cond-mat.mtrl-sci - 材料科学
cond-mat.stat-mech - 统计数学
cs.AI - 人工智能
cs.CL - 计算与语言
cs.CV - 机器视觉与模式识别
cs.DB - 数据库
cs.DC - 分布式、并行与集群计算
cs.DL - 数字图书馆
cs.DS - 数据结构与算法
cs.GT - 计算机科学与博弈论
cs.IR - 信息检索
cs.IT - 信息论
cs.LG - 自动学习
cs.NE - 神经与进化计算
cs.RO - 机器人学
cs.SD - 声音处理
cs.SE - 软件工程
cs.SI - 社交网络与信息网络
econ.EM - 计量经济学
eess.AS - 语音处理
eess.IV - 图像与视频处理
hep-ex - 高能物理实验
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.chem-ph -化学物理
physics.data-an - 数据分析、 统计和概率
q-bio.NC - 神经元与认知
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
• [cond-mat.mtrl-sci]BIGDML: Towards Exact Machine Learning Force Fields for Materials
• [cond-mat.stat-mech]Nonequilibrium Thermodynamics in Measuring Carbon Footprints: Disentangling Structure and Artifact in Input-Output Accounting
• [cs.AI]Coarse-to-Fine Curriculum Learning
• [cs.AI]Definitions of intent suitable for algorithms
• [cs.AI]Differentiable Quality Diversity
• [cs.AI]Exploration and preference satisfaction trade-off in reward-free learning
• [cs.AI]Giving Commands to a Self-Driving Car: How to Deal with Uncertain Situations?
• [cs.AI]Learning to Guide a Saturation-Based Theorem Prover
• [cs.AI]Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
• [cs.AI]North Carolina COVID-19 Agent-Based Model Framework for Hospitalization Forecasting Overview, Design Concepts, and Details Protocol
• [cs.AI]Reconciling Rewards with Predictive State Representations
• [cs.AI]Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
• [cs.AI]Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
• [cs.CL]A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing
• [cs.CL]A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021
• [cs.CL]A Unified Generative Framework for Aspect-Based Sentiment Analysis
• [cs.CL]Adversarial Training for Machine Reading Comprehension with Virtual Embeddings
• [cs.CL]Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection
• [cs.CL]Attention Temperature Matters in Abstractive Summarization Distillation
• [cs.CL]CAiRE in DialDoc21: Data Augmentation for Information-Seeking Dialogue System
• [cs.CL]CLTR: An End-to-End, Transformer-Based System for Cell Level TableRetrieval and Table Question Answering
• [cs.CL]Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading
• [cs.CL]Cyberbullying Detection Using Deep Neural Network from Social Media Comments in Bangla Language
• [cs.CL]Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
• [cs.CL]Exploiting Language Relatedness for Low Web-Resource Language Model Adaptation: An Indic Languages Study
• [cs.CL]Expressivity of Emergent Language is a Trade-off between Contextual Complexity and Unpredictability
• [cs.CL]Generating Hypothetical Events for Abductive Inference
• [cs.CL]Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures
• [cs.CL]Insight from NLP Analysis: COVID-19 Vaccines Sentiments on Social Media
• [cs.CL]Interpretable agent communication from scratch(with a generic visual processor emerging on the side)
• [cs.CL]Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making
• [cs.CL]Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference
• [cs.CL]Itihasa: A large-scale corpus for Sanskrit to English translation
• [cs.CL]Learning compositional structures for semantic graph parsing
• [cs.CL]Lexicon Learning for Few-Shot Neural Sequence Modeling
• [cs.CL]Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions
• [cs.CL]Measuring and Improving BERT’s Mathematical Abilities by Predicting the Order of Reasoning
• [cs.CL]Meta-Learning to Compositionally Generalize
• [cs.CL]Neural Abstractive Unsupervised Summarization of Online News Discussions
• [cs.CL]Obtaining Better Static Word Embeddings Using Contextual Embedding Models
• [cs.CL]One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets
• [cs.CL]Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks
• [cs.CL]Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction
• [cs.CL]Predicting Different Types of Subtle Toxicity in Unhealthy Online Conversations
• [cs.CL]Question Generation for Adaptive Education
• [cs.CL]Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation
• [cs.CL]Realistic Evaluation Principles for Cross-document Coreference Resolution
• [cs.CL]RewardsOfSum: Exploring Reinforcement Learning Rewards for Summarisation
• [cs.CL]SIGTYP 2021 Shared Task: Robust Spoken Language Identification
• [cs.CL]Self-supervised and Supervised Joint Training for Resource-rich Machine Translation
• [cs.CL]Structured Reordering for Modeling Latent Alignments in Sequence Transduction
• [cs.CL]Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality
• [cs.CL]TIMEDIAL: Temporal Commonsense Reasoning in Dialog
• [cs.CL]Translate, then Parse! A strong baseline for Cross-Lingual AMR Parsing
• [cs.CL]Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface
• [cs.CL]Ultra-Fine Entity Typing with Weak Supervision from a Masked Language Model
• [cs.CL]Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings
• [cs.CL]XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation
• [cs.CV]A Synchronized Reprojection-based Model for 3D Human Pose Estimation
• [cs.CV]Adversarial Semantic Hallucination for Domain Generalized Semantic Segmentation
• [cs.CV]Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation
• [cs.CV]An Intelligent Hybrid Model for Identity Document Classification
• [cs.CV]Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions
• [cs.CV]CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation
• [cs.CV]Chasing Sparsity in Vision Transformers:An End-to-End Exploration
• [cs.CV]Contrastive Representation Learning for Hand Shape Estimation
• [cs.CV]Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback
• [cs.CV]Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation
• [cs.CV]DETReg: Unsupervised Pretraining with Region Priors for Object Detection
• [cs.CV]Data-Efficient Instance Generation from Instance Discrimination
• [cs.CV]Demystifying Local Vision Transformer: Sparse Connectivity, Weight Sharing, and Dynamic Weight
• [cs.CV]Design of Low-Artifact Interpolation Kernels by Means of Computer Algebra
• [cs.CV]Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding
• [cs.CV]Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer
• [cs.CV]DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Rendering
• [cs.CV]Efficient training for future video generation based on hierarchical disentangled representation of latent variables
• [cs.CV]Few-Shot Action Localization without Knowing Boundaries
• [cs.CV]Fully Transformer Networks for Semantic Image Segmentation
• [cs.CV]Grapevine Winter Pruning Automation: On Potential Pruning Points Detection through 2D Plant Modeling using Grapevine Segmentation
• [cs.CV]HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation
• [cs.CV]Harnessing Unrecognizable Faces for Face Recognition
• [cs.CV]Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation
• [cs.CV]Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess
• [cs.CV]How to Design a Three-Stage Architecture for Audio-Visual Active Speaker Detection in the Wild
• [cs.CV]Image Deformation Estimation via Multi-Objective Optimization
• [cs.CV]Image2Point: 3D Point-Cloud Understanding with Pretrained 2D ConvNets
• [cs.CV]Interpreting Deep Learning based Cerebral Palsy Prediction with Channel Attention
• [cs.CV]Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation
• [cs.CV]Left Ventricle Contouring in Cardiac Images Based on Deep Reinforcement Learning
• [cs.CV]LipSync3D: Data-Efficient Learning of Personalized 3D Talking Faces from Video using Pose and Lighting Normalization
• [cs.CV]LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation
• [cs.CV]Low-Rank Subspaces in GANs
• [cs.CV]MViT: Mask Vision Transformer for Facial Expression Recognition in the wild
• [cs.CV]MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras
• [cs.CV]Multi-dataset Pretraining: A Unified Model for Semantic Segmentation
• [cs.CV]Multi-frame sequence generator of 4D human body motion
• [cs.CV]Multi-task Transformation Learning for Robust Out-of-Distribution Detection
• [cs.CV]Novel View Video Prediction Using a Dual Representation
• [cs.CV]On Improving Adversarial Transferability of Vision Transformers
• [cs.CV]On the relation between statistical learning and perceptual distances
• [cs.CV]On the role of feedback in visual processing: a predictive coding perspective
• [cs.CV]On the use of automatically generated synthetic image datasets for benchmarking face recognition
• [cs.CV]Person Re-Identification with a Locally Aware Transformer
• [cs.CV]Progressive Multi-scale Fusion Network for RGB-D Salient Object Detection
• [cs.CV]Progressive Spatio-Temporal Bilinear Network with Monte Carlo Dropout for Landmark-based Facial Expression Recognition with Uncertainty Estimation
• [cs.CV]RobustNav: Towards Benchmarking Robustness in Embodied Navigation
• [cs.CV]SDGMNet: Statistic-based Dynamic Gradient Modulation for Local Descriptor Learning
• [cs.CV]Salvage of Supervision in Weakly Supervised Detection
• [cs.CV]Scaling Vision Transformers
• [cs.CV]Segmentation and ABCD rule extraction for skin tumors classification
• [cs.CV]Self-Supervised Structure-from-Motion through Tightly-Coupled Depth and Egomotion Networks
• [cs.CV]Semantically Controllable Scene Generation with Guidance of Explicit Knowledge
• [cs.CV]Simulated Adversarial Testing of Face Recognition Models
• [cs.CV]SpaceMeshLab: Spatial Context Memoization and Meshgrid Atrous Convolution Consensus for Semantic Segmentation
• [cs.CV]Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks
• [cs.CV]SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation
• [cs.CV]Task-Generic Hierarchical Human Motion Prior using VAEs
• [cs.CV]Variational AutoEncoder for Reference based Image Super-Resolution
• [cs.CV]Weakly Supervised Volumetric Image Segmentation with Deformed Templates
• [cs.CV]White Paper Assistance: A Step Forward Beyond the Shortcut Learning
• [cs.DB]A highly scalable repository of waveform and vital signs data from bedside monitoring devices
• [cs.DC]Assessing Open Interfaces and Protocols of PLCs for Computation Offloading at Field Level
• [cs.DC]Asynchronous Distributed Optimization with Redundancy in Cost Functions
• [cs.DC]CloudChain: A Cloud Blockchain Using Shared Memory Consensus and RDMA
• [cs.DC]GearV: A Two-Gear Hypervisor for Mixed-Criticality IoT Systems
• [cs.DC]Launchpad: A Programming Model for Distributed Machine Learning Research
• [cs.DC]Near-Optimal Dispersion on Arbitrary Anonymous Graphs
• [cs.DC]PAIO: A Software-Defined Storage Data Plane Framework
• [cs.DL]ConSTR: A Contextual Search Term Recommender
• [cs.DS]Low-Congestion Shortcuts in Constant Diameter Graphs
• [cs.DS]Sketch-Based Streaming Anomaly Detection in Dynamic Graphs
• [cs.GT]Improving Social Welfare While Preserving Autonomy via a Pareto Mediator
• [cs.IR]Defining definition: a Text mining Approach to Define Innovative Technological Fields
• [cs.IR]Exploring Periodicity and Interactivity in Multi-Interest Framework for Sequential Recommendation
