cs.AI - 人工智能
cs.CL - 计算与语言
cs.CR - 加密与安全
cs.CV - 机器视觉与模式识别
cs.CY - 计算与社会
cs.DC - 分布式、并行与集群计算
cs.DL - 数字图书馆
cs.DS - 数据结构与算法
cs.HC - 人机接口
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.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.SP - 信号处理
eess.SY - 系统和控制
hep-ph - 高能物理现象学
math.AG - 代数几何
math.CO - 组合数学
math.FA - 泛函演算
math.NA - 数值分析
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.comp-ph - 计算物理学
physics.plasm-ph - 等离子体物理
q-bio.QM - 定量方法
q-fin.ST - 统计金融学
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
stat.OT - 其他统计学
• [cs.AI]A Unified Cognitive Learning Framework for Adapting to Dynamic Environment and Tasks
• [cs.AI]AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning
• [cs.AI]Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment
• [cs.AI]Did I do that? Blame as a means to identify controlled effects in reinforcement learning
• [cs.AI]Discovering Diverse Nearly Optimal Policies withSuccessor Features
• [cs.AI]Divide and Rule: Recurrent Partitioned Network for Dynamic Processes
• [cs.AI]Graph-based Exercise- and Knowledge-Aware Learning Network for Student Performance Prediction
• [cs.AI]Learning Representations for Sub-Symbolic Reasoning
• [cs.AI]On the KLM properties of a fuzzy DL with Typicality
• [cs.AI]Reward is enough for convex MDPs
• [cs.AI]Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs
• [cs.AI]Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning
• [cs.AI]To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods
• [cs.AI]Understanding peacefulness through the world news
• [cs.AI]Value propagation-based spatio-temporal interpolation inspired by Markov reward processes
• [cs.CL]A Coarse to Fine Question Answering System based on Reinforcement Learning
• [cs.CL]An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformers
• [cs.CL]Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
• [cs.CL]CIDER: Commonsense Inference for Dialogue Explanation and Reasoning
• [cs.CL]Corpus-Based Paraphrase Detection Experiments and Review
• [cs.CL]Dialogue-oriented Pre-training
• [cs.CL]Discontinuous Named Entity Recognition as Maximal Clique Discovery
• [cs.CL]Distribution Matching for Rationalization
• [cs.CL]DoT: An efficient Double Transformer for NLP tasks with tables
• [cs.CL]End-to-End Multihop Retrieval for Compositional Question Answering over Long Documents
• [cs.CL]Exploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models
• [cs.CL]Exploring Dynamic Selection of Branch Expansion Orders for Code Generation
• [cs.CL]Gender Bias Amplification During Speed-Quality Optimization in Neural Machine Translation
• [cs.CL]Gender Bias Hidden Behind Chinese Word Embeddings: The Case of Chinese Adjectives
• [cs.CL]HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations
• [cs.CL]HiddenCut: Simple Data Augmentation for Natural Language Understanding with Better Generalization
• [cs.CL]Improving Automatic Hate Speech Detection with Multiword Expression Features
• [cs.CL]Improving Formality Style Transfer with Context-Aware Rule Injection
• [cs.CL]Incorporating Visual Layout Structures for Scientific Text Classification
• [cs.CL]KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction
• [cs.CL]Language Model Evaluation Beyond Perplexity
• [cs.CL]LenAtten: An Effective Length Controlling Unit For Text Summarization
• [cs.CL]More than just Frequency? Demasking Unsupervised Hypernymy Prediction Methods
• [cs.CL]Multilingual Speech Translation with Unified Transformer: Huawei Noah’s Ark Lab at IWSLT 2021
• [cs.CL]NewsEmbed: Modeling News through Pre-trained DocumentRepresentations
• [cs.CL]Nora: The Well-Being Coach
• [cs.CL]On the Interplay Between Fine-tuning and Composition in Transformers
• [cs.CL]PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World
• [cs.CL]Preview, Attend and Review: Schema-Aware Curriculum Learning for Multi-Domain Dialog State Tracking
• [cs.CL]Question-aware Transformer Models for Consumer Health Question Summarization
• [cs.CL]Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition
• [cs.CL]Replicating and Extending “\textit{Because Their Treebanks Leak}”: Graph Isomorphism, Covariants, and Parser Performance
• [cs.CL]SHUOWEN-JIEZI: Linguistically Informed Tokenizers For Chinese Language Model Pretraining
• [cs.CL]SemEval-2021 Task 1: Lexical Complexity Prediction
• [cs.CL]SemEval-2021 Task 4: Reading Comprehension of Abstract Meaning
• [cs.CL]SpanNer: Named Entity Re-/Recognition as Span Prediction
• [cs.CL]Text Summarization with Latent Queries
• [cs.CL]Towards Quantifiable Dialogue Coherence Evaluation
• [cs.CL]Training ELECTRA Augmented with Multi-word Selection
• [cs.CL]Validating GAN-BioBERT: A Methodology For Assessing Reporting Trends In Clinical Trials
• [cs.CL]ViTA: Visual-Linguistic Translation by Aligning Object Tags
• [cs.CL]Volta at SemEval-2021 Task 6: Towards Detecting Persuasive Texts and Images using Textual and Multimodal Ensemble
• [cs.CL]Volta at SemEval-2021 Task 9: Statement Verification and Evidence Finding with Tables using TAPAS and Transfer Learning
• [cs.CR]GRAVITAS: Graphical Reticulated Attack Vectors for Internet-of-Things Aggregate Security
• [cs.CR]HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture
• [cs.CR]Instance-optimal Mean Estimation Under Differential Privacy
• [cs.CR]MalPhase: Fine-Grained Malware Detection Using Network Flow Data
• [cs.CR]Tight Accounting in the Shuffle Model of Differential Privacy
• [cs.CV]A Novel Graph-Theoretic Deep Representation Learning Method for Multi-Label Remote Sensing Image Retrieval
• [cs.CV]Adversarial VQA: A New Benchmark for Evaluating the Robustness of VQA Models
• [cs.CV]Analysis of Vision-based Abnormal Red Blood Cell Classification
• [cs.CV]Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation
• [cs.CV]Bootstrap Your Own Correspondences
• [cs.CV]Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
• [cs.CV]Comprehensive Validation of Automated Whole Body Skeletal Muscle, Adipose Tissue, and Bone Segmentation from 3D CT images for Body Composition Analysis: Towards Extended Body Composition
• [cs.CV]Consistent Two-Flow Network for Tele-Registration of Point Clouds
• [cs.CV]Continual 3D Convolutional Neural Networks for Real-time Processing of Videos
• [cs.CV]DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point Clouds
• [cs.CV]Deep learning for prediction of hepatocellular carcinoma recurrence after resection or liver transplantation: a discovery and validation study
• [cs.CV]Dense Nested Attention Network for Infrared Small Target Detection
• [cs.CV]Detecting Anomalies in Semantic Segmentation with Prototypes
• [cs.CV]Dual Normalization Multitasking for Audio-Visual Sounding Object Localization
• [cs.CV]EV-VGCNN: A Voxel Graph CNN for Event-based Object Classification
• [cs.CV]Exploring the Diversity and Invariance in Yourself for Visual Pre-Training Task
• [cs.CV]Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks
• [cs.CV]Full-Resolution Encoder-Decoder Networks with Multi-Scale Feature Fusion for Human Pose Estimation
• [cs.CV]Hardness Sampling for Self-Training Based Transductive Zero-Shot Learning
• [cs.CV]Independent Prototype Propagation for Zero-Shot Compositionality
• [cs.CV]Integrative Use of Computer Vision and Unmanned Aircraft Technologies in Public Inspection: Foreign Object Debris Image Collection
• [cs.CV]Language-Driven Image Style Transfer
• [cs.CV]Look Wide and Interpret Twice: Improving Performance on Interactive Instruction-following Tasks
• [cs.CV]Natural Statistics of Network Activations and Implications for Knowledge Distillation
• [cs.CV]PanoDR: Spherical Panorama Diminished Reality for Indoor Scenes
• [cs.CV]Predicting Vehicles Trajectories in Urban Scenarios with Transformer Networks and Augmented Information
• [cs.CV]Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes
• [cs.CV]Quantification of Carbon Sequestration in Urban Forests
• [cs.CV]Reconciliation of Statistical and Spatial Sparsity For Robust Image and Image-Set Classification
• [cs.CV]Rethinking Pseudo Labels for Semi-Supervised Object Detection
• [cs.CV]Rethinking Re-Sampling in Imbalanced Semi-Supervised Learning
• [cs.CV]Robust Mutual Learning for Semi-supervised Semantic Segmentation
• [cs.CV]Semi-Supervised Disparity Estimation with Deep Feature Reconstruction
• [cs.CV]Semi-Supervised Domain Generalization with Stochastic StyleMatch
• [cs.CV]Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features
• [cs.CV]Towards Real-time and Light-weight Line Segment Detection
• [cs.CV]TransVOS: Video Object Segmentation with Transformers
• [cs.CV]Urban Traffic Surveillance (UTS): A fully probabilistic 3D tracking approach based on 2D detections
• [cs.CV]VA-GCN: A Vector Attention Graph Convolution Network for learning on Point Clouds
• [cs.CV]You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection
• [cs.CY]”Why wouldn’t someone think of democracy as a target?”: Security practices & challenges of people involved with U.S. political campaigns
• [cs.CY]A Way to a Universal VR Accessibility Toolkit
• [cs.CY]AI-Ethics by Design. Evaluating Public Perception on the Importance of Ethical Design Principles of AI
• [cs.CY]Scientific Computing in the Cavendish Laboratory and the pioneering women Computors
• [cs.DC]Composing Networks of Automated Market Makers
• [cs.DC]Energy and Network Aware Workload Management for Geographically Distributed Data Centers
• [cs.DC]SMASH: Sparse Matrix Atomic Scratchpad Hashing
• [cs.DC]Triggerflow: Trigger-based Orchestration of Serverless Workflows
• [cs.DC]UniStore: A fault-tolerant marriage of causal and strong consistency (extended version)
• [cs.DL]Harvesting the Public MeSH Note field
• [cs.DL]The x-index: A new citation-distance-based index to measure academic influence
• [cs.DL]WebMIaS on Docker: Deploying Math-Aware Search in a Single Line of Code
• [cs.DS]-norm Flow Diffusion in Near-Linear Time
• [cs.DS]Fault-Tolerant Labeling and Compact Routing Schemes
• [cs.HC]Automating Visualization Quality Assessment: a Case Study in Higher Education
• [cs.HC]ClustRank: a Visual Quality Measure Trained on Perceptual Data for Sorting Scatterplots by Cluster Patterns
• [cs.HC]Generating Ten BCI Commands Using Four Simple Motor Imageries
• [cs.IR]Controllable Gradient Item Retrieval
• [cs.IR]Dual Graph enhanced Embedding Neural Network for CTRPrediction
• [cs.IR]FBAdTracker: An Interactive Data Collection and Analysis Tool for Facebook Advertisements
• [cs.IR]The Cold-start Proble
5a45
m: Minimal Users’ Activity Estimation
• [cs.IT]Distance and Position Estimation in Visible Light Systems with RGB LEDs
• [cs.IT]Fast Splitting Algorithms for Sparsity-Constrained and Noisy Group Testing
• [cs.IT]Low-Complexity Symbol-Level Precoding for MU-MISO Downlink Systems with QAM Signals
• [cs.IT]New Placement Delivery Array Construction for Coded Caching with Flexible Memory Size
• [cs.IT]Rate-Splitting Multiple Access in Cache-Aided Cloud-Radio Access Networks
• [cs.IT]Reinforce Security: A Model-Free Approach Towards Secure Wiretap Coding
• [cs.IT]Throughput-Outage Scaling Behaviors for Wireless Single-Hop D2D Caching Networks with Physical Model — Analysis and Derivations
• [cs.IT]Topology and Admittance Estimation: Precision Limits and Algorithms
• [cs.IT]Wireless Federated Learning with Limited Communication and Differential Privacy
• [cs.LG]A Compression-Compilation Framework for On-mobile Real-time BERT Applications
• [cs.LG]A reinforcement learning approach to improve communication performance and energy utilization in fog-based IoT
• [cs.LG]A study on the plasticity of neural networks
• [cs.LG]A unified PAC-Bayesian framework for machine unlearning via information risk minimization
• [cs.LG]AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry
• [cs.LG]Analysis of classifiers robust to noisy labels
• [cs.LG]Asymptotics of representation learning in finite Bayesian neural networks
• [cs.LG]Automated Grading of Anatomical Objective Structured Practical Exams Using Decision Trees
• [cs.LG]CSCAD: Correlation Structure-based Collective Anomaly Detection in Complex System
• [cs.LG]Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
• [cs.LG]Combining resampling and reweighting for faithful stochastic optimization
• [cs.LG]Concurrent Adversarial Learning for Large-Batch Training
• [cs.LG]Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests
• [cs.LG]Data-Driven Shadowgraph Simulation of a 3D Object
• [cs.LG]Decision Concept Lattice vs. Decision Trees and Random Forests
• [cs.LG]Deep Reinforcement Learning in Quantitative Algorithmic Trading: A Review
• [cs.LG]Duckworth-Lewis-Stern Method Comparison with Machine Learning Approach
• [cs.LG]Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints
• [cs.LG]Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images
• [cs.LG]Efficient Explanations With Relevant Sets
• [cs.LG]Enhancing Trajectory Prediction using Sparse Outputs: Application to Team Sports
• [cs.LG]Experiments with graph convolutional networks for solving the vertex -center problem
• [cs.LG]Explanations for Monotonic Classifiers
• [cs.LG]Exploring Sparse Expert Models and Beyond
• [cs.LG]Exposing Previously Undetectable Faults in Deep Neural Networks
• [cs.LG]Fair Clustering Using Antidote Data
• [cs.LG]Fair Representations by Compression
• [cs.LG]Federated Learning for Industrial Internet of Things in Future Industries
• [cs.LG]Fine-grained Generalization Analysis of Structured Output Prediction
• [cs.LG]GANs Can Play Lottery Tickets Too
• [cs.LG]Gaussian Processes with Differential Privacy
• [cs.LG]Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective
• [cs.LG]Generating Adversarial Examples with Graph Neural Networks
• [cs.LG]Gradient Play in Multi-Agent Markov Stochastic Games: Stationary Points and Convergence
• [cs.LG]H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning
• [cs.LG]Hop-Aware Dimension Optimization for Graph Neural Networks
• [cs.LG]How Attentive are Graph Attention Networks?
