimization
    • [cs.DS]Local Algorithms for Finding Densely Connected Clusters
    • [cs.DS]ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
    • [cs.GR]Neural UpFlow: A Scene Flow Learning Approach to Increase the Apparent Resolution of Particle-Based Liquids
    • [cs.GT]Learning to Price Against a Moving Target
    • [cs.HC]Cartographic Design of Cultural Maps
    • [cs.HC]Streetonomics: Quantifying Culture Using Street Names
    • [cs.IR]AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction
    • [cs.IR]Global Context Enhanced Graph Neural Networks for Session-based Recommendation
    • [cs.IR]Helping results assessment by adding explainable elements to the deep relevance matching model
    • [cs.IR]Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems
    • [cs.IT]Cooperative Beamforming for Wireless Fronthaul and Access Links in Ultra-Dense C-RANs with SWIPT: A First-Order Approach
    • [cs.IT]Entropy of the Conditional Expectation under Gaussian Noise
    • [cs.IT]Feedback Capacity Formulas of AGN Channels Driven by Nonstationary Autoregressive Moving Average Noise
    • [cs.IT]On the Cover and Pombra Gaussian Feedback Capacity: Complete Sequential Characterizations via a Sufficient Statistic
    • [cs.IT]Optimizing a Binary Intelligent Reflecting Surface for OFDM Communications under Mutual Coupling
    • [cs.IT]Satellite- and Cache-assisted UAV: A Joint Cache Placement, Resource Allocation, and Trajectory Optimization for 6G Aerial Networks
    • [cs.IT]Single-Server Private Linear Transformation: The Individual Privacy Case
    • [cs.IT]Single-Server Private Linear Transformation: The Joint Privacy Case
    • [cs.IT]Statistical Classification via Robust Hypothesis Testing
    • [cs.IT]Temporal Averaging LSTM-based Channel Estimation Scheme for IEEE 802.11p Standard
    • [cs.IT]The zero-rate threshold for adversarial bit-deletions is less than 1/2
    • [cs.LG]A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs
    • [cs.LG]A Lyapunov-Based Methodology for Constrained Optimization with Bandit Feedback
    • [cs.LG]A general approach for Explanations in terms of Middle Level Features
    • [cs.LG]Accelerating Neural Architecture Search via Proxy Data
    • [cs.LG]AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation
    • [cs.LG]Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions
    • [cs.LG]Attacking Adversarial Attacks as A Defense
    • [cs.LG]Bayesian Attention Belief Networks
    • [cs.LG]Bayesian Bellman Operators
    • [cs.LG]Bayesian Optimization over Hybrid Spaces
    • [cs.LG]BiFair: Training Fair Models with Bilevel Optimization
    • [cs.LG]ChaCha for Online AutoML
    • [cs.LG]Contextual Recommendations and Low-Regret Cutting-Plane Algorithms
    • [cs.LG]Cooperative Online Learning
    • [cs.LG]Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling
    • [cs.LG]Curriculum Design for Teaching via Demonstrations: Theory and Applications
    • [cs.LG]Deep Clustering based Fair Outlier Detection
    • [cs.LG]Densely connected normalizing flows
    • [cs.LG]Do Transformers Really Perform Bad for Graph Representation?
    • [cs.LG]Dynamic Instance-Wise Classification in Correlated Feature Spaces
    • [cs.LG]EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback
    • [cs.LG]EMFlow: Data Imputation in Latent Space via EM and Deep Flow Models
    • [cs.LG]EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
    • [cs.LG]Efficient Active Search for Combinatorial Optimization Problems
    • [cs.LG]Embedding Physics to Learn Spatiotemporal Dynamics from Sparse Data
    • [cs.LG]Energy-Based Models for Code Generation under Compilability Constraints
    • [cs.LG]Ex uno plures: Splitting One Model into an Ensemble of Subnetworks
    • [cs.LG]Expectation Programming
    • [cs.LG]Explainable AI for medical imaging: Explaining pneumothorax diagnoses with Bayesian Teaching
    • [cs.LG]Fixed-Budget Best-Arm Identification in Contextual Bandits: A Static-Adaptive Algorithm
    • [cs.LG]GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data
    • [cs.LG]Ghosts in Neural Networks: Existence, Structure and Role of Infinite-Dimensional Null Space
    • [cs.LG]Harmless Overparametrization in Two-layer Neural Networks
    • [cs.LG]I Don’t Need 今日学术视野(2021.6.11) - 图1: Identifiable Non-Linear ICA Without Side Information
    • [cs.LG]Interaction-Grounded Learning
    • [cs.LG]It Takes Two to Tango: Mixup for Deep Metric Learning
    • [cs.LG]Labeled Data Generation with Inexact Supervision
    • [cs.LG]Learning Pseudo-Backdoors for Mixed Integer Programs
    • [cs.LG]Learning normal form autoencoders for data-driven discovery of universal,parameter-dependent governing equations
    • [cs.LG]Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels
    • [cs.LG]Memory-based Optimization Methods for Model-Agnostic Meta-Learning
    • [cs.LG]Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
    • [cs.LG]Multistep Electric Vehicle Charging Station Occupancy Prediction using Mixed LSTM Neural Networks
    • [cs.LG]NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs
    • [cs.LG]Neighborhood Contrastive Learning Applied to Online Patient Monitoring
    • [cs.LG]Network insensitivity to parameter noise via adversarial regularization
    • [cs.LG]No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
    • [cs.LG]Nonlinear Hawkes Processes in Time-Varying System
    • [cs.LG]OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices
    • [cs.LG]Offline Inverse Reinforcement Learning
    • [cs.LG]On Margin-Based Cluster Recovery with Oracle Queries
    • [cs.LG]On the Evolution of Neuron Communities in a Deep Learning Architecture
    • [cs.LG]Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence
    • [cs.LG]Operationalizing Complex Causes:A Pragmatic View of Mediation
    • [cs.LG]PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning
    • [cs.LG]PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training
    • [cs.LG]Phase Retrieval using Single-Instance Deep Generative Prior
    • [cs.LG]Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning
    • [cs.LG]Polynomial magic! Hermite polynomials for private data generation
    • [cs.LG]Practical Machine Learning Safety: A Survey and Primer
    • [cs.LG]Predicting Deep Neural Network Generalization with Perturbation Response Curves
    • [cs.LG]Pretrained Encoders are All You Need
    • [cs.LG]Pretraining Representations for Data-Efficient Reinforcement Learning
    • [cs.LG]Probabilistic task modelling for meta-learning
    • [cs.LG]Provably Faster Algorithms for Bilevel Optimization
    • [cs.LG]Quickest change detection with unknown parameters: Constant complexity and near optimality
    • [cs.LG]Realizing GANs via a Tunable Loss Function
    • [cs.LG]Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
    • [cs.LG]Reliable Adversarial Distillation with Unreliable Teachers
    • [cs.LG]Scale Free Adversarial Multi Armed Bandits
    • [cs.LG]Scaling Up Graph Neural Networks Via Graph Coarsening
    • [cs.LG]Self-Improved Retrosynthetic Planning
    • [cs.LG]Self-Paced Context Evaluation for Contextual Reinforcement Learning
    • [cs.LG]Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction
    • [cs.LG]Simulating Continuum Mechanics with Multi-Scale Graph Neural Networks
    • [cs.LG]Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach
    • [cs.LG]TempoRL: Learning When to Act
    • [cs.LG]There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning
    • [cs.LG]Towards Deep Industrial Transfer Learning for Anomaly Detection on Time Series Data
    • [cs.LG]Towards the Memorization Effect of Neural Networks in Adversarial Training
    • [cs.LG]Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos
    • [cs.LG]Understanding Softmax Confidence and Uncertainty
    • [cs.LG]Vector Quantized Models for Planning
    • [cs.LG]Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL
    • [cs.LG]XBNet : An Extremely Boosted Neural Network
    • [cs.MA]Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games
    • [cs.NE]A 2020 taxonomy of algorithms inspired on living beings behavior
    • [cs.NE]A Case Study: Using Genetic Algorithm for Job Scheduling Problem
    • [cs.NE]Multiple simultaneous solution representations in a population based evolutionary algorithm
    • [cs.NE]Probabilistic Neural Network to Quantify Uncertainty of Wind Power Estimation
    • [cs.NI]Engineering-Economic Evaluation of Diffractive Non-Line-Of-Sight Backhaul (e3nb): A Techno-economic Model for 3D Wireless Backhaul Assessment
    • [cs.RO]A Communication Layer for Integrated Sensors and Robotic ecology Solutions to Ambient Intelligence
    • [cs.RO]Design and fabrication of solar powered remote controlled all terrain sprayer and mower robot
    • [cs.RO]HEAP — The autonomous walking excavator
    • [cs.SD]Intermittent Speech Recovery
    • [cs.SI]Design and Implementation of 5G eHealth Systems, Technologies, Use Cases and Future Challenges
    • [cs.SI]Diffusion Source Identification on Networks with Statistical Confidence
    • [cs.SI]Fundamental Privacy Limits in Bipartite Networks under Active Attacks
    • [cs.SI]Multiple Kernel Representation Learning on Networks
    • [cs.SI]Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks
    • [cs.SI]Surveillance of COVID-19 Pandemic using Social Media: A Reddit Study in North Carolina
    • [cs.SI]Tiplines to Combat Misinformation on Encrypted Platforms: A Case Study of the 2019 Indian Election on WhatsApp
    • [econ.EM]Automatically Differentiable Random Coefficient Logistic Demand Estimation
    • [econ.EM]Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraint
    • [econ.EM]On Estimating Multiple Treatment Effects with Regression
    • [eess.AS]SpeechBrain: A General-Purpose Speech Toolkit
    • [eess.IV]A multi-stage GAN for multi-organ chest X-ray image generation and segmentation
    • [eess.IV]Fast Computational Ghost Imaging using Unpaired Deep Learning and a Constrained Generative Adversarial Network
    • [eess.IV]Implicit field learning for unsupervised anomaly detection in medical images
    • [eess.IV]Rethink Transfer Learning in Medical Image Classification
    • [eess.IV]Spatio-Temporal Dual-Stream Neural Network for Sequential Whole-Body PET Segmentation
    • [eess.IV]TED-net: Convolution-free T2T Vision Transformer-based Encoder-decoder Dilation network for Low-dose CT Denoising
    • [eess.SY]Continuous-discrete multiple target tracking with out-of-sequence measurements
    • [eess.SY]Job Dispatching Policies for Queueing Systems with Unknown Service Rates
    • [math.OC]Avoiding Traps in Nonconvex Problems
    • [math.OC]Drones for Medical Delivery Considering Different Demands Classes: A Markov Decision Process Approach for Managing Health Centers Dispatching Medical Products
    • [math.OC]Efficient input placement for the optimal control of network moments
    • [math.OC]Optimal Inspection of Network Systems via Value of Information Analysis
    • [math.OC]Submodular + Concave
    • [math.OC]Using a New Nonlinear Gradient Method for Solving Large Scale Convex Optimization Problems with an Application on Arabic Medical Text
    • [math.PR]On the Hitting Time of Rapid Intensification Onset in Hurricane-like Vortices
    • [math.PR]Shrinkage Estimation of Functions of Large Noisy Symmetric Matrices
    • [math.PR]Some variations on the extremal index
    • [math.ST]General-order observation-driven models: ergodicity and consistency of the maximum likelihood estimator
    • [math.ST]Mixture weights optimisation for Alpha-Divergence Variational Inference
    • [quant-ph]Quantum Annealing for Automated Feature Selection in Stress Detection
    • [quant-ph]The dilemma of quantum neural networks
    • [stat.AP]Fracture Mechanics-Based Quantitative Matching of Forensic Evidence Fragments
    • [stat.AP]Odds Ratios are far from “portable”: A call to use realistic models for effect variation in meta-analysis
    • [stat.AP]Sirius: A Mutual Information Tool for Exploratory Visualization of Mixed Data
    • [stat.AP]Spatial modelling of COVID-19 incident cases using Richards’ curve: an application to the Italian regions
    • [stat.AP]UEFA EURO 2020 Forecast via Nested Zero-Inflated Generalized Poisson Regression
    • [stat.ME]A New Measure of Overlap: An Alternative to the p—value
    • [stat.ME]Bayesian Boosting for Linear Mixed Models
    • [stat.ME]Copula-Frailty Models for Recurrent Event Data Based on Monte Carlo EM Algorithm
    • [stat.ME]Fast construction of optimal composite likelihoods
    • [stat.ME]Markov-Switching State-Space Models with Applications to Neuroimaging
    • [stat.ME]Modelling for Poisson process intensities over irregular spatial domains
    • [stat.ME]On the Use of Minimum Penalties in Statistical Learning
    • [stat.ME]Ultra High Dimensional Change Point Detection
    • [stat.ME]Verification and Validation of Log-Periodic Power Law Models
    • [stat.ML]DIGRAC: Digraph Clustering with Flow Imbalance
    • [stat.ML]Fast and More Powerful Selective Inference for Sparse High-order Interaction Model
    • [stat.ML]Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms
    • [stat.ML]Fully differentiable model discovery
    • [stat.ML]Gaussian Mixture Estimation from Weighted Samples
    • [stat.ML]Independent mechanism analysis, a new concept?
    • [stat.ML]Learning Domain Invariant Representations by Joint Wasserstein Distance Minimization
    • [stat.ML]Loss function based second-order Jensen inequality and its application to particle variational inference
    • [stat.ML]Marginalizable Density Models
    • [stat.ML]Multi-Facet Clustering Variational Autoencoders
    • [stat.ML]Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
    • [stat.ML]Streaming Belief Propagation for Community Detection