• [cs.IR]HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation
• [cs.IR]MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
• [cs.IR]Optimization of Service Addition in Multilevel Index Model for Edge Computing
• [cs.IR]Review Polarity-wise Recommender
• [cs.IT]A Perspective on Time towards Wireless 6G
• [cs.IT]A Sequence Selection Bound for the Capacity of the Nonlinear Fiber Channel
• [cs.IT]Contention-based Grant-free Transmission with Extremely Sparse Orthogonal Pilot Scheme
• [cs.IT]Dilated Convolution based CSI Feedback Compression for Massive MIMO Systems
• [cs.IT]Low-complexity Voronoi shaping for the Gaussian channel
• [cs.IT]Modeling Uplink Coverage Performance in Hybrid Satellite-Terrestrial Networks
• [cs.IT]On the Linear Capacity of Conditional Disclosure of Secrets
• [cs.IT]On the Outage Capacity of the Massive MIMO Diversity Channel
• [cs.IT]Optimized Rate-Profiling for PAC Codes
• [cs.IT]Optimizing a Binary Intelligent Reflecting Surface for OFDM Communications under Mutual Coupling
• [cs.IT]Outage Performance of Multi-UAV Relaying-based Imperfect Hardware Hybrid Satellite-Terrestrial Networks
• [cs.IT]Principal Bit Analysis: Autoencoding with Schur-Concave Loss
• [cs.IT]Private Multi-Group Aggregation
• [cs.IT]Proof methods for robust low-rank matrix recovery
• [cs.LG]A Deep Value-network Based Approach for Multi-Driver Order Dispatching
• [cs.LG]A Survey of Transformers
• [cs.LG]A critical look at the current train/test split in machine learning
• [cs.LG]A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs
• [cs.LG]Adaptive Machine Unlearning
• [cs.LG]Amortized Generation of Sequential Counterfactual Explanations for Black-box Models
• [cs.LG]Automatic Generation of Machine Learning Synthetic Data Using ROS
• [cs.LG]Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
• [cs.LG]Breaking the Limits of Message Passing Graph Neural Networks
• [cs.LG]Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
• [cs.LG]Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models
• [cs.LG]Closed-Form Analytical Results for Maximum Entropy Reinforcement Learning
• [cs.LG]Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions
• [cs.LG]Coresets for Classification — Simplified and Strengthened
• [cs.LG]Correcting Momentum in Temporal Difference Learning
• [cs.LG]Deep Learning Statistical Arbitrage
• [cs.LG]Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation
• [cs.LG]Detecting Anomalous Event Sequences with Temporal Point Processes
• [cs.LG]Differentiable Multiple Shooting Layers
• [cs.LG]Dynamic Sparse Training for Deep Reinforcement Learning
• [cs.LG]Efficient Online Learning for Dynamic k-Clustering
• [cs.LG]Enhancing Robustness of Neural Networks through Fourier Stabilization
• [cs.LG]Evaluating Meta-Feature Selection for the Algorithm Recommendation Problem
• [cs.LG]FEAR: A Simple Lightweight Method to Rank Architectures
• [cs.LG]Fast Federated Learning in the Presence of Arbitrary Device Unavailability
• [cs.LG]Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
• [cs.LG]Fine-grained Out-of-Distribution Detection with Mixup Outlier Exposure
• [cs.LG]Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
• [cs.LG]Generative Flows with Invertible Attentions
• [cs.LG]Graph-MLP: Node Classification without Message Passing in Graph
• [cs.LG]Hash Layers For Large Sparse Models
• [cs.LG]Householder-Absolute Neural Layers For High Variability and Deep Trainability
• [cs.LG]Hybrid Method Based on NARX models and Machine Learning for Pattern Recognition
• [cs.LG]Incentive Mechanism for Privacy-Preserving Federated Learning
• [cs.LG]Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics
• [cs.LG]Interactive Label Cleaning with Example-based Explanations
• [cs.LG]LEADS: Learning Dynamical Systems that Generalize Across Environments
• [cs.LG]LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification
• [cs.LG]Learning Markov State Abstractions for Deep Reinforcement Learning
• [cs.LG]Learning from Multiple Noisy Partial Labelers
• [cs.LG]Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
• [cs.LG]Manifold Topology Divergence: a Framework for Comparing Data Manifolds
• [cs.LG]Meta Learning for Knowledge Distillation
• [cs.LG]Muddling Label Regularization: Deep Learning for Tabular Datasets
• [cs.LG]Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems
• [cs.LG]Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions
• [cs.LG]Nonsmooth Implicit Differentiation for Machine Learning and Optimization
• [cs.LG]Offline Policy Comparison under Limited Historical Agent-Environment Interactions
• [cs.LG]Parameter Inference with Bifurcation Diagrams
• [cs.LG]PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning
• [cs.LG]Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss
• [cs.LG]Provably Robust Detection of Out-of-distribution Data (almost) for free
• [cs.LG]RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting
• [cs.LG]Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization
• [cs.LG]Rethinking Graph Transformers with Spectral Attention
• [cs.LG]Robust Generalization despite Distribution Shift via Minimum Discriminating Information
• [cs.LG]Self-supervised Graph-level Representation Learning with Local and Global Structure
• [cs.LG]Stability and Generalization of Bilevel Programming in Hyperparameter Optimization
• [cs.LG]Staircase Attention for Recurrent Processing of Sequences
• [cs.LG]Supervised Machine Learning with Plausible Deniability
• [cs.LG]The Fast Kernel Transform
• [cs.LG]The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation
• [cs.LG]The Randomness of Input Data Spaces is an A Priori Predictor for Generalization
• [cs.LG]The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition
• [cs.LG]There Is No Turning Back: A Self-Supervised Approach for Reversibility-Aware Reinforcement Learning
• [cs.LG]Time-series Imputation of Temporally-occluded Multiagent Trajectories
• [cs.LG]Towards Practical Credit Assignment for Deep Reinforcement Learning
• [cs.LG]Towards a Theoretical Framework of Out-of-Distribution Generalization
• [cs.LG]Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning
• [cs.LG]Understanding (Generalized) Label Smoothing whenLearning with Noisy Labels
• [cs.LG]What Data Augmentation Do We Need for Deep-Learning-Based Finance?
• [cs.LG]What Makes Multimodal Learning Better than Single (Provably)
• [cs.LG]What training reveals about neural network complexity
• [cs.LG]When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
• [cs.NE]GSGP-CUDA — a CUDA framework for Geometric Semantic Genetic Programming
• [cs.NE]JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design
• [cs.RO]A novel partially-decoupled translational parallel manipulator with symbolic kinematics, singularity identification and workspace determination
• [cs.RO]Acoustic Power for Swarms of Microscopic Robots
• [cs.RO]Efficient Sampling in POMDPs with Lipschitz Bandits for Motion Planning in Continuous Spaces
• [cs.RO]Game-Theoretic Model Predictive Control with Data-Driven Identification of Vehicle Model for Head-to-Head Autonomous Racing
• [cs.RO]H-ModQuad: Modular Multi-Rotors with 4, 5, and 6 Controllable DOF
• [cs.RO]Learning Riemannian Manifolds for Geodesic Motion Skills
• [cs.RO]Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense Clutter
• [cs.RO]Model Predictive Robot-Environment Interaction Control for Mobile Manipulation Tasks
• [cs.RO]Planning Multimodal Exploratory Actions for Online Robot Attribute Learning
• [cs.RO]Property-Aware Robot Object Manipulation: a Generative Approach
• [cs.RO]Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty
• [cs.RO]Risk Ranked Recall: Collision Safety Metric for Object Detection Systems in Autonomous Vehicles
• [cs.RO]Safe Deep Q-Network for Autonomous Vehicles at Unsignalized Intersection
• [cs.RO]XIRL: Cross-embodiment Inverse Reinforcement Learning
• [cs.SD]Broadcasted Residual Learning for Efficient Keyword Spotting
• [cs.SD]Efficient Speech Emotion Recognition Using Multi-Scale CNN and Attention
• [cs.SD]NWT: Towards natural audio-to-video generation with representation learning
• [cs.SD]PILOT: Introducing Transformers for Probabilistic Sound Event Localization
• [cs.SD]Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition
• [cs.SE]How to Bake Quantum into Your Pet Petri Nets and Have Your Net Theory Too
• [cs.SI]Designing Toxic Content Classification for a Diversity of Perspectives
• [cs.SI]News consumption and social media regulations policy
• [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
• [econ.EM]Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment
• [eess.AS]Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions
• [eess.IV]AutoPtosis
• [eess.IV]EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation
• [eess.IV]Generative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scans
• [eess.IV]PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment
• [hep-ex]SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention
• [math.OC]Efficient solution method based on inverse dynamics for optimal control problems of rigid body systems
• [math.OC]Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks
• [math.OC]Optimized Data Rate Allocation for Dynamic Sensor Fusion over Resource Constrained Communication Networks
• [math.OC]Unbalanced Optimal Transport through Non-negative Penalized Linear Regression
• [math.OC]Using a New Nonlinear Gradient Method for Solving Large Scale Convex Optimization Problems with an Application on Arabic Medical Text
• [math.PR]Markov Chains Generated by Convolutions of Orthogonality Measures
• [math.PR]Maximum likelihood estimation for sub-fractional Vasicek model
• [math.ST]Bridge Simulation and Metric Estimation on Lie Groups
• [math.ST]Minimax and adaptive tests for detecting abrupt and possibly transitory changes in a Poisson process
• [math.ST]Process of the slope components of -regression quantile
• [physics.chem-ph]Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations
• [physics.data-an]Granger causality in the frequency domain: derivation and applications
• [q-bio.NC]Credit Assignment Through Broadcasting a Global Error Vector
• [q-bio.NC]Object Based Attention Through Internal Gating
• [quant-ph]Encoding-dependent generalization bounds for parametrized quantum circuits
• [quant-ph]NISQ Algorithm for Semidefinite Programming
• [stat.AP]Scalar on time-by-distribution regression and its application for modelling associations between daily-living physical activity and cognitive functions in Alzheimer’s Disease
• [stat.AP]Sensitivity analysis for random measurement error using regression calibration and simulation-extrapolation
• [stat.ME]A Unified Approach to Robust Inference for Genetic Covariance
• [stat.ME]A likelihood based sensitivity analysis for publication bias on summary ROC in meta-analysis of diagnostic test accuracy
• [stat.ME]Clustering with missing data: which imputation model for which cluster analysis method?
