归档 - 今日学术视野(2021.6.12) - 《爱可可老师分享》

cond-mat.stat-mech - 统计数学
cs.AI - 人工智能
cs.AR - 硬件体系结构
cs.CG - 计算几何学
cs.CL - 计算与语言
cs.CR - 加密与安全
cs.CV - 机器视觉与模式识别
cs.CY - 计算与社会
cs.DC - 分布式、并行与集群计算
cs.DL - 数字图书馆
cs.DS - 数据结构与算法
cs.GR - 计算机图形学
cs.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.RO - 机器人学
cs.SD - 声音处理
cs.SI - 社交网络与信息网络
eess.AS - 语音处理
eess.IV - 图像与视频处理
eess.SP - 信号处理
eess.SY - 系统和控制
hep-lat - 高能物理晶格
math.NA - 数值分析
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.flu-dyn - 流体动力学
physics.ins-det - 仪器和探测器
physics.soc-ph - 物理学与社会
q-bio.QM - 定量方法
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.stat-mech]Mismatching as a tool to enhance algorithmic performances of Monte Carlo methods for the planted clique model
• [cs.AI]Brittle AI, Causal Confusion, and Bad Mental Models: Challenges and Successes in the XAI Program
• [cs.AI]Fairness for Cooperative Multi-Agent Learning with Equivariant Policies
• [cs.AI]SCARI: Separate and Conquer Algorithm for Action Rules and Recommendations Induction
• [cs.AI]Visual scoping operations for physical assembly
• [cs.AR]Vector Symbolic Architectures as a Computing Framework for Nanoscale Hardware
• [cs.CG]An adaptive Origin-Destination flows cluster-detecting method to identify urban mobility trends
• [cs.CL]A Template-guided Hybrid Pointer Network for Knowledge-basedTask-oriented Dialogue Systems
• [cs.CL]AGGGEN: Ordering and Aggregating while Generating
• [cs.CL]AUGNLG: Few-shot Natural Language Generation using Self-trained Data Augmentation
• [cs.CL]Automatic Construction of Context-Aware Sentiment Lexicon in the Financial Domain Using Direction-Dependent Words
• [cs.CL]CogAlign: Learning to Align Textual Neural Representations to Cognitive Language Processing Signals
• [cs.CL]Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models
• [cs.CL]DESCGEN: A Distantly Supervised Datasetfor Generating Abstractive Entity Descriptions
• [cs.CL]DT-grams: Structured Dependency Grammar Stylometry for Cross-Language Authorship Attribution
• [cs.CL]Data augmentation to improve robustness of image captioning solutions
• [cs.CL]Deciphering Implicit Hate: Evaluating Automated Detection Algorithms for Multimodal Hate
• [cs.CL]End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering
• [cs.CL]Exploring Unsupervised Pretraining Objectives for Machine Translation
• [cs.CL]FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information
• [cs.CL]GroupBERT: Enhanced Transformer Architecture with Efficient Grouped Structures
• [cs.CL]How Robust are Model Rankings: A Leaderboard Customization Approach for Equitable Evaluation
• [cs.CL]ImaginE: An Imagination-Based Automatic Evaluation Metric for Natural Language Generation
• [cs.CL]Input Augmentation Improves Constrained Beam Search for Neural Machine Translation: NTT at WAT 2021
• [cs.CL]KARI: KAnari/QCRI’s End-to-End systems for the INTERSPEECH 2021 Indian Languages Code-Switching Challenge
• [cs.CL]Linguistically Informed Masking for Representation Learning in the Patent Domain
• [cs.CL]Low-Dimensional Structure in the Space of Language Representations is Reflected in Brain Responses
• [cs.CL]Marginal Utility Diminishes: Exploring the Minimum Knowledge for BERT Knowledge Distillation
• [cs.CL]Neural Text Classification and StackedHeterogeneous Embeddings for Named Entity Recognition in SMM4H 2021
• [cs.CL]PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition
• [cs.CL]Parallel Deep Learning-Driven Sarcasm Detection from Pop Culture Text and English Humor Literature
• [cs.CL]Progressive Multi-Granularity Training for Non-Autoregressive Translation
• [cs.CL]Ruddit: Norms of Offensiveness for English Reddit Comments
• [cs.CL]Shades of BLEU, Flavours of Success: The Case of MultiWOZ
• [cs.CL]Synthesizing Adversarial Negative Responses for Robust Response Ranking and Evaluation
• [cs.CL]VT-SSum: A Benchmark Dataset for Video Transcript Segmentation and Summarization
• [cs.CL]Variational Information Bottleneck for Effective Low-Resource Fine-Tuning
• [cs.CR]AI-enabled Automation for Completeness Checking of Privacy Policies
• [cs.CR]Cross-chain Interaction Model In a Fully Verified Way
• [cs.CR]FedDICE: A ransomware spread detection in a distributed integrated clinical environment using federated learning and SDN based mitigation
• [cs.CR]HASI: Hardware-Accelerated Stochastic Inference, A Defense Against Adversarial Machine Learning Attacks
• [cs.CR]Reinforcement Learning for Industrial Control Network Cyber Security Orchestration
• [cs.CR]Semantic-aware Binary Code Representation with BERT
• [cs.CR]Towards an Automated Pipeline for Detecting and Classifying Malware through Machine Learning
• [cs.CV]A Dataset And Benchmark Of Underwater Object Detection For Robot Picking
• [cs.CV]AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection
• [cs.CV]Adaptive Streaming Perception using Deep Reinforcement Learning
• [cs.CV]Adversarial Motion Modelling helps Semi-supervised Hand Pose Estimation
• [cs.CV]CAT: Cross Attention in Vision Transformer
• [cs.CV]Chasing Sparsity in Vision Transformers: An End-to-End Exploration
• [cs.CV]Consistent Instance False Positive Improves Fairness in Face Recognition
• [cs.CV]Context-Free TextSpotter for Real-Time and Mobile End-to-End Text Detection and Recognition
• [cs.CV]Cross-Modal Discrete Representation Learning
• [cs.CV]Cross-domain Contrastive Learning for Unsupervised Domain Adaptation
• [cs.CV]Curiously Effective Features for Image Quality Prediction
• [cs.CV]DUET: Detection Utilizing Enhancement for Text in Scanned or Captured Documents
• [cs.CV]Date Estimation in the Wild of Scanned Historical Photos: An Image Retrieval Approach
• [cs.CV]Deep Implicit Surface Point Prediction Networks
• [cs.CV]Deep neural network loses attention to adversarial images
• [cs.CV]Distribution-Aware Semantics-Oriented Pseudo-label for Imbalanced Semi-Supervised Learning
• [cs.CV]Dynamics-Regulated Kinematic Policy for Egocentric Pose Estimation
• [cs.CV]Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images
• [cs.CV]Face mask detection using convolution neural network
• [cs.CV]FetReg: Placental Vessel Segmentation and Registration in Fetoscopy Challenge Dataset
• [cs.CV]Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spotter
• [cs.CV]Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold
• [cs.CV]Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training
• [cs.CV]Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers
• [cs.CV]Learning by Watching
• [cs.CV]Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification
• [cs.CV]Learning to See by Looking at Noise
• [cs.CV]MST: Masked Self-Supervised Transformer for Visual Representation
• [cs.CV]Match What Matters: Generative Implicit Feature Replay for Continual Learning
• [cs.CV]MiDeCon: Unsupervised and Accurate Fingerprint and Minutia Quality Assessment based on Minutia Detection Confidence
• [cs.CV]Multi-Dataset Benchmarks for Masked Identification using Contrastive Representation Learning
• [cs.CV]Multi-resolution Outlier Pooling for Sorghum Classification
• [cs.CV]Pivotal Tuning for Latent-based Editing of Real Images
• [cs.CV]Plan2Scene: Converting Floorplans to 3D Scenes
• [cs.CV]Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement
• [cs.CV]RLCorrector: Reinforced Proofreading for Connectomics Image Segmentation
• [cs.CV]Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
• [cs.CV]Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
• [cs.CV]SVMA: A GAN-based model for Monocular 3D Human Pose Estimation
• [cs.CV]Salient Object Ranking with Position-Preserved Attention
• [cs.CV]Self-Supervised 3D Hand Pose Estimation from monocular RGB via Contrastive Learning
• [cs.CV]Space-time Mixing Attention for Video Transformer
• [cs.CV]Spatially Invariant Unsupervised 3D Object Segmentation with Graph Neural Networks
• [cs.CV]Supervising the Transfer of Reasoning Patterns in VQA
• [cs.CV]Tensor feature hallucination for few-shot learning
• [cs.CV]The 2021 Hotel-ID to Combat Human Trafficking Competition Dataset
• [cs.CV]To The Point: Correspondence-driven monocular 3D category reconstruction
• [cs.CV]Unsupervised Co-part Segmentation through Assembly
• [cs.CV]Unsupervised Video Person Re-identification via Noise and Hard frame Aware Clustering
• [cs.CV]Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis
• [cs.CV]Very Compact Clusters with Structural Regularization via Similarity and Connectivity
• [cs.CV]Visual Sensor Pose Optimisation Using Rendering-based Visibility Models for Robust Cooperative Perception
• [cs.CV]We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature
• [cs.CV]What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
• [cs.CY]Algorithm Auditing at a Large-Scale: Insights from Search Engine Audits
• [cs.CY]Algorithms and Decision-Making in the Public Sector
• [cs.CY]It’s COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks
• [cs.DC]Cocktail: Leveraging Ensemble Learning for Optimized Model Serving in Public Cloud
• [cs.DC]Energy-Efficient Naming in Beeping Networks
• [cs.DC]IChannels: Exploiting Current Management Mechanisms to Create Covert Channels in Modern Processors
• [cs.DC]Jointly Optimize Coding and Node Selection for Distributed Computing over Wireless Edge Networks
• [cs.DC]PDMA: Probabilistic Service Migration Approach for Delay-aware and Mobility-aware Mobile Edge Computing
• [cs.DC]StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs
• [cs.DC]VaLiPro: Linear Programming Validator for Cluster Computing Systems
• [cs.DL]Academics evaluating academics: a methodology to inform the review process on top of open citations
• [cs.DL]Citation Recommendation for Research Papers via Knowledge Graphs
• [cs.DL]Studying the characteristics of scientific communities using individual-level bibliometrics: the case of Big Data research
• [cs.DS]Fair Disaster Containment via Graph-Cut Problems
• [cs.DS]Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time
• [cs.DS]Incremental space-filling design based on coverings and spacings: improving upon low discrepancy sequences
• [cs.DS]Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions
• [cs.GR]Deep Direct Volume Rendering: Learning Visual Feature Mappings From Exemplary Images
• [cs.GR]DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact
• [cs.HC]An Extensible Dashboard Architecture For Visualizing Base And Analyzed Data
• [cs.IR]Analyzing Non-Textual Content Elements to Detect Academic Plagiarism
• [cs.IR]Deep Position-wise Interaction Network for CTR Prediction
• [cs.IR]GRASP: Graph Alignment through Spectral Signatures
• [cs.IT]Aerial Reconfigurable Intelligent Surface-Aided Wireless Communication Systems
• [cs.IT]Efficient Recovery of a Shared Secret via Cooperation: Applications to SDMM and PIR
• [cs.IT]FRI-TEM: Time Encoding Sampling of Finite-Rate-of-Innovation Signals
• [cs.IT]Hybrid Spherical- and Planar-Wave Channel Modeling and DCNN-powered Estimation for Terahertz Ultra-massive MIMO Systems
• [cs.IT]Outage Performance of $今日学术视野(2021.6.12) - 图1$ D Mobile UAV Caching for Hybrid Satellite-Terrestrial Networks