• [cs.LG]Hybrid Generative Models for Two-Dimensional Datasets
• [cs.LG]IID-GAN: an IID Sampling Perspective for Regularizing Mode Collapse
• [cs.LG]Improving Conditional Coverage via Orthogonal Quantile Regression
• [cs.LG]Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Offline RL
• [cs.LG]Information-Theoretic Analysis of Epistemic Uncertainty in Bayesian Meta-learning
• [cs.LG]Instance Correction for Learning with Open-set Noisy Labels
• [cs.LG]LRTuner: A Learning Rate Tuner for Deep Neural Networks
• [cs.LG]Learning Football Body-Orientation as a Matter of Classification
• [cs.LG]Learning and Generalization in RNNs
• [cs.LG]Locally Valid and Discriminative Confidence Intervals for Deep Learning Models
• [cs.LG]Machine-Learning Non-Conservative Dynamics for New-Physics Detection
• [cs.LG]Markpainting: Adversarial Machine Learning meets Inpainting
• [cs.LG]Minimax Regret for Bandit Convex Optimisation of Ridge Functions
• [cs.LG]More Behind Your Electricity Bill: a Dual-DNN Approach to Non-Intrusive Load Monitoring
• [cs.LG]Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs
• [cs.LG]Node-Variant Graph Filters in Graph Neural Networks
• [cs.LG]NoiLIn: Do Noisy Labels Always Hurt Adversarial Training?
• [cs.LG]On Fast Sampling of Diffusion Probabilistic Models
• [cs.LG]OpenBox: A Generalized Black-box Optimization Service
• [cs.LG]PUDLE: Implicit Acceleration of Dictionary Learning by Backpropagation
• [cs.LG]Parallelized Computation and Backpropagation Under Angle-Parametrized Orthogonal Matrices
• [cs.LG]Persistent Homology Captures the Generalization of Neural Networks Without A Validation Set
• [cs.LG]Probabilistic Deep Learning with Probabilistic Neural Networks and Deep Probabilistic Models
• [cs.LG]Procedural Content Generation: Better Benchmarks for Transfer Reinforcement Learning
• [cs.LG]Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning
• [cs.LG]RFCBF: enhance the performance and stability of Fast Correlation-Based Filter
• [cs.LG]Robust discovery of partial differential equations in complex situations
• [cs.LG]SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models
• [cs.LG]Sample Selection with Uncertainty of Losses for Learning with Noisy Labels
• [cs.LG]Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners
• [cs.LG]Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts
• [cs.LG]Student Performance Prediction Using Dynamic Neural Models
• [cs.LG]Surrogate Model Based Hyperparameter Tuning for Deep Learning with SPOT
• [cs.LG]Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
• [cs.LG]The Care Label Concept: A Certification Suite for Trustworthy and Resource-Aware Machine Learning
• [cs.LG]The zoo of Fairness metrics in Machine Learning
• [cs.LG]UNiTE: Unitary N-body Tensor Equivariant Network with Applications to Quantum Chemistry
• [cs.LG]What Matters for Adversarial Imitation Learning?
• [cs.MA]Large-scale, Dynamic and Distributed Coalition Formation with Spatial and Temporal Constraints
• [cs.MA]The Impact of Network Connectivity on Collective Learning
• [cs.NE]Diffusion Self-Organizing Map on the Hypersphere
• [cs.NI]Reinforcement Learning-based Dynamic Service Placement in Vehicular Networks
• [cs.RO]3D map creation using crowdsourced GNSS data
• [cs.RO]A Road-map to Robot Task Execution with the Functional Object-Oriented Network
• [cs.RO]Assembly Planning by Recognizing a Graphical Instruction Manual
• [cs.RO]DeepWalk: Omnidirectional Bipedal Gait by Deep Reinforcement Learning
• [cs.RO]DikpolaSat Mission: Improvement of Space Flight Performance and Optimal Control Using Trained Deep Neural Network — Trajectory Controller for Space Objects Collision Avoidance
• [cs.RO]Electric field measurements made on a robotic platform
• [cs.RO]Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects
• [cs.RO]Markov Localisation using Heatmap Regression and Deep Convolutional Odometry
• [cs.RO]Resource-aware Online Parameter Adaptation for Computationally-constrained Visual-Inertial Navigation Systems
• [cs.RO]Single-query Path Planning Using Sample-efficient Probability Informed Trees
• [cs.RO]Strobe: An Acceleration Meta-algorithm for Optimizing Robot Paths using Concurrent Interleaved Sub-Epoch Pods
• [cs.RO]What Can I Do Here? Learning New Skills by Imagining Visual Affordances
• [cs.SD]Adversarial Defense for Automatic Speaker Verification by Self-Supervised Learning
• [cs.SD]Omnizart: A General Toolbox for Automatic Music Transcription
• [cs.SD]Towards Explainable Convolutional Features for Music Audio Modeling
• [cs.SI]CoRank: A clustering cum graph ranking approach for extractive summarization
• [cs.SI]Construction of Simplicial Complexes with Prescribed Degree-Size Sequences
• [cs.SI]Optimizing travel routes using temporal networks constructed from GPS data
• [cs.SI]Parlermonium: A Data-Driven UX Design Evaluation of the Parler Platform
• [econ.EM]Specification tests for GARCH processes
• [eess.AS]Low-Resource Spoken Language Identification Using Self-Attentive Pooling and Deep 1D Time-Channel Separable Convolutions
• [eess.AS]StarGAN-ZSVC: Towards Zero-Shot Voice Conversion in Low-Resource Contexts
• [eess.IV]3D WaveUNet: 3D Wavelet Integrated Encoder-Decoder Network for Neuron Segmentation
• [eess.IV]COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network
• [eess.IV]Decoupling Shape and Density for Liver Lesion Synthesis Using Conditional Generative Adversarial Networks
• [eess.IV]Hybrid Deep Neural Network for Brachial Plexus Nerve Segmentation in Ultrasound Images
• [eess.IV]Hyperspectral Band Selection for Multispectral Image Classification with Convolutional Networks
• [eess.IV]RAI-Net: Range-Adaptive LiDAR Point Cloud Frame Interpolation Network
• [eess.IV]Two-stage domain adapted training for better generalization in real-world image restoration and super-resolution
• [eess.SP]A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEG
• [eess.SP]Dynamic-Deep: ECG Task-Aware Compression
• [eess.SP]Meta-HAR: Federated Representation Learning for Human Activity Recognition
• [eess.SP]Weak target detection with multi-bit quantization in colocated MIMO radar
• [eess.SY]A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems
• [hep-ph]A survey of machine learning-based physics event generation
• [math.AG]Tensor decomposition for learning Gaussian mixtures from moments
• [math.CO]The Sample Fréchet Mean of Sparse Graphs is Sparse
• [math.FA]Anti-Koopmanism
• [math.NA]Recovering wavelet coefficients from binary samples using fast transforms
• [math.OC]A Non-commutative Extension of Lee-Seung’s Algorithm for Positive Semidefinite Factorizations
• [math.OC]Control Occupation Kernel Regression for Nonlinear Control-Affine Systems
• [math.OC]On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry
• [math.OC]Optimal transport with -divergence regularization and generalized Sinkhorn algorithm
• [math.PR]Entropy and the Discrete Central Limit Theorem
• [math.ST]Bayes-optimal prediction with frequentist coverage control
• [math.ST]Distribution-free inference for regression: discrete, continuous, and in between
• [math.ST]Halfspace depth for general measures: The ray basis theorem and its consequences
• [math.ST]Median bias of M-estimators
• [math.ST]On some properties of the bimodal normal distribution and its bivariate version
• [math.ST]Stacked Grenander estimator of a discrete distribution
• [math.ST]Statistical tests based on Rényi entropy estimation
• [math.ST]The query complexity of sampling from strongly log-concave distributions in one dimension
• [physics.comp-ph]Deep-Learning Discovers Macroscopic Governing Equations for Viscous Gravity Currents from Microscopic Simulation Data
• [physics.comp-ph]Empirical Models for Multidimensional Regression of Fission Systems
• [physics.plasm-ph]Invertible Surrogate Models: Joint surrogate modelling and reconstruction of Laser-Wakefield Acceleration by invertible neural networks
• [q-bio.QM]Detection of preventable fetal distress during labor from scanned cardiotocogram tracings using deep learning
• [q-fin.ST]Mapping the NFT revolution: market trends, trade networks and visual features
• [quant-ph]Quantum Federated Learning with Quantum Data
• [stat.AP]A mixed-frequency approach for exchange rates predictions
• [stat.AP]A non-separable first-order spatio-temporal intensity for events on linear networks: an application to ambulance interventions
• [stat.AP]An introduction to network analysis for studies of medication use
• [stat.AP]Efficient adaptive MCMC implementation for Pseudo-Bayesian quantum tomography
• [stat.AP]Predicting COVID-19 Spread from Large-Scale Mobility Data
• [stat.AP]Simulating flood event sets using extremal principal components
• [stat.ME]Adaptive Conformal Inference Under Distribution Shift
• [stat.ME]Federated Estimation of Causal Effects from Observational Data
• [stat.ME]Logistic Regression Through the Veil of Imprecise Data
• [stat.ML]Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data
• [stat.ML]MARL with General Utilities via Decentralized Shadow Reward Actor-Critic
• [stat.ML]Post-Contextual-Bandit Inference
• [stat.ML]Transformation Models for Flexible Posteriors in Variational Bayes
• [stat.ML]Variational Autoencoders: A Harmonic Perspective
• [stat.ML]Variational Combinatorial Sequential Monte Carlo Methods for Bayesian Phylogenetic Inference
• [stat.ML]What’s a good imputation to predict with missing values?