• [stat.ME]Context-Specific Causal Discovery for Categorical Data Using Staged Trees
• [stat.ME]Do forecasts of bankruptcy cause bankruptcy? A machine learning sensitivity analysis
• [stat.ME]Efficient Estimation For The Joint Model of Survival and Longitudinal Data
• [stat.ME]Inference for Network Regression Models with Community Structure
• [stat.ME]Methodological considerations for estimating policy effects in the context of co-occurring policies
• [stat.ME]Searching for consistent associations with a multi-environment knockoff filter
• [stat.ME]Singhing with Confidence: Visualising the Performance of Confidence Structures
• [stat.ML]Adaptive transfer learning
• [stat.ML]Batch Normalization Orthogonalizes Representations in Deep Random Networks
• [stat.ML]Conditional Deep Inverse Rosenblatt Transports
• [stat.ML]Decentralized Learning in Online Queuing Systems
• [stat.ML]Intrinsic Dimension Estimation
• [stat.ML]Seismic Inverse Modeling Method based on Generative Adversarial Network
• [stat.ML]Targeted Active Learning for Bayesian Decision-Making
• [stat.ML]The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization
• [stat.ML]Weighted Sparse Subspace Representation: A Unified Framework for Subspace Clustering, Constrained Clustering, and Active Learning
·····································
• [cond-mat.mtrl-sci]BIGDML: Towards Exact Machine Learning Force Fields for Materials
Huziel E. Sauceda, Luis E. Gálvez-González, Stefan Chmiela, Lauro Oliver Paz-Borbón, Klaus-Robert Müller, Alexandre Tkatchenko
http://arxiv.org/abs/2106.04229v1
• [cond-mat.stat-mech]Nonequilibrium Thermodynamics in Measuring Carbon Footprints: Disentangling Structure and Artifact in Input-Output Accounting
Samuel P. Loomis, Mark Cooper, James P. Crutchfield
http://arxiv.org/abs/2106.03948v1
• [cs.AI]Coarse-to-Fine Curriculum Learning
Otilia Stretcu, Emmanouil Antonios Platanios, Tom M. Mitchell, Barnabás Póczos
http://arxiv.org/abs/2106.04072v1
• [cs.AI]Definitions of intent suitable for algorithms
Hal Ashton
http://arxiv.org/abs/2106.04235v1
• [cs.AI]Differentiable Quality Diversity
Matthew C. Fontaine, Stefanos Nikolaidis
http://arxiv.org/abs/2106.03894v1
• [cs.AI]Exploration and preference satisfaction trade-off in reward-free learning
Noor Sajid, Panagiotis Tigas, Alexey Zakharov, Zafeirios Fountas, Karl Friston
http://arxiv.org/abs/2106.04316v1
• [cs.AI]Giving Commands to a Self-Driving Car: How to Deal with Uncertain Situations?
Thierry Deruyttere, Victor Milewski, Marie-Francine Moens
http://arxiv.org/abs/2106.04232v1
• [cs.AI]Learning to Guide a Saturation-Based Theorem Prover
Ibrahim Abdelaziz, Maxwell Crouse, Bassem Makni, Vernon Austil, Cristina Cornelio, Shajith Ikbal, Pavan Kapanipathi, Ndivhuwo Makondo, Kavitha Srinivas, Michael Witbrock, Achille Fokoue
http://arxiv.org/abs/2106.03906v1
• [cs.AI]Multi-Agent Cooperative Bidding Games for Multi-Objective Optimization in e-Commercial Sponsored Search
Ziyu Guan, Hongchang Wu, Qingyu Cao, Hao Liu, Wei Zhao, Sheng Li, Cai Xu, Guang Qiu, Jian Xu, Bo Zheng
http://arxiv.org/abs/2106.04075v1
• [cs.AI]North Carolina COVID-19 Agent-Based Model Framework for Hospitalization Forecasting Overview, Design Concepts, and Details Protocol
Kasey Jones, Emily Hadley, Sandy Preiss, Caroline Kery, Peter Baumgartner, Marie Stoner, Sarah Rhea
http://arxiv.org/abs/2106.04461v1
• [cs.AI]Reconciling Rewards with Predictive State Representations
Andrea Baisero, Christopher Amato
http://arxiv.org/abs/2106.03926v1
• [cs.AI]Sample Complexity of Tree Search Configuration: Cutting Planes and Beyond
Maria-Florina Balcan, Siddharth Prasad, Tuomas Sandholm, Ellen Vitercik
http://arxiv.org/abs/2106.04033v1
• [cs.AI]Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
Tiago da Cruz Asmus, Graçaliz Pereira Dimuro, Benjamín Bedregal, José Antonio Sanz, Radko Mesiar, Humberto Bustince
http://arxiv.org/abs/2106.04233v1
• [cs.CL]A Falta de Pan, Buenas Son Tortas: The Efficacy of Predicted UPOS Tags for Low Resource UD Parsing
Mark Anderson, Mathieu Dehouck, Carlos Gómez Rodríguez
http://arxiv.org/abs/2106.04222v1
• [cs.CL]A Modest Pareto Optimisation Analysis of Dependency Parsers in 2021
Mar Anderson, Carlos Gómez Rodríguez
http://arxiv.org/abs/2106.04216v1
• [cs.CL]A Unified Generative Framework for Aspect-Based Sentiment Analysis
Hang Yan, Junqi Dai, Tuo ji, Xipeng Qiu, Zheng Zhang
http://arxiv.org/abs/2106.04300v1
• [cs.CL]Adversarial Training for Machine Reading Comprehension with Virtual Embeddings
Ziqing Yang, Yiming Cui, Chenglei Si, Wanxiang Che, Ting Liu, Shijin Wang, Guoping Hu
http://arxiv.org/abs/2106.04437v1
• [cs.CL]Are Pretrained Transformers Robust in Intent Classification? A Missing Ingredient in Evaluation of Out-of-Scope Intent Detection
Jian-Guo Zhang, Kazuma Hashimoto, Yao Wan, Ye Liu, Caiming Xiong, Philip S. Yu
http://arxiv.org/abs/2106.04564v1
• [cs.CL]Attention Temperature Matters in Abstractive Summarization Distillation
Shengqiang Zhang, Xingxing Zhang, Hangbo Bao, Furu Wei
http://arxiv.org/abs/2106.03441v2
• [cs.CL]CAiRE in DialDoc21: Data Augmentation for Information-Seeking Dialogue System
Etsuko Ishii, Yan Xu, Genta Indra Winata, Zhaojiang Lin, Andrea Madotto, Zihan Liu, Peng Xu, Pascale Fung
http://arxiv.org/abs/2106.03530v2
• [cs.CL]CLTR: An End-to-End, Transformer-Based System for Cell Level TableRetrieval and Table Question Answering
Feifei Pan, Mustafa Canim, Michael Glass, Alfio Gliozzo, Peter Fox
http://arxiv.org/abs/2106.04441v1
• [cs.CL]Cheap and Good? Simple and Effective Data Augmentation for Low Resource Machine Reading
Hoang Van, Vikas Yadav, Mihai Surdeanu
http://arxiv.org/abs/2106.04134v1
• [cs.CL]Cyberbullying Detection Using Deep Neural Network from Social Media Comments in Bangla Language
Md Faisal Ahmed, Zalish Mahmud, Zarin Tasnim Biash, Ahmed Ann Noor Ryen, Arman Hossain, Faisal Bin Ashraf
http://arxiv.org/abs/2106.04506v1
• [cs.CL]Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering
Aditya Gupta, Jiacheng Xu, Shyam Upadhyay, Diyi Yang, Manaal Faruqui
http://arxiv.org/abs/2106.04016v1
• [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/2106.03958v1
• [cs.CL]Expressivity of Emergent Language is a Trade-off between Contextual Complexity and Unpredictability
Shangmin Guo, Yi Ren, Kory Mathewson, Simon Kirby, Stefano V. Albrecht, Kenny Smith
http://arxiv.org/abs/2106.03982v1
• [cs.CL]Generating Hypothetical Events for Abductive Inference
Debjit Paul, Anette Frank
http://arxiv.org/abs/2106.03973v1
• [cs.CL]Hyperbolic Temporal Knowledge Graph Embeddings with Relational and Time Curvatures
Sebastien Montella, Lina Rojas-Barahona, Johannes Heinecke
http://arxiv.org/abs/2106.04311v1
• [cs.CL]Insight from NLP Analysis: COVID-19 Vaccines Sentiments on Social Media
Tao Na, Wei Cheng, Dongming Li, Wanyu Lu, Hongjiang Li
http://arxiv.org/abs/2106.04081v1
• [cs.CL]Interpretable agent communication from scratch(with a generic visual processor emerging on the side)
Roberto Dessì, Eugene Kharitonov, Marco Baroni
http://arxiv.org/abs/2106.04258v1
• [cs.CL]Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making
Zijun Yao, Chengjiang Li, Tiansi Dong, Xin Lv, Jifan Yu, Lei Hou, Juanzi Li, Yichi Zhang, Zelin Dai
http://arxiv.org/abs/2106.04174v1
• [cs.CL]Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference
Hai Hu, He Zhou, Zuoyu Tian, Yiwen Zhang, Yina Ma, Yanting Li, Yixin Nie, Kyle Richardson
http://arxiv.org/abs/2106.03983v1
• [cs.CL]Itihasa: A large-scale corpus for Sanskrit to English translation
Rahul Aralikatte, Miryam de Lhoneux, Anoop Kunchukuttan, Anders Søgaard
http://arxiv.org/abs/2106.03269v2
• [cs.CL]Learning compositional structures for semantic graph parsing
Jonas Groschwitz, Meaghan Fowlie, Alexander Koller
http://arxiv.org/abs/2106.04398v1
• [cs.CL]Lexicon Learning for Few-Shot Neural Sequence Modeling
Ekin Akyürek, Jacob Andreas
http://arxiv.org/abs/2106.03993v1
• [cs.CL]Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions
Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, Tatsunori Hashimoto
http://arxiv.org/abs/2106.03873v1
• [cs.CL]Measuring and Improving BERT’s Mathematical Abilities by Predicting the Order of Reasoning
Piotr Piękos, Henryk Michalewski, Mateusz Malinowski
http://arxiv.org/abs/2106.03921v1
• [cs.CL]Meta-Learning to Compositionally Generalize
Henry Conklin, Bailin Wang, Kenny Smith, Ivan Titov
http://arxiv.org/abs/2106.04252v1
• [cs.CL]Neural Abstractive Unsupervised Summarization of Online News Discussions
Ignacio Tampe Palma, Marcelo Mendoza, Evangelos Milios
http://arxiv.org/abs/2106.03953v1
• [cs.CL]Obtaining Better Static Word Embeddings Using Contextual Embedding Models
Prakhar Gupta, Martin Jaggi
http://arxiv.org/abs/2106.04302v1
• [cs.CL]One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets
Marco Damonte, Emilio Monti
http://arxiv.org/abs/2106.04476v1
• [cs.CL]Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks
Rabeeh Karimi Mahabadi, Sebastian Ruder, Mostafa Dehghani, James Henderson
