cond-mat.dis-nn - 无序系统与神经网络
cond-mat.mtrl-sci - 材料科学 cs.AI - 人工智能 cs.CG - 计算几何学 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MS - 数学软件 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SI - 社交网络与信息网络 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 math.FA - 泛函演算 math.OC - 优化与控制 math.ST - 统计理论 nlin.AO - 适应和自组织系统 nlin.CD - 混沌动力学 physics.acc-ph - 加速器物理学 physics.app-ph - 应用物理 physics.comp-ph - 计算物理学 physics.med-ph - 医学物理学 physics.soc-ph - 物理学与社会 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
• [9c9]Reserve Price Optimization for First Price Auctions
• [cond-mat.dis-nn]A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons
• [cond-mat.mtrl-sci]On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning
• [cs.AI]Avoiding Side Effects in Complex Environments
• [cs.AI]Consolidating Commonsense Knowledge
• [cs.AI]Marginal Utility for Planning in Continuous or Large Discrete Action Spaces
• [cs.AI]Modeling Human Driving Behavior through Generative Adversarial Imitation Learning
• [cs.AI]Petri Nets with Parameterised Data: Modelling and Verification (Extended Version)
• [cs.AI]Surveys without Questions: A Reinforcement Learning Approach
• [cs.CG]Unsupervised Learning of 3D Point Set Registration
• [cs.CL]A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
• [cs.CL]A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction
• [cs.CL]Augmenting Data for Sarcasm Detection with Unlabeled Conversation Context
• [cs.CL]ClarQ: A large-scale and diverse dataset for Clarification Question Generation
• [cs.CL]CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLP
• [cs.CL]ConfNet2Seq: Full Length Answer Generation from Spoken Questions
• [cs.CL]Discrete Latent Variable Representations for Low-Resource Text Classification
• [cs.CL]Emora STDM: A Versatile Framework for Innovative Dialogue System Development
• [cs.CL]Multi-hop Reading Comprehension across Documents with Path-based Graph Convolutional Network
• [cs.CL]Performance in the Courtroom: Automated Processing and Visualization of Appeal Court Decisions in France
• [cs.CL]Provenance for Linguistic Corpora Through Nanopublications
• [cs.CL]Report from the NSF Future Directions Workshop, Toward User-Oriented Agents: Research Directions and Challenges
• [cs.CL]Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics
• [cs.CL]Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge
• [cs.CL]Towards Unified Dialogue System Evaluation: A Comprehensive Analysis of Current Evaluation Protocols
• [cs.CR]Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors
• [cs.CR]DNS Tunneling: A Deep Learning based Lexicographical Detection Approach
• [cs.CR]Fingerprinting Analog IoT Sensors for Secret-Free Authentication
• [cs.CR]Learning With Differential Privacy
• [cs.CR]Optimizing Smart Grid Aggregators and Measuring Degree of Privacy in a Distributed Trust Based Anonymous Aggregation System
• [cs.CR]Resiliency by Retrograded Communication- The Revival of Shortwave as a Military Communication Channel
• [cs.CV]A Deep Learning Framework for Recognizing both Static and Dynamic Gestures
• [cs.CV]An Edge Information and Mask Shrinking Based Image Inpainting Approach
• [cs.CV]Attentive WaveBlock: Complementarity-enhanced Mutual Networks for Unsupervised Domain Adaptation in Person Re-identification
• [cs.CV]Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies
• [cs.CV]CLEval: Character-Level Evaluation for Text Detection and Recognition Tasks
• [cs.CV]CoMIR: Contrastive Multimodal Image Representation for Registration
• [cs.CV]Continual Learning for Affective Computing
• [cs.CV]Convolutional neural networks compression with low rank and sparse tensor decompositions
• [cs.CV]Dance Revolution: Long Sequence Dance Generation with Music via Curriculum Learning