• [stat.OT]Review of Low-Voltage Load Forecasting: Methods, Applications, and Recommendations
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• [cs.AI]A Unified Cognitive Learning Framework for Adapting to Dynamic Environment and Tasks
Qihui Wu, Tianchen Ruan, Fuhui Zhou, Yang Huang, Fan Xu, Shijin Zhao, Ya Liu, Xuyang Huang
http://arxiv.org/abs/2106.00501v1
• [cs.AI]AppBuddy: Learning to Accomplish Tasks in Mobile Apps via Reinforcement Learning
Maayan Shvo, Zhiming Hu, Rodrigo Toro Icarte, Iqbal Mohomed, Allan Jepson, Sheila A. McIlraith
http://arxiv.org/abs/2106.00133v1
• [cs.AI]Cooperative Multi-Agent Transfer Learning with Level-Adaptive Credit Assignment
Tianze Zhou, Fubiao Zhang, Kun Shao, Kai Li, Wenhan Huang, Jun Luo, Weixun Wang, Yaodong Yang, Hangyu Mao, Bin Wang, Dong Li, Wulong Liu, Jianye Hao
http://arxiv.org/abs/2106.00517v1
• [cs.AI]Did I do that? Blame as a means to identify controlled effects in reinforcement learning
Oriol Corcoll, Raul Vicente
http://arxiv.org/abs/2106.00266v1
• [cs.AI]Discovering Diverse Nearly Optimal Policies withSuccessor Features
Tom Zahavy, Brendan O’Donoghue, Andre Barreto, Volodymyr Mnih, Sebastian Flennerhag, Satinder Singh
http://arxiv.org/abs/2106.00669v1
• [cs.AI]Divide and Rule: Recurrent Partitioned Network for Dynamic Processes
Qianyu Feng, Bang Zhang, Yi Yang
http://arxiv.org/abs/2106.00258v1
• [cs.AI]Graph-based Exercise- and Knowledge-Aware Learning Network for Student Performance Prediction
Mengfan Liu, Pengyang Shao, Kun Zhang
http://arxiv.org/abs/2106.00263v1
• [cs.AI]Learning Representations for Sub-Symbolic Reasoning
Giuseppe Marra, Michelangelo Diligenti, Francesco Giannini, Marco Maggini
http://arxiv.org/abs/2106.00393v1
• [cs.AI]On the KLM properties of a fuzzy DL with Typicality
Laura Giordano
http://arxiv.org/abs/2106.00390v1
• [cs.AI]Reward is enough for convex MDPs
Tom Zahavy, Brendan O’Donoghue, Guillaume Desjardins, Satinder Singh
http://arxiv.org/abs/2106.00661v1
• [cs.AI]Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphs
Zixuan Li, Xiaolong Jin, Saiping Guan, Wei Li, Jiafeng Guo, Yuanzhuo Wang, Xueqi Cheng
http://arxiv.org/abs/2106.00327v1
• [cs.AI]Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning
Jiahui Li, Kun Kuang, Baoxiang Wang, Furui Liu, Long Chen, Fei Wu, Jun Xiao
http://arxiv.org/abs/2106.00285v1
• [cs.AI]To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods
Elvio G. Amparore, Alan Perotti, Paolo Bajardi
http://arxiv.org/abs/2106.00461v1
• [cs.AI]Understanding peacefulness through the world news
Vasiliki Voukelatou, Ioanna Miliou, Fosca Giannotti, Luca Pappalardo
http://arxiv.org/abs/2106.00306v1
• [cs.AI]Value propagation-based spatio-temporal interpolation inspired by Markov reward processes
Laurens Arp, Mitra Baratchi, Holger Hoos
http://arxiv.org/abs/2106.00538v1
• [cs.CL]A Coarse to Fine Question Answering System based on Reinforcement Learning
Yu Wang, Hongxia Jin
http://arxiv.org/abs/2106.00257v1
• [cs.CL]An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformers
Tharindu Ranasinghe, Constantin Orasan, Ruslan Mitkov
http://arxiv.org/abs/2106.00143v1
• [cs.CL]Bringing Structure into Summaries: a Faceted Summarization Dataset for Long Scientific Documents
Rui Meng, Khushboo Thaker, Lei Zhang, Yue Dong, Xingdi Yuan, Tong Wang, Daqing He
http://arxiv.org/abs/2106.00130v1
• [cs.CL]CIDER: Commonsense Inference for Dialogue Explanation and Reasoning
Deepanway Ghosal, Pengfei Hong, Siqi Shen, Navonil Majumder, Rada Mihalcea, Soujanya Poria
http://arxiv.org/abs/2106.00510v1
• [cs.CL]Corpus-Based Paraphrase Detection Experiments and Review
Tedo Vrbanec, Ana Mestrovic
http://arxiv.org/abs/2106.00145v1
• [cs.CL]Dialogue-oriented Pre-training
Yi Xu, Hai Zhao
http://arxiv.org/abs/2106.00420v1
• [cs.CL]Discontinuous Named Entity Recognition as Maximal Clique Discovery
Yucheng Wang, Bowen Yu, Hongsong Zhu, Tingwen Liu, Nan Yu, Limin Sun
http://arxiv.org/abs/2106.00218v1
• [cs.CL]Distribution Matching for Rationalization
Yongfeng Huang, Yujun Chen, Yulun Du, Zhilin Yang
http://arxiv.org/abs/2106.00320v1
• [cs.CL]DoT: An efficient Double Transformer for NLP tasks with tables
Syrine Krichene, Thomas Müller, Julian Martin Eisenschlos
http://arxiv.org/abs/2106.00479v1
• [cs.CL]End-to-End Multihop Retrieval for Compositional Question Answering over Long Documents
Haitian Sun, William W. Cohen, Ruslan Salakhutdinov
http://arxiv.org/abs/2106.00200v1
• [cs.CL]Exploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models
Chong Li, Cenyuan Zhang, Xiaoqing Zheng, Xuanjing Huang
http://arxiv.org/abs/2105.14813v2
• [cs.CL]Exploring Dynamic Selection of Branch Expansion Orders for Code Generation
Hui Jiang, Chulun Zhou, Fandong Meng, Biao Zhang, Jie Zhou, Degen Huang, Qingqiang Wu, Jinsong Su
http://arxiv.org/abs/2106.00261v1
• [cs.CL]Gender Bias Amplification During Speed-Quality Optimization in Neural Machine Translation
Adithya Renduchintala, Denise Diaz, Kenneth Heafield, Xian Li, Mona Diab
http://arxiv.org/abs/2106.00169v1
• [cs.CL]Gender Bias Hidden Behind Chinese Word Embeddings: The Case of Chinese Adjectives
Meichun Jiao, Ziyang Luo
http://arxiv.org/abs/2106.00181v1
• [cs.CL]HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations
Weixin Liang, Kai-Hui Liang, Zhou Yu
http://arxiv.org/abs/2106.00162v1
• [cs.CL]HiddenCut: Simple Data Augmentation for Natural Language Understanding with Better Generalization
Jiaao Chen, Dinghan Shen, Weizhu Chen, Diyi Yang
http://arxiv.org/abs/2106.00149v1
• [cs.CL]Improving Automatic Hate Speech Detection with Multiword Expression Features
Nicolas Zampieri, Irina Illina, Dominique Fohr
http://arxiv.org/abs/2106.00237v1
• [cs.CL]Improving Formality Style Transfer with Context-Aware Rule Injection
Zonghai Yao, Hong Yu
http://arxiv.org/abs/2106.00210v1
• [cs.CL]Incorporating Visual Layout Structures for Scientific Text Classification
Zejiang Shen, Kyle Lo, Lucy Lu Wang, Bailey Kuehl, Daniel S. Weld, Doug Downey
http://arxiv.org/abs/2106.00676v1
• [cs.CL]KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction
Abhishek Nadgeri, Anson Bastos, Kuldeep Singh, Isaiah Onando Mulang’, Johannes Hoffart, Saeedeh Shekarpour, Vijay Saraswat
http://arxiv.org/abs/2106.00459v1
• [cs.CL]Language Model Evaluation Beyond Perplexity
Clara Meister, Ryan Cotterell
http://arxiv.org/abs/2106.00085v1
• [cs.CL]LenAtten: An Effective Length Controlling Unit For Text Summarization
Zhongyi Yu, Zhenghao Wu, Hao Zheng, Zhe XuanYuan, Jefferson Fong, Weifeng Su
http://arxiv.org/abs/2106.00316v1
• [cs.CL]More than just Frequency? Demasking Unsupervised Hypernymy Prediction Methods
Thomas Bott, Dominik Schlechtweg, Sabine Schulte im Walde
http://arxiv.org/abs/2106.00055v1
• [cs.CL]Multilingual Speech Translation with Unified Transformer: Huawei Noah’s Ark Lab at IWSLT 2021
Xingshan Zeng, Liangyou Li, Qun Liu
http://arxiv.org/abs/2106.00197v1
• [cs.CL]NewsEmbed: Modeling News through Pre-trained DocumentRepresentations
Jialu Liu, Tianqi Liu, Cong Yu
http://arxiv.org/abs/2106.00590v1
• [cs.CL]Nora: The Well-Being Coach
Genta Indra Winata, Holy Lovenia, Etsuko Ishii, Farhad Bin Siddique, Yongsheng Yang, Pascale Fung
http://arxiv.org/abs/2106.00410v1
• [cs.CL]On the Interplay Between Fine-tuning and Composition in Transformers
Lang Yu, Allyson Ettinger
http://arxiv.org/abs/2105.14668v2
• [cs.CL]PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World
Rowan Zellers, Ari Holtzman, Matthew Peters, Roozbeh Mottaghi, Aniruddha Kembhavi, Ali Farhadi, Yejin Choi
http://arxiv.org/abs/2106.00188v1
• [cs.CL]Preview, Attend and Review: Schema-Aware Curriculum Learning for Multi-Domain Dialog State Tracking
Yinpei Dai, Hangyu Li, Yongbin Li, Jian Sun, Fei Huang, Luo Si, Xiaodan Zhu
http://arxiv.org/abs/2106.00291v1
• [cs.CL]Question-aware Transformer Models for Consumer Health Question Summarization
Shweta Yadav, Deepak Gupta, Asma Ben Abacha, Dina Demner-Fushman
http://arxiv.org/abs/2106.00219v1
• [cs.CL]Reinforced Iterative Knowledge Distillation for Cross-Lingual Named Entity Recognition
Shining Liang, Ming Gong, Jian Pei, Linjun Shou, Wanli Zuo, Xianglin Zuo, Daxin Jiang