http://arxiv.org/abs/2106.04489v1
• [cs.CL]Position Bias Mitigation: A Knowledge-Aware Graph Model for Emotion Cause Extraction
Hanqi Yan, Lin Gui, Gabriele Pergola, Yulan He
http://arxiv.org/abs/2106.03518v2
• [cs.CL]Predicting Different Types of Subtle Toxicity in Unhealthy Online Conversations
Shlok Gilda, Mirela Silva, Luiz Giovanini, Daniela Oliveira
http://arxiv.org/abs/2106.03952v1
• [cs.CL]Question Generation for Adaptive Education
Megha Srivastava, Noah Goodman
http://arxiv.org/abs/2106.04262v1
• [cs.CL]Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generation
Gabriel Orlanski, Alex Gittens
http://arxiv.org/abs/2106.04447v1
• [cs.CL]Realistic Evaluation Principles for Cross-document Coreference Resolution
Arie Cattan, Alon Eirew, Gabriel Stanovsky, Mandar Joshi, Ido Dagan
http://arxiv.org/abs/2106.04192v1
• [cs.CL]RewardsOfSum: Exploring Reinforcement Learning Rewards for Summarisation
Jacob Parnell, Inigo Jauregi Unanue, Massimo Piccardi
http://arxiv.org/abs/2106.04080v1
• [cs.CL]SIGTYP 2021 Shared Task: Robust Spoken Language Identification
Elizabeth Salesky, Badr M. Abdullah, Sabrina J. Mielke, Elena Klyachko, Oleg Serikov, Edoardo Ponti, Ritesh Kumar, Ryan Cotterell, Ekaterina Vylomova
http://arxiv.org/abs/2106.03895v1
• [cs.CL]Self-supervised and Supervised Joint Training for Resource-rich Machine Translation
Yong Cheng, Wei Wang, Lu Jiang, Wolfgang Macherey
http://arxiv.org/abs/2106.04060v1
• [cs.CL]Structured Reordering for Modeling Latent Alignments in Sequence Transduction
Bailin Wang, Mirella Lapata, Ivan Titov
http://arxiv.org/abs/2106.03257v2
• [cs.CL]Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality
Mina Lee, Chris Donahue, Alexander Iyabor, Robin Jia, Percy Liang
http://arxiv.org/abs/2106.04102v1
• [cs.CL]TIMEDIAL: Temporal Commonsense Reasoning in Dialog
Lianhui Qin, Aditya Gupta, Shyam Upadhyay, Luheng He, Yejin Choi, Manaal Faruqui
http://arxiv.org/abs/2106.04571v1
• [cs.CL]Translate, then Parse! A strong baseline for Cross-Lingual AMR Parsing
Sarah Uhrig, Yoalli Rezepka Garcia, Juri Opitz, Anette Frank
http://arxiv.org/abs/2106.04565v1
• [cs.CL]Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interface
Peng Xu, Wenjie Zi, Hamidreza Shahidi, Ákos Kádár, Keyi Tang, Wei Yang, Jawad Ateeq, Harsh Barot, Meidan Alon, Yanshuai Cao
http://arxiv.org/abs/2106.04559v1
• [cs.CL]Ultra-Fine Entity Typing with Weak Supervision from a Masked Language Model
Hongliang Dai, Yangqiu Song, Haixun Wang
http://arxiv.org/abs/2106.04098v1
• [cs.CL]Unsupervised Word Segmentation from Discrete Speech Units in Low-Resource Settings
Marcely Zanon Boito, Bolaji Yusuf, Lucas Ondel, Aline Villavicencio, Laurent Besacier
http://arxiv.org/abs/2106.04298v1
• [cs.CL]XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation
Subhabrata Mukherjee, Ahmed Hassan Awadallah, Jianfeng Gao
http://arxiv.org/abs/2106.04563v1
• [cs.CV]A Synchronized Reprojection-based Model for 3D Human Pose Estimation
Yicheng Deng, Cheng Sun, Yongqi Sun, Jiahui Zhu
http://arxiv.org/abs/2106.04274v1
• [cs.CV]Adversarial Semantic Hallucination for Domain Generalized Semantic Segmentation
Gabriel Tjio, Ping Liu, Joey Tianyi Zhou, Rick Siow Mong Goh
http://arxiv.org/abs/2106.04144v1
• [cs.CV]Affinity Attention Graph Neural Network for Weakly Supervised Semantic Segmentation
Bingfeng Zhang, Jimin Xiao, Jianbo Jiao, Yunchao Wei, Yao Zhao
http://arxiv.org/abs/2106.04054v1
• [cs.CV]An Intelligent Hybrid Model for Identity Document Classification
Nouna Khandan
http://arxiv.org/abs/2106.04345v1
• [cs.CV]Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions
Daniel Rosenberg, Itai Gat, Amir Feder, Roi Reichart
http://arxiv.org/abs/2106.04484v1
• [cs.CV]CSRNet: Cascaded Selective Resolution Network for Real-time Semantic Segmentation
Jingjing Xiong, Lai-Man Po, Wing-Yin Yu, Chang Zhou, Pengfei Xian, Weifeng Ou
http://arxiv.org/abs/2106.04400v1
• [cs.CV]Chasing Sparsity in Vision Transformers:An End-to-End Exploration
Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, Zhangyang Wang
http://arxiv.org/abs/2106.04533v1
• [cs.CV]Contrastive Representation Learning for Hand Shape Estimation
Christian Zimmermann, Max Argus, Thomas Brox
http://arxiv.org/abs/2106.04324v1
• [cs.CV]Conversational Fashion Image Retrieval via Multiturn Natural Language Feedback
Yifei Yuan, Wai Lam
http://arxiv.org/abs/2106.04128v1
• [cs.CV]Cross-Domain Gradient Discrepancy Minimization for Unsupervised Domain Adaptation
Zhekai Du, Jingjing Li, Hongzu Su, Lei Zhu, Ke Lu
http://arxiv.org/abs/2106.04151v1
• [cs.CV]DETReg: Unsupervised Pretraining with Region Priors for Object Detection
Amir Bar, Xin Wang, Vadim Kantorov, Colorado J Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson
http://arxiv.org/abs/2106.04550v1
• [cs.CV]Data-Efficient Instance Generation from Instance Discrimination
Ceyuan Yang, Yujun Shen, Yinghao Xu, Bolei Zhou
http://arxiv.org/abs/2106.04566v1
• [cs.CV]Demystifying Local Vision Transformer: Sparse Connectivity, Weight Sharing, and Dynamic Weight
Qi Han, Zejia Fan, Qi Dai, Lei Sun, Ming-Ming Cheng, Jiaying Liu, Jingdong Wang
http://arxiv.org/abs/2106.04263v1
• [cs.CV]Design of Low-Artifact Interpolation Kernels by Means of Computer Algebra
Peter Karpov
http://arxiv.org/abs/2106.04104v1
• [cs.CV]Discriminative Triad Matching and Reconstruction for Weakly Referring Expression Grounding
Mingjie Sun, Jimin Xiao, Eng Gee Lim, Si Liu, John Y. Goulermas
http://arxiv.org/abs/2106.04053v1
• [cs.CV]Diverse Part Discovery: Occluded Person Re-identification with Part-Aware Transformer
Yulin Li, Jianfeng He, Tianzhu Zhang, Xiang Liu, Yongdong Zhang, Feng Wu
http://arxiv.org/abs/2106.04095v1
• [cs.CV]DoubleField: Bridging the Neural Surface and Radiance Fields for High-fidelity Human Rendering
Ruizhi Shao, Hongwen Zhang, He Zhang, Yanpei Cao, Tao Yu, Yebin Liu
http://arxiv.org/abs/2106.03798v2
• [cs.CV]Efficient training for future video generation based on hierarchical disentangled representation of latent variables
Naoya Fushishita, Antonio Tejero-de-Pablos, Yusuke Mukuta, Tatsuya Harada
http://arxiv.org/abs/2106.03502v2
• [cs.CV]Few-Shot Action Localization without Knowing Boundaries
Ting-Ting Xie, Christos Tzelepis, Fan Fu, Ioannis Patras
http://arxiv.org/abs/2106.04150v1
• [cs.CV]Fully Transformer Networks for Semantic Image Segmentation
Sitong Wu, Tianyi Wu, Fangjian Lin, Shengwei Tian, Guodong Guo
http://arxiv.org/abs/2106.04108v1
• [cs.CV]Grapevine Winter Pruning Automation: On Potential Pruning Points Detection through 2D Plant Modeling using Grapevine Segmentation
Miguel Fernandes, Antonello Scaldaferri, Giuseppe Fiameni, Tao Teng, Matteo Gatti, Stefano Poni, Claudio Semini, Darwin Caldwell, Fei Chen
http://arxiv.org/abs/2106.04208v1
• [cs.CV]HPRNet: Hierarchical Point Regression for Whole-Body Human Pose Estimation
Nermin Samet, Emre Akbas
http://arxiv.org/abs/2106.04269v1
• [cs.CV]Harnessing Unrecognizable Faces for Face Recognition
Siqi Deng, Yuanjun Xiong, Meng Wang, Wei Xia, Stefano Soatto
http://arxiv.org/abs/2106.04112v1
• [cs.CV]Hierarchical Lovász Embeddings for Proposal-free Panoptic Segmentation
Tommi Kerola, Jie Li, Atsushi Kanehira, Yasunori Kudo, Alexis Vallet, Adrien Gaidon
http://arxiv.org/abs/2106.04555v1
• [cs.CV]Highly accurate digital traffic recording as a basis for future mobility research: Methods and concepts of the research project HDV-Mess
Laurent Kloeker, Fabian Thomsen, Lutz Eckstein, Philip Trettner, Tim Elsner, Julius Nehring-Wirxel, Kersten Schuster, Leif Kobbelt, Michael Hoesch
http://arxiv.org/abs/2106.04175v1
• [cs.CV]How to Design a Three-Stage Architecture for Audio-Visual Active Speaker Detection in the Wild
Okan Köpüklü, Maja Taseska, Gerhard Rigoll
http://arxiv.org/abs/2106.03932v1
• [cs.CV]Image Deformation Estimation via Multi-Objective Optimization
Takumi Nakane, Xuequan Lu, Haoran Xie, Chao Zhang
http://arxiv.org/abs/2106.04139v1
• [cs.CV]Image2Point: 3D Point-Cloud Understanding with Pretrained 2D ConvNets
Chenfeng Xu, Shijia Yang, Bohan Zhai, Bichen Wu, Xiangyu Yue, Wei Zhan, Peter Vajda, Kurt Keutzer, Masayoshi Tomizuka
http://arxiv.org/abs/2106.04180v1
• [cs.CV]Interpreting Deep Learning based Cerebral Palsy Prediction with Channel Attention
Manli Zhu, Qianhui Men, Edmond S. L. Ho, Howard Leung, Hubert P. H. Shum
http://arxiv.org/abs/2106.04471v1
• [cs.CV]Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation
Pengpeng Liu, Michael R. Lyu, Irwin King, Jia Xu
http://arxiv.org/abs/2106.04195v1
• [cs.CV]Left Ventricle Contouring in Cardiac Images Based on Deep Reinforcement Learning
Sixing Yin, Yameng Han, Shufang Li
http://arxiv.org/abs/2106.04127v1
• [cs.CV]LipSync3D: Data-Efficient Learning of Personalized 3D Talking Faces from Video using Pose and Lighting Normalization
Avisek Lahiri, Vivek Kwatra, Christian Frueh, John Lewis, Chris Bregler
http://arxiv.org/abs/2106.04185v1
• [cs.CV]LocalTrans: A Multiscale Local Transformer Network for Cross-Resolution Homography Estimation