• [cs.CV]Diagnosing Rarity in Human-Object Interaction Detection
• [cs.CV]Disentangled Non-Local Neural Networks
• [cs.CV]DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders
• [cs.CV]Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation
• [cs.CV]Exploring Weaknesses of VQA Models through Attribution Driven Insights
• [cs.CV]Fall Detector Adapted to Nursing Home Needs through an Optical-Flow based CNN
• [cs.CV]Fast Coherent Point Drift
• [cs.CV]Hypernetwork-Based Augmentation
• [cs.CV]Image Deconvolution via Noise-Tolerant Self-Supervised Inversion
• [cs.CV]Improving Deep Metric Learning with Virtual Classes and Examples Mining
• [cs.CV]JIT-Masker: Efficient Online Distillation for Background Matting
• [cs.CV]Joint Training of Variational Auto-Encoder and Latent Energy-Based Model
• [cs.CV]Kalman Filter Based Multiple Person Head Tracking
• [cs.CV]Large-Scale Adversarial Training for Vision-and-Language Representation Learning
• [cs.CV]Learning a Unified Sample Weighting Network for Object Detection
• [cs.CV]MOMS with Events: Multi-Object Motion Segmentation With Monocular Event Cameras
• [cs.CV]Map3D: Registration Based Multi-Object Tracking on 3D Serial Whole Slide Images
• [cs.CV]MatchGAN: A Self-Supervised Semi-Supervised Conditional Generative Adversarial Network
• [cs.CV]Minimum Potential Energy of Point Cloud for Robust Global Registration
• [cs.CV]Morphing Attack Detection — Database, Evaluation Platform and Benchmarking
• [cs.CV]Privacy-Aware Activity Classification from First Person Office Videos
• [cs.CV]Privacy-Preserving Visual Feature Descriptors through Adversarial Affine Subspace Embedding
• [cs.CV]Protecting Against Image Translation Deepfakes by Leaking Universal Perturbations from Black-Box Neural Networks
• [cs.CV]Quasi-Dense Instance Similarity Learning
• [cs.CV]RTEX: A novel methodology for Ranking, Tagging, and Explanatory diagnostic captioning of radiography exams
• [cs.CV]Rethinking the Truly Unsupervised Image-to-Image Translation
• [cs.CV]Revisiting visual-inertial structure from motion for odometry and SLAM initialization
• [cs.CV]Robust Multi-object Matching via Iterative Reweighting of the Graph Connection Laplacian
• [cs.CV]SLIC-UAV: A Method for monitoring recovery in tropical restoration projects through identification of signature species using UAVs
• [cs.CV]Spectral Image Segmentation with Global Appearance Modeling
• [cs.CV]Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
• [cs.CV]Telling Left from Right: Learning Spatial Correspondence between Sight and Sound
• [cs.CV]Towards Robust Fine-grained Recognition by Maximal Separation of Discriminative Features
• [cs.CV]Transferring and Regularizing Prediction for Semantic Segmentation
• [cs.CV]Understanding Human Hands in Contact at Internet Scale
• [cs.CV]VirTex: Learning Visual Representations from Textual Annotations
• [cs.CV]What makes instance discrimination good for transfer learning?
• [cs.CY]2020 UK Lockdown Cyber Narratives: the Secure, the Insecure and the Worrying
• [cs.CY]Analyzing Power Grid, ICT, and Market Without Domain Knowledge Using Distributed Artificial Intelligence
• [cs.CY]Design Considerations for High Impact, Automated Echocardiogram Analysis
• [cs.CY]Montreal AI Ethics Institute’s Response to Scotland’s AI Strategy
• [cs.CY]SECure: A Social and Environmental Certificate for AI Systems
• [cs.CY]System to Integrate Fairness Transparently: An Industry Approach
• [cs.DB]TableQA: a Large-Scale Chinese Text-to-SQL Dataset for Table-Aware SQL Generation
• [cs.DC]Efficient Partial Snapshot Implementations
• [cs.DC]GNNAdvisor: An Efficient Runtime System for GNN Acceleration on GPUs
• [cs.DL]PeopleMap: Visualization Tool for Mapping Out Researchers using Natural Language Processing