• [cs.IT]Single-Server Private Linear Transformation: The Individual Privacy Case
• [cs.IT]Single-Server Private Linear Transformation: The Joint Privacy Case
• [cs.IT]The Isometry-Dual Property in Flags of Many-Point Algebraic Geometry Codes
• [cs.LG]A Bagging and Boosting Based Convexly Combined Optimum Mixture Probabilistic Model
• [cs.LG]A Deep Variational Approach to Clustering Survival Data
• [cs.LG]A Mathematical Foundation for Robust Machine Learning based on Bias-Variance Trade-off
• [cs.LG]A Neural Tangent Kernel Perspective of GANs
• [cs.LG]A New Notion of Individually Fair Clustering: $今日学术视野(2021.6.12) - 图2$ -Equitable $今日学术视野(2021.6.12) - 图3$ -Center
• [cs.LG]A Unified Framework for Task-Driven Data Quality Management
• [cs.LG]A concise method for feature selection via normalized frequencies
• [cs.LG]A multi-objective perspective on jointly tuning hardware and hyperparameters
• [cs.LG]Adversarial Graph Augmentation to Improve Graph Contrastive Learning
• [cs.LG]Adversarial Option-Aware Hierarchical Imitation Learning
• [cs.LG]Artificial Intelligence in Drug Discovery:Applications and Techniques
• [cs.LG]Attentional meta-learners are polythetic classifiers
• [cs.LG]Automated Self-Supervised Learning for Graphs
• [cs.LG]Bayesian Bellman Operators
• [cs.LG]Beyond BatchNorm: Towards a General Understanding of Normalization in Deep Learning
• [cs.LG]DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection
• [cs.LG]DMIDAS: Deep Mixed Data Sampling Regression for Long Multi-Horizon Time Series Forecasting
• [cs.LG]Deception in Social Learning: A Multi-Agent Reinforcement Learning Perspective
• [cs.LG]Disentangled Attention as Intrinsic Regularization for Bimanual Multi-Object Manipulation
• [cs.LG]Distance Metric Learning through Minimization of the Free Energy
• [cs.LG]Does Knowledge Distillation Really Work?
• [cs.LG]ERMAS: Becoming Robust to Reward Function Sim-to-Real Gaps in Multi-Agent Simulations
• [cs.LG]Early-stopped neural networks are consistent
• [cs.LG]Explaining Time Series Predictions with Dynamic Masks
• [cs.LG]Eye of the Beholder: Improved Relation Generalization for Text-based Reinforcement Learning Agents
• [cs.LG]Fair Classification with Adversarial Perturbations
• [cs.LG]Fair Normalizing Flows
• [cs.LG]Front Contribution instead of Back Propagation
• [cs.LG]GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
• [cs.LG]Graph Symbiosis Learning
• [cs.LG]GraphiT: Encoding Graph Structure in Transformers
• [cs.LG]Group Equivariant Subsampling
• [cs.LG]Hybrid Machine Learning Forecasts for the UEFA EURO 2020
• [cs.LG]Hyperspace Neighbor Penetration Approach to Dynamic Programming for Model-Based Reinforcement Learning Problems with Slowly Changing Variables in A Continuous State Space
• [cs.LG]Informative Policy Representations in Multi-Agent Reinforcement Learning via Joint-Action Distributions
• [cs.LG]Investigating Alternatives to the Root Mean Square for Adaptive Gradient Methods
• [cs.LG]Learnable Hypergraph Laplacian for Hypergraph Learning
• [cs.LG]Learning Based Proximity Matrix Factorization for Node Embedding
• [cs.LG]Leveraged Weighted Loss for Partial Label Learning
• [cs.LG]Long-time integration of parametric evolution equations with physics-informed DeepONets
• [cs.LG]Mode recovery in neural autoregressive sequence modeling
• [cs.LG]Multi-VFL: A Vertical Federated Learning System for Multiple Data and Label Owners
• [cs.LG]Next-Gen Machine Learning Supported Diagnostic Systems for Spacecraft
• [cs.LG]On the overlooked issue of defining explanation objectives for local-surrogate explainers
• [cs.LG]Online Learning for Stochastic Shortest Path Model via Posterior Sampling
• [cs.LG]Operationalizing Complex Causes: A Pragmatic View of Mediation
• [cs.LG]Optimizing Reusable Knowledge for Continual Learning via Metalearning
• [cs.LG]Parameter and Feature Selection in Stochastic Linear Bandits
• [cs.LG]Probing transfer learning with a model of synthetic correlated datasets
• [cs.LG]Programming Puzzles
• [cs.LG]Pulling back information geometry
• [cs.LG]Rare event estimation using stochastic spectral embedding
• [cs.LG]Score Matching Model for Unbounded Data Score
• [cs.LG]Simple Graph Convolutional Networks
• [cs.LG]Simplifying Deep Reinforcement Learning via Self-Supervision
• [cs.LG]Stein Latent Optimization for GANs
• [cs.LG]Temporal and Object Quantification Networks
• [cs.LG]Thompson Sampling with a Mixture Prior
• [cs.LG]Transformed CNNs: recasting pre-trained convolutional layers with self-attention
• [cs.LG]Understanding the Under-Coverage Bias in Uncertainty Estimation
• [cs.LG]Vector Quantized Models for Planning
• [cs.LG]Vertical Federated Learning without Revealing Intersection Membership
• [cs.LG]Zero Time Waste: Recycling Predictions in Early Exit Neural Networks
• [cs.LG]ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs
• [cs.MA]Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games
• [cs.NE]Spatiotemporal Spike-Pattern Selectivity in Single Mixed-Signal Neurons with Balanced Synapses
• [cs.NE]Swarm Intelligence for Self-Organized Clustering
• [cs.NE]Unsupervised Behaviour Discovery with Quality-Diversity Optimisation
• [cs.RO]3D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training
• [cs.RO]Convex Risk Bounded Continuous-Time Trajectory Planning in Uncertain Nonconvex Environments
• [cs.RO]DREAMS: Drilling and Extraction Automated System
• [cs.RO]Differentiable Robust LQR Layers
• [cs.SD]Improving multi-speaker TTS prosody variance with a residual encoder and normalizing flows
• [cs.SD]MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training
• [cs.SD]U2++: Unified Two-pass Bidirectional End-to-end Model for Speech Recognition
• [cs.SI]Italian Twitter semantic network during the Covid-19 epidemic
• [cs.SI]Mechanisms and Attributes of Echo Chambers in Social Media
• [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
• [eess.AS]Audiovisual transfer learning for audio tagging and sound event detection
• [eess.IV]Anatomy X-Net: A Semi-Supervised Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification
• [eess.IV]CALTeC: Content-Adaptive Linear Tensor Completion for Collaborative Intelligence
• [eess.IV]CoviLearn: A Machine Learning Integrated Smart X-Ray Device in Healthcare Cyber-Physical System for Automatic Initial Screening of COVID-19
• [eess.IV]Domain Specific Transporter Framework to Detect Fractures in Ultrasound
• [eess.IV]End-to-end lung nodule detection framework with model-based feature projection block
• [eess.IV]Joint Landmark and Structure Learning for Automatic Evaluation of Developmental Dysplasia of the Hip
• [eess.IV]Rethink Transfer Learning in Medical Image Classification
• [eess.IV]Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN
• [eess.IV]The Medical Segmentation Decathlon
• [eess.SP]Fastening the Initial Access in 5G NR Sidelink for 6G V2X Networks
• [eess.SP]SignalNet: A Low Resolution Sinusoid Decomposition and Estimation Network
• [eess.SY]Multiple Dynamic Pricing for Demand Response with Adaptive Clustering-based Customer Segmentation in Smart Grids
• [hep-lat]Flow-based sampling for fermionic lattice field theories
• [math.NA]A Discontinuity Capturing Shallow Neural Network for Elliptic Interface Problems
• [math.OC]Distributionally Robust Prescriptive Analytics with Wasserstein Distance
• [math.OC]Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach
• [math.OC]Near-Optimal High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise
• [math.OC]Public Transit for Special Events: Ridership Prediction and Train Optimization
• [math.OC]dFDA-VeD: A Dynamic Future Demand Aware Vehicle Dispatching System
• [math.PR]A Central Limit Theorem, Loss Aversion and Multi-Armed Bandits
• [math.ST]Bayesian inference of a non-local proliferation model
• [math.ST]Bias, Consistency, and Alternative Perspectives of the Infinitesimal Jackknife
• [math.ST]Confidence in Causal Discovery with Linear Causal Models
• [math.ST]Dependence and mixing for perturbations of copula-based Markov chains
• [math.ST]Information Geometry of Reversible Markov Chains
• [math.ST]Online Debiased Lasso
• [math.ST]Sign Consistency of the Generalized Elastic Net Estimator
• [math.ST]Strong Gaussian Approximation for the Sum of Random Vectors
• [physics.flu-dyn]Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models
• [physics.ins-det]CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing Flows
• [physics.soc-ph]Theoretical Modeling of Communication Dynamics
• [q-bio.QM]Adaptive machine learning for protein engineering
• [q-bio.QM]Fine-Grained System Identification of Nonlinear Neural Circuits
• [quant-ph]Grover’s Algorithm for Question Answering
• [quant-ph]Perturbation Theory for Quantum Information
• [quant-ph]Quantum Natural Gradient for Variational Bayes
• [stat.AP]Are We There Yet? Big Data Significantly Overestimates COVID-19 Vaccination in the US
• [stat.AP]Calculating the Likelihood Ratio for Multiple Pieces of Evidence
• [stat.AP]Dynamic Shape Modeling to Analyze Modes ofMigration During Cell Motility
• [stat.AP]Forecast combination based forecast reconciliation: insights and extensions
• [stat.AP]Global and Tail Dependence: A Differential Geometry Approach
• [stat.AP]On the Use of Data from Multiple Mobile Network Operators in Europe to fight COVID-19
• [stat.AP]Robust Prediction Interval estimation for Gaussian Processes by Cross-Validation method
• [stat.ME]A Variational View on Statistical Multiscale Estimation
• [stat.ME]A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint
• [stat.ME]Bayesian semi-parametric inference for diffusion processes using splines
• [stat.ME]Does Bayesian Model Averaging improve polynomial extrapolations? Two toy problems as tests
• [stat.ME]The Attraction Indian Buffet Distribution
• [stat.ML]An Interpretable Neural Network for Parameter Inference
• [stat.ML]Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features
• [stat.ML]DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel
• [stat.ML]Data augmentation in Bayesian neural networks and the cold posterior effect
• [stat.ML]From inexact optimization to learning via gradient concentration
• [stat.ML]GBHT: Gradient Boosting Histogram Transform for Density Estimation
• [stat.ML]Identifiability of interaction kernels in mean-field equations of interacting particles
• [stat.ML]Large-scale optimal transport map estimation using projection pursuit
• [stat.ML]Learning Nonparametric Volterra Kernels with Gaussian Processes
• [stat.ML]Linear Classifiers Under Infinite Imbalance
• [stat.ML]Loss function based second-order Jensen inequality and its application to particle variational inference
• [stat.ML]Matrix Completion with Model-free Weighting
• [stat.ML]Meta-Learning for Symbolic Hyperparameter Defaults
• [stat.ML]Quantized Conditional COT-GAN for Video Prediction
• [stat.ML]Score-based Generative Modeling in Latent Space
• [stat.ML]Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics
• [stat.ML]Support Recovery of Sparse Signals from a Mixture of Linear Measurements
• [stat.ML]Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows

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• [cond-mat.stat-mech]Mismatching as a tool to enhance algorithmic performances of Monte Carlo methods for the planted clique model
Maria Chiara Angelini, Paolo Fachin, Simone de Feo
http://arxiv.org/abs/2106.05720v1

• [cs.AI]Brittle AI, Causal Confusion, and Bad Mental Models: Challenges and Successes in the XAI Program
Jeff Druce, James Niehaus, Vanessa Moody, David Jensen, Michael L. Littman
http://arxiv.org/abs/2106.05506v1

• [cs.AI]Fairness for Cooperative Multi-Agent Learning with Equivariant Policies
Niko A. Grupen, Bart Selman, Daniel D. Lee
http://arxiv.org/abs/2106.05727v1

• [cs.AI]SCARI: Separate and Conquer Algorithm for Action Rules and Recommendations Induction
Marek Sikora, Paweł Matyszok, Łukasz Wróbel
http://arxiv.org/abs/2106.05348v1

• [cs.AI]Visual scoping operations for physical assembly
Felix J Binder, Marcelo M Mattar, David Kirsh, Judith E Fan
http://arxiv.org/abs/2106.05654v1

• [cs.AR]Vector Symbolic Architectures as a Computing Framework for Nanoscale Hardware
Denis Kleyko, Mike Davies, E. Paxon Frady, Pentti Kanerva, Spencer J. Kent, Bruno A. Olshausen, Evgeny Osipov, Jan M. Rabaey, Dmitri A. Rachkovskij, Abbas Rahimi, Friedrich T. Sommer
http://arxiv.org/abs/2106.05268v1

• [cs.CG]An adaptive Origin-Destination flows cluster-detecting method to identify urban mobility trends
Mengyuan Fang, Luliang Tang, Zihan Kan, Xue Yang, Tao Pei, Qingquan Li, Chaokui Li
http://arxiv.org/abs/2106.05436v1

• [cs.CL]A Template-guided Hybrid Pointer Network for Knowledge-basedTask-oriented Dialogue Systems
Dingmin Wang, Ziyao Chen, Wanwei He, Li Zhong, Yunzhe Tao, Min Yang
http://arxiv.org/abs/2106.05830v1

• [cs.CL]AGGGEN: Ordering and Aggregating while Generating
Xinnuo Xu, Ondřej Dušek, Verena Rieser, Ioannis Konstas
http://arxiv.org/abs/2106.05580v1

• [cs.CL]AUGNLG: Few-shot Natural Language Generation using Self-trained Data Augmentation
Xinnuo Xu, Guoyin Wang, Young-Bum Kim, Sungjin Lee
http://arxiv.org/abs/2106.05589v1

• [cs.CL]Automatic Construction of Context-Aware Sentiment Lexicon in the Financial Domain Using Direction-Dependent Words
Jihye Park, Hye Jin Lee, Sungzoon Cho
http://arxiv.org/abs/2106.05723v1

• [cs.CL]CogAlign: Learning to Align Textual Neural Representations to Cognitive Language Processing Signals
Yuqi Ren, Deyi Xiong
http://arxiv.org/abs/2106.05544v1

• [cs.CL]Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models
Tyler A. Chang, Yifan Xu, Weijian Xu, Zhuowen Tu
http://arxiv.org/abs/2106.05505v1

• [cs.CL]DESCGEN: A Distantly Supervised Datasetfor Generating Abstractive Entity Descriptions
Weijia Shi, Mandar Joshi, Luke Zettlemoyer
http://arxiv.org/abs/2106.05365v1

• [cs.CL]DT-grams: Structured Dependency Grammar Stylometry for Cross-Language Authorship Attribution
Benjamin Murauer, Günther Specht
http://arxiv.org/abs/2106.05677v1

• [cs.CL]Data augmentation to improve robustness of image captioning solutions
Shashank Bujimalla, Mahesh Subedar, Omesh Tickoo
http://arxiv.org/abs/2106.05437v1

• [cs.CL]Deciphering Implicit Hate: Evaluating Automated Detection Algorithms for Multimodal Hate
Austin Botelho, Bertie Vidgen, Scott A. Hale
http://arxiv.org/abs/2106.05903v1

• [cs.CL]End-to-End Training of Multi-Document Reader and Retriever for Open-Domain Question Answering
Devendra Singh Sachan, Siva Reddy, William Hamilton, Chris Dyer, Dani Yogatama
http://arxiv.org/abs/2106.05346v1

• [cs.CL]Exploring Unsupervised Pretraining Objectives for Machine Translation
Christos Baziotis, Ivan Titov, Alexandra Birch, Barry Haddow
http://arxiv.org/abs/2106.05634v1

• [cs.CL]FEVEROUS: Fact Extraction and VERification Over Unstructured and Structured information
Rami Aly, Zhijiang Guo, Michael Schlichtkrull, James Thorne, Andreas Vlachos, Christos Christodoulopoulos, Oana Cocarascu, Arpit Mittal
http://arxiv.org/abs/2106.05707v1

• [cs.CL]GroupBERT: Enhanced Transformer Architecture with Efficient Grouped Structures
Ivan Chelombiev, Daniel Justus, Douglas Orr, Anastasia Dietrich, Frithjof Gressmann, Alexandros Koliousis, Carlo Luschi
http://arxiv.org/abs/2106.05822v1

• [cs.CL]How Robust are Model Rankings: A Leaderboard Customization Approach for Equitable Evaluation
Swaroop Mishra, Anjana Arunkumar
http://arxiv.org/abs/2106.05532v1

• [cs.CL]ImaginE: An Imagination-Based Automatic Evaluation Metric for Natural Language Generation
Wanrong Zhu, Xin Eric Wang, An Yan, Miguel Eckstein, William Yang Wang
http://arxiv.org/abs/2106.05970v1

• [cs.CL]Input Augmentation Improves Constrained Beam Search for Neural Machine Translation: NTT at WAT 2021
Katsuki Chousa, Makoto Morishita
http://arxiv.org/abs/2106.05450v1

• [cs.CL]KARI: KAnari/QCRI’s End-to-End systems for the INTERSPEECH 2021 Indian Languages Code-Switching Challenge
Amir Hussein, Shammur Chowdhury, Ahmed Ali
http://arxiv.org/abs/2106.05885v1

• [cs.CL]Linguistically Informed Masking for Representation Learning in the Patent Domain
Sophia Althammer, Mark Buckley, Sebastian Hofstätter, Allan Hanbury
http://arxiv.org/abs/2106.05768v1

• [cs.CL]Low-Dimensional Structure in the Space of Language Representations is Reflected in Brain Responses
Richard Antonello, Javier Turek, Vy Vo, Alexander Huth
http://arxiv.org/abs/2106.05426v1

• [cs.CL]Marginal Utility Diminishes: Exploring the Minimum Knowledge for BERT Knowledge Distillation
Yuanxin Liu, Fandong Meng, Zheng Lin, Weiping Wang, Jie Zhou
http://arxiv.org/abs/2106.05691v1

• [cs.CL]Neural Text Classification and StackedHeterogeneous Embeddings for Named Entity Recognition in SMM4H 2021
Usama Yaseen, Stefan Langer
http://arxiv.org/abs/2106.05823v1

• [cs.CL]PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition
Cheng-I Jeff Lai, Yang Zhang, Alexander H. Liu, Shiyu Chang, Yi-Lun Liao, Yung-Sung Chuang, Kaizhi Qian, Sameer Khurana, David Cox, James Glass
http://arxiv.org/abs/2106.05933v1

• [cs.CL]Parallel Deep Learning-Driven Sarcasm Detection from Pop Culture Text and English Humor Literature
Sourav Das, Anup Kumar Kolya
http://arxiv.org/abs/2106.05752v1

• [cs.CL]Progressive Multi-Granularity Training for Non-Autoregressive Translation
Liang Ding, Longyue Wang, Xuebo Liu, Derek F. Wong, Dacheng Tao, Zhaopeng Tu
http://arxiv.org/abs/2106.05546v1

• [cs.CL]Ruddit: Norms of Offensiveness for English Reddit Comments
Rishav Hada, Sohi Sudhir, Pushkar Mishra, Helen Yannakoudakis, Saif M. Mohammad, Ekaterina Shutova
http://arxiv.org/abs/2106.05664v1

• [cs.CL]Shades of BLEU, Flavours of Success: The Case of MultiWOZ
Tomáš Nekvinda, Ondřej Dušek
http://arxiv.org/abs/2106.05555v1

• [cs.CL]Synthesizing Adversarial Negative Responses for Robust Response Ranking and Evaluation
Prakhar Gupta, Yulia Tsvetkov, Jeffrey P. Bigham
http://arxiv.org/abs/2106.05894v1

• [cs.CL]VT-SSum: A Benchmark Dataset for Video Transcript Segmentation and Summarization
Tengchao Lv, Lei Cui, Momcilo Vasilijevic, Furu Wei
http://arxiv.org/abs/2106.05606v1

• [cs.CL]Variational Information Bottleneck for Effective Low-Resource Fine-Tuning
Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson
http://arxiv.org/abs//abs/2106.05469v1

• [cs.CR]AI-enabled Automation for Completeness Checking of Privacy Policies
Orlando Amaral, Sallam Abualhaija, Damiano Torre, Mehrdad Sabetzadeh, Lionel C. Briand
http://arxiv.org/abs/2106.05688v1

• [cs.CR]Cross-chain Interaction Model In a Fully Verified Way
Hong Su
http://arxiv.org/abs/2106.05463v1

• [cs.CR]FedDICE: A ransomware spread detection in a distributed integrated clinical environment using federated learning and SDN based mitigation
Chandra Thapa, Kallol Krishna Karmakar, Alberto Huertas Celdran, Seyit Camtepe, Vijay Varadharajan, Surya Nepal
http://arxiv.org/abs/2106.05434v1

• [cs.CR]HASI: Hardware-Accelerated Stochastic Inference, A Defense Against Adversarial Machine Learning Attacks
Mohammad Hossein Samavatian, Saikat Majumdar, Kristin Barber, Radu Teodorescu
http://arxiv.org/abs/2106.05825v1

• [cs.CR]Reinforcement Learning for Industrial Control Network Cyber Security Orchestration
John Mern, Kyle Hatch, Ryan Silva, Jeff Brush, Mykel J. Kochenderfer
http://arxiv.org/abs/2106.05332v1