Ruizhi Shao, Gaochang Wu, Yuemei Zhou, Ying Fu, Lu Fang, Yebin Liu
http://arxiv.org/abs/2106.04067v1
• [cs.CV]Low-Rank Subspaces in GANs
Jiapeng Zhu, Ruili Feng, Yujun Shen, Deli Zhao, Zhengjun Zha, Jingren Zhou, Qifeng Chen
http://arxiv.org/abs/2106.04488v1
• [cs.CV]MViT: Mask Vision Transformer for Facial Expression Recognition in the wild
Hanting Li, Mingzhe Sui, Feng Zhao, Zhengjun Zha, Feng Wu
http://arxiv.org/abs/2106.04520v1
• [cs.CV]MoCo-Flow: Neural Motion Consensus Flow for Dynamic Humans in Stationary Monocular Cameras
Xuelin Chen, Weiyu Li, Daniel Cohen-Or, Niloy J. Mitra, Baoquan Chen
http://arxiv.org/abs/2106.04477v1
• [cs.CV]Multi-dataset Pretraining: A Unified Model for Semantic Segmentation
Bowen Shi, Xiaopeng Zhang, Haohang Xu, Wenrui Dai, Junni Zou, Hongkai Xiong, Qi Tian
http://arxiv.org/abs/2106.04121v1
• [cs.CV]Multi-frame sequence generator of 4D human body motion
Marsot Mathieu, Wuhrer Stefanie, Franco Jean-Sebastien, Durocher Stephane
http://arxiv.org/abs/2106.04387v1
• [cs.CV]Multi-task Transformation Learning for Robust Out-of-Distribution Detection
Sina Mohseni, Arash Vahdat, Jay Yadawa
http://arxiv.org/abs/2106.03899v1
• [cs.CV]Novel View Video Prediction Using a Dual Representation
Sarah Shiraz, Krishna Regmi, Shruti Vyas, Yogesh S. Rawat, Mubarak Shah
http://arxiv.org/abs/2106.03956v1
• [cs.CV]On Improving Adversarial Transferability of Vision Transformers
Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Fahad Shahbaz Khan, Fatih Porikli
http://arxiv.org/abs/2106.04169v1
• [cs.CV]On the relation between statistical learning and perceptual distances
Alexander Hepburn, Valero Laparra, Raul Santos-Rodriguez, Johannes Ballé, Jesús Malo
http://arxiv.org/abs/2106.04427v1
• [cs.CV]On the role of feedback in visual processing: a predictive coding perspective
Andrea Alamia, Milad Mozafari, Bhavin Choksi, Rufin VanRullen
http://arxiv.org/abs/2106.04225v1
• [cs.CV]On the use of automatically generated synthetic image datasets for benchmarking face recognition
Laurent Colbois, Tiago de Freitas Pereira, Sébastien Marcel
http://arxiv.org/abs/2106.04215v1
• [cs.CV]Person Re-Identification with a Locally Aware Transformer
Charu Sharma, Siddhant R. Kapil, David Chapman
http://arxiv.org/abs/2106.03720v2
• [cs.CV]Progressive Multi-scale Fusion Network for RGB-D Salient Object Detection
Guangyu Ren, Yanchu Xie, Tianhong Dai, Tania Stathaki
http://arxiv.org/abs/2106.03941v1
• [cs.CV]Progressive Spatio-Temporal Bilinear Network with Monte Carlo Dropout for Landmark-based Facial Expression Recognition with Uncertainty Estimation
Negar Heidari, Alexandros Iosifidis
http://arxiv.org/abs/2106.04332v1
• [cs.CV]RobustNav: Towards Benchmarking Robustness in Embodied Navigation
Prithvijit Chattopadhyay, Judy Hoffman, Roozbeh Mottaghi, Aniruddha Kembhavi
http://arxiv.org/abs/2106.04531v1
• [cs.CV]SDGMNet: Statistic-based Dynamic Gradient Modulation for Local Descriptor Learning
Jiayi Ma, Yuxin Deng
http://arxiv.org/abs/2106.04434v1
• [cs.CV]Salvage of Supervision in Weakly Supervised Detection
Lin Sui, Chen-Lin Zhang, Jianxin Wu
http://arxiv.org/abs/2106.04073v1
• [cs.CV]Scaling Vision Transformers
Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer
http://arxiv.org/abs/2106.04560v1
• [cs.CV]Segmentation and ABCD rule extraction for skin tumors classification
Mahammed Messadi, Hocine Cherifi, Abdelhafid Bessaid
http://arxiv.org/abs/2106.04372v1
• [cs.CV]Self-Supervised Structure-from-Motion through Tightly-Coupled Depth and Egomotion Networks
Brandon Wagstaff, Valentin Peretroukhin, Jonathan Kelly
http://arxiv.org/abs/2106.04007v1
• [cs.CV]Semantically Controllable Scene Generation with Guidance of Explicit Knowledge
Wenhao Ding, Bo Li, Kim Ji Eun, Ding Zhao
http://arxiv.org/abs/2106.04066v1
• [cs.CV]Simulated Adversarial Testing of Face Recognition Models
Nataniel Ruiz, Adam Kortylewski, Weichao Qiu, Cihang Xie, Sarah Adel Bargal, Alan Yuille, Stan Sclaroff
http://arxiv.org/abs/2106.04569v1
• [cs.CV]SpaceMeshLab: Spatial Context Memoization and Meshgrid Atrous Convolution Consensus for Semantic Segmentation
Taehun Kim, Jinseong Kim, Daijin Kim
http://arxiv.org/abs/2106.04025v1
• [cs.CV]Subject-Independent Brain-Computer Interface for Decoding High-Level Visual Imagery Tasks
Dae-Hyeok Lee, Dong-Kyun Han, Sung-Jin Kim, Ji-Hoon Jeong, Seong-Whan Lee
http://arxiv.org/abs/2106.04026v1
• [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/2106.04403v1
• [cs.CV]Task-Generic Hierarchical Human Motion Prior using VAEs
Jiaman Li, Ruben Villegas, Duygu Ceylan, Jimei Yang, Zhengfei Kuang, Hao Li, Yajie Zhao
http://arxiv.org/abs/2106.04004v1
• [cs.CV]Variational AutoEncoder for Reference based Image Super-Resolution
Zhi-Song Liu, Wan-Chi Siu, Li-Wen Wang
http://arxiv.org/abs/2106.04090v1
• [cs.CV]Weakly Supervised Volumetric Image Segmentation with Deformed Templates
Udaranga Wickramasinghe, Pascal Fua
http://arxiv.org/abs/2106.03987v1
• [cs.CV]White Paper Assistance: A Step Forward Beyond the Shortcut Learning
Xuan Cheng, Xiaomin Wang, Jiali Deng, Minghui Liu, Ming Liu
http://arxiv.org/abs/2106.04178v1
• [cs.DB]A highly scalable repository of waveform and vital signs data from bedside monitoring devices
Sanjay Malunjkar, Susan Weber, Somalee Datta
http://arxiv.org/abs/2106.03965v1
• [cs.DC]Assessing Open Interfaces and Protocols of PLCs for Computation Offloading at Field Level
Michael Gundall, Hans Dieter Schotten
http://arxiv.org/abs/2106.04517v1
• [cs.DC]Asynchronous Distributed Optimization with Redundancy in Cost Functions
Shuo Liu, Nirupam Gupta, Nitin H. Vaidya
http://arxiv.org/abs/2106.03998v1
• [cs.DC]CloudChain: A Cloud Blockchain Using Shared Memory Consensus and RDMA
Minghui Xu, Shuo Liu, Dongxiao Yu, Xiuzhen Cheng, Shaoyong Guo, Jiguo Yu
http://arxiv.org/abs/2106.04122v1
• [cs.DC]GearV: A Two-Gear Hypervisor for Mixed-Criticality IoT Systems
Kaiwen Long, Chong Xing, Yuebin Qi, Pei Zhang, Changsong Wu, Wenxiao Fang, Jing Tan, Jie Chen, Shiming Zhang, Zuosheng Wang, Zuanmin Liu, Cao Liang, Jiaxiang Xu
http://arxiv.org/abs/2106.04514v1
• [cs.DC]Launchpad: A Programming Model for Distributed Machine Learning Research
Fan Yang, Gabriel Barth-Maron, Piotr Stańczyk, Matthew Hoffman, Siqi Liu, Manuel Kroiss, Aedan Pope, Alban Rrustemi
http://arxiv.org/abs/2106.04516v1
• [cs.DC]Near-Optimal Dispersion on Arbitrary Anonymous Graphs
Ajay D. Kshemkalyani, Gokarna Sharma
http://arxiv.org/abs/2106.03943v1
• [cs.DC]PAIO: A Software-Defined Storage Data Plane Framework
Ricardo Macedo, Yusuke Tanimura, Jason Haga, Vijay Chidambaram, José Pereira, João Paulo
http://arxiv.org/abs/2106.03617v2
• [cs.DL]ConSTR: A Contextual Search Term Recommender
Thomas Krämer, Zeljko Carevic, Dwaipayan Roy, Claus-Peter Klas, Philipp Mayr
http://arxiv.org/abs/2106.04376v1
• [cs.DS]Low-Congestion Shortcuts in Constant Diameter Graphs
Shimon Kogan, Merav Parter
http://arxiv.org/abs/2106.01894v2
• [cs.DS]Sketch-Based Streaming Anomaly Detection in Dynamic Graphs
Siddharth Bhatia, Mohit Wadhwa, Philip S. Yu, Bryan Hooi
http://arxiv.org/abs/2106.04486v1
• [cs.GT]Improving Social Welfare While Preserving Autonomy via a Pareto Mediator
Stephen McAleer, John Lanier, Michael Dennis, Pierre Baldi, Roy Fox
http://arxiv.org/abs/2106.03927v1
• [cs.IR]Defining definition: a Text mining Approach to Define Innovative Technological Fields
Vito Giordano, Filippo Chiarello, Elena Cervelli
http://arxiv.org/abs/2106.04210v1
• [cs.IR]Exploring Periodicity and Interactivity in Multi-Interest Framework for Sequential Recommendation
Gaode Chen, Xinghua Zhang, Yanyan Zhao, Cong Xue, Ji Xiang
http://arxiv.org/abs/2106.04415v1
• [cs.IR]HieRec: Hierarchical User Interest Modeling for Personalized News Recommendation
Tao Qi, Fangzhao Wu, Chuhan Wu, Peiru Yang, Yang Yu, Xing Xie, Yongfeng Huang
http://arxiv.org/abs/2106.04408v1
• [cs.IR]MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
Anders H. Brams, Anders L. Jakobsen, Theis E. Jendal, Matteo Lissandrini, Peter Dolog, Katja Hose
http://arxiv.org/abs/2106.04209v1
• [cs.IR]Optimization of Service Addition in Multilevel Index Model for Edge Computing
Jiayan Gu, Yan Wu, Ashiq Anjum, John Panneerselvam, Yao Lu, Bo Yuan
http://arxiv.org/abs/2106.04494v1
• [cs.IR]Review Polarity-wise Recommender
Han Liu, Yangyang Guo, Jianhua Yin, Zan Gao, Liqiang Nie
http://arxiv.org/abs/2106.04155v1
• [cs.IT]A Perspective on Time towards Wireless 6G
Petar Popovski, Federico Chiariotti, Kaibin Huang, Anders E. Kalør, Marios Kountouris, Nikolaos Pappas, Beatriz Soret
http://arxiv.org/abs/2106.04314v1
• [cs.IT]A Sequence Selection Bound for the Capacity of the Nonlinear Fiber Channel
Stella Civelli, Enrico Forestieri, Alexey Lotsmanov, Dmitry Razdoburdin, Marco Secondini
http://arxiv.org/abs/2106.04097v1
• [cs.IT]Contention-based Grant-free Transmission with Extremely Sparse Orthogonal Pilot Scheme
Zhifeng Yuan, Zhigang Li, Weimin Li, Yihua Ma
http://arxiv.org/abs/2106.04172v1
• [cs.IT]Dilated Convolution based CSI Feedback Compression for Massive MIMO Systems