http://arxiv.org/abs/2106.00241v1
• [cs.CL]Replicating and Extending “\textit{Because Their Treebanks Leak}”: Graph Isomorphism, Covariants, and Parser Performance
Mark Anderson, Anders Søgaard, Carlos Gómez Rodríguez
http://arxiv.org/abs/2106.00352v1
• [cs.CL]SHUOWEN-JIEZI: Linguistically Informed Tokenizers For Chinese Language Model Pretraining
Chenglei Si, Zhengyan Zhang, Yingfa Chen, Fanchao Qi, Xiaozhi Wang, Zhiyuan Liu, Maosong Sun
http://arxiv.org/abs/2106.00400v1
• [cs.CL]SemEval-2021 Task 1: Lexical Complexity Prediction
Matthew Shardlow, Richard Evans, Gustavo Henrique Paetzold, Marcos Zampieri
http://arxiv.org/abs/2106.00473v1
• [cs.CL]SemEval-2021 Task 4: Reading Comprehension of Abstract Meaning
Boyuan Zheng, Xiaoyu Yang, Yu-Ping Ruan, Zhenhua Ling, Quan Liu, Si Wei, Xiaodan Zhu
http://arxiv.org/abs/2105.14879v2
• [cs.CL]SpanNer: Named Entity Re-/Recognition as Span Prediction
Jinlan Fu, Xuanjing Huang, Pengfei Liu
http://arxiv.org/abs/2106.00641v1
• [cs.CL]Text Summarization with Latent Queries
Yumo Xu, Mirella Lapata
http://arxiv.org/abs/2106.00104v1
• [cs.CL]Towards Quantifiable Dialogue Coherence Evaluation
Zheng Ye, Liucun Lu, Lishan Huang, Liang Lin, Xiaodan Liang
http://arxiv.org/abs/2106.00507v1
• [cs.CL]Training ELECTRA Augmented with Multi-word Selection
Jiaming Shen, Jialu Liu, Tianqi Liu, Cong Yu, Jiawei Han
http://arxiv.org/abs/2106.00139v1
• [cs.CL]Validating GAN-BioBERT: A Methodology For Assessing Reporting Trends In Clinical Trials
Joshua J Myszewski, Emily Klossowski, Patrick Meyer, Kristin Bevil, Lisa Klesius, Kristopher M Schroeder
http://arxiv.org/abs/2106.00665v1
• [cs.CL]ViTA: Visual-Linguistic Translation by Aligning Object Tags
Kshitij Gupta, Devansh Gautam, Radhika Mamidi
http://arxiv.org/abs/2106.00250v1
• [cs.CL]Volta at SemEval-2021 Task 6: Towards Detecting Persuasive Texts and Images using Textual and Multimodal Ensemble
Kshitij Gupta, Devansh Gautam, Radhika Mamidi
http://arxiv.org/abs/2106.00240v1
• [cs.CL]Volta at SemEval-2021 Task 9: Statement Verification and Evidence Finding with Tables using TAPAS and Transfer Learning
Devansh Gautam, Kshitij Gupta, Manish Shrivastava
http://arxiv.org/abs/2106.00248v1
• [cs.CR]GRAVITAS: Graphical Reticulated Attack Vectors for Internet-of-Things Aggregate Security
Jacob Brown, Tanujay Saha, Niraj K. Jha
http://arxiv.org/abs/2106.00073v1
• [cs.CR]HEMET: A Homomorphic-Encryption-Friendly Privacy-Preserving Mobile Neural Network Architecture
Qian Lou, Lei Jiang
http://arxiv.org/abs/2106.00038v1
• [cs.CR]Instance-optimal Mean Estimation Under Differential Privacy
Ziyue Huang, Yuting Liang, Ke Yi
http://arxiv.org/abs/2106.00463v1
• [cs.CR]MalPhase: Fine-Grained Malware Detection Using Network Flow Data
Michal Piskozub, Fabio De Gaspari, Frederick Barr-Smith, Luigi V. Mancini, Ivan Martinovic
http://arxiv.org/abs/2106.00541v1
• [cs.CR]Tight Accounting in the Shuffle Model of Differential Privacy
Antti Koskela, Mikko A. Heikkilä, Antti Honkela
http://arxiv.org/abs/2106.00477v1
• [cs.CV]A Novel Graph-Theoretic Deep Representation Learning Method for Multi-Label Remote Sensing Image Retrieval
Gencer Sumbul, Begüm Demir
http://arxiv.org/abs/2106.00506v1
• [cs.CV]Adversarial VQA: A New Benchmark for Evaluating the Robustness of VQA Models
Linjie Li, Jie Lei, Zhe Gan, Jingjing Liu
http://arxiv.org/abs/2106.00245v1
• [cs.CV]Analysis of Vision-based Abnormal Red Blood Cell Classification
Annika Wong, Nantheera Anantrasirichai, Thanarat H. Chalidabhongse, Duangdao Palasuwan, Attakorn Palasuwan, David Bull
http://arxiv.org/abs/2106.00389v1
• [cs.CV]Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation
Binghao Liu, Yao Ding, Jianbin Jiao, Xiangyang Ji, Qixiang Ye
http://arxiv.org/abs/2106.00184v1
• [cs.CV]Bootstrap Your Own Correspondences
Mohamed El Banani, Justin Johnson
http://arxiv.org/abs/2106.00677v1
• [cs.CV]Closer Look at the Uncertainty Estimation in Semantic Segmentation under Distributional Shift
Sebastian Cygert, Bartłomiej Wróblewski, Karol Woźniak, Radosław Słowiński, Andrzej Czyżewski
http://arxiv.org/abs/2106.00076v1
• [cs.CV]Comprehensive Validation of Automated Whole Body Skeletal Muscle, Adipose Tissue, and Bone Segmentation from 3D CT images for Body Composition Analysis: Towards Extended Body Composition
Da Ma, Vincent Chow, Karteek Popuri, Mirza Faisal Beg
http://arxiv.org/abs/2106.00652v1
• [cs.CV]Consistent Two-Flow Network for Tele-Registration of Point Clouds
Zihao Yan, Zimu Yi, Ruizhen Hu, Niloy J. Mitra, Daniel Cohen-Or, Hui Huang
http://arxiv.org/abs/2106.00329v1
• [cs.CV]Continual 3D Convolutional Neural Networks for Real-time Processing of Videos
Lukas Hedegaard, Alexandros Iosifidis
http://arxiv.org/abs/2106.00050v1
• [cs.CV]DLA-Net: Learning Dual Local Attention Features for Semantic Segmentation of Large-Scale Building Facade Point Clouds
Yanfei Su, Weiquan Liu, Zhimin Yuan, Ming Cheng, Zhihong Zhang, Xuelun Shen, Cheng Wang
http://arxiv.org/abs/2106.00376v1
• [cs.CV]Deep learning for prediction of hepatocellular carcinoma recurrence after resection or liver transplantation: a discovery and validation study
Zhikun Liu, Yuanpeng Liu, Yuan Hong, Jinwen Meng, Jianguo Wang, Shusen Zheng, Xiao Xu
http://arxiv.org/abs/2106.00090v1
• [cs.CV]Dense Nested Attention Network for Infrared Small Target Detection
Boyang Li, Chao Xiao, Longguang Wang, Yingqian Wang, Zaiping Lin, Miao Li, Wei An, Yulan Guo
http://arxiv.org/abs/2106.00487v1
• [cs.CV]Detecting Anomalies in Semantic Segmentation with Prototypes
Dario Fontanel, Fabio Cermelli, Massimiliano Mancini, Barbara Caputo
http://arxiv.org/abs/2106.00472v1
• [cs.CV]Dual Normalization Multitasking for Audio-Visual Sounding Object Localization
Tokuhiro Nishikawa, Daiki Shimada, Jerry Jun Yokono
http://arxiv.org/abs/2106.00180v1
• [cs.CV]EV-VGCNN: A Voxel Graph CNN for Event-based Object Classification
Yongjian Deng, Hao Chen, Huiying Chen, Youfu Li
http://arxiv.org/abs/2106.00216v1
• [cs.CV]Exploring the Diversity and Invariance in Yourself for Visual Pre-Training Task
Longhui Wei, Lingxi Xie, Wengang Zhou, Houqiang Li, Qi Tian
http://arxiv.org/abs/2106.00537v1
• [cs.CV]Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks
Xiaoyu Lin, Deblina Bhattacharjee, Majed El Helou, Sabine Süsstrunk
http://arxiv.org/abs/2106.00673v1
• [cs.CV]Full-Resolution Encoder-Decoder Networks with Multi-Scale Feature Fusion for Human Pose Estimation
Jie Ou, Mingjian Chen, Hong Wu
http://arxiv.org/abs/2106.00566v1
• [cs.CV]Hardness Sampling for Self-Training Based Transductive Zero-Shot Learning
Liu Bo, Qiulei Dong, Zhanyi Hu
http://arxiv.org/abs/2106.00264v1
• [cs.CV]Independent Prototype Propagation for Zero-Shot Compositionality
Frank Ruis, Gertjan Burghours, Doina Bucur
http://arxiv.org/abs/2106.00305v1
• [cs.CV]Integrative Use of Computer Vision and Unmanned Aircraft Technologies in Public Inspection: Foreign Object Debris Image Collection
Travis J. E. Munyer, Daniel Brinkman, Chenyu Huang, Xin Zhong
http://arxiv.org/abs/2106.00161v1
• [cs.CV]Language-Driven Image Style Transfer
Tsu-Jui Fu, Xin Eric Wang, William Yang Wang
http://arxiv.org/abs/2106.00178v1
• [cs.CV]Look Wide and Interpret Twice: Improving Performance on Interactive Instruction-following Tasks
Van-Quang Nguyen, Masanori Suganuma, Takayuki Okatani
http://arxiv.org/abs/2106.00596v1
• [cs.CV]Natural Statistics of Network Activations and Implications for Knowledge Distillation
Michael Rotman, Lior Wolf
http://arxiv.org/abs/2106.00368v1
• [cs.CV]PanoDR: Spherical Panorama Diminished Reality for Indoor Scenes
V. Gkitsas, V. Sterzentsenko, N. Zioulis, G. Albanis, D. Zarpalas
http://arxiv.org/abs/2106.00446v1
• [cs.CV]Predicting Vehicles Trajectories in Urban Scenarios with Transformer Networks and Augmented Information
A. Quintanar, D. Fernández-Llorca, I. Parra, R. Izquierdo, M. A. Sotelo
http://arxiv.org/abs/2106.00559v1
• [cs.CV]Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes
Jian-Wei Zhang, Lei Lv, Yawei Luo, Hao-Zhe Feng, Yi Yang, Wei Chen
http://arxiv.org/abs/2106.00572v1