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

    • [cs.AI]Don’t Get Yourself into Trouble! Risk-aware Decision-Making for Autonomous Vehicles
    Kasra Mokhtari, Alan R. Wagner
    http://arxiv.org/abs/2106.04625v1

    • [cs.AI]Geospatial Reasoning with Shapefiles for Supporting Policy Decisions
    Henrique Santos, James P. McCusker, Deborah L. McGuinness
    http://arxiv.org/abs/2106.04771v1

    • [cs.AI]Information Avoidance and Overvaluation in Sequential Decision Making under Epistemic Constraints
    Shuo Li, Matteo Pozzi
    http://arxiv.org/abs/2106.04984v1

    • [cs.AI]Measurable Monte Carlo Search Error Bounds
    John Mern, Mykel J. Kochenderfer
    http://arxiv.org/abs/2106.04715v1

    • [cs.AI]Non-Parametric Stochastic Sequential Assignment With Random Arrival Times
    Danial Dervovic, Parisa Hassanzadeh, Samuel Assefa, Prashant Reddy
    http://arxiv.org/abs/2106.04944v1

    • [cs.AI]Planning for Novelty: Width-Based Algorithms for Common Problems in Control, Planning and Reinforcement Learning
    Nir Lipovetzky
    http://arxiv.org/abs/2106.04866v1

    • [cs.CG]Relative Clustering Coefficient
    Elena Farahbakhsh Touli, Oscar Lindberg
    http://arxiv.org/abs/2106.05145v1

    • [cs.CL]A Comparative Study on Neural Architectures and Training Methods for Japanese Speech Recognition
    Shigeki Karita, Yotaro Kubo, Michiel Adriaan Unico Bacchiani, Llion Jones
    http://arxiv.org/abs/2106.05111v1

    • [cs.CL]A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021
    Mark Anderson, Carlos Gómez Rodríguez
    http://arxiv.org/abs/2106.04216v2

    • [cs.CL]A Review of Human Evaluation for Style Transfer
    Eleftheria Briakou, Sweta Agrawal, Ke Zhang, Joel Tetreault, Marine Carpuat
    http://arxiv.org/abs/2106.04747v1

    • [cs.CL]AUGVIC: Exploiting BiText Vicinity for Low-Resource NMT
    Tasnim Mohiuddin, M Saiful Bari, Shafiq Joty
    http://arxiv.org/abs/2106.05141v1

    • [cs.CL]Auto-tagging of Short Conversational Sentences using Natural Language Processing Methods
    Şükrü Ozan, D. Emre Taşar
    http://arxiv.org/abs/2106.04959v1

    • [cs.CL]Automatic Sexism Detection with Multilingual Transformer Models
    Schütz Mina, Boeck Jaqueline, Liakhovets Daria, Slijepčević Djordje, Kirchknopf Armin, Hecht Manuel, Bogensperger Johannes, Schlarb Sven, Schindler Alexander, Zeppelzauer Matthias
    http://arxiv.org/abs/2106.04908v1

    • [cs.CL]CLTR: An End-to-End, Transformer-Based System for Cell Level Table Retrieval and Table Question Answering
    Feifei Pan, Mustafa Canim, Michael Glass, Alfio Gliozzo, Peter Fox
    http://arxiv.org/abs/2106.04441v2

    • [cs.CL]Case Studies on using Natural Language Processing Techniques in Customer Relationship Management Software
    Şükrü Ozan
    http://arxiv.org/abs/2106.05160v1

    • [cs.CL]Catchphrase: Automatic Detection of Cultural References
    Nir Sweed, Dafna Shahaf
    http://arxiv.org/abs/2106.04830v1

    • [cs.CL]Compacter: Efficient Low-Rank Hypercomplex Adapter Layers
    Rabeeh Karimi Mahabadi, James Henderson, Sebastian Ruder
    http://arxiv.org/abs/2106.04647v1

    • [cs.CL]Comprehension Based Question Answering using Bloom’s Taxonomy
    Pritish Sahu, Michael Cogswell, Sara Rutherford-Quach, Ajay Divakaran
    http://arxiv.org/abs/2106.04653v1

    • [cs.CL]Crosslingual Embeddings are Essential in UNMT for Distant Languages: An English to IndoAryan Case Study
    Tamali Banerjee, Rudra Murthy V, Pushpak Bhattacharyya
    http://arxiv.org/abs/2106.04995v1

    • [cs.CL]DGA-Net Dynamic Gaussian Attention Network for Sentence Semantic Matching
    Kun Zhang, Guangyi Lv, Meng Wang, Enhong Chen
    http://arxiv.org/abs/2106.04905v1

    • [cs.CL]DravidianMultiModality: A Dataset for Multi-modal Sentiment Analysis in Tamil and Malayalam
    Bharathi Raja Chakravarthi, Jishnu Parameswaran P. K, Premjith B, K. P Soman, Rahul Ponnusamy, Prasanna Kumar Kumaresan, Kingston Pal Thamburaj, John P. McCrae
    http://arxiv.org/abs/2106.04853v1

    • [cs.CL]Exploiting Language Relatedness for Low Web-Resource Language Model Adaptation: An Indic Languages Study
    Yash Khemchandani, Sarvesh Mehtani, Vaidehi Patil, Abhijeet Awasthi, Partha Talukdar, Sunita Sarawagi
    http://arxiv.org/abs/2106.03958v2

    • [cs.CL]FastSeq: Make Sequence Generation Faster
    Yu Yan, Fei Hu, Jiusheng Chen, Nikhil Bhendawade, Ting Ye, Yeyun Gong, Nan Duan, Desheng Cui, Bingyu Chi, Ruifei Zhang
    http://arxiv.org/abs/2106.04718v1

    • [cs.CL]Fragmented and Valuable: Following Sentiment Changes in Food Tweets
    Maija Kāle, Matīss Rikters
    http://arxiv.org/abs/2106.04903v1

    • [cs.CL]Instantaneous Grammatical Error Correction with Shallow Aggressive Decoding
    Xin Sun, Tao Ge, Furu Wei, Houfeng Wang
    http://arxiv.org/abs/2106.04970v1