• [cs.CR]Semantic-aware Binary Code Representation with BERT
Hyungjoon Koo, Soyeon Park, Daejin Choi, Taesoo Kim
http://arxiv.org/abs/2106.05478v1

• [cs.CR]Towards an Automated Pipeline for Detecting and Classifying Malware through Machine Learning
Nicola Loi, Claudio Borile, Daniele Ucci
http://arxiv.org/abs/2106.05625v1

• [cs.CV]A Dataset And Benchmark Of Underwater Object Detection For Robot Picking
Chongwei Liu, Haojie Li, Shuchang Wang, Ming Zhu, Dong Wang, Xin Fan, Zhihui Wang
http://arxiv.org/abs/2106.05681v1

• [cs.CV]AFAN: Augmented Feature Alignment Network for Cross-Domain Object Detection
Hongsong Wang, Shengcai Liao, Ling Shao
http://arxiv.org/abs/2106.05499v1

• [cs.CV]Adaptive Streaming Perception using Deep Reinforcement Learning
Anurag Ghosh, Akshay Nambi, Aditya Singh, Harish YVS, Tanuja Ganu
http://arxiv.org/abs/2106.05665v1

• [cs.CV]Adversarial Motion Modelling helps Semi-supervised Hand Pose Estimation
Adrian Spurr, Pavlo Molchanov, Umar Iqbal, Jan Kautz, Otmar Hilliges
http://arxiv.org/abs/2106.05954v1

• [cs.CV]CAT: Cross Attention in Vision Transformer
Hezheng Lin, Xing Cheng, Xiangyu Wu, Fan Yang, Dong Shen, Zhongyuan Wang, Qing Song, Wei Yuan
http://arxiv.org/abs/2106.05786v1

• [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/2106.04533v2

• [cs.CV]Consistent Instance False Positive Improves Fairness in Face Recognition
Xingkun Xu, Yuge Huang, Pengcheng Shen, Shaoxin Li, Jilin Li, Feiyue Huang, Yong Li, Zhen Cui
http://arxiv.org/abs/2106.05519v1

• [cs.CV]Context-Free TextSpotter for Real-Time and Mobile End-to-End Text Detection and Recognition
Ryota Yoshihashi, Tomohiro Tanaka, Kenji Doi, Takumi Fujino, Naoaki Yamashita
http://arxiv.org/abs/2106.05611v1

• [cs.CV]Cross-Modal Discrete Representation Learning
Alexander H. Liu, SouYoung Jin, Cheng-I Jeff Lai, Andrew Rouditchenko, Aude Oliva, James Glass
http://arxiv.org/abs/2106.05438v1

• [cs.CV]Cross-domain Contrastive Learning for Unsupervised Domain Adaptation
Rui Wang, Zuxuan Wu, Zejia Weng, Jingjing Chen, Guo-Jun Qi, Yu-Gang Jiang
http://arxiv.org/abs/2106.05528v1

• [cs.CV]Curiously Effective Features for Image Quality Prediction
Sören Becker, Thomas Wiegand, Sebastian Bosse
http://arxiv.org/abs/2106.05946v1

• [cs.CV]DUET: Detection Utilizing Enhancement for Text in Scanned or Captured Documents
Eun-Soo Jung, HyeongGwan Son, Kyusam Oh, Yongkeun Yun, Soonhwan Kwon, Min Soo Kim
http://arxiv.org/abs/2106.05542v1

• [cs.CV]Date Estimation in the Wild of Scanned Historical Photos: An Image Retrieval Approach
Adrià Molina, Pau Riba, Lluis Gomez, Oriol Ramos-Terrades, Josep Lladós
http://arxiv.org/abs/2106.05618v1

• [cs.CV]Deep Implicit Surface Point Prediction Networks
Rahul Venkatesh, Tejan Karmali, Sarthak Sharma, Aurobrata Ghosh, László A. Jeni, R. Venkatesh Babu, Maneesh Singh
http://arxiv.org/abs/2106.05779v1

• [cs.CV]Deep neural network loses attention to adversarial images
Shashank Kotyan, Danilo Vasconcellos Vargas
http://arxiv.org/abs/2106.05657v1

• [cs.CV]Distribution-Aware Semantics-Oriented Pseudo-label for Imbalanced Semi-Supervised Learning
Youngtaek Oh, Dong-Jin Kim, In So Kweon
http://arxiv.org/abs/2106.05682v1

• [cs.CV]Dynamics-Regulated Kinematic Policy for Egocentric Pose Estimation
Zhengyi Luo, Ryo Hachiuma, Ye Yuan, Kris Kitani
http://arxiv.org/abs/2106.05969v1

• [cs.CV]Enforcing Morphological Information in Fully Convolutional Networks to Improve Cell Instance Segmentation in Fluorescence Microscopy Images
Willard Zamora-Cardenas, Mauro Mendez, Saul Calderon-Ramirez, Martin Vargas, Gerardo Monge, Steve Quiros, David Elizondo, David Elizondo, Miguel A. Molina-Cabello
http://arxiv.org/abs/2106.05843v1

• [cs.CV]Face mask detection using convolution neural network
Riya Shah Rutva Shah
http://arxiv.org/abs/2106.05728v1

• [cs.CV]FetReg: Placental Vessel Segmentation and Registration in Fetoscopy Challenge Dataset
Sophia Bano, Alessandro Casella, Francisco Vasconcelos, Sara Moccia, George Attilakos, Ruwan Wimalasundera, Anna L. David, Dario Paladini, Jan Deprest, Leonardo S. Mattos, Danail Stoyanov
http://arxiv.org/abs/2106.05923v1

• [cs.CV]Implicit Feature Alignment: Learn to Convert Text Recognizer to Text Spotter
Tianwei Wang, Yuanzhi Zhu, Lianwen Jin, Dezhi Peng, Zhe Li, Mengchao He, Yongpan Wang, Canjie Luo
http://arxiv.org/abs/2106.05920v1

• [cs.CV]Implicit-PDF: Non-Parametric Representation of Probability Distributions on the Rotation Manifold
Kieran Murphy, Carlos Esteves, Varun Jampani, Srikumar Ramalingam, Ameesh Makadia
http://arxiv.org/abs/2106.05965v1

• [cs.CV]Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training
Dawei Zhou, Nannan Wang, Xinbo Gao, Bo Han, Jun Yu, Xiaoyu Wang, Tongliang Liu
http://arxiv.org/abs/2106.05453v1

• [cs.CV]Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers
Mandela Patrick, Dylan Campbell, Yuki M. Asano, Ishan Misra Florian Metze, Christoph Feichtenhofer, Andrea Vedaldi, Jo\ão F. Henriques
http://arxiv.org/abs/2106.05392v1

• [cs.CV]Learning by Watching
Jimuyang Zhang, Eshed Ohn-Bar
http://arxiv.org/abs/2106.05966v1

• [cs.CV]Learning to Affiliate: Mutual Centralized Learning for Few-shot Classification
Yang Liu, Weifeng Zhang, Chao Xiang, Tu Zheng, Deng Cai
http://arxiv.org/abs/2106.05517v1

• [cs.CV]Learning to See by Looking at Noise
Manel Baradad, Jonas Wulff, Tongzhou Wang, Phillip Isola, Antonio Torralba
http://arxiv.org/abs/2106.05963v1

• [cs.CV]MST: Masked Self-Supervised Transformer for Visual Representation
Zhaowen Li, Zhiyang Chen, Fan Yang, Wei Li, Yousong Zhu, Chaoyang Zhao, Rui Deng, Liwei Wu, Rui Zhao, Ming Tang, Jinqiao Wang
http://arxiv.org/abs/2106.05656v1

• [cs.CV]Match What Matters: Generative Implicit Feature Replay for Continual Learning
Kevin Thandiackal, Tiziano Portenier, Andrea Giovannini, Maria Gabrani, Orcun Goksel
http://arxiv.org/abs/2106.05350v1

• [cs.CV]MiDeCon: Unsupervised and Accurate Fingerprint and Minutia Quality Assessment based on Minutia Detection Confidence
Philipp Terhörst, André Boller, Naser Damer, Florian Kirchbuchner, Arjan Kuijper
http://arxiv.org/abs/2106.05601v1

• [cs.CV]Multi-Dataset Benchmarks for Masked Identification using Contrastive Representation Learning
Sachith Seneviratne, Nuran Kasthuriaarachchi, Sanka Rasnayaka
http://arxiv.org/abs/2106.05596v1

• [cs.CV]Multi-resolution Outlier Pooling for Sorghum Classification
Chao Ren, Justin Dulay, Gregory Rolwes, Duke Pauli, Nadia Shakoor, Abby Stylianou
http://arxiv.org/abs/2106.05748v1

• [cs.CV]Pivotal Tuning for Latent-based Editing of Real Images
Daniel Roich, Ron Mokady, Amit H. Bermano, Daniel Cohen-Or
http://arxiv.org/abs/2106.05744v1

• [cs.CV]Plan2Scene: Converting Floorplans to 3D Scenes
Madhawa Vidanapathirana, Qirui Wu, Yasutaka Furukawa, Angel X. Chang, Manolis Savva
http://arxiv.org/abs/2106.05375v1

• [cs.CV]Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement
Zefan Li, Chenxi Li, Alan Yuille, Bingbing Ni, Wenjun Zhang, Wen Gao
http://arxiv.org/abs/2106.05554v1

• [cs.CV]RLCorrector: Reinforced Proofreading for Connectomics Image Segmentation
Khoa Tuan Nguyen, Ganghee Jang, Won-ki Jeong
http://arxiv.org/abs/2106.05487v1

• [cs.CV]Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
Wouter Van Gansbeke, Simon Vandenhende, Stamatios Georgoulis, Luc Van Gool
http://arxiv.org/abs/2106.05967v1

• [cs.CV]Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline
Ankit Goyal, Hei Law, Bowei Liu, Alejandro Newell, Jia Deng
http://arxiv.org/abs/2106.05304v1

• [cs.CV]SVMA: A GAN-based model for Monocular 3D Human Pose Estimation
Yicheng Deng, Yongqi Sun, Jiahui Zhu
http://arxiv.org/abs/2106.05616v1

• [cs.CV]Salient Object Ranking with Position-Preserved Attention
Hao Fang, Daoxin Zhang, Yi Zhang, Minghao Chen, Jiawei Li, Yao Hu, Deng Cai, Xiaofei He
http://arxiv.org/abs/2106.05047v2

• [cs.CV]Self-Supervised 3D Hand Pose Estimation from monocular RGB via Contrastive Learning
Adrian Spurr, Aneesh Dahiya, Xucong Zhang, Xi Wang, Otmar Hilliges
http://arxiv.org/abs/2106.05953v1

• [cs.CV]Space-time Mixing Attention for Video Transformer
Adrian Bulat, Juan-Manuel Perez-Rua, Swathikiran Sudhakaran, Brais Martinez, Georgios Tzimiropoulos
http://arxiv.org/abs/2106.05968v1

• [cs.CV]Spatially Invariant Unsupervised 3D Object Segmentation with Graph Neural Networks
Tianyu Wang, Kee Siong Ng, Miaomiao Liu
http://arxiv.org/abs/2106.05607v1