Shunpu Tang, Junjuan Xia, Lisheng Fan, Xianfu Lei, Wei Xu, Arumugam Nallanathan
http://arxiv.org/abs/2106.04043v1
• [cs.IT]Low-complexity Voronoi shaping for the Gaussian channel
S. Li, A. Mirani, M. Karlsson, E. Agrell
http://arxiv.org/abs/2106.03262v2
• [cs.IT]Modeling Uplink Coverage Performance in Hybrid Satellite-Terrestrial Networks
Bassel Al Homssi, Akram Al-Hourani
http://arxiv.org/abs/2106.04293v1
• [cs.IT]On the Linear Capacity of Conditional Disclosure of Secrets
Zhou Li, Hua Sun
http://arxiv.org/abs/2106.04483v1
• [cs.IT]On the Outage Capacity of the Massive MIMO Diversity Channel
Marco Martalo, Riccardo Raheli
http://arxiv.org/abs/2106.04203v1
• [cs.IT]Optimized Rate-Profiling for PAC Codes
He Sun, Emanuele Viterbo, Rongke Liu
http://arxiv.org/abs/2106.04074v1
• [cs.IT]Optimizing a Binary Intelligent Reflecting Surface for OFDM Communications under Mutual Coupling
Emil Björnson
http://arxiv.org/abs/2106.04280v1
• [cs.IT]Outage Performance of Multi-UAV Relaying-based Imperfect Hardware Hybrid Satellite-Terrestrial Networks
Pankaj K. Sharma, Deepika Gupta
http://arxiv.org/abs/2106.04223v1
• [cs.IT]Principal Bit Analysis: Autoencoding with Schur-Concave Loss
Sourbh Bhadane, Aaron B. Wagner, Jayadev Acharya
http://arxiv.org/abs/2106.02796v2
• [cs.IT]Private Multi-Group Aggregation
Carolina Naim, Rafael G. L. D’Oliveira, Salim El Rouayheb
http://arxiv.org/abs/2106.04467v1
• [cs.IT]Proof methods for robust low-rank matrix recovery
Tim Fuchs, David Gross, Peter Jung, Felix Krahmer, Richard Kueng, Dominik Stöger
http://arxiv.org/abs/2106.04382v1
• [cs.LG]A Deep Value-network Based Approach for Multi-Driver Order Dispatching
Xiaocheng Tang, Zhiwei Qin, Fan Zhang, Zhaodong Wang, Zhe Xu, Yintai Ma, Hongtu Zhu, Jieping Ye
http://arxiv.org/abs/2106.04493v1
• [cs.LG]A Survey of Transformers
Tianyang Lin, Yuxin Wang, Xiangyang Liu, Xipeng Qiu
http://arxiv.org/abs/2106.04554v1
• [cs.LG]A critical look at the current train/test split in machine learning
Jimin Tan, Jianan Yang, Sai Wu, Gang Chen, Jake Zhao
http://arxiv.org/abs/2106.04525v1
• [cs.LG]A self consistent theory of Gaussian Processes captures feature learning effects in finite CNNs
Gadi Naveh, Zohar Ringel
http://arxiv.org/abs/2106.04110v1
• [cs.LG]Adaptive Machine Unlearning
Varun Gupta, Christopher Jung, Seth Neel, Aaron Roth, Saeed Sharifi-Malvajerdi, Chris Waites
http://arxiv.org/abs/2106.04378v1
• [cs.LG]Amortized Generation of Sequential Counterfactual Explanations for Black-box Models
Sahil Verma, Keegan Hines, John P. Dickerson
http://arxiv.org/abs/2106.03962v1
• [cs.LG]Automatic Generation of Machine Learning Synthetic Data Using ROS
Kyle M. Hart, Ari B. Goodman, Ryan P. O’Shea
http://arxiv.org/abs/2106.04547v1
• [cs.LG]Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash
http://arxiv.org/abs/2106.04420v1
• [cs.LG]Breaking the Limits of Message Passing Graph Neural Networks
Muhammet Balcilar, Pierre Héroux, Benoit Gaüzère, Pascal Vasseur, Sébastien Adam, Paul Honeine
http://arxiv.org/abs/2106.04319v1
• [cs.LG]Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein
http://arxiv.org/abs/2106.04537v1
• [cs.LG]Chow-Liu++: Optimal Prediction-Centric Learning of Tree Ising Models
Enric Boix-Adsera, Guy Bresler, Frederic Koehler
http://arxiv.org/abs/2106.03969v1
• [cs.LG]Closed-Form Analytical Results for Maximum Entropy Reinforcement Learning
Argenis Arriojas, Stas Tiomkin, Rahul V. Kulkarni
http://arxiv.org/abs/2106.03931v1
• [cs.LG]Cooperative Stochastic Multi-agent Multi-armed Bandits Robust to Adversarial Corruptions
Junyan Liu, Shuai Li, Dapeng Li
http://arxiv.org/abs/2106.04207v1
• [cs.LG]Coresets for Classification — Simplified and Strengthened
Tung Mai, Anup B. Rao, Cameron Musco
http://arxiv.org/abs/2106.04254v1
• [cs.LG]Correcting Momentum in Temporal Difference Learning
Emmanuel Bengio, Joelle Pineau, Doina Precup
http://arxiv.org/abs/2106.03955v1
• [cs.LG]Deep Learning Statistical Arbitrage
Jorge Guijarro-Ordonez, Markus Pelger, Greg Zanotti
http://arxiv.org/abs/2106.04028v1
• [cs.LG]Deep Proxy Causal Learning and its Application to Confounded Bandit Policy Evaluation
Liyuan Xu, Heishiro Kanagawa, Arthur Gretton
http://arxiv.org/abs/2106.03907v1
• [cs.LG]Detecting Anomalous Event Sequences with Temporal Point Processes
Oleksandr Shchur, Ali Caner Türkmen, Tim Januschowski, Jan Gasthaus, Stephan Günnemann
http://arxiv.org/abs/2106.04465v1
• [cs.LG]Differentiable Multiple Shooting Layers
Stefano Massaroli, Michael Poli, Sho Sonoda, Taji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
http://arxiv.org/abs/2106.03885v1
• [cs.LG]Dynamic Sparse Training for Deep Reinforcement Learning
Ghada Sokar, Elena Mocanu, Decebal Constantin Mocanu, Mykola Pechenizkiy, Peter Stone
http://arxiv.org/abs/2106.04217v1
• [cs.LG]Efficient Online Learning for Dynamic k-Clustering
Dimitris Fotakis, Georgios Piliouras, Stratis Skoulakis
http://arxiv.org/abs/2106.04336v1
• [cs.LG]Enhancing Robustness of Neural Networks through Fourier Stabilization
Netanel Raviv, Aidan Kelley, Michael Guo, Yevgeny Vorobeychik
http://arxiv.org/abs/2106.04435v1
• [cs.LG]Evaluating Meta-Feature Selection for the Algorithm Recommendation Problem
Geand Trindade Pereira, Moises Rocha dos Santos, Andre Carlos Ponce de Leon Ferreira de Carvalho
http://arxiv.org/abs/2106.03954v1
• [cs.LG]FEAR: A Simple Lightweight Method to Rank Architectures
Debadeepta Dey, Shital Shah, Sebastien Bubeck
http://arxiv.org/abs/2106.04010v1
• [cs.LG]Fast Federated Learning in the Presence of Arbitrary Device Unavailability
Xinran Gu, Kaixuan Huang, Jingzhao Zhang, Longbo Huang
http://arxiv.org/abs/2106.04159v1
• [cs.LG]Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina Balcan, Virginia Smith, Ameet Talwalkar
http://arxiv.org/abs/2106.04502v1
• [cs.LG]Fine-grained Out-of-Distribution Detection with Mixup Outlier Exposure
Jingyang Zhang, Nathan Inkawhich, Yiran Chen, Hai Li
http://arxiv.org/abs/2106.03917v1
• [cs.LG]Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation
Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio
http://arxiv.org/abs/2106.04399v1
• [cs.LG]Generative Flows with Invertible Attentions
Rhea Sanjay Sukthanker, Zhiwu Huang, Suryansh Kumar, Radu Timofte, Luc Van Gool
http://arxiv.org/abs/2106.03959v1
• [cs.LG]Graph-MLP: Node Classification without Message Passing in Graph
Yang Hu, Haoxuan You, Zhecan Wang, Zhicheng Wang, Erjin Zhou, Yue Gao
http://arxiv.org/abs/2106.04051v1
• [cs.LG]Hash Layers For Large Sparse Models
Stephen Roller, Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston
http://arxiv.org/abs/2106.04426v1
• [cs.LG]Householder-Absolute Neural Layers For High Variability and Deep Trainability
Yueyao Yu, Yin Zhang
http://arxiv.org/abs/2106.04088v1
• [cs.LG]Hybrid Method Based on NARX models and Machine Learning for Pattern Recognition
P. H. O. Silva, A. S. Cerqueira, E. G. Nepomuceno
http://arxiv.org/abs/2106.04021v1
• [cs.LG]Incentive Mechanism for Privacy-Preserving Federated Learning
Shuyuan Zheng, Yang Cao, Masatoshi Yoshikawa
http://arxiv.org/abs/2106.04384v1
• [cs.LG]Incorporating NODE with Pre-trained Neural Differential Operator for Learning Dynamics
Shiqi Gong, Qi Meng, Yue Wang, Lijun Wu, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
http://arxiv.org/abs/2106.04166v1
• [cs.LG]Interactive Label Cleaning with Example-based Explanations
Stefano Teso, Andrea Bontempelli, Fausto Giunchiglia, Andrea Passerini
http://arxiv.org/abs/2106.03922v1
• [cs.LG]LEADS: Learning Dynamical Systems that Generalize Across Environments
Yuan Yin, Ibrahim Ayed, Emmanuel de Bézenac, Nicolas Baskiotis, Patrick Gallinari
http://arxiv.org/abs/2106.04546v1
• [cs.LG]LaplaceNet: A Hybrid Energy-Neural Model for Deep Semi-Supervised Classification
Philip Sellars, Angelica I. Aviles-Rivero, Carola-Bibiane Schönlieb
http://arxiv.org/abs/2106.04527v1
• [cs.LG]Learning Markov State Abstractions for Deep Reinforcement Learning
Cameron Allen, Neev Parikh, Omer Gottesman, George Konidaris
http://arxiv.org/abs/2106.04379v1
• [cs.LG]Learning from Multiple Noisy Partial Labelers
Peilin Yu, Tiffany Ding, Stephen H. Bach
http://arxiv.org/abs/2106.04530v1
• [cs.LG]Linear Convergence of Entropy-Regularized Natural Policy Gradient with Linear Function Approximation
Semih Cayci, Niao He, R. Srikant
http://arxiv.org/abs/2106.04096v1
• [cs.LG]Manifold Topology Divergence: a Framework for Comparing Data Manifolds
Serguei Barannikov, Ilya Trofimov, Grigorii Sotnikov, Ekaterina Trimbach, Alexander Korotin, Alexander Filippov, Evgeny Burnaev
http://arxiv.org/abs/2106.04024v1
• [cs.LG]Meta Learning for Knowledge Distillation
Wangchunshu Zhou, Canwen Xu, Julian McAuley
http://arxiv.org/abs/2106.04570v1
• [cs.LG]Muddling Label Regularization: Deep Learning for Tabular Datasets
Karim Lounici, Katia Meziani, Benjamin Riu
http://arxiv.org/abs/2106.04462v1
• [cs.LG]Multi-output Gaussian Processes for Uncertainty-aware Recommender Systems
Yinchong Yang, Florian Buettner
http://arxiv.org/abs/2106.04221v1