    • [cs.CL]Joint System-Wise Optimization for Pipeline Goal-Oriented Dialog System
    Zichuan Lin, Jing Huang, Bowen Zhou, Xiaodong He, Tengyu Ma
    http://arxiv.org/abs/2106.04835v1

    • [cs.CL]Learning Multilingual Representation for Natural Language Understanding with Enhanced Cross-Lingual Supervision
    Yinpeng Guo, Liangyou Li, Xin Jiang, Qun Liu
    http://arxiv.org/abs/2106.05166v1

    • [cs.CL]MICE: A Crosslinguistic Emotion Corpus in Malay, Indonesian, Chinese and English
    Ng Bee Chin, Yosephine Susanto, Erik Cambria
    http://arxiv.org/abs/2106.04831v1

    • [cs.CL]Making Better Use of Bilingual Information for Cross-Lingual AMR Parsing
    Yitao Cai, Zhe Lin, Xiaojun Wan
    http://arxiv.org/abs/2106.04814v1

    • [cs.CL]Multi-hop Graph Convolutional Network with High-order Chebyshev Approximation for Text Reasoning
    Shuoran Jiang, Qingcai Chen, Xin Liu, Baotian Hu, Lisai Zhang
    http://arxiv.org/abs/2106.05221v1

    • [cs.CL]Neural Extractive Search
    Shauli Ravfogel, Hillel Taub-Tabib, Yoav Goldberg
    http://arxiv.org/abs/2106.04612v1

    • [cs.CL]Neural Supervised Domain Adaptation by Augmenting Pre-trained Models with Random Units
    Sara Meftah, Nasredine Semmar, Youssef Tamaazousti, Hassane Essafi, Fatiha Sadat
    http://arxiv.org/abs/2106.04935v1

    • [cs.CL]On Sample Based Explanation Methods for NLP:Efficiency, Faithfulness, and Semantic Evaluation
    Wei Zhang, Ziming Huang, Yada Zhu, Guangnan Ye, Xiaodong Cui, Fan Zhang
    http://arxiv.org/abs/2106.04753v1

    • [cs.CL]On the Lack of Robust Interpretability of Neural Text Classifiers
    Muhammad Bilal Zafar, Michele Donini, Dylan Slack, Cédric Archambeau, Sanjiv Das, Krishnaram Kenthapadi
    http://arxiv.org/abs/2106.04631v1

    • [cs.CL]Order-Agnostic Cross Entropy for Non-Autoregressive Machine Translation
    Cunxiao Du, Zhaopeng Tu, Jing Jiang
    http://arxiv.org/abs/2106.05093v1

    • [cs.CL]Phraseformer: Multimodal Key-phrase Extraction using Transformer and Graph Embedding
    Narjes Nikzad-Khasmakhi, Mohammad-Reza Feizi-Derakhshi, Meysam Asgari-Chenaghlu, Mohammad-Ali Balafar, Ali-Reza Feizi-Derakhshi, Taymaz Rahkar-Farshi, Majid Ramezani, Zoleikha Jahanbakhsh-Nagadeh, Elnaz Zafarani-Moattar, Mehrdad Ranjbar-Khadivi
    http://arxiv.org/abs/2106.04939v1

    • [cs.CL]Predicting the Success of Domain Adaptation in Text Similarity
    Nicolai Pogrebnyakov, Shohreh Shaghaghian
    http://arxiv.org/abs/2106.04641v1

    • [cs.CL]Probing Multilingual Language Models for Discourse
    Murathan Kurfalı, Robert Östling
    http://arxiv.org/abs/2106.04832v1

    • [cs.CL]Psycholinguistic Tripartite Graph Network for Personality Detection
    Tao Yang, Feifan Yang, Haolan Ouyang, Xiaojun Quan
    http://arxiv.org/abs/2106.04963v1

    • [cs.CL]RealTranS: End-to-End Simultaneous Speech Translation with Convolutional Weighted-Shrinking Transformer
    Xingshan Zeng, Liangyou Li, Qun Liu
    http://arxiv.org/abs/2106.04833v1

    • [cs.CL]Sentence Embeddings using Supervised Contrastive Learning
    Danqi Liao
    http://arxiv.org/abs/2106.04791v1

    • [cs.CL]Sequential End-to-End Intent and Slot Label Classification and Localization
    Yiran Cao, Nihal Potdar, Anderson R. Avila
    http://arxiv.org/abs/2106.04660v1

    • [cs.CL]Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data
    Moshe Hazoom, Vibhor Malik, Ben Bogin
    http://arxiv.org/abs/2106.05006v1

    • [cs.CL]UniKeyphrase: A Unified Extraction and Generation Framework for Keyphrase Prediction
    Huanqin Wu, Wei Liu, Lei Li, Dan Nie, Tao Chen, Feng Zhang, Di Wang
    http://arxiv.org/abs/2106.04847v1

    • [cs.CL]Unsupervised Automatic Speech Recognition: A Review
    Hanan Aldarmaki, Asad Ullah, Nazar Zaki
    http://arxiv.org/abs/2106.04897v1

    • [cs.CL]What Would a Teacher Do? Predicting Future Talk Moves
    Ananya Ganesh, Martha Palmer, Katharina Kann
    http://arxiv.org/abs/2106.05249v1

    • [cs.CR]A Blockchain-Based Trust Management Framework with Verifiable Interactions
    Shantanu Pal, Ambrose Hill, Tahiry Rabehaja, Michael Hitchens
    http://arxiv.org/abs/2106.04885v1

    • [cs.CR]A reversible system based on hybrid toggle radius-4 cellular automata and its application as a block cipher
    Everton R. Lira, Heverton B. de Macêdo, Danielli A. Lima, Leonardo Alt, Gina M. B. Oliveira
    http://arxiv.org/abs/2106.04777v1

    • [cs.CR]Handcrafted Backdoors in Deep Neural Networks
    Sanghyun Hong, Nicholas Carlini, Alexey Kurakin
    http://arxiv.org/abs/2106.04690v1

    • [cs.CR]Recovering AES Keys with a Deep Cold Boot Attack
    Itamar Zimerman, Eliya Nachmani, Lior Wolf
    http://arxiv.org/abs/2106.04876v1

    • [cs.CR]Tackling spam in the era of end-to-end encryption: A case study of WhatsApp
    Pushkal Agarwal, Aravindh Raman, Kiran Garimella, Damilola Ibosiola, Gareth Tyson, Nishanth Sastry
    http://arxiv.org/abs/2106.05184v1

    • [cs.CV]A machine learning pipeline for aiding school identification from child trafficking images
    Sumit Mukherjee, Tina Sederholm, Anthony C. Roman, Ria Sankar, Sherrie Caltagirone, Juan Lavista Ferres
    http://arxiv.org/abs/2106.05215v1

    • [cs.CV]Agile wide-field imaging with selective high resolution
    Lintao Peng, Liheng Bian, Tiexin Liu, Jun Zhang
    http://arxiv.org/abs/2106.05082v1

    • [cs.CV]An Efficient Point of Gaze Estimator for Low-Resolution Imaging Systems Using Extracted Ocular Features Based Neural Architecture
    Atul Sahay, Imon Mukherjee, Kavi Arya
    http://arxiv.org/abs/2106.05106v1

    • [cs.CV]CLCC: Contrastive Learning for Color Constancy
    Yi-Chen Lo, Chia-Che Chang, Hsuan-Chao Chiu, Yu-Hao Huang, Chia-Ping Chen, Yu-Lin Chang, Kevin Jou
    http://arxiv.org/abs/2106.04989v1

    • [cs.CV]Cervical Cytology Classification Using PCA & GWO Enhanced Deep Features Selection
    Hritam Basak, Rohit Kundu, Sukanta Chakraborty, Nibaran Das
    http://arxiv.org/abs/2106.04919v1

    • [cs.CV]Check It Again: Progressive Visual Question Answering via Visual Entailment
    Qingyi Si, Zheng Lin, Mingyu Zheng, Peng Fu, Weiping Wang
    http://arxiv.org/abs/2106.04605v1

    • [cs.CV]CoAtNet: Marrying Convolution and Attention for All Data Sizes
    Zihang Dai, Hanxiao Liu, Quoc V. Le, Mingxing Tan
    http://arxiv.org/abs/2106.04803v1

    • [cs.CV]Deep Tiny Network for Recognition-Oriented Face Image Quality Assessment
    Baoyun Peng, Min Liu, Heng Yang, Zhaoning Zhang, Dongsheng Li
    http://arxiv.org/abs/2106.04852v1

    • [cs.CV]Distilling Image Classifiers in Object Detectors
    Shuxuan Guo, Jose M. Alvarez, Mathieu Salzmann
    http://arxiv.org/abs/2106.05209v1

    • [cs.CV]Dual-Modality Vehicle Anomaly Detection via Bilateral Trajectory Tracing
    Jingyuan Chen, Guanchen Ding, Yuchen Yang, Wenwei Han, Kangmin Xu, Tianyi Gao, Zhe Zhang, Wanping Ouyang, Hao Cai, Zhenzhong Chen
    http://arxiv.org/abs/2106.05003v1

    • [cs.CV]Exploiting Learned Symmetries in Group Equivariant Convolutions
    Attila Lengyel, Jan C. van Gemert
    http://arxiv.org/abs/2106.04914v1

    • [cs.CV]Generative Models as a Data Source for Multiview Representation Learning
    Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip Isola
    http://arxiv.org/abs/2106.05258v1

    • [cs.CV]Geometry-Consistent Neural Shape Representation with Implicit Displacement Fields
    Wang Yifan, Lukas Rahmann, Olga Sorkine-Hornung
    http://arxiv.org/abs/2106.05187v1

    • [cs.CV]Grounding inductive biases in natural images:invariance stems from variations in data
    Diane Bouchacourt, Mark Ibrahim, Ari S. Morcos
    http://arxiv.org/abs/2106.05121v1

    • [cs.CV]Knowledge distillation: A good teacher is patient and consistent
    Lucas Beyer, Xiaohua Zhai, Amélie Royer, Larisa Markeeva, Rohan Anil, Alexander Kolesnikov
    http://arxiv.org/abs/2106.05237v1