• [cs.CV]Supervising the Transfer of Reasoning Patterns in VQA
Corentin Kervadec, Christian Wolf, Grigory Antipov, Moez Baccouche, Madiha Nadri
http://arxiv.org/abs/2106.05597v1

• [cs.CV]Tensor feature hallucination for few-shot learning
Michalis Lazarou, Yannis Avrithis, Tania Stathaki
http://arxiv.org/abs/2106.05321v1

• [cs.CV]The 2021 Hotel-ID to Combat Human Trafficking Competition Dataset
Rashmi Kamath, Greg Rolwes, Samuel Black, Abby Stylianou
http://arxiv.org/abs/2106.05746v1

• [cs.CV]To The Point: Correspondence-driven monocular 3D category reconstruction
Filippos Kokkinos, Iasonas Kokkinos
http://arxiv.org/abs/2106.05662v1

• [cs.CV]Unsupervised Co-part Segmentation through Assembly
Qingzhe Gao, Bin Wang, Libin Liu, Baoquan Chen
http://arxiv.org/abs/2106.05897v1

• [cs.CV]Unsupervised Video Person Re-identification via Noise and Hard frame Aware Clustering
Pengyu Xie, Xin Xu, Zheng Wang, Toshihiko Yamasaki
http://arxiv.org/abs/2106.05441v1

• [cs.CV]Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis
Julia Rosenzweig, Eduardo Brito, Hans-Ulrich Kobialka, Maram Akila, Nico M. Schmidt, Peter Schlicht, Jan David Schneider, Fabian Hüger, Matthias Rottmann, Sebastian Houben, Tim Wirtz
http://arxiv.org/abs/2106.05549v1

• [cs.CV]Very Compact Clusters with Structural Regularization via Similarity and Connectivity
Xin Ma, Won Hwa Kim
http://arxiv.org/abs/2106.05430v1

• [cs.CV]Visual Sensor Pose Optimisation Using Rendering-based Visibility Models for Robust Cooperative Perception
Eduardo Arnold, Sajjad Mozaffari, Mehrdad Dianati, Paul Jennings
http://arxiv.org/abs/2106.05308v1

• [cs.CV]We Can Always Catch You: Detecting Adversarial Patched Objects WITH or WITHOUT Signature
Bin Liang, Jiachun Li, Jianjun Huang
http://arxiv.org/abs/2106.05261v2

• [cs.CV]What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments?
Weijian Deng, Stephen Gould, Liang Zheng
http://arxiv.org/abs/2106.05961v1

• [cs.CY]Algorithm Auditing at a Large-Scale: Insights from Search Engine Audits
Roberto Ulloa, Mykola Makhortykh, Aleksandra Urman
http://arxiv.org/abs/2106.05831v1

• [cs.CY]Algorithms and Decision-Making in the Public Sector
Karen Levy, Kyla Chasalow, Sarah Riley
http://arxiv.org/abs/2106.03673v2

• [cs.CY]It’s COMPASlicated: The Messy Relationship between RAI Datasets and Algorithmic Fairness Benchmarks
Michelle Bao, Angela Zhou, Samantha Zottola, Brian Brubach, Sarah Desmarais, Aaron Horowitz, Kristian Lum, Suresh Venkatasubramanian
http://arxiv.org/abs/2106.05498v1

• [cs.DC]Cocktail: Leveraging Ensemble Learning for Optimized Model Serving in Public Cloud
Jashwant Raj Gunasekaran, Cyan Subhra Mishra, Prashanth Thinakaran, Mahmut Taylan Kandemir, Chita R. Das
http://arxiv.org/abs/2106.05345v1

• [cs.DC]Energy-Efficient Naming in Beeping Networks
Ny Aina Andriambolamalala, Vlady Ravelomanana
http://arxiv.org/abs/2106.03753v2

• [cs.DC]IChannels: Exploiting Current Management Mechanisms to Create Covert Channels in Modern Processors
Jawad Haj-Yahya, Jeremie S. Kim, A. Giray Yaglikci, Ivan Puddu, Lois Orosa, Juan Gómez Luna, Mohammed Alser, Onur Mutlu
http://arxiv.org/abs/2106.05050v2

• [cs.DC]Jointly Optimize Coding and Node Selection for Distributed Computing over Wireless Edge Networks
Cong T. Nguyen, Diep N. Nguyen, Dinh Thai Hoang, Hoang-Anh Pham, Eryk Dutkiewicz
http://arxiv.org/abs/2106.05475v1

• [cs.DC]PDMA: Probabilistic Service Migration Approach for Delay-aware and Mobility-aware Mobile Edge Computing
Minxian Xu, Qiheng Zhou, Huaming Wu, Weiwei Lin, Kejiang Ye, Chengzhong Xu
http://arxiv.org/abs/2106.05584v1

• [cs.DC]StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs
Artur Podobas, Martin Svedin, Steven W. D. Chien, Ivy B. Peng, Naresh Balaji Ravichandran, Pawel Herman, Anders Lansner, Stefano Markidis
http://arxiv.org/abs/2106.05373v1

• [cs.DC]VaLiPro: Linear Programming Validator for Cluster Computing Systems
Leonid B. Sokolinsky, Irina M. Sokolinskaya
http://arxiv.org/abs/2106.05485v1

• [cs.DL]Academics evaluating academics: a methodology to inform the review process on top of open citations
Federica Bologna, Angelo Di Iorio, Silvio Peroni, Francesco Poggi
http://arxiv.org/abs/2106.05725v1

• [cs.DL]Citation Recommendation for Research Papers via Knowledge Graphs
Arthur Brack, Anett Hoppe, Ralph Ewerth
http://arxiv.org/abs/2106.05633v1

• [cs.DL]Studying the characteristics of scientific communities using individual-level bibliometrics: the case of Big Data research
Xiaozan Lyu, Rodrigo Costas
http://arxiv.org/abs/2106.05581v1

• [cs.DS]Fair Disaster Containment via Graph-Cut Problems
Amy Babay, Michael Dinitz, Prathyush Sambaturu, Aravind Srinivasan, Leonidas Tsepenekas, Anil Vullikanti
http://arxiv.org/abs/2106.05424v1

• [cs.DS]Hierarchical Agglomerative Graph Clustering in Nearly-Linear Time
Laxman Dhulipala, David Eisenstat, Jakub Łącki, Vahab Mirrokni, Jessica Shi
http://arxiv.org/abs/2106.05610v1

• [cs.DS]Incremental space-filling design based on coverings and spacings: improving upon low discrepancy sequences
Amaya Nogales Gómez, Luc Pronzato, Maria-João Rendas
http://arxiv.org/abs/2106.05833v1

• [cs.DS]Lower Bounds on Metropolized Sampling Methods for Well-Conditioned Distributions
Yin Tat Lee, Ruoqi Shen, Kevin Tian
http://arxiv.org/abs/2106.05480v1

• [cs.GR]Deep Direct Volume Rendering: Learning Visual Feature Mappings From Exemplary Images
Jakob Weiss, Nassir Navab
http://arxiv.org/abs/2106.05429v1

• [cs.GR]DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact
Yifei Li, Tao Du, Kui Wu, Jie Xu, Wojciech Matusik
http://arxiv.org/abs/2106.05306v1

• [cs.HC]An Extensible Dashboard Architecture For Visualizing Base And Analyzed Data
Abhishek Santra, Kunal Samant, Endrit Memeti, Enamul Karim, Sharma Chakravarthy
http://arxiv.org/abs/2106.05357v1

• [cs.IR]Analyzing Non-Textual Content Elements to Detect Academic Plagiarism
Norman Meuschke
http://arxiv.org/abs/2106.05764v1

• [cs.IR]Deep Position-wise Interaction Network for CTR Prediction
Jianqiang Huang, Ke Hu, Qingtao Tang, Mingjian Chen, Yi Qi, Jia Cheng, Jun Lei
http://arxiv.org/abs/2106.05482v1

• [cs.IR]GRASP: Graph Alignment through Spectral Signatures
Judith Hermanns, Anton Tsitsulin, Marina Munkhoeva, Alex Bronstein, Davide Mottin, Panagiotis Karras
http://arxiv.org/abs/2106.05729v1

• [cs.IT]Aerial Reconfigurable Intelligent Surface-Aided Wireless Communication Systems
Tri Nhu Do, Georges Kaddoum, Thanh Luan Nguyen, Daniel Benevides da Costa, Zygmunt J. Haas
http://arxiv.org/abs/2106.05380v1

• [cs.IT]Efficient Recovery of a Shared Secret via Cooperation: Applications to SDMM and PIR
Jie Li, Camilla Hollanti, Oliver Gnilke
http://arxiv.org/abs/2106.05785v1

• [cs.IT]FRI-TEM: Time Encoding Sampling of Finite-Rate-of-Innovation Signals
Hila Namman, Satish Mulleti, Yonina C. Eldar
http://arxiv.org/abs/2106.05564v1

• [cs.IT]Hybrid Spherical- and Planar-Wave Channel Modeling and DCNN-powered Estimation for Terahertz Ultra-massive MIMO Systems
Yuhang Chen, Longfei Yan, Chong Han
http://arxiv.org/abs/2106.05491v1

• [cs.IT]Outage Performance of $今日学术视野(2021.6.12) - 图4$ D Mobile UAV Caching for Hybrid Satellite-Terrestrial Networks
Pankaj K. Sharma, Deepika Gupta, Dong In Kim
http://arxiv.org/abs/2106.05671v1

• [cs.IT]Single-Server Private Linear Transformation: The Individual Privacy Case
Anoosheh Heidarzadeh, Nahid Esmati, Alex Sprintson
http://arxiv.org/abs/2106.05222v2

• [cs.IT]Single-Server Private Linear Transformation: The Joint Privacy Case
Anoosheh Heidarzadeh, Nahid Esmati, Alex Sprintson
http://arxiv.org/abs/2106.05220v2

• [cs.IT]The Isometry-Dual Property in Flags of Many-Point Algebraic Geometry Codes
Maria Bras-Amorós, Alonso S. Castellanos, Luciane Quoos
http://arxiv.org/abs/2106.05600v1

• [cs.LG]A Bagging and Boosting Based Convexly Combined Optimum Mixture Probabilistic Model
Mian Arif Shams Adnan, H. M. Miraz Mahmud
http://arxiv.org/abs/2106.05840v1

• [cs.LG]A Deep Variational Approach to Clustering Survival Data
Laura Manduchi, Ričards Marcinkevičs, Michela C. Massi, Verena Gotta, Timothy Müller, Flavio Vasella, Marian C. Neidert, Marc Pfister, Julia E. Vogt
http://arxiv.org/abs/2106.05763v1

• [cs.LG]A Mathematical Foundation for Robust Machine Learning based on Bias-Variance Trade-off
Ou Wu, Weiyao Zhu, Yingjun Deng, Haixiang Zhang, Qinghu Hou
http://arxiv.org/abs/2106.05522v1

• [cs.LG]A Neural Tangent Kernel Perspective of GANs
Jean-Yves Franceschi, Emmanuel de Bézenac, Ibrahim Ayed, Mickaël Chen, Sylvain Lamprier, Patrick Gallinari
http://arxiv.org/abs/2106.05566v1