• [cs.GT]Online Learning in Iterated Prisoner’s Dilemma to Mimic Human Behavior
• [cs.GT]Optimally Deceiving a Learning Leader in Stackelberg Games
• [cs.HC]Affective Movement Generation using Laban Effort and Shape and Hidden Markov Models
• [cs.HC]Creating a Robot Coach for Mindfulness and Wellbeing: A Longitudinal Study
• [cs.HC]Mental Workload and Language Production in Non-Native Speaker IPA Interaction
• [cs.HC]See what I’m saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers
• [cs.HC]Transparency in Language Generation: Levels of Automation
• [cs.IR]Embed2Detect: Temporally Clustered Embedded Words for Event Detection in Social Media
• [cs.IT]AoI-optimal Joint Sampling and Updating for Wireless Powered Communication Systems
• [cs.IT]Codes with locality from cyclic extensions of Deligne-Lusztig curves
• [cs.IT]Combinatorics with Copula for Code based Post-Quantum Cryptography
• [cs.IT]On Decoding Fountain Codes with Erroneous Received Symbols
• [cs.IT]Relay Aided Intelligent Reconfigurable Surfaces: Achieving the Potential Without So Many Antennas
• [cs.IT]Sample-Efficient Low Rank Phase Retrieval
• [cs.IT]The block mutual coherence property condition for signal recovery
• [cs.IT]The high-order block RIP for non-convex block-sparse compressed sensing
• [cs.IT]The perturbation analysis of nonconvex low-rank matrix robust recovery
• [cs.IT]Uplink and Downlink MIMO-NOMA with Simultaneous Triangularization
• [cs.LG]A Class of Algorithms for General Instrumental Variable Models
• [cs.LG]A Generalised Linear Model Framework for Variational Autoencoders based on Exponential Dispersion Families
• [cs.LG]A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning
• [cs.LG]A multi-objective-based approach for Fair Principal Component Analysis
• [cs.LG]Achieving robustness in classification using optimal transport with hinge regularization
• [cs.LG]AdaS: Adaptive Scheduling of Stochastic Gradients
• [cs.LG]Adaptation Strategies for Automated Machine Learning on Evolving Data
• [cs.LG]Adaptive Reward-Free Exploration
• [cs.LG]Bandit Samplers for Training Graph Neural Networks
• [cs.LG]Blissful Ignorance: Anti-Transfer Learning for Task Invariance
• [cs.LG]Cumulant GAN
• [cs.LG]DFraud3- Multi-Component Fraud Detection freeof Cold-start
• [cs.LG]DNF-Net: A Neural Architecture for Tabular Data
• [cs.LG]Deep Differential System Stability — Learning advanced computations from examples
• [cs.LG]Deep Learning Requires Explicit Regularization for Reliable Predictive Probability
• [cs.LG]Deep Learning for Stable Monotone Dynamical Systems
• [cs.LG]Demystifying Self-Supervised Learning: An Information-Theoretical Framework
• [cs.LG]Deterministic Gaussian Averaged Neural Networks
• [cs.LG]Diagnosis and Analysis of Celiac Disease and Environmental Enteropathy on Biopsy Images using Deep Learning Approaches
• [cs.LG]Directional convergence and alignment in deep learning
• [cs.LG]Distributed Reinforcement Learning in Multi-Agent Networked Systems
• [cs.LG]Distribution Regression for Continuous-Time Processes via the Expected Signature
• [cs.LG]Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification
• [cs.LG]Dynamically Stable Infinite-Width Limits of Neural Classifiers
• [cs.LG]Efficient Contextual Bandits with Continuous Actions
• [cs.LG]Embed Me If You Can: A Geometric Perceptron
• [cs.LG]Exploration by Maximizing Rényi Entropy for Zero-Shot Meta RL
• [cs.LG]Fair Data Integration
• [cs.LG]G5: A Universal GRAPH-BERT for Graph-to-Graph Transfer and Apocalypse Learning
• [cs.LG]GAIT-prop: A biologically plausible learning rule derived from backpropagation of error
• [cs.LG]GANgster: A Fraud Review Detector based on Regulated GAN with Data Augmentation
• [cs.LG]How Interpretable and Trustworthy are GAMs?