    • [cs.CV]Learning to Rank Words: Optimizing Ranking Metrics for Word Spotting
    Pau Riba, Adrià Molina, Lluis Gomez, Oriol Ramos-Terrades, Josep Lladós
    http://arxiv.org/abs/2106.05144v1

    • [cs.CV]More than meets the eye: Self-supervised depth reconstruction from brain activity
    Guy Gaziv, Michal Irani
    http://arxiv.org/abs/2106.05113v1

    • [cs.CV]NeRF in detail: Learning to sample for view synthesis
    Relja Arandjelović, Andrew Zisserman
    http://arxiv.org/abs/2106.05264v1

    • [cs.CV]PAM: Understanding Product Images in Cross Product Category Attribute Extraction
    Rongmei Lin, Xiang He, Jie Feng, Nasser Zalmout, Yan Liang, Li Xiong, Xin Luna Dong
    http://arxiv.org/abs/2106.04630v1

    • [cs.CV]PCNet: A Structure Similarity Enhancement Method for Multispectral and Multimodal Image Registration
    Si-Yuan Cao, Hui-Liang Shen, Lun Luo, Shu-Jie Chen, Chunguang Li
    http://arxiv.org/abs/2106.05124v1

    • [cs.CV]Point Cloud Upsampling via Disentangled Refinement
    Ruihui Li, Xianzhi Li, Pheng-Ann Heng, Chi-Wing Fu
    http://arxiv.org/abs/2106.04779v1

    • [cs.CV]Real Time Egocentric Object Segmentation: THU-READ Labeling and Benchmarking Results
    E. Gonzalez-Sosa, G. Robledo, D. Gonzalez-Morin, P. Perez-Garcia, A. Villegas
    http://arxiv.org/abs/2106.04957v1

    • [cs.CV]Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
    Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang
    http://arxiv.org/abs/2106.05210v1

    • [cs.CV]SDGMNet: Statistic-based Dynamic Gradient Modulation for Local Descriptor Learning
    Jiayi Ma, Yuxin Deng
    http://arxiv.org/abs/2106.04434v2

    • [cs.CV]SHARP: Shape-Aware Reconstruction of People In Loose Clothing
    Sai Sagar Jinka, Rohan Chacko, Astitva Srivastava, Avinash Sharma, P. J. Narayanan
    http://arxiv.org/abs/2106.04778v1

    • [cs.CV]ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation
    Lihe Yang, Wei Zhuo, Lei Qi, Yinghuan Shi, Yang Gao
    http://arxiv.org/abs/2106.05095v1

    • [cs.CV]Salient Object Ranking with Position-Preserved Attention
    Hao Fang, Daoxin Zhang, Yi Zhang, Minghao Chen, Jiawei Li, Yao Hu, Deng Cai, Xiaofei He
    http://arxiv.org/abs/2106.05047v1

    • [cs.CV]Salient Positions based Attention Network for Image Classification
    Sheng Fang, Kaiyu Li, Zhe Li
    http://arxiv.org/abs/2106.04996v1

    • [cs.CV]Self-supervised Feature Enhancement: Applying Internal Pretext Task to Supervised Learning
    Yuhang Yang, Zilin Ding, Xuan Cheng, Xiaomin Wang, Ming Liu
    http://arxiv.org/abs/2106.04921v1

    • [cs.CV]Self-supervision of Feature Transformation for Further Improving Supervised Learning
    Zilin Ding, Yuhang Yang, Xuan Cheng, Xiaomin Wang, Ming Liu
    http://arxiv.org/abs/2106.04922v1

    • [cs.CV]Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Time
    Shaowei Liu, Hanwen Jiang, Jiarui Xu, Sifei Liu, Xiaolong Wang
    http://arxiv.org/abs/2106.05266v1

    • [cs.CV]Semi-supervised lane detection with Deep Hough Transform
    Yancong Lin, Silvia-Laura Pintea, Jan van Gemert
    http://arxiv.org/abs/2106.05094v1

    • [cs.CV]SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation
    Ioannis Kazakos, Carles Ventura, Miriam Bellver, Carina Silberer, Xavier Giro-i-Nieto
    http://arxiv.org/abs/2106.04403v2

    • [cs.CV]Towards Defending against Adversarial Examples via Attack-Invariant Features
    Dawei Zhou, Tongliang Liu, Bo Han, Nannan Wang, Chunlei Peng, Xinbo Gao
    http://arxiv.org/abs/2106.05036v1

    • [cs.CV]Towards Explainable Abnormal Infant Movements Identification: A Body-part Based Prediction and Visualisation Framework
    Kevin D. McCay, Edmond S. L. Ho, Dimitrios Sakkos, Wai Lok Woo, Claire Marcroft, Patricia Dulson, Nicholas D. Embleton
    http://arxiv.org/abs/2106.04966v1

    • [cs.CV]Towards Training Stronger Video Vision Transformers for EPIC-KITCHENS-100 Action Recognition
    Ziyuan Huang, Zhiwu Qing, Xiang Wang, Yutong Feng, Shiwei Zhang, Jianwen Jiang, Zhurong Xia, Mingqian Tang, Nong Sang, Marcelo H. Ang Jr
    http://arxiv.org/abs/2106.05058v1

    • [cs.CV]Tracking by Joint Local and Global Search: A Target-aware Attention based Approach
    Xiao Wang, Jin Tang, Bin Luo, Yaowei Wang, Yonghong Tian, Feng Wu
    http://arxiv.org/abs/2106.04840v1

    • [cs.CV]VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation
    Linjie Li, Jie Lei, Zhe Gan, Licheng Yu, Yen-Chun Chen, Rohit Pillai, Yu Cheng, Luowei Zhou, Xin Eric Wang, William Yang Wang, Tamara Lee Berg, Mohit Bansal, Jingjing Liu, Lijuan Wang, Zicheng Liu
    http://arxiv.org/abs/2106.04632v1

    • [cs.CV]We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature
    Bin Liang, Jiachun Li, Jianjun Huang
    http://arxiv.org/abs/2106.05261v1

    • [cs.CY]Understanding Privacy Attitudes and Concerns Towards Remote Communications During the COVID-19 Pandemic
    Pardis Emami-Naeini, Tiona Francisco, Tadayoshi Kohno, Franziska Roesner
    http://arxiv.org/abs/2106.05227v1

    • [cs.DC]Benchmarking NetBASILISK: a Network Security Project for Science
    Jem Guhit, Edward Colone, Shawn McKee, Kris Steinhoff, Katarina Thomas
    http://arxiv.org/abs/2106.04811v1

    • [cs.DC]Benchmarking the Nvidia GPU Lineage
    Martin Svedin, Steven W. D. Chien, Gibson Chikafa, Niclas Jansson, Artur Podobas
    http://arxiv.org/abs/2106.04979v1

    • [cs.DC]Blockchain for IoT Access Control: Recent Trends and Future Research Directions
    Shantanu Pal, Ali Dorri, Raja Jurdak
    http://arxiv.org/abs/2106.04808v1

    • [cs.DC]Communication-efficient SGD: From Local SGD to One-Shot Averaging
    Artin Spiridonoff, Alex Olshevsky, Ioannis Ch. Paschalidis
    http://arxiv.org/abs/2106.04759v1

    • [cs.DC]IChannels: Exploiting Current Management Mechanisms to Create Covert Channels in Modern Processors
    Jawad Haj-Yahya, Jeremie S. Kim, A. Giray Yaglikci, Ivan Puddu, Lois Orosa, Juan Gómez Luna, Mohammed Alser, Onur Mutlu
    http://arxiv.org/abs/2106.05050v1

    • [cs.DC]LB4OMP: A Dynamic Load Balancing Library for Multithreaded Applications
    Jonas H. Müller Korndörfer, Ahmed Eleliemy, Ali Mohammed, Florina M. Ciorba
    http://arxiv.org/abs/2106.05108v1

    • [cs.DC]Workflows Community Summit: Advancing the State-of-the-art of Scientific Workflows Management Systems Research and Development
    Rafael Ferreira da Silva, Henri Casanova, Kyle Chard, Tainã Coleman, Dan Laney, Dong Ahn, Shantenu Jha, Dorran Howell, Stian Soiland-Reys, Ilkay Altintas, Douglas Thain, Rosa Filgueira, Yadu Babuji, Rosa M. Badia, Bartosz Balis, Silvina Caino-Lores, Scott Callaghan, Frederik Coppens, Michael R. Crusoe, Kaushik De, Frank Di Natale, Tu M. A. Do, Bjoern Enders, Thomas Fahringer, Anne Fouilloux, Grigori Fursin, Alban Gaignard, Alex Ganose, Daniel Garijo, Sandra Gesing, Carole Goble, Adil Hasan, Sebastiaan Huber, Daniel S. Katz, Ulf Leser, Douglas Lowe, Bertram Ludaescher, Ketan Maheshwari, Maciej Malawski, Rajiv Mayani, Kshitij Mehta, Andre Merzky, Todd Munson, Jonathan Ozik, Loïc Pottier, Sashko Ristov, Mehdi Roozmeh, Renan Souza, Frédéric Suter, Benjamin Tovar, Matteo Turilli, Karan Vahi, Alvaro Vidal-Torreira, Wendy Whitcup, Michael Wilde, Alan Williams, Matthew Wolf, Justin Wozniak
    http://arxiv.org/abs/2106.05177v1

    • [cs.DL]Scientometric engineering: Revealing spatiotemporal citation dynamics via open eprints
    Keisuke Okamura
    http://arxiv.org/abs/2106.05027v1

    • [cs.DS]Boolean Matrix Factorization via Nonnegative Auxiliary Optimization
    Duc P. Truong, Erik Skau, Derek Desantis, Boian Alexandrov
    http://arxiv.org/abs/2106.04708v1