• [cs.LG]A New Notion of Individually Fair Clustering: $今日学术视野(2021.6.12) - 图5$ -Equitable $今日学术视野(2021.6.12) - 图6$ -Center
Darshan Chakrabarti, John P. Dickerson, Seyed A. Esmaeili, Aravind Srinivasan, Leonidas Tsepenekas
http://arxiv.org/abs/2106.05423v1

• [cs.LG]A Unified Framework for Task-Driven Data Quality Management
Tianhao Wang, Yi Zeng, Ming Jin, Ruoxi Jia
http://arxiv.org/abs/2106.05484v1

• [cs.LG]A concise method for feature selection via normalized frequencies
Song Tan, Xia He
http://arxiv.org/abs/2106.05814v1

• [cs.LG]A multi-objective perspective on jointly tuning hardware and hyperparameters
David Salinas, Valerio Perrone, Olivier Cruchant, Cedric Archambeau
http://arxiv.org/abs/2106.05680v1

• [cs.LG]Adversarial Graph Augmentation to Improve Graph Contrastive Learning
Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville
http://arxiv.org/abs/2106.05819v1

• [cs.LG]Adversarial Option-Aware Hierarchical Imitation Learning
Mingxuan Jing, Wenbing Huang, Fuchun Sun, Xiaojian Ma, Tao Kong, Chuang Gan, Lei Li
http://arxiv.org/abs/2106.05530v1

• [cs.LG]Artificial Intelligence in Drug Discovery:Applications and Techniques
Jianyuan Deng, Zhibo Yang, Dimitris Samaras, Fusheng Wang
http://arxiv.org/abs/2106.05386v1

• [cs.LG]Attentional meta-learners are polythetic classifiers
Ben Day, Ramon Viñas, Nikola Simidjievski, Pietro Liò
http://arxiv.org/abs/2106.05317v1

• [cs.LG]Automated Self-Supervised Learning for Graphs
Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
http://arxiv.org/abs/2106.05470v1

• [cs.LG]Bayesian Bellman Operators
Matthew Fellows, Kristian Hartikainen, Shimon Whiteson
http://arxiv.org/abs/2106.05012v2

• [cs.LG]Beyond BatchNorm: Towards a General Understanding of Normalization in Deep Learning
Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka
http://arxiv.org/abs/2106.05956v1

• [cs.LG]DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection
Hadi Hojjati, Narges Armanfard
http://arxiv.org/abs/2106.05410v1

• [cs.LG]DMIDAS: Deep Mixed Data Sampling Regression for Long Multi-Horizon Time Series Forecasting
Cristian Challu, Kin G. Olivares, Gus Welter, Artur Dubrawski
http://arxiv.org/abs/2106.05860v1

• [cs.LG]Deception in Social Learning: A Multi-Agent Reinforcement Learning Perspective
Paul Chelarescu
http://arxiv.org/abs/2106.05402v1

• [cs.LG]Disentangled Attention as Intrinsic Regularization for Bimanual Multi-Object Manipulation
Minghao Zhang, Pingcheng Jian, Yi Wu, Huazhe Xu, Xiaolong Wang
http://arxiv.org/abs/2106.05907v1

• [cs.LG]Distance Metric Learning through Minimization of the Free Energy
Dusan Stosic, Darko Stosic, Teresa B. Ludermir, Borko Stosic
http://arxiv.org/abs/2106.05495v1

• [cs.LG]Does Knowledge Distillation Really Work?
Samuel Stanton, Pavel Izmailov, Polina Kirichenko, Alexander A. Alemi, Andrew Gordon Wilson
http://arxiv.org/abs/2106.05945v1

• [cs.LG]ERMAS: Becoming Robust to Reward Function Sim-to-Real Gaps in Multi-Agent Simulations
Eric Zhao, Alexander R. Trott, Caiming Xiong, Stephan Zheng
http://arxiv.org/abs/2106.05492v1

• [cs.LG]Early-stopped neural networks are consistent
Ziwei Ji, Justin D. Li, Matus Telgarsky
http://arxiv.org/abs/2106.05932v1

• [cs.LG]Explaining Time Series Predictions with Dynamic Masks
Jonathan Crabbé, Mihaela van der Schaar
http://arxiv.org/abs/2106.05303v1

• [cs.LG]Eye of the Beholder: Improved Relation Generalization for Text-based Reinforcement Learning Agents
Keerthiram Murugesan, Subhajit Chaudhury, Kartik Talamadupula
http://arxiv.org/abs/2106.05387v1

• [cs.LG]Fair Classification with Adversarial Perturbations
L. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi
http://arxiv.org/abs/2106.05964v1

• [cs.LG]Fair Normalizing Flows
Mislav Balunović, Anian Ruoss, Martin Vechev
http://arxiv.org/abs/2106.05937v1

• [cs.LG]Front Contribution instead of Back Propagation
Swaroop Mishra, Anjana Arunkumar
http://arxiv.org/abs/2106.05569v1

• [cs.LG]GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
Matthias Fey, Jan E. Lenssen, Frank Weichert, Jure Leskovec
http://arxiv.org/abs/2106.05609v1

• [cs.LG]Graph Symbiosis Learning
Liang Zeng, Jin Xu, Zijun Yao, Yanqiao Zhu, Jian Li
http://arxiv.org/abs/2106.05455v1

• [cs.LG]GraphiT: Encoding Graph Structure in Transformers
Grégoire Mialon, Dexiong Chen, Margot Selosse, Julien Mairal
http://arxiv.org/abs/2106.05667v1

• [cs.LG]Group Equivariant Subsampling
Jin Xu, Hyunjik Kim, Tom Rainforth, Yee Whye Teh
http://arxiv.org/abs/2106.05886v1

• [cs.LG]Hybrid Machine Learning Forecasts for the UEFA EURO 2020
Andreas Groll, Lars Magnus Hvattum, Christophe Ley, Franziska Popp, Gunther Schauberger, Hans Van Eetvelde, Achim Zeileis
http://arxiv.org/abs/2106.05799v1

• [cs.LG]Hyperspace Neighbor Penetration Approach to Dynamic Programming for Model-Based Reinforcement Learning Problems with Slowly Changing Variables in A Continuous State Space
Vincent Zha, Ivey Chiu, Alexandre Guilbault, Jaime Tatis
http://arxiv.org/abs/2106.05497v1

• [cs.LG]Informative Policy Representations in Multi-Agent Reinforcement Learning via Joint-Action Distributions
Yifan Yu, Haobin Jiang, Zongqing Lu
http://arxiv.org/abs/2106.05802v1

• [cs.LG]Investigating Alternatives to the Root Mean Square for Adaptive Gradient Methods
Brett Daley, Christopher Amato
http://arxiv.org/abs/2106.05449v1

• [cs.LG]Learnable Hypergraph Laplacian for Hypergraph Learning
Jiying Zhang, Yuzhao Chen, Xi Xiao, Runiu Lu, Shu-Tao Xia
http://arxiv.org/abs/2106.05701v1

• [cs.LG]Learning Based Proximity Matrix Factorization for Node Embedding
Xingyi Zhang, Kun Xie, Sibo Wang, Zengfeng Huang
http://arxiv.org/abs/2106.05476v1

• [cs.LG]Leveraged Weighted Loss for Partial Label Learning
Hongwei Wen, Jingyi Cui, Hanyuan Hang, Jiabin Liu, Yisen Wang, Zhouchen Lin
http://arxiv.org/abs/2106.05731v1

• [cs.LG]Long-time integration of parametric evolution equations with physics-informed DeepONets
Sifan Wang, Paris Perdikaris
http://arxiv.org/abs/2106.05384v1

• [cs.LG]Mode recovery in neural autoregressive sequence modeling
Ilia Kulikov, Sean Welleck, Kyunghyun Cho
http://arxiv.org/abs/2106.05459v1

• [cs.LG]Multi-VFL: A Vertical Federated Learning System for Multiple Data and Label Owners
Vaikkunth Mugunthan, Pawan Goyal, Lalana Kagal
http://arxiv.org/abs/2106.05468v1

• [cs.LG]Next-Gen Machine Learning Supported Diagnostic Systems for Spacecraft
Athanasios Vlontzos, Gabriel Sutherland, Siddha Ganju, Frank Soboczenski
http://arxiv.org/abs/2106.05659v1

• [cs.LG]On the overlooked issue of defining explanation objectives for local-surrogate explainers
Rafael Poyiadzi, Xavier Renard, Thibault Laugel, Raul Santos-Rodriguez, Marcin Detyniecki
http://arxiv.org/abs/2106.05810v1

• [cs.LG]Online Learning for Stochastic Shortest Path Model via Posterior Sampling
Mehdi Jafarnia-Jahromi, Liyu Chen, Rahul Jain, Haipeng Luo
http://arxiv.org/abs/2106.05335v1

• [cs.LG]Operationalizing Complex Causes: A Pragmatic View of Mediation
Limor Gultchin, David S. Watson, Matt J. Kusner, Ricardo Silva
http://arxiv.org/abs/2106.05074v2

• [cs.LG]Optimizing Reusable Knowledge for Continual Learning via Metalearning
Julio Hurtado, Alain Raymond-Saez, Alvaro Soto
http://arxiv.org/abs/2106.05390v1

• [cs.LG]Parameter and Feature Selection in Stochastic Linear Bandits
Ahmadreza Moradipari, Yasin Abbasi-Yadkori, Mahnoosh Alizadeh, Mohammad Ghavamzadeh
http://arxiv.org/abs/2106.05378v1

• [cs.LG]Probing transfer learning with a model of synthetic correlated datasets
Federica Gerace, Luca Saglietti, Stefano Sarao Mannelli, Andrew Saxe, Lenka Zdeborová
http://arxiv.org/abs/2106.05418v1

• [cs.LG]Programming Puzzles
Tal Schuster, Ashwin Kalyan, Oleksandr Polozov, Adam Tauman Kalai
http://arxiv.org/abs/2106.05784v1

• [cs.LG]Pulling back information geometry
Georgios Arvanitidis, Miguel González-Duque, Alison Pouplin, Dimitris Kalatzis, Søren Hauberg
http://arxiv.org/abs/2106.05367v1

• [cs.LG]Rare event estimation using stochastic spectral embedding
P. -R. Wagner, S. Marelli, I. Papaioannou, D. Straub, B. Sudret
http://arxiv.org/abs/2106.05824v1

• [cs.LG]Score Matching Model for Unbounded Data Score
Dongjun Kim, Seungjae Shin, Kyungwoo Song, Wanmo Kang, Il-Chul Moon
http://arxiv.org/abs/2106.05527v1

• [cs.LG]Simple Graph Convolutional Networks
Luca Pasa, Nicolò Navarin, Wolfgang Erb, Alessandro Sperduti
http://arxiv.org/abs/2106.05809v1

• [cs.LG]Simplifying Deep Reinforcement Learning via Self-Supervision
Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu
http://arxiv.org/abs/2106.05526v1

• [cs.LG]Stein Latent Optimization for GANs
Uiwon Hwang, Heeseung Kim, Dahuin Jung, Hyemi Jang, Hyungyu Lee, Sungroh Yoon
http://arxiv.org/abs/2106.05319v1