• [cs.CV]Quantification of Carbon Sequestration in Urban Forests
Levente Klein, Wang Zhou, Conrad Albrecht
http://arxiv.org/abs/2106.00182v1
• [cs.CV]Reconciliation of Statistical and Spatial Sparsity For Robust Image and Image-Set Classification
Hao Cheng, Kim-Hui Yap, Bihan Wen
http://arxiv.org/abs/2106.00256v1
• [cs.CV]Rethinking Pseudo Labels for Semi-Supervised Object Detection
Hengduo Li, Zuxuan Wu, Abhinav Shrivastava, Larry S. Davis
http://arxiv.org/abs/2106.00168v1
• [cs.CV]Rethinking Re-Sampling in Imbalanced Semi-Supervised Learning
Ju He, Adam Kortylewski, Shaokang Yang, Shuai Liu, Cheng Yang, Changhu Wang, Alan Yuille
http://arxiv.org/abs/2106.00209v1
• [cs.CV]Robust Mutual Learning for Semi-supervised Semantic Segmentation
Pan Zhang, Bo Zhang, Ting Zhang, Dong Chen, Fang Wen
http://arxiv.org/abs/2106.00609v1
• [cs.CV]Semi-Supervised Disparity Estimation with Deep Feature Reconstruction
Julia Guerrero-Viu, Sergio Izquierdo, Philipp Schröppel, Thomas Brox
http://arxiv.org/abs/2106.00318v1
• [cs.CV]Semi-Supervised Domain Generalization with Stochastic StyleMatch
Kaiyang Zhou, Chen Change Loy, Ziwei Liu
http://arxiv.org/abs/2106.00592v1
• [cs.CV]Towards Efficient Cross-Modal Visual Textual Retrieval using Transformer-Encoder Deep Features
Nicola Messina, Giuseppe Amato, Fabrizio Falchi, Claudio Gennaro, Stéphane Marchand-Maillet
http://arxiv.org/abs/2106.00358v1
• [cs.CV]Towards Real-time and Light-weight Line Segment Detection
Geonmo Gu, Byungsoo Ko, SeoungHyun Go, Sung-Hyun Lee, Jingeun Lee, Minchul Shin
http://arxiv.org/abs/2106.00186v1
• [cs.CV]TransVOS: Video Object Segmentation with Transformers
Jianbiao Mei, Mengmeng Wang, Yeneng Lin, Yong Liu
http://arxiv.org/abs/2106.00588v1
• [cs.CV]Urban Traffic Surveillance (UTS): A fully probabilistic 3D tracking approach based on 2D detections
Henry Bradler, Adrian Kretz, Rudolf Mester
http://arxiv.org/abs/2105.14993v2
• [cs.CV]VA-GCN: A Vector Attention Graph Convolution Network for learning on Point Clouds
Haotian Hu, Fanyi Wang, Huixiao Le
http://arxiv.org/abs/2106.00227v1
• [cs.CV]You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection
Yuxin Fang, Bencheng Liao, Xinggang Wang, Jiemin Fang, Jiyang Qi, Rui Wu, Jianwei Niu, Wenyu Liu
http://arxiv.org/abs/2106.00666v1
• [cs.CY]“Why wouldn’t someone think of democracy as a target?”: Security practices & challenges of people involved with U.S. political campaigns
Sunny Consolvo, Patrick Gage Kelley, Tara Matthews, Kurt Thomas, Lee Dunn, Elie Bursztein
http://arxiv.org/abs/2106.00236v1
• [cs.CY]A Way to a Universal VR Accessibility Toolkit
Felix J. Thiel, Anthony Steed
http://arxiv.org/abs/2106.00321v1
• [cs.CY]AI-Ethics by Design. Evaluating Public Perception on the Importance of Ethical Design Principles of AI
Kimon Kieslich, Birte Keller, Christopher Starke
http://arxiv.org/abs/2106.00326v1
• [cs.CY]Scientific Computing in the Cavendish Laboratory and the pioneering women Computors
Verity Allan, Caitriona Leedham
http://arxiv.org/abs/2106.00365v1
• [cs.DC]Composing Networks of Automated Market Makers
Daniel Engel, Maurice Herlihy
http://arxiv.org/abs/2106.00083v1
• [cs.DC]Energy and Network Aware Workload Management for Geographically Distributed Data Centers
Ninad Hogade, Sudeep Pasricha, Howard Jay Siegel
http://arxiv.org/abs/2106.00066v1
• [cs.DC]SMASH: Sparse Matrix Atomic Scratchpad Hashing
Kaustubh Shivdikar
http://arxiv.org/abs/2105.14156v1
• [cs.DC]Triggerflow: Trigger-based Orchestration of Serverless Workflows
Aitor Arjona, Pedro García-López, Josep Sampé, Aleksander Slominski, Lionel Villard
http://arxiv.org/abs/2106.00583v1
• [cs.DC]UniStore: A fault-tolerant marriage of causal and strong consistency (extended version)
Manuel Bravo, Alexey Gotsman, Borja de Régil, Hengfeng Wei
http://arxiv.org/abs/2106.00344v1
• [cs.DL]Harvesting the Public MeSH Note field
Anastasios Nentidis, Anastasia Krithara, Grigorios Tsoumakas, Georgios Paliouras
http://arxiv.org/abs/2106.00302v1
• [cs.DL]The x-index: A new citation-distance-based index to measure academic influence
Yun Wan, Feng Xiao, Bintong Chen, Lu Li
http://arxiv.org/abs/2105.14759v2
• [cs.DL]WebMIaS on Docker: Deploying Math-Aware Search in a Single Line of Code
Dávid Lupták, Vít Novotný, Michal Štefánik, Petr Sojka
http://arxiv.org/abs/2106.00411v1
• [cs.DS]-norm Flow Diffusion in Near-Linear Time
Li Chen, Richard Peng, Di Wang
http://arxiv.org/abs/2105.14629v1
• [cs.DS]Fault-Tolerant Labeling and Compact Routing Schemes
Michal Dory, Merav Parter
http://arxiv.org/abs/2106.00374v1
• [cs.HC]Automating Visualization Quality Assessment: a Case Study in Higher Education
Nicolas Steven Holliman
http://arxiv.org/abs/2106.00077v1
• [cs.HC]ClustRank: a Visual Quality Measure Trained on Perceptual Data for Sorting Scatterplots by Cluster Patterns
Mostafa Abbas, Ehsan Ullah, Abdelkader Baggag, Halima Bensmail, Michael Sedlmair, Michael Aupetit
http://arxiv.org/abs/2106.00599v1
• [cs.HC]Generating Ten BCI Commands Using Four Simple Motor Imageries
Nuri Korkan, Tamer Olmez, Zumray Dokur
http://arxiv.org/abs/2105.14493v1
• [cs.IR]Controllable Gradient Item Retrieval
Haonan Wang, Chang Zhou, Carl Yang, Hongxia Yang, Jingrui He
http://arxiv.org/abs/2106.00062v1
• [cs.IR]Dual Graph enhanced Embedding Neural Network for CTRPrediction
Wei Guo, Rong Su, Renhao Tan, Huifeng Guo, Yingxue Zhang, Zhirong Liu, Ruiming Tang, Xiuqiang He
http://arxiv.org/abs/2106.00314v1
• [cs.IR]FBAdTracker: An Interactive Data Collection and Analysis Tool for Facebook Advertisements
Ujun Jeong, Kaize Ding, Huan Liu
http://arxiv.org/abs/2106.00142v1
• [cs.IR]The Cold-start Proble
5a45
m: Minimal Users’ Activity Estimation
Juraj Visnovsky, Ondrej Kassak, Michal Kompan, Maria Bielikova
http://arxiv.org/abs/2106.00102v1
• [cs.IT]Distance and Position Estimation in Visible Light Systems with RGB LEDs
Ilker Demirel, Sinan Gezici
http://arxiv.org/abs/2106.00396v1
• [cs.IT]Fast Splitting Algorithms for Sparsity-Constrained and Noisy Group Testing
Eric Price, Jonathan Scarlett, Nelvin Tan
http://arxiv.org/abs/2106.00308v1
• [cs.IT]Low-Complexity Symbol-Level Precoding for MU-MISO Downlink Systems with QAM Signals
Sungyeal Park, Yunseong Cho, Songnam Hong
http://arxiv.org/abs/2106.00433v1
• [cs.IT]New Placement Delivery Array Construction for Coded Caching with Flexible Memory Size
Xianzhang Wu
http://arxiv.org/abs/2106.00480v1
• [cs.IT]Rate-Splitting Multiple Access in Cache-Aided Cloud-Radio Access Networks
Robert-Jeron Reifert, Alaa Alameer Ahmad, Yijie Mao, Aydin Sezgin, Bruno Clerckx
http://arxiv.org/abs/2106.00369v1
• [cs.IT]Reinforce Security: A Model-Free Approach Towards Secure Wiretap Coding
Rick Fritschek, Rafael F. Schaefer, Gerhard Wunder
http://arxiv.org/abs/2106.00343v1
• [cs.IT]Throughput-Outage Scaling Behaviors for Wireless Single-Hop D2D Caching Networks with Physical Model — Analysis and Derivations
Ming-Chun Lee, Andreas F. Molisch, Mingyue Ji
http://arxiv.org/abs/2106.00300v1
• [cs.IT]Topology and Admittance Estimation: Precision Limits and Algorithms
Yuxiao Liu, Ning Zhang, Qingchun Hou, Audun Botterud, Chongqing Kang
http://arxiv.org/abs/2106.00532v1
• [cs.IT]Wireless Federated Learning with Limited Communication and Differential Privacy
Amir Sonee, Stefano Rini, Yu-Chih Huang
http://arxiv.org/abs/2106.00564v1
• [cs.LG]A Compression-Compilation Framework for On-mobile Real-time BERT Applications
Wei Niu, Zhenglun Kong, Geng Yuan, Weiwen Jiang, Jiexiong Guan, Caiwen Ding, Pu Zhao, Sijia Liu, Bin Ren, Yanzhi Wang
http://arxiv.org/abs/2106.00526v1
• [cs.LG]A reinforcement learning approach to improve communication performance and energy utilization in fog-based IoT
Babatunji Omoniwa, Maxime Gueriau, Ivana Dusparic
http://arxiv.org/abs/2106.00654v1
• [cs.LG]A study on the plasticity of neural networks
Tudor Berariu, Wojciech Czarnecki, Soham De, Jorg Bornschein, Samuel Smith, Razvan Pascanu, Claudia Clopath
http://arxiv.org/abs/2106.00042v1
• [cs.LG]A unified PAC-Bayesian framework for machine unlearning via information risk minimization
Sharu Theresa Jose, Osvaldo Simeone
http://arxiv.org/abs/2106.00265v1