    • [cs.DS]Local Algorithms for Finding Densely Connected Clusters
    Peter Macgregor, He Sun
    http://arxiv.org/abs/2106.05245v1

    • [cs.DS]ParChain: A Framework for Parallel Hierarchical Agglomerative Clustering using Nearest-Neighbor Chain
    Shangdi Yu, Yiqiu Wang, Yan Gu, Laxman Dhulipala, Julian Shun
    http://arxiv.org/abs/2106.04727v1

    • [cs.GR]Neural UpFlow: A Scene Flow Learning Approach to Increase the Apparent Resolution of Particle-Based Liquids
    Bruno Roy, Pierre Poulin, Eric Paquette
    http://arxiv.org/abs/2106.05143v1

    • [cs.GT]Learning to Price Against a Moving Target
    Renato Paes Leme, Balasubramanian Sivan, Yifeng Teng, Pratik Worah
    http://arxiv.org/abs/2106.04689v1

    • [cs.HC]Cartographic Design of Cultural Maps
    Edyta Paulina Bogucka, Marios Constantinides, Luca Maria Aiello, Daniele Quercia, Wonyoung So, Melanie Bancilhon
    http://arxiv.org/abs/2106.04688v1

    • [cs.HC]Streetonomics: Quantifying Culture Using Street Names
    Melanie Bancilhon, Marios Constantinides, Edyta Paulina Bogucka, Luca Maria Aiello, Daniele Quercia
    http://arxiv.org/abs/2106.04675v1

    • [cs.IR]AutoFT: Automatic Fine-Tune for Parameters Transfer Learning in Click-Through Rate Prediction
    Xiangli Yang, Qing Liu, Rong Su, Ruiming Tang, Zhirong Liu, Xiuqiang He
    http://arxiv.org/abs/2106.04873v1

    • [cs.IR]Global Context Enhanced Graph Neural Networks for Session-based Recommendation
    Ziyang Wang, Wei Wei, Gao Cong, Xiao-Li Li, Xian-Ling Mao, Minghui Qiu
    http://arxiv.org/abs/2106.05081v1

    • [cs.IR]Helping results assessment by adding explainable elements to the deep relevance matching model
    Ioannis Chios, Suzan Verberne
    http://arxiv.org/abs/2106.05147v1

    • [cs.IR]Initialization Matters: Regularizing Manifold-informed Initialization for Neural Recommendation Systems
    Yinan Zhang, Boyang Li, Yong Liu, Hao Wang, Chunyan Miao
    http://arxiv.org/abs/2106.04993v1

    • [cs.IT]Cooperative Beamforming for Wireless Fronthaul and Access Links in Ultra-Dense C-RANs with SWIPT: A First-Order Approach
    Fangqing Tan, Peiran Wu, Yik-Chung Wu, Minghua Xia
    http://arxiv.org/abs/2106.04750v1

    • [cs.IT]Entropy of the Conditional Expectation under Gaussian Noise
    Arda Atalik, Alper Köse, Michael Gastpar
    http://arxiv.org/abs/2106.04677v1

    • [cs.IT]Feedback Capacity Formulas of AGN Channels Driven by Nonstationary Autoregressive Moving Average Noise
    Stelios Louka, Christos Kourtellaris, Charalambos D. Charalambous
    http://arxiv.org/abs/2106.04969v1

    • [cs.IT]On the Cover and Pombra Gaussian Feedback Capacity: Complete Sequential Characterizations via a Sufficient Statistic
    Charalambos D. Charalambous, Christos Kourtellaris, Stelios Louka
    http://arxiv.org/abs/2106.05075v1

    • [cs.IT]Optimizing a Binary Intelligent Reflecting Surface for OFDM Communications under Mutual Coupling
    Emil Björnson
    http://arxiv.org/abs/2106.04280v2

    • [cs.IT]Satellite- and Cache-assisted UAV: A Joint Cache Placement, Resource Allocation, and Trajectory Optimization for 6G Aerial Networks
    Dinh-Hieu Tran, Symeon Chatzinotas, Björn Ottersten
    http://arxiv.org/abs/2106.05016v1

    • [cs.IT]Single-Server Private Linear Transformation: The Individual Privacy Case
    Anoosheh Heidarzadeh, Nahid Esmati, Alex Sprintson
    http://arxiv.org/abs/2106.05222v1

    • [cs.IT]Single-Server Private Linear Transformation: The Joint Privacy Case
    Anoosheh Heidarzadeh, Nahid Esmati, Alex Sprintson
    http://arxiv.org/abs/2106.05220v1

    • [cs.IT]Statistical Classification via Robust Hypothesis Testing
    Hüseyin Afşer
    http://arxiv.org/abs/2106.04824v1

    • [cs.IT]Temporal Averaging LSTM-based Channel Estimation Scheme for IEEE 802.11p Standard
    Abdul Karim Gizzini, Marwa Chafii, Shahab Ehsanfar, Raed M. Shubair
    http://arxiv.org/abs/2106.04829v1

    • [cs.IT]The zero-rate threshold for adversarial bit-deletions is less than 1/2
    Venkatesan Guruswami, Xiaoyu He, Ray Li
    http://arxiv.org/abs/2106.05250v1

    • [cs.LG]A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs
    Runzhong Wang, Zhigang Hua, Gan Liu, Jiayi Zhang, Junchi Yan, Feng Qi, Shuang Yang, Jun Zhou, Xiaokang Yang
    http://arxiv.org/abs/2106.04927v1

    • [cs.LG]A Lyapunov-Based Methodology for Constrained Optimization with Bandit Feedback
    Semih Cayci, Yilin Zheng, Atilla Eryilmaz
    http://arxiv.org/abs/2106.05165v1

    • [cs.LG]A general approach for Explanations in terms of Middle Level Features
    Andrea Apicella, Francesco Isgrò, Roberto Prevete
    http://arxiv.org/abs/2106.05037v1

    • [cs.LG]Accelerating Neural Architecture Search via Proxy Data
    Byunggook Na, Jisoo Mok, Hyeokjun Choe, Sungroh Yoon
    http://arxiv.org/abs/2106.04784v1

    • [cs.LG]AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation
    David Berthelot, Rebecca Roelofs, Kihyuk Sohn, Nicholas Carlini, Alex Kurakin
    http://arxiv.org/abs/2106.04732v1

    • [cs.LG]Adaptive Inference through Early-Exit Networks: Design, Challenges and Directions
    Stefanos Laskaridis, Alexandros Kouris, Nicholas D. Lane
    http://arxiv.org/abs/2106.05022v1

    • [cs.LG]Attacking Adversarial Attacks as A Defense
    Boxi Wu, Heng Pan, Li Shen, Jindong Gu, Shuai Zhao, Zhifeng Li, Deng Cai, Xiaofei He, Wei Liu
    http://arxiv.org/abs/2106.04938v1

    • [cs.LG]Bayesian Attention Belief Networks
    Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou
    http://arxiv.org/abs/2106.05251v1

    • [cs.LG]Bayesian Bellman Operators
    Matthew Fellows, Kristian Hartikainen, Shimon Whiteson
    http://arxiv.org/abs/2106.05012v1

    • [cs.LG]Bayesian Optimization over Hybrid Spaces
    Aryan Deshwal, Syrine Belakaria, Janardhan Rao Doppa
    http://arxiv.org/abs/2106.04682v1

    • [cs.LG]BiFair: Training Fair Models with Bilevel Optimization
    Mustafa Safa Ozdayi, Murat Kantarcioglu, Rishabh Iyer
    http://arxiv.org/abs/2106.04757v1

    • [cs.LG]ChaCha for Online AutoML
    Qingyun Wu, Chi Wang, John Langford, Paul Mineiro, Marco Rossi
    http://arxiv.org/abs/2106.04815v1

    • [cs.LG]Contextual Recommendations and Low-Regret Cutting-Plane Algorithms
    Sreenivas Gollapudi, Guru Guruganesh, Kostas Kollias, Pasin Manurangsi, Renato Paes Leme, Jon Schneider
    http://arxiv.org/abs/2106.04819v1

    • [cs.LG]Cooperative Online Learning
    Tommaso R. Cesari, Riccardo Della Vecchia
    http://arxiv.org/abs/2106.04982v1

    • [cs.LG]Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling
    Chuizheng Meng, Sirisha Rambhatla, Yan Liu
    http://arxiv.org/abs/2106.05223v1

    • [cs.LG]Curriculum Design for Teaching via Demonstrations: Theory and Applications
    Gaurav Yengera, Rati Devidze, Parameswaran Kamalaruban, Adish Singla
    http://arxiv.org/abs/2106.04696v1

    • [cs.LG]Deep Clustering based Fair Outlier Detection
    Hanyu Song, Peizhao Li, Hongfu Liu
    http://arxiv.org/abs/2106.05127v1

    • [cs.LG]Densely connected normalizing flows
    Matej Grcić, Ivan Grubišić, Siniša Šegvić
    http://arxiv.org/abs/2106.04627v1

    • [cs.LG]Do Transformers Really Perform Bad for Graph Representation?
    Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng, Guolin Ke, Di He, Yanming Shen, Tie-Yan Liu
    http://arxiv.org/abs/2106.05234v1

    • [cs.LG]Dynamic Instance-Wise Classification in Correlated Feature Spaces
    Yasitha Warahena Liyanage, Daphney-Stavroula Zois, Charalampos Chelmis
    http://arxiv.org/abs/2106.04668v1

    • [cs.LG]EF21: A New, Simpler, Theoretically Better, and Practically Faster Error Feedback
    Peter Richtárik, Igor Sokolov, Ilyas Fatkhullin
    http://arxiv.org/abs/2106.05203v1

    • [cs.LG]EMFlow: Data Imputation in Latent Space via EM and Deep Flow Models
    Qi Ma, Sujit K. Ghosh
    http://arxiv.org/abs/2106.04804v1

    • [cs.LG]EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions
    Laurens Bliek, Arthur Guijt, Rickard Karlsson, Sicco Verwer, Mathijs de Weerdt
    http://arxiv.org/abs/2106.04618v1