• [cs.LG]Implicit Kernel Attention
• [cs.LG]Improved Algorithms for Convex-Concave Minimax Optimization
• [cs.LG]Interpretable Visualizations with Differentiating Embedding Networks
• [cs.LG]Latent Transformations for Discrete-Data Normalising Flows
• [cs.LG]Learning Continuous-Time Dynamics by Stochastic Differential Networks
• [cs.LG]Learning Halfspaces with Tsybakov Noise
• [cs.LG]Learning Individually Inferred Communication for Multi-Agent Cooperation
• [cs.LG]Learning Navigation Costs from Demonstration with Semantic Observations
• [cs.LG]Learning normalizing flows from Entropy-Kantorovich potentials
• [cs.LG]Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction
• [cs.LG]Learning to Incentivize Other Learning Agents
• [cs.LG]Learning to Infer 3D Object Models from Images
• [cs.LG]Model-Size Reduction for Reservoir Computing by Concatenating Internal States Through Time
• [cs.LG]NADS: Neural Architecture Distribution Search for Uncertainty Awareness
• [cs.LG]NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity
• [cs.LG]Neural Methods for Point-wise Dependency Estimation
• [cs.LG]On Coresets For Regularized Regression
• [cs.LG]On Mixup Regularization
• [cs.LG]On Noise Injection in Generative Adversarial Networks
• [cs.LG]On the Maximum Mutual Information Capacity of Neural Architectures
• [cs.LG]PAC Bounds for Imitation and Model-based Batch Learning of Contextual Markov Decision Processes
• [cs.LG]Probabilistic Auto-Encoder
• [cs.LG]Real-Time Video Inference on Edge Devices via Adaptive Model Streaming
• [cs.LG]Recovery and Generalization in Over-Realized Dictionary Learning
• [cs.LG]Robust model training and generalisation with Studentising flows
• [cs.LG]STL-SGD: Speeding Up Local SGD with Stagewise Communication Period
• [cs.LG]Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation
• [cs.LG]Scalable Partial Explainability in Neural Networks via Flexible Activation Functions
• [cs.LG]Self-Supervised Reinforcement Learning for Recommender Systems
• [cs.LG]Smoothed Geometry for Robust Attribution
• [cs.LG]TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation
• [cs.LG]The Backbone Method for Ultra-High Dimensional Sparse Machine Learning
• [cs.LG]Understanding Regularisation Methods for Continual Learning
• [cs.LG]Wide and Deep Graph Neural Networks with Distributed Online Learning
• [cs.LG]Zeroth-Order Supervised Policy Improvement
• [cs.LO]A framework for step-wise explaining how to solve constraint satisfaction problems
• [cs.MS]Accelerating linear solvers for large-scale Stokes problems with C++ metaprogramming
• [cs.NE]A Novel Meta-Heuristic Optimization Algorithm Inspired by the Spread of Viruses
• [cs.NE]Growing Artificial Neural Networks
• [cs.NE]Hardware Implementation of Spiking Neural Networks Using Time-To-First-Spike Encoding
• [cs.NE]Sensorimotor Visual Perception on Embodied System Using Free Energy Principle
• [cs.NE]Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case
• [cs.NI]On the Feasibility of Perfect Resilience with Local Fast Failover
• [cs.NI]Recurrent Neural Networks for Handover Management in Next-Generation Self-Organized Networks
• [cs.RO]Complementary Visual Neuronal Systems Model for Collision Sensing
• [cs.RO]Deep Drone Acrobatics
• [cs.RO]Ergodic Specifications for Flexible Swarm Control: From User Commands to Persistent Adaptation
• [cs.RO]From proprioception to long-horizon planning in novel environments: A hierarchical RL model
• [cs.RO]Geometric Solutions for General Actuator Routing on Inflated-Beam Soft Growing Robots
• [cs.RO]Geometric and Stiffness Modeling and Design of Calibration Experiments for the 7 dof Serial Manipulator KUKA iiwa 14 R820