• [cs.LG]AAPM DL-Sparse-View CT Challenge Submission Report: Designing an Iterative Network for Fanbeam-CT with Unknown Geometry
Martin Genzel, Jan Macdonald, Maximilian März
http://arxiv.org/abs/2106.00280v1
• [cs.LG]Analysis of classifiers robust to noisy labels
Alex Díaz, Damian Steele
http://arxiv.org/abs/2106.00274v1
• [cs.LG]Asymptotics of representation learning in finite Bayesian neural networks
Jacob A. Zavatone-Veth, Abdulkadir Canatar, Cengiz Pehlevan
http://arxiv.org/abs/2106.00651v1
• [cs.LG]Automated Grading of Anatomical Objective Structured Practical Exams Using Decision Trees
Jason Bernard, Ranil Sonnadara, Anthony N. Saraco, Josh P. Mitchell, Alex B. Bak, Ilana Bayer, Bruce C. Wainman
http://arxiv.org/abs/2106.00502v1
• [cs.LG]CSCAD: Correlation Structure-based Collective Anomaly Detection in Complex System
Huiling Qin, Xianyuan Zhan, Yu Zheng
http://arxiv.org/abs/2105.14476v1
• [cs.LG]Clustering-friendly Representation Learning via Instance Discrimination and Feature Decorrelation
Yaling Tao, Kentaro Takagi, Kouta Nakata
http://arxiv.org/abs/2106.00131v1
• [cs.LG]Combining resampling and reweighting for faithful stochastic optimization
Jing An, Lexing Ying
http://arxiv.org/abs/2105.14694v1
• [cs.LG]Concurrent Adversarial Learning for Large-Batch Training
Yong Liu, Xiangning Chen, Minhao Cheng, Cho-Jui Hsieh, Yang You
http://arxiv.org/abs/2106.00221v1
• [cs.LG]Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests
Victor Veitch, Alexander D’Amour, Steve Yadlowsky, Jacob Eisenstein
http://arxiv.org/abs/2106.00545v1
• [cs.LG]Data-Driven Shadowgraph Simulation of a 3D Object
Anna Willmann, Patrick Stiller, Alexander Debus, Arie Irman, Richard Pausch, Yen-Yu Chang, Michael Bussmann, Nico Hoffmann
http://arxiv.org/abs/2106.00317v1
• [cs.LG]Decision Concept Lattice vs. Decision Trees and Random Forests
Egor Dudyrev, Sergei O. Kuznetsov
http://arxiv.org/abs/2106.00387v1
• [cs.LG]Deep Reinforcement Learning in Quantitative Algorithmic Trading: A Review
Tidor-Vlad Pricope
http://arxiv.org/abs/2106.00123v1
• [cs.LG]Duckworth-Lewis-Stern Method Comparison with Machine Learning Approach
Kumail Abbas, Sajjad Haider
http://arxiv.org/abs/2106.00175v1
• [cs.LG]Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy Constraints
Yuxuan Sun, Sheng Zhou, Zhisheng Niu, Deniz Gündüz
http://arxiv.org/abs/2106.00490v1
• [cs.LG]Effect of large-scale pre-training on full and few-shot transfer learning for natural and medical images
Mehdi Cherti, Jenia Jitsev
http://arxiv.org/abs/2106.00116v1
• [cs.LG]Efficient Explanations With Relevant Sets
Yacine Izza, Alexey Ignatiev, Nina Narodytska, Martin C. Cooper, Joao Marques-Silva
http://arxiv.org/abs/2106.00546v1
• [cs.LG]Enhancing Trajectory Prediction using Sparse Outputs: Application to Team Sports
Brandon Victor, Aiden Nibali, Zhen He, David L. Carey
http://arxiv.org/abs/2106.00173v1
• [cs.LG]Experiments with graph convolutional networks for solving the vertex -center problem
Elisabeth Gaar, Markus Sinnl
http://arxiv.org/abs/2106.00357v1
• [cs.LG]Explanations for Monotonic Classifiers
Joao Marques-Silva, Thomas Gerspacher, Martin Cooper, Alexey Ignatiev, Nina Narodytska
http://arxiv.org/abs/2106.00154v1
• [cs.LG]Exploring Sparse Expert Models and Beyond
An Yang, Junyang Lin, Rui Men, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Jiamang Wang, Yong Li, Di Zhang, Wei Lin, Lin Qu, Jingren Zhou, Hongxia Yang
http://arxiv.org/abs/2105.15082v2
• [cs.LG]Exposing Previously Undetectable Faults in Deep Neural Networks
Isaac Dunn, Hadrien Pouget, Daniel Kroening, Tom Melham
http://arxiv.org/abs/2106.00576v1
• [cs.LG]Fair Clustering Using Antidote Data
Anshuman Chhabra, Adish Singla, Prasant Mohapatra
http://arxiv.org/abs/2106.00600v1
• [cs.LG]Fair Representations by Compression
Xavier Gitiaux, Huzefa Rangwala
http://arxiv.org/abs/2105.14044v1
• [cs.LG]Federated Learning for Industrial Internet of Things in Future Industries
Dinh C. Nguyen, Ming Ding, Pubudu N. Pathirana, Aruna Seneviratne, Jun Li, Dusit Niyato, H. Vincent Poor
http://arxiv.org/abs/2105.14659v1
• [cs.LG]Fine-grained Generalization Analysis of Structured Output Prediction
Waleed Mustafa, Yunwen Lei, Antoine Ledent, Marius Kloft
http://arxiv.org/abs/2106.00115v1
• [cs.LG]GANs Can Play Lottery Tickets Too
Xuxi Chen, Zhenyu Zhang, Yongduo Sui, Tianlong Chen
http://arxiv.org/abs/2106.00134v1
• [cs.LG]Gaussian Processes with Differential Privacy
Antti Honkela
http://arxiv.org/abs/2106.00474v1
• [cs.LG]Generalized AdaGrad (G-AdaGrad) and Adam: A State-Space Perspective
Kushal Chakrabarti, Nikhil Chopra
http://arxiv.org/abs/2106.00092v1
• [cs.LG]Generating Adversarial Examples with Graph Neural Networks
Florian Jaeckle, M. Pawan Kumar
http://arxiv.org/abs/2105.14644v1
• [cs.LG]Gradient Play in Multi-Agent Markov Stochastic Games: Stationary Points and Convergence
Runyu Zhang, Zhaolin Ren, Na Li
http://arxiv.org/abs/org/abs/2106.00198v1
• [cs.LG]H-FL: A Hierarchical Communication-Efficient and Privacy-Protected Architecture for Federated Learning
He Yang
http://arxiv.org/abs/2106.00275v1
• [cs.LG]Hop-Aware Dimension Optimization for Graph Neural Networks
Ailing Zeng, Minhao Liu, Zhiwei Liu, Ruiyuan Gao, Qiang Xu
http://arxiv.org/abs/2105.14490v1
• [cs.LG]How Attentive are Graph Attention Networks?
Shaked Brody, Uri Alon, Eran Yahav
http://arxiv.org/abs/2105.1
2000
4491v1
2000
4491v1)
• [cs.LG]Hybrid Generative Models for Two-Dimensional Datasets
Hoda Shajari, Jaemoon Lee, Sanjay Ranka, Anand Rangarajan
http://arxiv.org/abs/2106.00203v1
• [cs.LG]IID-GAN: an IID Sampling Perspective for Regularizing Mode Collapse
Liangliang Shi, Yang Li, Junchi Yan
http://arxiv.org/abs/2106.00563v1
• [cs.LG]Improving Conditional Coverage via Orthogonal Quantile Regression
Shai Feldman, Stephen Bates, Yaniv Romano
http://arxiv.org/abs/2106.00394v1
• [cs.LG]Improving Long-Term Metrics in Recommendation Systems using Short-Horizon Offline RL
Bogdan Mazoure, Paul Mineiro, Pavithra Srinath, Reza Sharifi Sedeh, Doina Precup, Adith Swaminathan
http://arxiv.org/abs/2106.00589v1
• [cs.LG]Information-Theoretic Analysis of Epistemic Uncertainty in Bayesian Meta-learning
Sharu Theresa Jose, Sangwoo Park, Osvaldo Simeone
http://arxiv.org/abs/2106.00252v1
• [cs.LG]Instance Correction for Learning with Open-set Noisy Labels
Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama
http://arxiv.org/abs/2106.00455v1
• [cs.LG]LRTuner: A Learning Rate Tuner for Deep Neural Networks
Nikhil Iyer, V Thejas, Nipun Kwatra, Ramachandran Ramjee, Muthian Sivathanu
http://arxiv.org/abs/2105.14526v1
• [cs.LG]Learning Football Body-Orientation as a Matter of Classification
Adrià Arbués-Sangüesa, Adrián Martín, Paulino Granero, Coloma Ballester, Gloria Haro
http://arxiv.org/abs/2106.00359v1
• [cs.LG]Learning and Generalization in RNNs
Abhishek Panigrahi, Navin Goyal
http://arxiv.org/abs/2106.00047v1
• [cs.LG]Locally Valid and Discriminative Confidence Intervals for Deep Learning Models
Zhen Lin, Shubhendu Trivedi, Jimeng Sun
http://arxiv.org/abs/2106.00225v1
• [cs.LG]Machine-Learning Non-Conservative Dynamics for New-Physics Detection
Ziming Li, Bohan Wang, Qi Meng, Wei Chen, Max Tegmark, Tie-Yan Liu
http://arxiv.org/abs/2106.00026v1
• [cs.LG]Markpainting: Adversarial Machine Learning meets Inpainting
David Khachaturov, Ilia Shumailov, Yiren Zhao, Nicolas Papernot, Ross Anderson
http://arxiv.org/abs/2106.00660v1
• [cs.LG]Minimax Regret for Bandit Convex Optimisation of Ridge Functions
Tor Lattimore
http://arxiv.org/abs/2106.00444v1
• [cs.LG]More Behind Your Electricity Bill: a Dual-DNN Approach to Non-Intrusive Load Monitoring
Yu Zhang, Guoming Tang, Qianyi Huang, Yi Wang, Hong Xu
http://arxiv.org/abs/2106.00297v1
• [cs.LG]Multi-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs
Harsh Satija, Philip S. Thomas, Joelle Pineau, Romain Laroche
http://arxiv.org/abs/2106.00099v1
• [cs.LG]Node-Variant Graph Filters in Graph Neural Networks
Fernando Gama, Brendon G. Anderson, Somayeh Sojoudi
http://arxiv.org/abs/2106.00089v1
• [cs.LG]NoiLIn: Do Noisy Labels Always Hurt Adversarial Training?
Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Gang Niu, Lizhen Cui, Masashi Sugiyama
http://arxiv.org/abs/2105.14676v1
• [cs.LG]On Fast Sampling of Diffusion Probabilistic Models
Zhifeng Kong, Wei Ping
http://arxiv.org/abs/2106.00132v1
• [cs.LG]OpenBox: A Generalized Black-box Optimization Service
Yang Li, Yu Shen, Wentao Zhang, Yuanwei Chen, Huaijun Jiang, Mingchao Liu, Jiawei Jiang, Jinyang Gao, Wentao Wu, Zhi Yang, Ce Zhang, Bin Cui
http://arxiv.org/abs/2106.00421v1
• [cs.LG]PUDLE: Implicit Acceleration of Dictionary Learning by Backpropagation
Bahareh Tolooshams, Demba Ba
http://arxiv.org/abs/2106.00058v1
• [cs.LG]Parallelized Computation and Backpropagation Under Angle-Parametrized Orthogonal Matrices
Firas Hamze
http://arxiv.org/abs/2106.00003v1
• [cs.LG]Persistent Homology Captures the Generalization of Neural Networks Without A Validation Set
Asier Gutiérrez-Fandiño, David Pérez-Fernández, Jordi Armengol-Estapé, Marta Villegas
http://arxiv.org/abs/2106.00012v1
• [cs.LG]Probabilistic Deep Learning with Probabilistic Neural Networks and Deep Probabilistic Models
Daniel T. Chang
http://arxiv.org/abs/2106.00120v1
• [cs.LG]Procedural Content Generation: Better Benchmarks for Transfer Reinforcement Learning
Matthias Müller-Brockhausen, Mike Preuss, Aske Plaat
http://arxiv.org/abs/2105.14780v1
• [cs.LG]Quantifying Predictive Uncertainty in Medical Image Analysis with Deep Kernel Learning
Zhiliang Wu, Yinchong Yang, Jindong Gu, Volker Tresp
http://arxiv.org/abs/2106.00638v1
• [cs.LG]RFCBF: enhance the performance and stability of Fast Correlation-Based Filter
Xiongshi Deng, Min Li, Lei Wang, Qikang Wan
http://arxiv.org/abs/2105.14519v1
• [cs.LG]Robust discovery of partial differential equations in complex situations
Hao Xu, Dongxiao Zhang
http://arxiv.org/abs/2106.00008v1
• [cs.LG]SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models
Zaccharie Ramzi, Florian Mannel, Shaojie Bai, Jean-Luc Starck, Philippe Ciuciu, Thomas Moreau
http://arxiv.org/abs/2106.00553v1
• [cs.LG]Sample Selection with Uncertainty of Losses for Learning with Noisy Labels
Xiaobo Xia, Tongliang Liu, Bo Han, Mingming Gong, Jun Yu, Gang Niu, Masashi Sugiyama
http://arxiv.org/abs/2106.00445v1
• [cs.LG]Semi-supervised Models are Strong Unsupervised Domain Adaptation Learners
Yabin Zhang, Haojian Zhang, Bin Deng, Shuai Li, Kui Jia, Lei Zhang
http://arxiv.org/abs/2106.00417v1
• [cs.LG]Sequential Domain Adaptation by Synthesizing Distributionally Robust Experts
Bahar Taskesen, Man-Chung Yue, Jose Blanchet, Daniel Kuhn, Viet Anh Nguyen
http://arxiv.org/abs/2106.00322v1
• [cs.LG]Student Performance Prediction Using Dynamic Neural Models
Marina Delianidi, Konstantinos Diamantaras, George Chrysogonidis, Vasileios Nikiforidis
http://arxiv.org/abs/2106.00524v1
• [cs.LG]Surrogate Model Based Hyperparameter Tuning for Deep Learning with SPOT
Thomas Bartz-Beielstein
http://arxiv.org/abs/2105.14625v1
• [cs.LG]Tesseract: Tensorised Actors for Multi-Agent Reinforcement Learning
Anuj Mahajan, Mikayel Samvelyan, Lei Mao, Viktor Makoviychuk, Animesh Garg, Jean Kossaifi, Shimon Whiteson, Yuke Zhu, Animashree Anandkumar
http://arxiv.org/abs/2106.00136v1
• [cs.LG]The Care Label Concept: A Certification Suite for Trustworthy and Resource-Aware Machine Learning
Katharina Morik, Helena Kotthaus, Lukas Heppe, Danny Heinrich, Raphael Fischer, Andreas Pauly, Nico Piatkowski
http://arxiv.org/abs/2106.00512v1
• [cs.LG]The zoo of Fairness metrics in Machine Learning
Alessandro Castelnovo, Riccardo Crupi, Greta Greco, Daniele Regoli
http://arxiv.org/abs/2106.00467v1
• [cs.LG]UNiTE: Unitary N-body Tensor Equivariant Network with Applications to Quantum Chemistry
Zhuoran Qiao, Anders S. Christensen, Frederick R. Manby, Matthew Welborn, Anima Anandkumar, Thomas F. Miller III
http://arxiv.org/abs/2105.14655v1
• [cs.LG]What Matters for Adversarial Imitation Learning?
Manu Orsini, Anton Raichuk, Léonard Hussenot, Damien Vincent, Robert Dadashi, Sertan Girgin, Matthieu Geist, Olivier Bachem, Olivier Pietquin, Marcin Andrychowicz
http://arxiv.org/abs/2106.00672v1
• [cs.MA]Large-scale, Dynamic and Distributed Coalition Formation with Spatial and Temporal Constraints
Luca Capezzuto, Danesh Tarapore, Sarvapali D. Ramchurn
http://arxiv.org/abs/2106.00379v1
• [cs.MA]The Impact of Network Connectivity on Collective Learning
Michael Crosscombe, Jonathan Lawry
http://arxiv.org/abs/2106.00655v1
• [cs.NE]Diffusion Self-Organizing Map on the Hypersphere
M. Andrecut
http://arxiv.org/abs/2106.00014v1
• [cs.NI]Reinforcement Learning-based Dynamic Service Placement in Vehicular Networks
Anum Talpur, Mohan Gurusamy
http://arxiv.org/abs/2105.15022v2
• [cs.RO]3D map creation using crowdsourced GNSS data
Terence Lines, Ana Basiri
http://arxiv.org/abs/2106.00107v1
• [cs.RO]A Road-map to Robot Task Execution with the Functional Object-Oriented Network
David Paulius, Alejandro Agostini, Yu Sun, Dongheui Lee
http://arxiv.org/abs/2106.00158v1
• [cs.RO]Assembly Planning by Recognizing a Graphical Instruction Manual
Issei Sera, Natsuki Yamanobe, Ixchel G. Ramirez-Alpizar, Zhenting Wang, Weiwei Wan, Kensuke Harada
http://arxiv.org/abs/2106.00424v1
• [cs.RO]DeepWalk: Omnidirectional Bipedal Gait by Deep Reinforcement Learning
Diego Rodriguez, Sven Behnke
http://arxiv.org/abs/2106.00534v1
• [cs.RO]DikpolaSat Mission: Improvement of Space Flight Performance and Optimal Control Using Trained Deep Neural Network — Trajectory Controller for Space Objects Collision Avoidance
Manuel Ntumba, Saurabh Gore, Jean Baptiste Awanyo
http://arxiv.org/abs/2106.00007v1
• [cs.RO]Electric field measurements made on a robotic platform
Karen Aplin, Zihao Xiong
http://arxiv.org/abs/2106.00407v1
• [cs.RO]Extended Tactile Perception: Vibration Sensing through Tools and Grasped Objects
Tasbolat Taunyazov, Luar Shui Song, Eugene Lim, Hian Hian See, David Lee, Benjamin C. K. Tee, Harold Soh
http://arxiv.org/abs/2106.00489v1
• [cs.RO]Markov Localisation using Heatmap Regression and Deep Convolutional Odometry
Oscar Mendez, Simon Hadfield, Richard Bowden
http://arxiv.org/abs/2106.00371v1
• [cs.RO]Resource-aware Online Parameter Adaptation for Computationally-constrained Visual-Inertial Navigation Systems
Pranay Mathur, Nikhil Khedekar, Kostas Alexis
http://arxiv.org/abs/2106.00289v1
• [cs.RO]Single-query Path Planning Using Sample-efficient Probability Informed Trees
Daniel Rakita, Bilge Mutlu, Michael Gleicher
http://arxiv.org/abs/2106.00150v1
• [cs.RO]Strobe: An Acceleration Meta-algorithm for Optimizing Robot Paths using Concurrent Interleaved Sub-Epoch Pods
Daniel Rakita, Bilge Mutlu, Michael Gleicher
http://arxiv.org/abs/2106.00153v1
• [cs.RO]What Can I Do Here? Learning New Skills by Imagining Visual Affordances
Alexander Khazatsky, Ashvin Nair, Daniel Jing, Sergey Levine
http://arxiv.org/abs/2106.00671v1
• [cs.SD]Adversarial Defense for Automatic Speaker Verification by Self-Supervised Learning
Haibin Wu, Xu Li, Andy T. Liu, Zhiyong Wu, Helen Meng, Hung-yi Lee
http://arxiv.org/abs/2106.00273v1
• [cs.SD]Omnizart: A General Toolbox for Automatic Music Transcription
Yu-Te Wu, Yin-Jyun Luo, Tsung-Ping Chen, I-Chieh Wei, Jui-Yang Hsu, Yi-Chin Chuang, Li Su
http://arxiv.org/abs/2106.00497v1
• [cs.SD]Towards Explainable Convolutional Features for Music Audio Modeling
Anna K. Yanchenko, Mohammadreza Soltani, Robert J. Ravier, Sayan Mukherjee, Vahid Tarokh
http://arxiv.org/abs/2106.00110v1
• [cs.SI]CoRank: A clustering cum graph ranking approach for extractive summarization
Mohd Khizir Siddiqui, Amreen Ahmad, Om Pal, Tanvir Ahmad
http://arxiv.org/abs/2106.00619v1
• [cs.SI]Construction of Simplicial Complexes with Prescribed Degree-Size Sequences
Tzu-Chi Yen
http://arxiv.org/abs/2106.00185v1
• [cs.SI]Optimizing travel routes using temporal networks constructed from GPS data
Tatsuro Mukai, Yuichi Ikeda
http://arxiv.org/abs/2106.00328v1
• [cs.SI]Parlermonium: A Data-Driven UX Design Evaluation of the Parler Platform
Emma Pieroni, Peter Jachim, Nathaniel Jachim, Filipo Sharevski
http://arxiv.org/abs/2106.00163v1
• [econ.EM]Specification tests for GARCH processes
Giuseppe Cavaliere, Indeewara Perera, Anders Rahbek
http://arxiv.org/abs/2105.14081v1
• [eess.AS]Low-Resource Spoken Language Identification Using Self-Attentive Pooling and Deep 1D Time-Channel Separable Convolutions
Roman Bedyakin, Nikolay Mikhaylovskiy
http://arxiv.org/abs/2106.00052v1
• [eess.AS]StarGAN-ZSVC: Towards Zero-Shot Voice Conversion in Low-Resource Contexts
Matthew Baas, Herman Kamper
http://arxiv.org/abs/2106.00043v1
• [eess.IV]3D WaveUNet: 3D Wavelet Integrated Encoder-Decoder Network for Neuron Segmentation
Qiufu Li, Linlin Shen
http://arxiv.org/abs/2106.00259v1
• [eess.IV]COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network
Tawsifur Rahman, Alex Akinbi, Muhammad E. H. Chowdhury, Tarik A. Rashid, Abdulkadir Şengür, Amith Khandakar, Khandaker Reajul Islam, Aras M. Ismael
http://arxiv.org/abs/2106.00436v1