    • [cs.LG]Efficient Active Search for Combinatorial Optimization Problems
    André Hottung, Yeong-Dae Kwon, Kevin Tierney
    http://arxiv.org/abs/2106.05126v1

    • [cs.LG]Embedding Physics to Learn Spatiotemporal Dynamics from Sparse Data
    Chengping Rao, Hao Sun, Yang Liu
    http://arxiv.org/abs/2106.04781v1

    • [cs.LG]Energy-Based Models for Code Generation under Compilability Constraints
    Tomasz Korbak, Hady Elsahar, Marc Dymetman, Germán Kruszewski
    http://arxiv.org/abs/2106.04985v1

    • [cs.LG]Ex uno plures: Splitting One Model into an Ensemble of Subnetworks
    Zhilu Zhang, Vianne R. Gao, Mert R. Sabuncu
    http://arxiv.org/abs/2106.04767v1

    • [cs.LG]Expectation Programming
    Tim Reichelt, Adam Goliński, Luke Ong, Tom Rainforth
    http://arxiv.org/abs/2106.04953v1

    • [cs.LG]Explainable AI for medical imaging: Explaining pneumothorax diagnoses with Bayesian Teaching
    Tomas Folke, Scott Cheng-Hsin Yang, Sean Anderson, Patrick Shafto
    http://arxiv.org/abs/2106.04684v1

    • [cs.LG]Fixed-Budget Best-Arm Identification in Contextual Bandits: A Static-Adaptive Algorithm
    MohammadJavad Azizi, Branislav Kveton, Mohammad Ghavamzadeh
    http://arxiv.org/abs/2106.04763v1

    • [cs.LG]GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data
    Jens Petersen, Gregor Köhler, David Zimmerer, Fabian Isensee, Paul F. Jäger, Klaus H. Maier-Hein
    http://arxiv.org/abs/2106.04967v1

    • [cs.LG]Ghosts in Neural Networks: Existence, Structure and Role of Infinite-Dimensional Null Space
    Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
    http://arxiv.org/abs/2106.04770v1

    • [cs.LG]Harmless Overparametrization in Two-layer Neural Networks
    Huiyuan Wang, Wei Lin
    http://arxiv.org/abs/2106.04795v1

    • [cs.LG]I Don’t Need 今日学术视野(2021.6.11) - 图2: Identifiable Non-Linear ICA Without Side Information
    Matthew Willetts, Brooks Paige
    http://arxiv.org/abs/2106.05238v1

    • [cs.LG]Interaction-Grounded Learning
    Tengyang Xie, John Langford, Paul Mineiro, Ida Momennejad
    http://arxiv.org/abs/2106.04887v1

    • [cs.LG]It Takes Two to Tango: Mixup for Deep Metric Learning
    Shashanka Venkataramanan, Bill Psomas, Yannis Avrithis, Ewa Kijak, Laurent Amsaleg, Konstantinos Karantzalos
    http://arxiv.org/abs/2106.04990v1

    • [cs.LG]Labeled Data Generation with Inexact Supervision
    Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang
    http://arxiv.org/abs/2106.04716v1

    • [cs.LG]Learning Pseudo-Backdoors for Mixed Integer Programs
    Aaron Ferber, Jialin Song, Bistra Dilkina, Yisong Yue
    http://arxiv.org/abs/2106.05080v1

    • [cs.LG]Learning normal form autoencoders for data-driven discovery of universal,parameter-dependent governing equations
    Manu Kalia, Steven L. Brunton, Hil G. E. Meijer, Christoph Brune, J. Nathan Kutz
    http://arxiv.org/abs/2106.05102v1

    • [cs.LG]Learning subtree pattern importance for Weisfeiler-Lehmanbased graph kernels
    Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka
    http://arxiv.org/abs/2106.04739v1

    • [cs.LG]Memory-based Optimization Methods for Model-Agnostic Meta-Learning
    Bokun Wang, Zhuoning Yuan, Yiming Ying, Tianbao Yang
    http://arxiv.org/abs/2106.04911v1

    • [cs.LG]Multi-layered Network Exploration via Random Walks: From Offline Optimization to Online Learning
    Xutong Liu, Jinhang Zuo, Xiaowei Chen, Wei Chen, John C. S. Lui
    http://arxiv.org/abs/2106.05065v1

    • [cs.LG]Multistep Electric Vehicle Charging Station Occupancy Prediction using Mixed LSTM Neural Networks
    Tai-Yu Ma, Sébastien Faye
    http://arxiv.org/abs/2106.04986v1

    • [cs.LG]NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs
    Enyan Dai, Charu Aggarwal, Suhang Wang
    http://arxiv.org/abs/2106.04714v1

    • [cs.LG]Neighborhood Contrastive Learning Applied to Online Patient Monitoring
    Hugo Yèche, Gideon Dresdner, Francesco Locatello, Matthias Hüser, Gunnar Rätsch
    http://arxiv.org/abs/2106.05142v1

    • [cs.LG]Network insensitivity to parameter noise via adversarial regularization
    Julian Bücher, Fynn Faber, Dylan R. Muir
    http://arxiv.org/abs/2106.05009v1

    • [cs.LG]No Fear of Heterogeneity: Classifier Calibration for Federated Learning with Non-IID Data
    Mi Luo, Fei Chen, Dapeng Hu, Yifan Zhang, Jian Liang, Jiashi Feng
    http://arxiv.org/abs/2106.05001v1

    • [cs.LG]Nonlinear Hawkes Processes in Time-Varying System
    Feng Zhou, Quyu Kong, Yixuan Zhang, Cheng Feng, Jun Zhu
    http://arxiv.org/abs/2106.04844v1

    • [cs.LG]OODIn: An Optimised On-Device Inference Framework for Heterogeneous Mobile Devices
    Stylianos I. Venieris, Ioannis Panopoulos, Iakovos S. Venieris
    http://arxiv.org/abs/2106.04723v1

    • [cs.LG]Offline Inverse Reinforcement Learning
    Firas Jarboui, Vianney Perchet
    http://arxiv.org/abs/2106.05068v1

    • [cs.LG]On Margin-Based Cluster Recovery with Oracle Queries
    Marco Bressan, Nicolò Cesa-Bianchi, Silvio Lattanzi, Andrea Paudice
    http://arxiv.org/abs/2106.04913v1

    • [cs.LG]On the Evolution of Neuron Communities in a Deep Learning Architecture
    Sakib Mostafa, Debajyoti Mondal
    http://arxiv.org/abs/2106.04693v1

    • [cs.LG]Online Optimization in Games via Control Theory: Connecting Regret, Passivity and Poincaré Recurrence
    Yun Kuen Cheung, Georgios Piliouras
    http://arxiv.org/abs/2106.04748v1

    • [cs.LG]Operationalizing Complex Causes:A Pragmatic View of Mediation
    Limor Gultchin, David S. Watson, Matt J. Kusner, Ricardo Silva
    http://arxiv.org/abs/2106.05074v1

    • [cs.LG]PEARL: Data Synthesis via Private Embeddings and Adversarial Reconstruction Learning
    Seng Pei Liew, Tsubasa Takahashi, Michihiko Ueno
    http://arxiv.org/abs/2106.04590v1

    • [cs.LG]PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-training
    Kimin Lee, Laura Smith, Pieter Abbeel
    http://arxiv.org/abs/2106.05091v1

    • [cs.LG]Phase Retrieval using Single-Instance Deep Generative Prior
    Kshitij Tayal, Raunak Manekar, Zhong Zhuang, David Yang, Vipin Kumar, Felix Hofmann, Ju Sun
    http://arxiv.org/abs/2106.04812v1

    • [cs.LG]Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning
    Tengyang Xie, Nan Jiang, Huan Wang, Caiming Xiong, Yu Bai
    http://arxiv.org/abs/2106.04895v1

    • [cs.LG]Polynomial magic! Hermite polynomials for private data generation
    Mijung Park, Margarita Vinaroz, Mohammad-Amin Charusaie, Frederik Harder
    http://arxiv.org/abs/2106.05042v1

    • [cs.LG]Practical Machine Learning Safety: A Survey and Primer
    Sina Mohseni, Haotao Wang, Zhiding Yu, Chaowei Xiao, Zhangyang Wang, Jay Yadawa
    http://arxiv.org/abs/2106.04823v1

    • [cs.LG]Predicting Deep Neural Network Generalization with Perturbation Response Curves
    Yair Schiff, Brian Quanz, Payel Das, Pin-Yu Chen
    http://arxiv.org/abs/2106.04765v1

    • [cs.LG]Pretrained Encoders are All You Need
    Mina Khan, P Srivatsa, Advait Rane, Shriram Chenniappa, Rishabh Anand, Sherjil Ozair, Pattie Maes
    http://arxiv.org/abs/2106.05139v1

    • [cs.LG]Pretraining Representations for Data-Efficient Reinforcement Learning
    Max Schwarzer, Nitarshan Rajkumar, Michael Noukhovitch, Ankesh Anand, Laurent Charlin, Devon Hjelm, Philip Bachman, Aaron Courville
    http://arxiv.org/abs/2106.04799v1

    • [cs.LG]Probabilistic task modelling for meta-learning
    Cuong C. Nguyen, Thanh-Toan Do, Gustavo Carneiro
    http://arxiv.org/abs/2106.04802v1

    • [cs.LG]Provably Faster Algorithms for Bilevel Optimization
    Junjie Yang, Kaiyi Ji, Yingbin Liang
    http://arxiv.org/abs/2106.04692v1

    • [cs.LG]Quickest change detection with unknown parameters: Constant complexity and near optimality
    Firas Jarboui, Viannet Perchet
    http://arxiv.org/abs/2106.05061v1

    • [cs.LG]Realizing GANs via a Tunable Loss Function
    Gowtham R. Kurri, Tyler Sypherd, Lalitha Sankar
    http://arxiv.org/abs/2106.05232v1