• [cs.RO]Graph Neural Networks for Motion Planning
• [cs.RO]The Role of Modularity and Neuro-Regulation for the Production of Multiple Behaviors
• [cs.RO]Tuning-Free Contact-Implicit Trajectory Optimization
• [cs.SD]Perceiving Music Quality with GANs
• [cs.SI]A Toolkit for Analyzing and Visualizing Online Users via Reshare Cascade Modeling
• [cs.SI]Extracting and categorising the reactions to COVID-19 by the South African public — A social media study
• [cs.SI]Fair Clustering for Diverse and Experienced Groups
• [cs.SI]Forming an Electoral College for a Graph: a Heuristic Semi-supervised Learning Framework
• [cs.SI]Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps
• [cs.SI]Modeling and Simulation of COVID-19 Pandemic for Cincinnati Tri-State Area
• [cs.SI]Robust Detection of Adaptive Spammers by Nash Reinforcement Learning
• [cs.SI]Understanding the Dynamics of Information Flow During Disaster Response Using Absorbing Markov Chains
• [eess.AS]Deep generative models for musical audio synthesis
• [eess.AS]Investigating Robustness of Adversarial Samples Detection for Automatic Speaker Verification
• [eess.AS]XiaoiceSing: A High-Quality and Integrated Singing Voice Synthesis System
• [eess.IV]COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature
• [eess.IV]DSU-net: Dense SegU-net for automatic head-and-neck tumor segmentation in MR images
• [eess.IV]Fully-automated deep learning slice-based muscle estimation from CT images for sarcopenia assessment
• [eess.IV]Interpreting CNN for Low Complexity Learned Sub-pixel Motion Compensation in Video Coding
• [eess.IV]TensorFlow with user friendly Graphical Framework for object detection API
• [eess.IV]W-net: Simultaneous segmentation of multi-anatomical retinal structures using a multi-task deep neural network
• [eess.SP]A PDD Decoder for Binary Linear Codes With Neural Check Polytope Projection
• [eess.SP]A Primer on Large Intelligent Surface (LIS) for Wireless Sensing in an Industrial Setting
• [eess.SP]A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers
• [eess.SP]Energy-Efficient Fixed-Gain AF Relay Assisted OFDM with Index Modulation
• [eess.SP]On Matched Filtering for Statistical Change Point Detection
• [eess.SP]User Cooperation for IRS-aided Secure SWIPT MIMO: Active Attacks and Passive Eavesdropping
• [eess.SY]Data-driven Thermal Model Inference with ARMAX, in Smart Environments, based on Normalized Mutual Information
• [eess.SY]Stochastic properties of an inverted pendulum on a wheel on a soft surface
• [eess.SY]The Effects of Driver Coupling and Automation Impedance on Emergency Steering Interventions
• [math.FA]Tight frames over the quaternions and equiangular lines
• [math.OC]Ensuring smoothly navigable approximation sets by Bezier curve parameterizations in evolutionary bi-objective optimization — applied to brachytherapy treatment planning for prostate cancer
• [math.OC]Revisiting the Continuity of Rotation Representations in Neural Networks
• [math.OC]Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward
• [math.ST]Asymptotics of Ridge(less) Regression under General Source Condition
• [math.ST]Convergence of Pseudo-Bayes Factors in Forward and Inverse Regression Problems
• [math.ST]Exact and asymptotic properties of $δ$-records in the linear drift model
• [math.ST]Fast increased fidelity approximate Gibbs samplers for Bayesian Gaussian process regression
• [math.ST]How simplifying and flexible is the simplifying assumption in pair-copula constructions — some analytic answers in dimension three and beyond
• [math.ST]Some More Properties of the Unit-Gompertz Distribution
• [nlin.AO]Deep Time-Delay Reservoir Computing: Dynamics and Memory Capacity