• [cs.LG]Neural Hybrid Automata: Learning Dynamics with Multiple Modes and Stochastic Transitions
Michael Poli, Stefano Massaroli, Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Atsushi Yamashita, Hajime Asama, Jinkyoo Park, Animesh Garg
http://arxiv.org/abs/2106.04165v1
• [cs.LG]Nonsmooth Implicit Differentiation for Machine Learning and Optimization
Jérôme Bolte, Tam Le, Edouard Pauwels, Antonio Silveti-Falls
http://arxiv.org/abs/2106.04350v1
• [cs.LG]Offline Policy Comparison under Limited Historical Agent-Environment Interactions
Anton Dereventsov, Joseph D. Daws Jr., Clayton Webster
http://arxiv.org/abs/2106.03934v1
• [cs.LG]Parameter Inference with Bifurcation Diagrams
Gregory Szep, Neil Dalchau, Attila Csikasz-Nagy
http://arxiv.org/abs/2106.04243v1
• [cs.LG]PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning
Tao Yu, Cuiling Lan, Wenjun Zeng, Mingxiao Feng, Zhibo Chen
http://arxiv.org/abs/2106.04152v1
• [cs.LG]Provable Guarantees for Self-Supervised Deep Learning with Spectral Contrastive Loss
Jeff Z. HaoChen, Colin Wei, Adrien Gaidon, Tengyu Ma
http://arxiv.org/abs/2106.04156v1
• [cs.LG]Provably Robust Detection of Out-of-distribution Data (almost) for free
Alexander Meinke, Julian Bitterwolf, Matthias Hein
http://arxiv.org/abs/2106.04260v1
• [cs.LG]RECOWNs: Probabilistic Circuits for Trustworthy Time Series Forecasting
Nils Thoma, Zhongjie Yu, Fabrizio Ventola, Kristian Kersting
http://arxiv.org/abs/2106.04148v1
• [cs.LG]Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization
Bing-Jing Hsieh, Ping-Chun Hsieh, Xi Liu
http://arxiv.org/abs/2106.04335v1
• [cs.LG]Rethinking Graph Transformers with Spectral Attention
Devin Kreuzer, Dominique Beaini, William L. Hamilton, Vincent Létourneau, Prudencio Tossou
http://arxiv.org/abs/2106.03893v1
• [cs.LG]Robust Generalization despite Distribution Shift via Minimum Discriminating Information
Tobias Sutter, Andreas Krause, Daniel Kuhn
http://arxiv.org/abs/2106.04443v1
• [cs.LG]Self-supervised Graph-level Representation Learning with Local and Global Structure
Minghao Xu, Hang Wang, Bingbing Ni, Hongyu Guo, Jian Tang
http://arxiv.org/abs/2106.04113v1
• [cs.LG]Stability and Generalization of Bilevel Programming in Hyperparameter Optimization
Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang
http://arxiv.org/abs/2106.04188v1
• [cs.LG]Staircase Attention for Recurrent Processing of Sequences
Da Ju, Stephen Roller, Sainbayar Sukhbaatar, Jason Weston
http://arxiv.org/abs/2106.04279v1
• [cs.LG]Supervised Machine Learning with Plausible Deniability
Stefan Rass, Sandra König, Jasmin Wachter, Manuel Egger, Manuel Hobisch
http://arxiv.org/abs/2106.04267v1
• [cs.LG]The Fast Kernel Transform
John Paul Ryan, Sebastian Ament, Carla P. Gomes, Anil Damle
http://arxiv.org/abs/2106.04487v1
• [cs.LG]The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation
Alex J. Chan, Ioana Bica, Alihan Huyuk, Daniel Jarrett, Mihaela van der Schaar
http://arxiv.org/abs/2106.04240v1
• [cs.LG]The Randomness of Input Data Spaces is an A Priori Predictor for Generalization
Martin Briesch, Dominik Sobania, Franz Rothlauf
http://arxiv.org/abs/2106.04181v1
• [cs.LG]The best of both worlds: stochastic and adversarial episodic MDPs with unknown transition
Tiancheng Jin, Longbo Huang, Haipeng Luo
http://arxiv.org/abs/2106.04117v1
• [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/2106.04480v1
• [cs.LG]Time-series Imputation of Temporally-occluded Multiagent Trajectories
Shayegan Omidshafiei, Daniel Hennes, Marta Garnelo, Eugene Tarassov, Zhe Wang, Romuald Elie, Jerome T. Connor, Paul Muller, Ian Graham, William Spearman, Karl Tuyls
http://arxiv.org/abs/2106.04219v1
• [cs.LG]Towards Practical Credit Assignment for Deep Reinforcement Learning
Vyacheslav Alipov, Riley Simmons-Edler, Nikita Putintsev, Pavel Kalinin, Dmitry Vetrov
http://arxiv.org/abs/2106.04499v1
• [cs.LG]Towards a Theoretical Framework of Out-of-Distribution Generalization
Haotian Ye, Chuanlong Xie, Tianle Cai, Ruichen Li, Zhenguo Li, Liwei Wang
http://arxiv.org/abs/2106.04496v1
• [cs.LG]Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran
http://arxiv.org/abs/2106.04015v1
• [cs.LG]Understanding (Generalized) Label Smoothing whenLearning with Noisy Labels
Jiaheng Wei, Hangyu Liu, Tongliang Liu, Gang Niu, Yang Liu
http://arxiv.org/abs/2106.04149v1
• [cs.LG]What Data Augmentation Do We Need for Deep-Learning-Based Finance?
Liu Ziyin, Kentaro Minami, Kentaro Imajo
http://arxiv.org/abs/2106.04114v1
• [cs.LG]What Makes Multimodal Learning Better than Single (Provably)
Yu Huang, Chenzhuang Du, Zihui Xue, Xuanyao Chen, Hang Zhao, Longbo Huang
http://arxiv.org/abs/2106.04538v1
• [cs.LG]What training reveals about neural network complexity
Andreas Loukas, Marinos Poiitis, Stefanie Jegelka
http://arxiv.org/abs/2106.04186v1
• [cs.LG]When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting
Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
http://arxiv.org/abs/2106.03904v1
• [cs.NE]GSGP-CUDA — a CUDA framework for Geometric Semantic Genetic Programming
Leonardo Trujillo, Jose Manuel Muñoz Contreras, Daniel E Hernandez, Mauro Castelli, Juan J Tapia
http://arxiv.org/abs/2106.04034v1
• [cs.NE]JANUS: Parallel Tempered Genetic Algorithm Guided by Deep Neural Networks for Inverse Molecular Design
AkshatKumar Nigam, Robert Pollice, Alan Aspuru-Guzik
http://arxiv.org/abs/2106.04011v1
• [cs.RO]A novel partially-decoupled translational parallel manipulator with symbolic kinematics, singularity identification and workspace determination
Huiping Shen, Yinan Zhao, Ju Li, Guanglei Wu, Damien Chablat
http://arxiv.org/abs/2106.04337v1
• [cs.RO]Acoustic Power for Swarms of Microscopic Robots
Tad Hogg
http://arxiv.org/abs/2106.03923v1
• [cs.RO]Efficient Sampling in POMDPs with Lipschitz Bandits for Motion Planning in Continuous Spaces
Ömer Şahin Taş, Felix Hauser, Martin Lauer
http://arxiv.org/abs/2106.04206v1
• [cs.RO]Game-Theoretic Model Predictive Control with Data-Driven Identification of Vehicle Model for Head-to-Head Autonomous Racing
Chanyoung Jung, Seungwook Lee, Hyunki Seong, Andrea Finazzi, David Hyunchul Shim
http://arxiv.org/abs/2106.04094v1
• [cs.RO]H-ModQuad: Modular Multi-Rotors with 4, 5, and 6 Controllable DOF
Jiawei Xu, Diego S. D’Antonio, David Saldaña
http://arxiv.org/abs/2106.04048v1
• [cs.RO]Learning Riemannian Manifolds for Geodesic Motion Skills
Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
http://arxiv.org/abs/2106.04315v1
• [cs.RO]Learning to Detect Multi-Modal Grasps for Dexterous Grasping in Dense Clutter
Matt Corsaro, Stefanie Tellex, George Konidaris
http://arxiv.org/abs/2106.03919v1
• [cs.RO]Model Predictive Robot-Environment Interaction Control for Mobile Manipulation Tasks
Maria Vittoria Minniti, Ruben Grandia, Kevin Fäh, Farbod Farshidian, Marco Hutter
http://arxiv.org/abs/2106.04202v1
• [cs.RO]Planning Multimodal Exploratory Actions for Online Robot Attribute Learning
Xiaohan Zhang, Jivko Sinapov, Shiqi Zhang
http://arxiv.org/abs/2106.03029v2
• [cs.RO]Property-Aware Robot Object Manipulation: a Generative Approach
Luca Garello, Linda Lastrico, Francesco Rea, Fulvio Mastrogiovanni, Nicoletta Noceti, Alessandra Sciutti
http://arxiv.org/abs/2106.04385v1
• [cs.RO]Residual Feedback Learning for Contact-Rich Manipulation Tasks with Uncertainty
Alireza Ranjbar, Ngo Anh Vien, Hanna Ziesche, Joschka Boedecker, Gerhard Neumann
http://arxiv.org/abs/2106.04306v1
• [cs.RO]Risk Ranked Recall: Collision Safety Metric for Object Detection Systems in Autonomous Vehicles
Ayoosh Bansal, Jayati Singh, Micaela Verucchi, Marco Caccamo
http://arxiv.org/abs/2106.04146v1
• [cs.RO]Safe Deep Q-Network for Autonomous Vehicles at Unsignalized Intersection
Kasra Mokhtari, Alan R. Wagner
http://arxiv.org/abs/2106.04561v1
• [cs.RO]XIRL: Cross-embodiment Inverse Reinforcement Learning
Kevin Zakka, Andy Zeng, Pete Florence, Jonathan Tompson, Jeannette Bohg, Debidatta Dwibedi
http://arxiv.org/abs/2106.03911v1
• [cs.SD]Broadcasted Residual Learning for Efficient Keyword Spotting
Byeonggeun Kim, Simyung Chang, Jinkyu Lee, Dooyong Sung
http://arxiv.org/abs/2106.04140v1
• [cs.SD]Efficient Speech Emotion Recognition Using Multi-Scale CNN and Attention
Zixuan Peng, Yu Lu, Shengfeng Pan, Yunfeng Liu
http://arxiv.org/abs/2106.04133v1
• [cs.SD]NWT: Towards natural audio-to-video generation with representation learning
Rayhane Mama, Marc S. Tyndel, Hashiam Kadhim, Cole Clifford, Ragavan Thurairatnam
http://arxiv.org/abs/2106.04283v1
• [cs.SD]PILOT: Introducing Transformers for Probabilistic Sound Event Localization
Christopher Schymura, Benedikt Bönninghoff, Tsubasa Ochiai, Marc Delcroix, Keisuke Kinoshita, Tomohiro Nakatani, Shoko Araki, Dorothea Kolossa
http://arxiv.org/abs/2106.03903v1
• [cs.SD]Raw Waveform Encoder with Multi-Scale Globally Attentive Locally Recurrent Networks for End-to-End Speech Recognition
Max W. Y. Lam, Jun Wang, Chao Weng, Dan Su, Dong Yu
http://arxiv.org/abs/2106.04275v1