• [cs.LG]Temporal and Object Quantification Networks
Jiayuan Mao, Zhezheng Luo, Chuang Gan, Joshua B. Tenenbaum, Jiajun Wu, Leslie Pack Kaelbling, Tomer D. Ullman
http://arxiv.org/abs/2106.05891v1

• [cs.LG]Thompson Sampling with a Mixture Prior
Joey Hong, Branislav Kveton, Manzil Zaheer, Mohammad Ghavamzadeh, Craig Boutilier
http://arxiv.org/abs/2106.05608v1

• [cs.LG]Transformed CNNs: recasting pre-trained convolutional layers with self-attention
Stéphane d’Ascoli, Levent Sagun, Giulio Biroli, Ari Morcos
http://arxiv.org/abs/2106.05795v1

• [cs.LG]Understanding the Under-Coverage Bias in Uncertainty Estimation
Yu Bai, Song Mei, Huan Wang, Caiming Xiong
http://arxiv.org/abs/2106.05515v1

• [cs.LG]Vector Quantized Models for Planning
Sherjil Ozair, Yazhe Li, Ali Razavi, Ioannis Antonoglou, Aäron van den Oord, Oriol Vinyals
http://arxiv.org/abs/2106.04615v2

• [cs.LG]Vertical Federated Learning without Revealing Intersection Membership
Jiankai Sun, Xin Yang, Yuanshun Yao, Aonan Zhang, Weihao Gao, Junyuan Xie, Chong Wang
http://arxiv.org/abs/2106.05508v1

• [cs.LG]Zero Time Waste: Recycling Predictions in Early Exit Neural Networks
Maciej Wołczyk, Bartosz Wójcik, Klaudia Bałazy, Igor Podolak, Jacek Tabor, Marek Śmieja, Tomasz Trzciński
http://arxiv.org/abs/2106.05409v1

• [cs.LG]ZoPE: A Fast Optimizer for ReLU Networks with Low-Dimensional Inputs
Christopher A. Strong, Sydney M. Katz, Anthony L. Corso, Mykel J. Kochenderfer
http://arxiv.org/abs/2106.05325v1

• [cs.MA]Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games
Xiangyu Liu, Hangtian Jia, Ying Wen, Yaodong Yang, Yujing Hu, Yingfeng Chen, Changjie Fan, Zhipeng Hu
http://arxiv.org/abs/2106.04958v2

• [cs.NE]Spatiotemporal Spike-Pattern Selectivity in Single Mixed-Signal Neurons with Balanced Synapses
Mattias Nilsson, Foteini Liwicki, Fredrik Sandin
http://arxiv.org/abs/2106.05686v1

• [cs.NE]Swarm Intelligence for Self-Organized Clustering
Michael C. Thrun, Alfred Ultsch
http://arxiv.org/abs/2106.05521v1

• [cs.NE]Unsupervised Behaviour Discovery with Quality-Diversity Optimisation
Luca Grillotti, Antoine Cully
http://arxiv.org/abs/2106.05648v1

• [cs.RO]3D Semantic Mapping from Arthroscopy using Out-of-distribution Pose and Depth and In-distribution Segmentation Training
Yaqub Jonmohamadi, Shahnewaz Ali, Fengbei Liu, Jonathan Roberts, Ross Crawford, Gustavo Carneiro, Ajay K. Pandey
http://arxiv.org/abs/2106.05525v1

• [cs.RO]Convex Risk Bounded Continuous-Time Trajectory Planning in Uncertain Nonconvex Environments
Ashkan Jasour, Weiqiao Han, Brian Williams
http://arxiv.org/abs/2106.05489v1

• [cs.RO]DREAMS: Drilling and Extraction Automated System
Mohamed Khaled, Srivignesh Srinivasan, Alkassoum Toure, Muhao Chen, Emily Kincaid, Thomas Lopaz, Luis Rodriguez, Jessica Ezemba, Ayodeji Adeniran, Teresa Valdez, Uthej Vattipalli, Le linh, Ahmed Madi, Eduardo Gildin, Robert Skelton, Sam Noynaert, George Moridis
http://arxiv.org/abs/2106.05874v1

• [cs.RO]Differentiable Robust LQR Layers
Ngo Anh Vien, Gerhard Neumann
http://arxiv.org/abs/2106.05535v1

• [cs.SD]Improving multi-speaker TTS prosody variance with a residual encoder and normalizing flows
Iván Vallés-Pérez, Julian Roth, Grzegorz Beringer, Roberto Barra-Chicote, Jasha Droppo
http://arxiv.org/abs/2106.05762v1

• [cs.SD]MusicBERT: Symbolic Music Understanding with Large-Scale Pre-Training
Mingliang Zeng, Xu Tan, Rui Wang, Zeqian Ju, Tao Qin, Tie-Yan Liu
http://arxiv.org/abs/2106.05630v1

• [cs.SD]U2++: Unified Two-pass Bidirectional End-to-end Model for Speech Recognition
Di Wu, Binbin Zhang, Chao Yang, Zhendong Peng, Wenjing Xia, Xiaoyu Chen, Xin Lei
http://arxiv.org/abs/2106.05642v1

• [cs.SI]Italian Twitter semantic network during the Covid-19 epidemic
Mattia Mattei, Guido Caldarelli, Tiziano Squartini, Fabio Saracco
http://arxiv.org/abs/2106.05815v1

• [cs.SI]Mechanisms and Attributes of Echo Chambers in Social Media
Bohan Jiang, Mansooreh Karami, Lu Cheng, Tyler Black, Huan Liu
http://arxiv.org/abs/2106.05401v1

• [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/2106.04292v3

• [cs.SI]Surveillance of COVID-19 Pandemic using Social Media: A Reddit Study in North Carolina
Christopher Whitfield, Yang Liu, Mohd Anwar
http://arxiv.org/abs/2106.04515v3

• [eess.AS]Audiovisual transfer learning for audio tagging and sound event detection
Wim Boes, Hugo Van hamme
http://arxiv.org/abs/2106.05408v1

• [eess.IV]Anatomy X-Net: A Semi-Supervised Anatomy Aware Convolutional Neural Network for Thoracic Disease Classification
Uday Kamal, Mohammad Zunaed, Nusrat Binta Nizam, Taufiq Hasan
http://arxiv.org/abs/2106.05915v1

• [eess.IV]CALTeC: Content-Adaptive Linear Tensor Completion for Collaborative Intelligence
Ashiv Dhondea, Robert A. Cohen, Ivan V. Bajić
http://arxiv.org/abs/2106.05531v1

• [eess.IV]CoviLearn: A Machine Learning Integrated Smart X-Ray Device in Healthcare Cyber-Physical System for Automatic Initial Screening of COVID-19
Debanjan Das, Chirag Samal, Deewanshu Ukey, Gourav Chowdhary, Saraju P. Mohanty
http://arxiv.org/abs/2106.05861v1

• [eess.IV]Domain Specific Transporter Framework to Detect Fractures in Ultrasound
Arpan Tripathi, Abhilash Rakkunedeth, Mahesh Raveendranatha Panicker, Jack Zhang, Naveenjyote Boora, Jacob Jaremko
http://arxiv.org/abs/2106.05929v1

• [eess.IV]End-to-end lung nodule detection framework with model-based feature projection block
Ivan Drokin, Elena Ericheva
http://arxiv.org/abs/2106.05741v1

• [eess.IV]Joint Landmark and Structure Learning for Automatic Evaluation of Developmental Dysplasia of the Hip
Xindi Hu, Limin Wang, Xin Yang, Xu Zhou, Wufeng Xue, Yan Cao, Shengfeng Liu, Yuhao Huang, Shuangping Guo, Ning Shang, Dong Ni, Ning Gu
http://arxiv.org/abs/2106.05458v1

• [eess.IV]Rethink Transfer Learning in Medical Image Classification
Le P
1000
eng, Hengyue Liang, Taihui Li, Ju Sun
http://arxiv.org/abs/2106.05152v2

• [eess.IV]Super-Resolution Image Reconstruction Based on Self-Calibrated Convolutional GAN
Yibo Guo, Haidi Wang, Yiming Fan, Shunyao Li, Mingliang Xu
http://arxiv.org/abs/2106.05545v1

• [eess.IV]The Medical Segmentation Decathlon
Michela Antonelli, Annika Reinke, Spyridon Bakas, Keyvan Farahani, AnnetteKopp-Schneider, Bennett A. Landman, Geert Litjens, Bjoern Menze, Olaf Ronneberger, Ronald M. Summers, Bram van Ginneken, Michel Bilello, Patrick Bilic, Patrick F. Christ, Richard K. G. Do, Marc J. Gollub, Stephan H. Heckers, Henkjan Huisman, William R. Jarnagin, Maureen K. McHugo, Sandy Napel, Jennifer S. Goli Pernicka, Kawal Rhode, Catalina Tobon-Gomez, Eugene Vorontsov, Henkjan Huisman, James A. Meakin, Sebastien Ourselin, Manuel Wiesenfarth, Pablo Arbelaez, Byeonguk Bae, Sihong Chen, Laura Daza, Jianjiang Feng, Baochun He, Fabian Isensee, Yuanfeng Ji, Fucang Jia, Namkug Kim, Ildoo Kim, Dorit Merhof, Akshay Pai, Beomhee Park, Mathias Perslev, Ramin Rezaiifar, Oliver Rippel, Ignacio Sarasua, Wei Shen, Jaemin Son, Christian Wachinger, Liansheng Wang, Yan Wang, Yingda Xia, Daguang Xu, Zhanwei Xu, Yefeng Zheng, Amber L. Simpson, Lena Maier-Hein, M. Jorge Cardoso
http://arxiv.org/abs/2106.05735v1

• [eess.SP]Fastening the Initial Access in 5G NR Sidelink for 6G V2X Networks
Marouan Mizmizi, Francesco Linsalata, Mattia Brambilla, Filippo Morandi, Kai Dong, Maurizio Magarini, Monica Nicoli, Majid Nasiri Khormuji, Peng Wang, Renaud Alexandre Pitaval, Umberto Spagnolini
http://arxiv.org/abs/2106.05716v1

• [eess.SP]SignalNet: A Low Resolution Sinusoid Decomposition and Estimation Network
Ryan Dreifuerst, Robert W. Heath Jr
http://arxiv.org/abs/2106.05490v1

• [eess.SY]Multiple Dynamic Pricing for Demand Response with Adaptive Clustering-based Customer Segmentation in Smart Grids
Fanlin Meng, Qian Ma, Zixu Liu, Xiao-Jun Zeng
http://arxiv.org/abs/2106.05905v1

• [hep-lat]Flow-based sampling for fermionic lattice field theories
Michael S. Albergo, Gurtej Kanwar, Sébastien Racanière, Danilo J. Rezende, Julian M. Urban, Denis Boyda, Kyle Cranmer, Daniel C. Hackett, Phiala E. Shanahan
http://arxiv.org/abs/2106.05934v1

• [math.NA]A Discontinuity Capturing Shallow Neural Network for Elliptic Interface Problems
Wei-Fan Hu, Te-Sheng Lin, Ming-Chih Lai
http://arxiv.org/abs/2106.05587v1