• [eess.IV]Decoupling Shape and Density for Liver Lesion Synthesis Using Conditional Generative Adversarial Networks
Dario Augusto Borges Oliveira
http://arxiv.org/abs/2106.00629v1
• [eess.IV]Hybrid Deep Neural Network for Brachial Plexus Nerve Segmentation in Ultrasound Images
Juul P. A. van Boxtel, Vincent R. J. Vousten, Josien Pluim, Nastaran Mohammadian Rad
http://arxiv.org/abs/2106.00373v1
• [eess.IV]Hyperspectral Band Selection for Multispectral Image Classification with Convolutional Networks
Giorgio Morales, John Sheppard, Riley Logan, Joseph Shaw
http://arxiv.org/abs/2106.00645v1
• [eess.IV]RAI-Net: Range-Adaptive LiDAR Point Cloud Frame Interpolation Network
Lili Zhao, Zezhi Zhu, Xuhu Lin, Xuezhou Guo, Qian Yin, Wenyi Wang, Jianwen Chen
http://arxiv.org/abs/2106.00496v1
• [eess.IV]Two-stage domain adapted training for better generalization in real-world image restoration and super-resolution
Cansu Korkmaz, A. Murat Tekalp, Zafer Dogan
http://arxiv.org/abs/2106.00504v1
• [eess.SP]A Compact and Interpretable Convolutional Neural Network for Cross-Subject Driver Drowsiness Detection from Single-Channel EEG
Jian Cui, Zirui Lan, Yisi Liu, Ruilin Li, Fan Li, Olga Sourina, Wolfgang Mueller-Wittig
http://arxiv.org/abs/2106.00613v1
• [eess.SP]Dynamic-Deep: ECG Task-Aware Compression
Eli Brosh, Elad Wasserstein, Anat Bremler-Barr
http://arxiv.org/abs/2106.00606v1
• [eess.SP]Meta-HAR: Federated Representation Learning for Human Activity Recognition
Chenglin Li, Di Niu, Bei Jiang, Xiao Zuo, Jianming Yang
http://arxiv.org/abs/2106.00615v1
• [eess.SP]Weak target detection with multi-bit quantization in colocated MIMO radar
Hang Xiao, Shixing Yang, Wei Yi
http://arxiv.org/abs/2106.00612v1
• [eess.SY]A Question of Time: Revisiting the Use of Recursive Filtering for Temporal Calibration of Multisensor Systems
Jonathan Kelly, Christopher Grebe, Matthew Giamou
http://arxiv.org/abs/2106.00391v1
• [hep-ph]A survey of machine learning-based physics event generation
Yasir Alanazi, N. Sato, Pawel Ambrozewicz, Astrid N. Hiller Blin, W. Melnitchouk, Marco Battaglieri, Tianbo Liu, Yaohang Li
http://arxiv.org/abs/2106.00643v1
• [math.AG]Tensor decomposition for learning Gaussian mixtures from moments
Rima Khouja, Pierre-Alexandre Mattei, Be
57be
rnard Mourrain
http://arxiv.org/abs/2106.00555v1
• [math.CO]The Sample Fréchet Mean of Sparse Graphs is Sparse
Daniel Ferguson, Francois G. Meyer
http://arxiv.org/abs/2105.14397v2
• [math.FA]Anti-Koopmanism
Efrain Gonzalez, Moad Abudia, Michael Jury, Rushikesh Kamalapurkar, Joel A. Rosenfeld
http://arxiv.org/abs/2106.00106v1
• [math.NA]Recovering wavelet coefficients from binary samples using fast transforms
Vegard Antun
http://arxiv.org/abs/2106.00554v1
• [math.OC]A Non-commutative Extension of Lee-Seung’s Algorithm for Positive Semidefinite Factorizations
Yong Sheng Soh, Antonios Varvitsiotis
http://arxiv.org/abs/2106.00293v1
• [math.OC]Control Occupation Kernel Regression for Nonlinear Control-Affine Systems
Moad Abudia, Tejasvi Channagiri, Joel A. Rosenfeld, Rushikesh Kamalapurkar
http://arxiv.org/abs/2106.00103v1
• [math.OC]On Riemannian Optimization over Positive Definite Matrices with the Bures-Wasserstein Geometry
Andi Han, Bamdev Mishra, Pratik Jawanpuria, Junbin Gao
http://arxiv.org/abs/2106.00286v1
• [math.OC]Optimal transport with -divergence regularization and generalized Sinkhorn algorithm
Dávid Terjék, Diego González-Sánchez
http://arxiv.org/abs/2105.14337v1
• [math.PR]Entropy and the Discrete Central Limit Theorem
Lampros Gavalakis, Ioannis Kontoyiannis
http://arxiv.org/abs/2106.00514v1
• [math.ST]Bayes-optimal prediction with frequentist coverage control
Peter Hoff
http://arxiv.org/abs/2105.14045v1
• [math.ST]Distribution-free inference for regression: discrete, continuous, and in between
Yonghoon Lee, Rina Foygel Barber
http://arxiv.org/abs/2105.14075v1
• [math.ST]Halfspace depth for general measures: The ray basis theorem and its consequences
Petra Laketa, Stanislav Nagy
http://arxiv.org/abs/2106.00616v1
• [math.ST]Median bias of M-estimators
Arun Kumar Kuchibhotla
http://arxiv.org/abs/2106.00164v1
• [math.ST]On some properties of the bimodal normal distribution and its bivariate version
Roberto Vila, Helton Saulo, Jamer Roldan
http://arxiv.org/abs/2106.00097v1
• [math.ST]Stacked Grenander estimator of a discrete distribution
Vladimir Pastukhov
http://arxiv.org/abs/2106.00560v1
• [math.ST]Statistical tests based on Rényi entropy estimation
Mehmet Siddik Cadirci, Dafydd Evans, Nikolai Leonenko, Oleg Seleznjev
http://arxiv.org/abs/2106.00453v1
• [math.ST]The query complexity of sampling from strongly log-concave distributions in one dimension
Sinho Chewi, Patrik Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
http://arxiv.org/abs/2105.14163v1
• [physics.comp-ph]Deep-Learning Discovers Macroscopic Governing Equations for Viscous Gravity Currents from Microscopic Simulation Data
Junsheng Zeng, Hao Xu, Yuntian Chen, Dongxiao Zhang
http://arxiv.org/abs/2106.00009v1
• [physics.comp-ph]Empirical Models for Multidimensional Regression of Fission Systems
Akshay J. Dave, Jiankai Yu, Jarod Wilson, Bren Phillips, Kaichao Sun, Benoit Forget
http://arxiv.org/abs/2105.14645v1
• [physics.plasm-ph]Invertible Surrogate Models: Joint surrogate modelling and reconstruction of Laser-Wakefield Acceleration by invertible neural networks
Friedrich Bethke, Richard Pausch, Patrick Stiller, Alexander Debus, Michael Bussmann, Nico Hoffmann
http://arxiv.org/abs/2106.00432v1
• [q-bio.QM]Detection of preventable fetal distress during labor from scanned cardiotocogram tracings using deep learning
Martin G. Frasch, Shadrian B. Strong, David Nilosek, Joshua Leaverton, Barry S. Schifrin
http://arxiv.org/abs/2106.00628v1
• [q-fin.ST]Mapping the NFT revolution: market trends, trade networks and visual features
Matthieu Nadini, Laura Alessandretti, Flavio Di Giacinto, Mauro Martino, Luca Maria Aiello, Andrea Baronchelli
http://arxiv.org/abs/2106.00647v1
• [quant-ph]Quantum Federated Learning with Quantum Data
Mahdi Chehimi, Walid Saad
http://arxiv.org/abs/2106.00005v1
• [stat.AP]A mixed-frequency approach for exchange rates predictions
Raffaele Mattera, Michelangelo Misuraca, Germana Scepi, Maria Spano
http://arxiv.org/abs/2106.00283v1
• [stat.AP]A non-separable first-order spatio-temporal intensity for events on linear networks: an application to ambulance interventions
Andrea Gilardi, Riccardo Borgoni, Jorge Mateu
http://arxiv.org/abs/2106.00457v1
• [stat.AP]An introduction to network analysis for studies of medication use
Mohsen Askar, Raphael Nozal Cañadas, Kristian Svendsen
http://arxiv.org/abs/2106.00413v1
• [stat.AP]Efficient adaptive MCMC implementation for Pseudo-Bayesian quantum tomography
The Tien Mai
http://arxiv.org/abs/2106.00577v1
• [stat.AP]Predicting COVID-19 Spread from Large-Scale Mobility Data
Amray Schwabe, Joel Persson, Stefan Feuerriegel
http://arxiv.org/abs/2106.00356v1
• [stat.AP]Simulating flood event sets using extremal principal components
Christian Rohrbeck, Daniel Cooley
http://arxiv.org/abs/2106.00630v1
• [stat.ME]Adaptive Conformal Inference Under Distribution Shift
Isaac Gibbs, Emmanuel Candès
http://arxiv.org/abs/2106.00170v1
• [stat.ME]Federated Estimation of Causal Effects from Observational Data
Thanh Vinh Vo, Trong Nghia Hoang, Young Lee, Tze-Yun Leong
http://arxiv.org/abs/2106.00456v1
• [stat.ME]Logistic Regression Through the Veil of Imprecise Data
Nicholas Gray, Scott Ferson
http://arxiv.org/abs/2106.00492v1
• [stat.ML]Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data
Shixiang Zhu, Alexander Bukharin, Liyan Xie, Shihao Yang, Pinar Keskinocak, Yao Xie
http://arxiv.org/abs/2106.00072v1
• [stat.ML]MARL with General Utilities via Decentralized Shadow Reward Actor-Critic
Junyu Zhang, Amrit Singh Bedi, Mengdi Wang, Alec Koppel
http://arxiv.org/abs/2106.00543v1
• [stat.ML]Post-Contextual-Bandit Inference
Aurélien Bibaut, Antoine Chambaz, Maria Dimakopoulou, Nathan Kallus, Mark van der Laan
http://arxiv.org/abs/2106.00418v1
• [stat.ML]Transformation Models for Flexible Posteriors in Variational Bayes
Sefan Hörtling, Daniel Dold, Oliver Dürr, Beate Sick
http://arxiv.org/abs/2106.00528v1
• [stat.ML]Variational Autoencoders: A Harmonic Perspective
Alexander Camuto, Matthew Willetts
http://arxiv.org/abs/2105.14866v2
• [stat.ML]Variational Combinatorial Sequential Monte Carlo Methods for Bayesian Phylogenetic Inference
Antonio Khalil Moretti, Liyi Zhang, Christian A. Naesseth, Hadiah Venner, David Blei, Itsik Pe’er
http://arxiv.org/abs/2106.00075v1
• [stat.ML]What’s a good imputation to predict with missing values?
Marine Le Morvan, Julie Josse, Erwan Scornet, Gaël Varoquaux
http://arxiv.org/abs/2106.00311v1
• [stat.OT]Review of Low-Voltage Load Forecasting: Methods, Applications, and Recommendations
Stephen Haben, Siddharth Arora, Georgios Giasemidis, Marcus Voss, Danica Vukadinovic Greetham
http://arxiv.org/abs/2106.00006v1
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