• [cs.SE]How to Bake Quantum into Your Pet Petri Nets and Have Your Net Theory Too
Heinz W. Schmidt
http://arxiv.org/abs/2106.03539v1
• [cs.SI]Designing Toxic Content Classification for a Diversity of Perspectives
Deepak Kumar, Patrick Gage Kelley, Sunny Consolvo, Joshua Mason, Elie Bursztein, Zakir Durumeric, Kurt Thomas, Michael Bailey
http://arxiv.org/abs/2106.04511v1
• [cs.SI]News consumption and social media regulations policy
Gabriele Etta, Matteo Cinelli, Alessandro Galeazzi, Carlo Michele Valensise, Mauro Conti, Walter Quattrociocchi
http://arxiv.org/abs/2106.03924v1
• [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/2106.04292v1
• [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/2106.04515v1
• [econ.EM]Testing Monotonicity of Mean Potential Outcomes in a Continuous Treatment
Yu-Chin Hsu, Martin Huber, Ying-Ying Lee, Chu-An Liu
http://arxiv.org/abs/2106.04237v1
• [eess.AS]Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions
Yohei Kawaguchi, Keisuke Imoto, Yuma Koizumi, Noboru Harada, Daisuke Niizumi, Kota Dohi, Ryo Tanabe, Harsh Purohit, Takashi Endo
http://arxiv.org/abs/2106.04492v1
• [eess.IV]AutoPtosis
Abdullah Aleem, Manoj Prabhakar Nallabothula, Pete Setabutr, Joelle A. Hallak, Darvin Yi
http://arxiv.org/abs/2106.03905v1
• [eess.IV]EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation
Yuting He, Rongjun Ge, Xiaoming Qi, Guanyu Yang, Yang Chen, Youyong Kong, Huazhong Shu, Jean-Louis Coatrieux, Shuo Li
http://arxiv.org/abs/2106.04130v1
• [eess.IV]Generative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scans
Luka Posilović, Duje Medak, Marko Subasic, Marko Budimir, Sven Loncaric
http://arxiv.org/abs/2106.04281v1
• [eess.IV]PolypGen: A multi-center polyp detection and segmentation dataset for generalisability assessment
Sharib Ali, Debesh Jha, Noha Ghatwary, Stefano Realdon, Renato Cannizzaro, Osama E. Salem, Dominique Lamarque, Christian Daul, Kim V. Anonsen, Michael A. Riegler, Pål Halvorsen, Jens Rittscher, Thomas de Lange, James E. East
http://arxiv.org/abs/2106.04463v1
• [hep-ex]SPANet: Generalized Permutationless Set Assignment for Particle Physics using Symmetry Preserving Attention
Alexander Shmakov, Michael James Fenton, Ta-Wei Ho, Shih-Chieh Hsu, Daniel Whiteson, Pierre Baldi
http://arxiv.org/abs/2106.03898v1
• [math.OC]Efficient solution method based on inverse dynamics for optimal control problems of rigid body systems
Sotaro Katayama, Toshiyuki Ohtsuka
http://arxiv.org/abs/2106.04176v1
• [math.OC]Lower Bounds and Optimal Algorithms for Smooth and Strongly Convex Decentralized Optimization Over Time-Varying Networks
Dmitry Kovalev, Elnur Gasanov, Peter Richtárik, Alexander Gasnikov
http://arxiv.org/abs/2106.04469v1
• [math.OC]Optimized Data Rate Allocation for Dynamic Sensor Fusion over Resource Constrained Communication Networks
Hyunho Jung, Ali Reza Pedram, Travis Craig Cuvelier, Takashi Tanaka
http://arxiv.org/abs/2106.04001v1
• [math.OC]Unbalanced Optimal Transport through Non-negative Penalized Linear Regression
Laetitia Chapel, Rémi Flamary, Haoran Wu, Cédric Févotte, Gilles Gasso
http://arxiv.org/abs/2106.04145v1
• [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 Eisab, Natalia Dobrenkoa, Natalia Gusarovaa
http://arxiv.org/abs/2106.04383v1
• [math.PR]Markov Chains Generated by Convolutions of Orthogonality Measures
Satoru Odake, Ryu Sasaki
http://arxiv.org/abs/2106.04082v1
• [math.PR]Maximum likelihood estimation for sub-fractional Vasicek model
B. L. S. Prakasa Rao
http://arxiv.org/abs/2106.03350v1
• [math.ST]Bridge Simulation and Metric Estimation on Lie Groups
Mathias Højgaard Jensen, Sarang Joshi, Stefan Sommer
http://arxiv.org/abs/2106.03431v1
• [math.ST]Minimax and adaptive tests for detecting abrupt and possibly transitory changes in a Poisson process
Magalie Fromont, Fabrice Grela, Ronan Le Guével
http://arxiv.org/abs/2106.04333v1
• [math.ST]Process of the slope components of -regression quantile
Jana Jurečková
http://arxiv.org/abs/2106.04373v1
• [physics.chem-ph]Augmenting Molecular Deep Generative Models with Topological Data Analysis Representations
Yair Schiff, Vijil Chenthamarakshan, Samuel Hoffman, Karthikeyan Natesan Ramamurthy, Payel Das
http://arxiv.org/abs/2106.04464v1
• [physics.data-an]Granger causality in the frequency domain: derivation and applications
Vinicius Lima, Fernanda Jaiara Dellajustina, Renan O. Shimoura, Mauricio Girardi-Schappo, Nilton L. Kamiji, Rodrigo F. O. Pena, Antonio C. Roque
http://arxiv.org/abs/2106.03990v1
• [q-bio.NC]Credit Assignment Through Broadcasting a Global Error Vector
David G. Clark, L. F. Abbott, SueYeon Chung
http://arxiv.org/abs/2106.04089v1
• [q-bio.NC]Object Based Attention Through Internal Gating
Jordan Lei, Ari S. Benjamin, Konrad P. Kording
http://arxiv.org/abs/2106.04540v1
• [quant-ph]Encoding-dependent generalization bounds for parametrized quantum circuits
Matthias C. Caro, Elies Gil-Fuster, Johannes Jakob Meyer, Jens Eisert, Ryan Sweke
http://arxiv.org/abs/2106.03880v1
• [quant-ph]NISQ Algorithm for Semidefinite Programming
Kishor Bharti, Tobias Haug, Vlatko Vedral, Leong-Chuan Kwek
http://arxiv.org/abs/2106.03891v1
• [stat.AP]Scalar on time-by-distribution regression and its application for modelling associations between daily-living physical activity and cognitive functions in Alzheimer’s Disease
Rahul Ghosal, Vijay R. Varma, Dmitri Volfson, Jacek Urbanek, Jeffrey M. Hausdorff, Amber Watts, Vadim Zipunnikov
http://arxiv.org/abs/2106.03979v1
• [stat.AP]Sensitivity analysis for random measurement error using regression calibration and simulation-extrapolation
Linda Nab, Rolf H. H. Groenwold
http://arxiv.org/abs/2106.04285v1
• [stat.ME]A Unified Approach to Robust Inference for Genetic Covariance
Jianqiao Wang, Sai Li, Hongzhe Li
http://arxiv.org/abs/2106.04106v1
• [stat.ME]A likelihood based sensitivity analysis for publication bias on summary ROC in meta-analysis of diagnostic test accuracy
Yi Zhou, Ao Huang, Satoshi Hattori
http://arxiv.org/abs/2106.04253v1
• [stat.ME]Clustering with missing data: which imputation model for which cluster analysis method?
Vincent Audigier, Ndèye Niang, Matthieu Resche-Rigon
http://arxiv.org/abs/2106.04424v1
• [stat.ME]Context-Specific Causal Discovery for Categorical Data Using Staged Trees
Manuele Leonelli, Gherardo Varando
http://arxiv.org/abs/2106.04416v1
• [stat.ME]Do forecasts of bankruptcy cause bankruptcy? A machine learning sensitivity analysis
Demetrios Papakostas, P. Richard Hahn, Jared Murray, Frank Zhou, Joseph Gerakos
http://arxiv.org/abs/2106.04503v1
• [stat.ME]Efficient Estimation For The Joint Model of Survival and Longitudinal Data
Khandoker Akib Mohammad, Yuichi Hirose, Yuan Yao, Budhi Surya
http://arxiv.org/abs/2106.04142v1
• [stat.ME]Inference for Network Regression Models with Community Structure
Mengjie Pan, Tyler H. McCormick, Bailey K. Fosdick
http://arxiv.org/abs/2106.04271v1
• [stat.ME]Methodological considerations for estimating policy effects in the context of co-occurring policies
Beth Ann Griffin, Megan S. Schuler, Joseph Pane, Stephen W. Patrick, Rosanna Smart, Bradley D. Stein, Geoffrey Grimm, Elizabeth A. Stuart
http://arxiv.org/abs/2106.04304v1
• [stat.ME]Searching for consistent associations with a multi-environment knockoff filter
Shuangning Li, Matteo Sesia, Yaniv Romano, Emmanuel Candès, Chiara Sabatti
http://arxiv.org/abs/2106.04118v1
• [stat.ME]Singhing with Confidence: Visualising the Performance of Confidence Structures
Alexander Wimbush, Nicholas Gray, Scott Ferson
http://arxiv.org/abs/2106.04433v1
• [stat.ML]Adaptive transfer learning
Henry W. J. Reeve, Timothy I. Cannings, Richard J. Samworth
http://arxiv.org/abs/2106.04455v1
• [stat.ML]Batch Normalization Orthogonalizes Representations in Deep Random Networks
Hadi Daneshmand, Amir Joudaki, Francis Bach
http://arxiv.org/abs/2106.03970v1
• [stat.ML]Conditional Deep Inverse Rosenblatt Transports
Tiangang Cui, Sergey Dolgov, Olivier Zahm
http://arxiv.org/abs/2106.04170v1
• [stat.ML]Decentralized Learning in Online Queuing Systems
Flore Sentenac, Etienne Boursier, Vianney Perchet
http://arxiv.org/abs/2106.04228v1
• [stat.ML]Intrinsic Dimension Estimation
Adam Block, Zeyu Jia, Yury Polyanskiy, Alexander Rakhlin
http://arxiv.org/abs/2106.04018v1
• [stat.ML]Seismic Inverse Modeling Method based on Generative Adversarial Network
Pengfei Xie, YanShu Yin, JiaGen Hou, Mei Chen, Lixin Wang
http://arxiv.org/abs/2106.04197v1
• [stat.ML]Targeted Active Learning for Bayesian Decision-Making
Louis Filstroff, Iiris Sundin, Petrus Mikkola, Aleksei Tiulpin, Juuso Kylmäoja, Samuel Kaski
http://arxiv.org/abs/2106.04193v1
• [stat.ML]The Future is Log-Gaussian: ResNets and Their Infinite-Depth-and-Width Limit at Initialization
Mufan Bill Li, Mihai Nica, Daniel M. Roy
http://arxiv.org/abs/2106.04013v1
• [stat.ML]Weighted Sparse Subspace Representation: A Unified Framework for Subspace Clustering, Constrained Clustering, and Active Learning
Hankui Peng, Nicos G. Pavlidis
http://arxiv.org/abs/2106.04330v1