• [nlin.CD]Stabilization of the wheeled inverted pendulum on a soft surface
• [physics.acc-ph]Superconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory
• [physics.app-ph]FBG-Based Triaxial Force Sensor Integrated with an Eccentrically Configured Imaging Probe for Endoluminal Optical Biopsy
• [physics.app-ph]Machine learning model to cluster and map tribocorrosion regimes in feature space
• [physics.comp-ph]Enabling Nonlinear Manifold Projection Reduced-Order Models by Extending Convolutional Neural Networks to Unstructured Data
• [physics.med-ph]Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation
• [physics.soc-ph]Analysis of node2vec random walks on networks
• [quant-ph]Binary Classification with Classical Instances and Quantum Labels
• [stat.AP]On a Multi-Year Microlevel Collective Risk Model
• [stat.AP]What Drives Inflation and How: Evidence from Additive Mixed Models Selected by cAIC
• [stat.ME]A Bayesian Time-Varying Autoregressive Model for Improved Short- and Long-Term Prediction
• [stat.ME]A Bridge between Cross-validation Bayes Factors and Geometric Intrinsic Bayes Factors
• [stat.ME]Bayesian Eigenvalue Regularization via Cumulative Shrinkage Process
• [stat.ME]Conformal Inference of Counterfactuals and Individual Treatment Effects
• [stat.ME]Grouped GEE Analysis for Longitudinal Data
• [stat.ME]Higher-order interactions in statistical physics and machine learning: A non-parametric solution to the inverse problem
• [stat.ME]Modeling high-dimensional dependence among astronomical data
• [stat.ME]Probabilistic Best Subset Selection by Gradient-Based Optimization
• [stat.ME]Study on estimators of the PDF and CDF of the one parameter polynomial exponential distribution
• [stat.ME]The Limits to Learning an SIR Process: Granular Forecasting for Covid-19
• [stat.ME]Wilks’ theorem for semiparametric regressions with weakly dependent data
• [stat.ML]A Variational Approach to Privacy and Fairness
• [stat.ML]Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (or : How to Prove Kabashima’s Replica Formula)
• [stat.ML]Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning
• [stat.ML]CoinPress: Practical Private Mean and Covariance Estimation
• [stat.ML]Convergence of adaptive algorithms for weakly convex constrained optimization
• [stat.ML]Deep Structural Causal Models for Tractable Counterfactual Inference
• [stat.ML]Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization
• [stat.ML]Improved Design of Quadratic Discriminant Analysis Classifier in Unbalanced Settings
• [stat.ML]Interpretable, similarity-driven multi-view embeddings from high-dimensional biomedical data
• [stat.ML]Mixup Training as the Complexity Reduction
• [stat.ML]Modeling Shared Responses in Neuroimaging Studies through MultiView ICA
• [stat.ML]Multi-index Antithetic Stochastic Gradient Algorithm
• [stat.ML]Multiplicative noise and heavy tails in stochastic optimization
• [stat.ML]Neural Ordinary Differential Equations on Manifolds
• [stat.ML]On mistakes we made in prior Computational Psychiatry Data driven approach projects and how they jeopardize translation of those findings in clinical practice
• [stat.ML]Pointer Graph Networks
• [stat.ML]Robust Grouped Variable Selection Using Distributionally Robust Optimization
• [stat.ML]Robustified Multivariate Regression and Classification Using Distributionally Robust Optimization under the Wasserstein Metric
• [stat.ML]Similarity-based Classification: Connecting Similarity Learning to Binary Classification
• [stat.ML]Sparse recovery by reduced variance stochastic approximation
• [stat.ML]Stanza: A Nonlinear State Space Model for Probabilistic Inference in Non-Stationary Time Series