    • [cs.LG]Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints
    Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, Karl H. Johansson
    http://arxiv.org/abs/2106.05135v1

    • [cs.LG]Reliable Adversarial Distillation with Unreliable Teachers
    Jianing Zhu, Jiangchao Yao, Bo Han, Jingfeng Zhang, Tongliang Liu, Gang Niu, Jingren Zhou, Jianliang Xu, Hongxia Yang
    http://arxiv.org/abs/2106.04928v1

    • [cs.LG]Scale Free Adversarial Multi Armed Bandits
    Sudeep Raja Putta, Shipra Agrawal
    http://arxiv.org/abs/2106.04700v1

    • [cs.LG]Scaling Up Graph Neural Networks Via Graph Coarsening
    Zengfeng Huang, Shengzhong Zhang, Chong Xi, Tang Liu, Min Zhou
    http://arxiv.org/abs/2106.05150v1

    • [cs.LG]Self-Improved Retrosynthetic Planning
    Junsu Kim, Sungsoo Ahn, Hankook Lee, Jinwoo Shin
    http://arxiv.org/abs/2106.04880v1

    • [cs.LG]Self-Paced Context Evaluation for Contextual Reinforcement Learning
    Theresa Eimer, André Biedenkapp, Frank Hutter, Marius Lindauer
    http://arxiv.org/abs/2106.05110v1

    • [cs.LG]Self-Supervised Graph Learning with Hyperbolic Embedding for Temporal Health Event Prediction
    Chang Lu, Chandan K. Reddy, Yue Ning
    http://arxiv.org/abs/2106.04751v1

    • [cs.LG]Simulating Continuum Mechanics with Multi-Scale Graph Neural Networks
    Mario Lino, Chris Cantwell, Anil A. Bharath, Stathi Fotiadis
    http://arxiv.org/abs/2106.04900v1

    • [cs.LG]Symmetric Spaces for Graph Embeddings: A Finsler-Riemannian Approach
    Federico López, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard
    http://arxiv.org/abs/2106.04941v1

    • [cs.LG]TempoRL: Learning When to Act
    André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer
    http://arxiv.org/abs/2106.05262v1

    • [cs.LG]There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning
    Nathan Grinsztajn, Johan Ferret, Olivier Pietquin, Philippe Preux, Matthieu Geist
    http://arxiv.org/abs/2106.04480v2

    • [cs.LG]Towards Deep Industrial Transfer Learning for Anomaly Detection on Time Series Data
    Benjamin Maschler, Tim Knodel, Michael Weyrich
    http://arxiv.org/abs/2106.04920v1

    • [cs.LG]Towards the Memorization Effect of Neural Networks in Adversarial Training
    Han Xu, Xiaorui Liu, Wentao Wang, Wenbiao Ding, Zhongqin Wu, Zitao Liu, Anil Jain, Jiliang Tang
    http://arxiv.org/abs/2106.04794v1

    • [cs.LG]Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos
    Lele Luan, Yang Liu, Hao Sun
    http://arxiv.org/abs/2106.04776v1

    • [cs.LG]Understanding Softmax Confidence and Uncertainty
    Tim Pearce, Alexandra Brintrup, Jun Zhu
    http://arxiv.org/abs/2106.04972v1

    • [cs.LG]Vector Quantized Models for Planning
    Sherjil Ozair, Yazhe Li, Ali Razavi, Ioannis Antonoglou, Aäron van den Oord, Oriol Vinyals
    http://arxiv.org/abs/2106.04615v1

    • [cs.LG]Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL
    Yanchao Sun, Ruijie Zheng, Yongyuan Liang, Furong Huang
    http://arxiv.org/abs/2106.05087v1

    • [cs.LG]XBNet : An Extremely Boosted Neural Network
    Tushar Sarkar
    http://arxiv.org/abs/2106.05239v1

    • [cs.MA]Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games
    Xiangyu Liu, Hangtian Jia, Ying Wen, Yaodong Yang, Yujing Hu, Yingfeng Chen, Changjie Fan, Zhipeng Hu
    http://arxiv.org/abs/2106.04958v1

    • [cs.NE]A 2020 taxonomy of algorithms inspired on living beings behavior
    Luis Torres-Treviño
    http://arxiv.org/abs/2106.04775v1

    • [cs.NE]A Case Study: Using Genetic Algorithm for Job Scheduling Problem
    Burak Tağtekin, Mahiye Uluyağmur Öztürk, Mert Kutay Sezer
    http://arxiv.org/abs/2106.04854v1

    • [cs.NE]Multiple simultaneous solution representations in a population based evolutionary algorithm
    Eric S. Fraga
    http://arxiv.org/abs/2106.05096v1

    • [cs.NE]Probabilistic Neural Network to Quantify Uncertainty of Wind Power Estimation
    Farzad Karami, Nasser Kehtarnavaz, Mario Rotea
    http://arxiv.org/abs/2106.04656v1

    • [cs.NI]Engineering-Economic Evaluation of Diffractive Non-Line-Of-Sight Backhaul (e3nb): A Techno-economic Model for 3D Wireless Backhaul Assessment
    Edward J. Oughton, Erik Boch, Julius Kusuma
    http://arxiv.org/abs/2106.04906v1

    • [cs.RO]A Communication Layer for Integrated Sensors and Robotic ecology Solutions to Ambient Intelligence
    Giuseppe Amato, Stefano Chessa, Mauro Dragone, Claudio Gennaro, Claudio Vairo
    http://arxiv.org/abs/2106.05100v1

    • [cs.RO]Design and fabrication of solar powered remote controlled all terrain sprayer and mower robot
    Sri Tarun Ayyagari, Sharan Kumar Kizhakke Erakkat, Srikanth TS, Manichandra Neerati
    http://arxiv.org/abs/2106.05236v1

    • [cs.RO]HEAP — The autonomous walking excavator
    Dominic Jud, Simon Kerscher, Martin Wermelinger, Edo Jelavic, Pascal Egli, Philipp Leemann, Gabriel Hottiger, Marco Hutter
    http://arxiv.org/abs/2106.05059v1

    • [cs.SD]Intermittent Speech Recovery
    Yu-Chen Lin, Tsun-An Hsieh, Kuo-Hsuan Hung, Cheng Yu, Harinath Garudadri, Yu Tsao, Tei-Wei Kuo
    http://arxiv.org/abs/2106.05229v1

    • [cs.SI]Design and Implementation of 5G eHealth Systems, Technologies, Use Cases and Future Challenges
    Di Zhang, Joel J. P. C. Rodrigues, Yunkai Zhai, Takuro Sato
    http://arxiv.org/abs/2106.05086v1

    • [cs.SI]Diffusion Source Identification on Networks with Statistical Confidence
    Quinlan Dawkins, Tianxi Li, Haifeng Xu
    http://arxiv.org/abs/2106.04800v1

    • [cs.SI]Fundamental Privacy Limits in Bipartite Networks under Active Attacks
    Mahshad Shariatnasab, Farhad Shirani, Elza Erkip
    http://arxiv.org/abs/2106.04766v1

    • [cs.SI]Multiple Kernel Representation Learning on Networks
    Abdulkadir Celikkanat, Yanning Shen, Fragkiskos D. Malliaros
    http://arxiv.org/abs/2106.05057v1

    • [cs.SI]Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks
    Changlin Wan, Muhan Zhang, Wei Hao, Sha Cao, Pan Li, Chi Zhang
    http://arxiv.org/abs/2106.04292v2

    • [cs.SI]Surveillance of COVID-19 Pandemic using Social Media: A Reddit Study in North Carolina
    Christopher Whitfield, Yang Liu, Mohad Anwar
    http://arxiv.org/abs/2106.04515v2

    • [cs.SI]Tiplines to Combat Misinformation on Encrypted Platforms: A Case Study of the 2019 Indian Election on WhatsApp
    Ashkan Kazemi, Kiran Garimella, Gautam Kishore Shahi, Devin Gaffney, Scott A. Hale
    http://arxiv.org/abs/2106.04726v1

    • [econ.EM]Automatically Differentiable Random Coefficient Logistic Demand Estimation
    Andrew Chia
    http://arxiv.org/abs/2106.04636v1

    • [econ.EM]Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraint
    Shosei Sakaguchi
    http://arxiv.org/abs/2106.05031v1

    • [econ.EM]On Estimating Multiple Treatment Effects with Regression
    Paul Goldsmith-Pinkham, Peter Hull, Michal Kolesár
    http://arxiv.org/abs/2106.05024v1

    • [eess.AS]SpeechBrain: A General-Purpose Speech Toolkit
    Mirco Ravanelli, Titouan Parcollet, Peter Plantinga, Aku Rouhe, Samuele Cornell, Loren Lugosch, Cem Subakan, Nauman Dawalatabad, Abdelwahab Heba, Jianyuan Zhong, Ju-Chieh Chou, Sung-Lin Yeh, Szu-Wei Fu, Chien-Feng Liao, Elena Rastorgueva, François Grondin, William Aris, Hwidong Na, Yan Gao, Renato De Mori, Yoshua Bengio
    http://arxiv.org/abs/2106.04624v1

    • [eess.IV]A multi-stage GAN for multi-organ chest X-ray image generation and segmentation
    Giorgio Ciano, Paolo Andreini, Tommaso Mazzierli, Monica Bianchini, Franco Scarselli
    http://arxiv.org/abs/2106.05132v1

    • [eess.IV]Fast Computational Ghost Imaging using Unpaired Deep Learning and a Constrained Generative Adversarial Network
    Fatemeh Alishahi, Amirhossein Mohajerin-Ariaei
    http://arxiv.org/abs/2106.04822v1

    • [eess.IV]Implicit field learning for unsupervised anomaly detection in medical images
    Sergio Naval Marimont, Giacomo Tarroni
    http://arxiv.org/abs/2106.05214v1