• [math.OC]Distributionally Robust Prescriptive Analytics with Wasserstein Distance
Tianyu Wang, Ningyuan Chen, Chun Wang
http://arxiv.org/abs/2106.05724v1

• [math.OC]Exploiting Local Convergence of Quasi-Newton Methods Globally: Adaptive Sample Size Approach
Qiujiang Jin, Aryan Mokhtari
http://arxiv.org/abs/2106.05445v1

• [math.OC]Near-Optimal High Probability Complexity Bounds for Non-Smooth Stochastic Optimization with Heavy-Tailed Noise
Eduard Gorbunov, Marina Danilova, Innokentiy Shibaev, Pavel Dvurechensky, Alexander Gasnikov
http://arxiv.org/abs/2106.05958v1

• [math.OC]Public Transit for Special Events: Ridership Prediction and Train Optimization
Tejas Santanam, Anthony Trasatti, Pascal Van Hentenryck, Hanyu Zhang
http://arxiv.org/abs/2106.05359v1

• [math.OC]dFDA-VeD: A Dynamic Future Demand Aware Vehicle Dispatching System
Yang Guo, Tarique Anwar, Jian Yang, Jia Wu
http://arxiv.org/abs/2106.05737v1

• [math.PR]A Central Limit Theorem, Loss Aversion and Multi-Armed Bandits
Zengjing Chen, Larry G. Epstein, Guodong Zhang
http://arxiv.org/abs/2106.05472v1

• [math.ST]Bayesian inference of a non-local proliferation model
Zuzanna Szymańska, Jakub Skrzeczkowski, Błażej Miasojedow, Piotr Gwiazda
http://arxiv.org/abs/2106.05955v1

• [math.ST]Bias, Consistency, and Alternative Perspectives of the Infinitesimal Jackknife
Wei Peng, Lucas Mentch, Leonard Stefanski
http://arxiv.org/abs/2106.05918v1

• [math.ST]Confidence in Causal Discovery with Linear Causal Models
David Strieder, Tobias Freidling, Stefan Haffner, Mathias Drton
http://arxiv.org/abs/2106.05694v1

• [math.ST]Dependence and mixing for perturbations of copula-based Markov chains
Martial Longla, Mathias Muia Nthiani, Fidel Djongreba Ndikwa
http://arxiv.org/abs/2106.05766v1

• [math.ST]Information Geometry of Reversible Markov Chains
Geoffrey Wolfer, Shun Watanabe
http://arxiv.org/abs/2106.05669v1

• [math.ST]Online Debiased Lasso
Ruijian Han, Lan Luo, Yuanyuan Lin, Jian Huang
http://arxiv.org/abs/2106.05925v1

• [math.ST]Sign Consistency of the Generalized Elastic Net Estimator
Wencan Zhu, Eric Adjakossa, Céline Lévy-Leduc, Nils Ternès
http://arxiv.org/abs/2106.05454v1

• [math.ST]Strong Gaussian Approximation for the Sum of Random Vectors
Nazar Buzun, Nikolay Shvetsov, Dmitry V. Dylov
http://arxiv.org/abs/2106.05890v1

• [physics.flu-dyn]Real-time simulation of parameter-dependent fluid flows through deep learning-based reduced order models
Stefania Fresca, Andrea Manzoni
http://arxiv.org/abs/2106.05722v1

• [physics.ins-det]CaloFlow: Fast and Accurate Generation of Calorimeter Showers with Normalizing Flows
Claudius Krause, David Shih
http://arxiv.org/abs/2106.05285v1

• [physics.soc-ph]Theoretical Modeling of Communication Dynamics
Torsten Enßlin, Viktoria Kainz, Céline Bœhm
http://arxiv.org/abs/2106.05414v1

• [q-bio.QM]Adaptive machine learning for protein engineering
Brian L. Hie, Kevin K. Yang
http://arxiv.org/abs/2106.05466v1

• [q-bio.QM]Fine-Grained System Identification of Nonlinear Neural Circuits
Dawna Bagherian, James Gornet, Jeremy Bernstein, Yu-Li Ni, Yisong Yue, Markus Meister
http://arxiv.org/abs/2106.05400v1

• [quant-ph]Grover’s Algorithm for Question Answering
A. D. Correia, M. Moortgat, H. T. C. Stoof
http://arxiv.org/abs/2106.05299v1

• [quant-ph]Perturbation Theory for Quantum Information
Michael R Grace, Saikat Guha
http://arxiv.org/abs/2106.05533v1

• [quant-ph]Quantum Natural Gradient for Variational Bayes
Anna Lopatnikova, Minh-Ngoc Tran
http://arxiv.org/abs/2106.05807v1

• [stat.AP]Are We There Yet? Big Data Significantly Overestimates COVID-19 Vaccination in the US
Valerie C. Bradley, Shiro Kuriwaki, Michael Isakov, Dino Sejdinovic, Xiao-Li Meng, Seth Flaxman
http://arxiv.org/abs/2106.05818v1

• [stat.AP]Calculating the Likelihood Ratio for Multiple Pieces of Evidence
Norman Fenton, Martin Neil
http://arxiv.org/abs/2106.05328v1

• [stat.AP]Dynamic Shape Modeling to Analyze Modes ofMigration During Cell Motility
Ximu Deng, Rituparna Sarkar, Elisabeth Labruyere, Jean-Christophe Olivo-Marin, Anuj Srivastava
http://arxiv.org/abs/2106.05617v1

• [stat.AP]Forecast combination based forecast reconciliation: insights and extensions
Tommaso Di Fonzo, Daniele Girolimetto
http://arxiv.org/abs/2106.05653v1

• [stat.AP]Global and Tail Dependence: A Differential Geometry Approach
Davide Lauria, Svetlozar T. Rachev, A. Alexandre Trindade
http://arxiv.org/abs/2106.05865v1

• [stat.AP]On the Use of Data from Multiple Mobile Network Operators in Europe to fight COVID-19
Michele Vespe, Stefano Maria Iacus, Carlos Santamaria, Francesco Sermi, Spyridon Spyratos
http://arxiv.org/abs/2106.05647v1

• [stat.AP]Robust Prediction Interval estimation for Gaussian Processes by Cross-Validation method
Naoufal Acharki, Antoine Bertoncello, Josselin Garnier
http://arxiv.org/abs/2106.05396v1

• [stat.ME]A Variational View on Statistical Multiscale Estimation
Markus Haltmeier, Housen Li, Axel Munk
http://arxiv.org/abs/2106.05828v1

• [stat.ME]A tutorial on individualized treatment effect prediction from randomized trials with a binary endpoint
J Hoogland, J IntHout, M Belias, MM Rovers, RD Riley, FE Harrell Jr, KGM Moons, TPA Debray, JB Reitsma
http://arxiv.org/abs/2106.05588v1

• [stat.ME]Bayesian semi-parametric inference for diffusion processes using splines
Paul A. Jenkins, Murray Pollock, Gareth O. Roberts
http://arxiv.org/abs/2106.05820v1

• [stat.ME]Does Bayesian Model Averaging improve polynomial extrapolations? Two toy problems as tests
M. A. Connell, I. Billig, D. R. Phillips
http://arxiv.org/abs/2106.05906v1

• [stat.ME]The Attraction Indian Buffet Distribution
Richard L. Warr, David B. Dahl, Jeremy M. Meyer, Arthur Lui
http://arxiv.org/abs/2106.05403v1

• [stat.ML]An Interpretable Neural Network for Parameter Inference
Johann Pfitzinger
http://arxiv.org/abs/2106.05536v1

• [stat.ML]Compositional Modeling of Nonlinear Dynamical Systems with ODE-based Random Features
Thomas M. McDonald, Mauricio A. Álvarez
http://arxiv.org/abs/2106.05960v1

• [stat.ML]DNN-Based Topology Optimisation: Spatial Invariance and Neural Tangent Kernel
Benjamin Dupuis, Arthur Jacot
http://arxiv.org/abs/2106.05710v1

• [stat.ML]Data augmentation in Bayesian neural networks and the cold posterior effect
Seth Nabarro, Stoil Ganev, Adrià Garriga-Alonso, Vincent Fortuin, Mark van der Wilk, Laurence Aitchison
http://arxiv.org/abs/2106.05586v1

• [stat.ML]From inexact optimization to learning via gradient concentration
Bernhard Stankewitz, Nicole Mücke, Lorenzo Rosasco
http://arxiv.org/abs/2106.05397v1

• [stat.ML]GBHT: Gradient Boosting Histogram Transform for Density Estimation
Jingyi Cui, Hanyuan Hang, Yisen Wang, Zhouchen Lin
http://arxiv.org/abs/2106.05738v1

• [stat.ML]Identifiability of interaction kernels in mean-field equations of interacting particles
Quanjun Lang, Fei Lu
http://arxiv.org/abs/2106.05565v1

• [stat.ML]Large-scale optimal transport map estimation using projection pursuit
Cheng Meng, Yuan Ke, Jingyi Zhang, Mengrui Zhang, Wenxuan Zhong, Ping Ma
http://arxiv.org/abs/2106.05838v1

• [stat.ML]Learning Nonparametric Volterra Kernels with Gaussian Processes
Magnus Ross, Michael T. Smith, Mauricio A. Álvarez
http://arxiv.org/abs/2106.05582v1

• [stat.ML]Linear Classifiers Under Infinite Imbalance
Paul Glasserman, Mike Li
http://arxiv.org/abs/2106.05797v1

• [stat.ML]Loss function based second-order Jensen inequality and its application to particle variational inference
Futoshi Futami, Tomoharu Iwata, Naonori Ueda, Issei Sato, Masashi Sugiyama
http://arxiv.org/abs/2106.05010v2

• [stat.ML]Matrix Completion with Model-free Weighting
Jiayi Wang, Raymond K. W. Wong, Xiaojun Mao, Kwun Chuen Gary Chan
http://arxiv.org/abs/2106.05850v1

• [stat.ML]Meta-Learning for Symbolic Hyperparameter Defaults
Pieter Gijsbers, Florian Pfisterer, Jan N. van Rijn, Bernd Bischl, Joaquin Vanschoren
http://arxiv.org/abs/2106.05767v1

• [stat.ML]Quantized Conditional COT-GAN for Video Prediction
Tianlin Xu, Beatrice Acciaio
http://arxiv.org/abs/2106.05658v1

• [stat.ML]Score-based Generative Modeling in Latent Space
Arash Vahdat, Karsten Kreis, Jan Kautz
http://arxiv.org/abs/2106.05931v1

• [stat.ML]Separation Results between Fixed-Kernel and Feature-Learning Probability Metrics
Carles Domingo-Enrich, Youssef Mroueh
http://arxiv.org/abs/2106.05739v1

• [stat.ML]Support Recovery of Sparse Signals from a Mixture of Linear Measurements
Venkata Gandikota, Arya Mazumdar, Soumyabrata Pal
http://arxiv.org/abs/2106.05951v1

• [stat.ML]Tractable Density Estimation on Learned Manifolds with Conformal Embedding Flows
Brendan Leigh Ross, Jesse C. Cresswell
http://arxiv.org/abs/2106.05275v1