• [stat.ML]Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits
• [stat.ML]Variance reduction for Langevin Monte Carlo in high dimensional sampling problems
• [stat.ML]Weighted Lasso Estimates for Sparse Logistic Regression: Non-asymptotic Properties with Measurement Error
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• [9c9]Reserve Price Optimization for First Price Auctions
Zhe Feng, Sébastien Lahaie, Jon Schneider, Jinchao Ye
http://arxiv.org/abs/2006.06519v1
• [cond-mat.dis-nn]A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons
Gabriel Mahuas, Giulio Isacchini, Olivier Marre, Ulisse Ferrari, Thierry Mora
http://arxiv.org/abs/2006.06497v1
• [cond-mat.mtrl-sci]On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning
A. Gilad Kusne, Heshan Yu, Changming Wu, Huairuo Zhang, Jason Hattrick-Simpers, Brian DeCost, Suchismita Sarker, Corey Oses, Cormac Toher, Stefano Curtarolo, Albert V. Davydov, Ritesh Agarwal, Leonid A. Bendersky, Mo Li, Apurva Mehta, Ichiro Takeuchi
http://arxiv.org/abs/2006.06141v1
• [cs.AI]Avoiding Side Effects in Complex Environments
Alexander Matt Turner, Neale Ratzlaff, Prasad Tadepalli
http://arxiv.org/abs/2006.06547v1
• [cs.AI]Consolidating Commonsense Knowledge
Filip Ilievski, Pedro Szekely, Jingwei Cheng, Fu Zhang, Ehsan Qasemi
http://arxiv.org/abs/2006.06114v1
• [cs.AI]Marginal Utility for Planning in Continuous or Large Discrete Action Spaces
Zaheen Farraz Ahmad, Levi H. S. Lelis, Michael Bowling
http://arxiv.org/abs/2006.06054v1
• [cs.AI]Modeling Human Driving Behavior through Generative Adversarial Imitation Learning
Raunak Bhattacharyya, Blake Wulfe, Derek Phillips, Alex Kuefler, Jeremy Morton, Ransalu Senanayake, Mykel Kochenderfer
http://arxiv.org/abs/2006.06412v1
• [cs.AI]Petri Nets with Parameterised Data: Modelling and Verification (Extended Version)
Silvio Ghilardi, Alessandro Gianola, Marco Montali, Andrey Rivkin
http://arxiv.org/abs/2006.06630v1
• [cs.AI]Surveys without Questions: A Reinforcement Learning Approach
Atanu R Sinha, Deepali Jain, Nikhil Sheoran, Sopan Khosla, Reshmi Sasidharan
http://arxiv.org/abs/2006.06323v1
• [cs.CG]Unsupervised Learning of 3D Point Set Registration
Lingjing Wang, Xiang Li, Yi Fang
http://arxiv.org/abs/2006.06200v1
• [cs.CL]A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages
Pedro Ortiz Suárez, Laurent Romary, Benoît Sagot
http://arxiv.org/abs/2006.06202v1
• [cs.CL]A Probabilistic Model with Commonsense Constraints for Pattern-based Temporal Fact Extraction
Yang Zhou, Tong Zhao, Meng Jiang
http://arxiv.org/abs/2006.06436v1
• [cs.CL]Augmenting Data for Sarcasm Detection with Unlabeled Conversation Context
Hankyol Lee, Youngjae Yu, Gunhee Kim
http://arxiv.org/abs/2006.06259v1
• [cs.CL]ClarQ: A large-scale and diverse dataset for Clarification Question Generation
Vaibhav Kumar, Alan W. black
http://arxiv.org/abs/2006.05986v2
• [cs.CL]CoSDA-ML: Multi-Lingual Code-Switching Data Augmentation for Zero-Shot Cross-Lingual NLP
Libo Qin, Minheng Ni, Yue Zhang, Wanxiang Che
http://arxiv.org/abs/2006.06402v1
• [cs.CL]ConfNet2Seq: Full Length Answer Generation from Spoken Questions
Vaishali Pal, Manish Shrivastava, Laurent Besacier
http://arxiv.org/abs/2006.05163v2
• [cs.CL]Discrete Latent Variable Representations for Low-Resource Text Classification
Shuning Jin, Sam Wiseman, Karl Stratos, Karen Livescu
http://arxiv.org/abs/2006.06226v1
• [cs.CL]Emora STDM: A Versatile Framework for Innovative Dialogue System Development
James D. Finch, Jinho D. Choi
http://arxiv.org/abs/2006.06143v1
• [cs.CL]Multi-hop Reading Comprehension across Documents with Path-based Graph Convolutional Network
Zeyun Tang, Yongliang Shen, Xinyin Ma, Wei Xu, Jiale Yu, Weiming Lu
http://arxiv.org/abs/2006.06478v1