    • [eess.IV]Rethink Transfer Learning in Medical Image Classification
    Le Peng, Hengyue Liang, Taihui Li, Ju Sun
    http://arxiv.org/abs/2106.05152v1

    • [eess.IV]Spatio-Temporal Dual-Stream Neural Network for Sequential Whole-Body PET Segmentation
    Kai-Chieh Liang, Lei Bi, Ashnil Kumar, Michael Fulham, Jinman Kim
    http://arxiv.org/abs/2106.04961v1

    • [eess.IV]TED-net: Convolution-free T2T Vision Transformer-based Encoder-decoder Dilation network for Low-dose CT Denoising
    Dayang Wang, Zhan Wu, Hengyong Yu
    http://arxiv.org/abs/2106.04650v1

    • [eess.SY]Continuous-discrete multiple target tracking with out-of-sequence measurements
    Ángel F. García-Fernández, Wei Yi
    http://arxiv.org/abs/2106.04898v1

    • [eess.SY]Job Dispatching Policies for Queueing Systems with Unknown Service Rates
    Tuhinangshu Choudhury, Gauri Joshi, Weina Wang, Sanjay Shakkottai
    http://arxiv.org/abs/2106.04707v1

    • [math.OC]Avoiding Traps in Nonconvex Problems
    Sean Deyo, Veit Elser
    http://arxiv.org/abs/2106.05206v1

    • [math.OC]Drones for Medical Delivery Considering Different Demands Classes: A Markov Decision Process Approach for Managing Health Centers Dispatching Medical Products
    Amin Asadi, Sarah Nurre Pinkley
    http://arxiv.org/abs/2106.04729v1

    • [math.OC]Efficient input placement for the optimal control of network moments
    Philip Solimine, Anke Meyer-Baese
    http://arxiv.org/abs/2106.05265v1

    • [math.OC]Optimal Inspection of Network Systems via Value of Information Analysis
    Chaochao Lin, Junho Song, Matteo Pozzi
    http://arxiv.org/abs/2106.04988v1

    • [math.OC]Submodular + Concave
    Siddharth Mitra, Moran Feldman, Amin Karbasi
    http://arxiv.org/abs/2106.04769v1

    • [math.OC]Using a New Nonlinear Gradient Method for Solving Large Scale Convex Optimization Problems with an Application on Arabic Medical Text
    Jaafar Hammoud, Ali Eisa, Natalia Dobrenko, Natalia Gusarova
    http://arxiv.org/abs/2106.04383v2

    • [math.PR]On the Hitting Time of Rapid Intensification Onset in Hurricane-like Vortices
    Wai-Tong Louis Fan, Chanh Kieu, Dimitrios Sakellariou, Mahashweta Patra
    http://arxiv.org/abs/2106.04721v1

    • [math.PR]Shrinkage Estimation of Functions of Large Noisy Symmetric Matrices
    Panagiotis Lolas, Lexing Ying
    http://arxiv.org/abs/2106.05183v1

    • [math.PR]Some variations on the extremal index
    Gloria Buriticá, Meyer Nicolas, Thomas Mikosch, Olivier Wintenberger
    http://arxiv.org/abs/2106.05117v1

    • [math.ST]General-order observation-driven models: ergodicity and consistency of the maximum likelihood estimator
    Tepmony Sim, Randal Douc, François Roueff
    http://arxiv.org/abs/2106.05201v1

    • [math.ST]Mixture weights optimisation for Alpha-Divergence Variational Inference
    Kamélia Daudel, Randal Douc
    http://arxiv.org/abs/2106.05114v1

    • [quant-ph]Quantum Annealing for Automated Feature Selection in Stress Detection
    Rajdeep Kumar Nath, Himanshu Thapliyal, Travis S. Humble
    http://arxiv.org/abs/2106.05134v1

    • [quant-ph]The dilemma of quantum neural networks
    Yang Qian, Xinbiao Wang, Yuxuan Du, Xingyao Wu, Dacheng Tao
    http://arxiv.org/abs/2106.04975v1

    • [stat.AP]Fracture Mechanics-Based Quantitative Matching of Forensic Evidence Fragments
    Geoffrey Z. Thompson, Bishoy Dawood, Tianyu Yu, Barbara K. Lograsso, John D. Vanderkolk, Ranjan Maitra, William Q. Meeker, Ashraf F. Bastawros
    http://arxiv.org/abs/2106.04809v1

    • [stat.AP]Odds Ratios are far from “portable”: A call to use realistic models for effect variation in meta-analysis
    Mengli Xiao, Haitao Chu, Stephen Cole, Yong Chen, Richard MacLehose, David Richardson, Sander Greenland
    http://arxiv.org/abs/2106.02673v2

    • [stat.AP]Sirius: A Mutual Information Tool for Exploratory Visualization of Mixed Data
    Jane L. Adams, Todd F. Deluca, Christopher M. Danforth, Peter S. Dodds, Yuhang Zheng, Konstantinos Anastasakis, Boyoon Choi, Allison Min, Michael M. Bessey
    http://arxiv.org/abs/2106.05260v1

    • [stat.AP]Spatial modelling of COVID-19 incident cases using Richards’ curve: an application to the Italian regions
    Marco Mingione, Pierfrancesco Alaimo Di Loro, Alessio Farcomeni, Fabio Divino, Gianfranco Lovison, Giovanna Jona Lasinio, Antonello Maruotti
    http://arxiv.org/abs/2106.05067v1

    • [stat.AP]UEFA EURO 2020 Forecast via Nested Zero-Inflated Generalized Poisson Regression
    Lorenz A. Gilch
    http://arxiv.org/abs/2106.05174v1

    • [stat.ME]A New Measure of Overlap: An Alternative to the p—value
    Stephen G Walker
    http://arxiv.org/abs/2106.01821v2

    • [stat.ME]Bayesian Boosting for Linear Mixed Models
    Boyao Zhang, Colin Griesbach, Cora Kim, Nadia Müller-Voggel, Elisabeth Bergherr
    http://arxiv.org/abs/2106.04862v1

    • [stat.ME]Copula-Frailty Models for Recurrent Event Data Based on Monte Carlo EM Algorithm
    Khaled F. Bedair, Yili Hong, Hussein R. Al-Khalidi
    http://arxiv.org/abs/2106.05204v1

    • [stat.ME]Fast construction of optimal composite likelihoods
    Zhendong Huang, Davide Ferrari
    http://arxiv.org/abs/2106.05219v1

    • [stat.ME]Markov-Switching State-Space Models with Applications to Neuroimaging
    David Degras, Chee Ming Ting, Hernando Ombao
    http://arxiv.org/abs/2106.05092v1

    • [stat.ME]Modelling for Poisson process intensities over irregular spatial domains
    Chunyi Zhao, Athanasios Kottas
    http://arxiv.org/abs/2106.04654v1

    • [stat.ME]On the Use of Minimum Penalties in Statistical Learning
    Ben Sherwood, Bradley S. Price
    http://arxiv.org/abs/2106.05172v1

    • [stat.ME]Ultra High Dimensional Change Point Detection
    Xin Liu, Liwen Zhang, Zhen Zhang
    http://arxiv.org/abs/2106.04869v1

    • [stat.ME]Verification and Validation of Log-Periodic Power Law Models
    Jarret Petrillo
    http://arxiv.org/abs/2106.05116v1

    • [stat.ML]DIGRAC: Digraph Clustering with Flow Imbalance
    Yixuan He, Gesine Reinert, Mihai Cucuringu
    http://arxiv.org/abs/2106.05194v1

    • [stat.ML]Fast and More Powerful Selective Inference for Sparse High-order Interaction Model
    Diptesh Das, Vo Nguyen Le Duy, Hiroyuki Hanada, Koji Tsuda, Ichiro Takeuchi
    http://arxiv.org/abs/2106.04929v1

    • [stat.ML]Fractal Structure and Generalization Properties of Stochastic Optimization Algorithms
    Alexander Camuto, George Deligiannidis, Murat A. Erdogdu, Mert Gürbüzbalaban, Umut Şimşekli, Lingjiong Zhu
    http://arxiv.org/abs/2106.04881v1

    • [stat.ML]Fully differentiable model discovery
    Gert-Jan Both, Remy Kusters
    http://arxiv.org/abs/2106.04886v1

    • [stat.ML]Gaussian Mixture Estimation from Weighted Samples
    Daniel Frisch, Uwe D. Hanebeck
    http://arxiv.org/abs/2106.05109v1

    • [stat.ML]Independent mechanism analysis, a new concept?
    Luigi Gresele, Julius von Kügelgen, Vincent Stimper, Bernhard Schölkopf, Michel Besserve
    http://arxiv.org/abs/2106.05200v1

    • [stat.ML]Learning Domain Invariant Representations by Joint Wasserstein Distance Minimization
    Léo Andéol, Yusei Kawakami, Yuichiro Wada, Takafumi Kanamori, Klaus-Robert Müller, Grégoire Montavon
    http://arxiv.org/abs/2106.04923v1

    • [stat.ML]Loss function based second-order Jensen inequality and its application to particle variational inference
    Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
    http://arxiv.org/abs/2106.05010v1

    • [stat.ML]Marginalizable Density Models
    Dar Gilboa, Ari Pakman, Thibault Vatter
    http://arxiv.org/abs/2106.04741v1

    • [stat.ML]Multi-Facet Clustering Variational Autoencoders
    Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Christopher C Holmes
    http://arxiv.org/abs/2106.05241v1

    • [stat.ML]Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
    Julius von Kügelgen, Yash Sharma, Luigi Gresele, Wieland Brendel, Bernhard Schölkopf, Michel Besserve, Francesco Locatello
    http://arxiv.org/abs/2106.04619v1

    • [stat.ML]Streaming Belief Propagation for Community Detection
    Yuchen Wu, MohammadHossein Bateni, Andre Linhares, Filipe Miguel Goncalves de Almeida, Andrea Montanari, Ashkan Norouzi-Fard, Jakab Tardos
    http://arxiv.org/abs/2106.04805v1