• [cs.CL]Performance in the Courtroom: Automated Processing and Visualization of Appeal Court Decisions in France
Paul Boniol, George Panagopoulos, Christos Xypolopoulos, Rajaa El Hamdani, David Restrepo Amariles, Michalis Vazirgiannis
http://arxiv.org/abs/2006.06251v1
• [cs.CL]Provenance for Linguistic Corpora Through Nanopublications
Timo Lek, Anna de Groot, Tobias Kuhn, Roser Morante
http://arxiv.org/abs/2006.06341v1
• [cs.CL]Report from the NSF Future Directions Workshop, Toward User-Oriented Agents: Research Directions and Challenges
Maxine Eskenazi, Tiancheng Zhao
http://arxiv.org/abs/2006.06026v1
• [cs.CL]Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics
Nitika Mathur, Tim Baldwin, Trevor Cohn
http://arxiv.org/abs/2006.06264v1
• [cs.CL]Teaching Pre-Trained Models to Systematically Reason Over Implicit Knowledge
Alon Talmor, Oyvind Tafjord, Peter Clark, Yoav Goldberg, Jonathan Berant
http://arxiv.org/abs/2006.06609v1
• [cs.CL]Towards Unified Dialogue System Evaluation: A Comprehensive Analysis of Current Evaluation Protocols
Sarah E. Finch, Jinho D. Choi
http://arxiv.org/abs/2006.06110v1
• [cs.CR]Adversarial Attack Vulnerability of Medical Image Analysis Systems: Unexplored Factors
Suzanne C. Wetstein, Cristina González-Gonzalo, Gerda Bortsova, Bart Liefers, Florian Dubost, Ioannis Katramados, Laurens Hogeweg, Bram van Ginneken, Josien P. W. Pluim, Marleen de Bruijne, Clara I. Sánchez, Mitko Veta
http://arxiv.org/abs/2006.06356v1
• [cs.CR]DNS Tunneling: A Deep Learning based Lexicographical Detection Approach
Franco Palau, Carlos Catania, Jorge Guerra, Sebastian Garcia, Maria Rigaki
http://arxiv.org/abs/2006.06122v1
• [cs.CR]Fingerprinting Analog IoT Sensors for Secret-Free Authentication
Felix Lorenz, Lauritz Thamsen, Andreas Wilke, Ilja Behnke, Jens Waldmüller-Littke, Ilya Komarov, Odej Kao, Manfred Paeschke
http://arxiv.org/abs/2006.06296v1
• [cs.CR]Learning With Differential Privacy
Poushali Sengupta, Sudipta Paul, Subhankar Mishra
http://arxiv.org/abs/2006.05609v2
• [cs.CR]Optimizing Smart Grid Aggregators and Measuring Degree of Privacy in a Distributed Trust Based Anonymous Aggregation System
Mohammad Saidur Rahman
http://arxiv.org/abs/2006.06070v1
• [cs.CR]Resiliency by Retrograded Communication- The Revival of Shortwave as a Military Communication Channel
Jan Kallberg, Stephen S. Hamilton
http://arxiv.org/abs/2006.06148v1
• [cs.CV]A Deep Learning Framework for Recognizing both Static and Dynamic Gestures
Osama Mazhar, Sofiane Ramdani, Andrea Cherubini
http://arxiv.org/abs/2006.06321v1
• [cs.CV]An Edge Information and Mask Shrinking Based Image Inpainting Approach
Huali Xu, Xiangdong Su, Meng Wang, Xiang Hao, Guanglai Gao
http://arxiv.org/abs/2006.06196v1
• [cs.CV]Attentive WaveBlock: Complementarity-enhanced Mutual Networks for Unsupervised Domain Adaptation in Person Re-identification
Wenhao Wang, Fang Zhao, Shengcai Liao, Ling Shao
http://arxiv.org/abs/2006.06525v1
• [cs.CV]Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies
Yu Huang, Yue Chen
http://arxiv.org/abs/2006.06091v1
• [cs.CV]CLEval: Character-Level Evaluation for Text Detection and Recognition Tasks
Youngmin Baek, Daehyun Nam, Sungrae Park, Junyeop Lee, Seung Shin, Jeonghun Baek, Chae Young Lee, Hwalsuk Lee
http://arxiv.org/abs/2006.06244v1
• [cs.CV]CoMIR: Contrastive Multimodal Image Representation for Registration
Nicolas Pielawski, Elisabeth Wetzer, Johan Öfverstedt, Jiahao Lu, Carolina Wählby, Joakim Lindblad, Nataša Sladoje
http://arxiv.org/abs/2006.06325v1
• [cs.CV]Continual Learning for Affective Computing
Nikhil Churamani
http://arxiv.org/abs/2006.06113v1
• [cs.CV]Convolutional neural networks compression with low rank and sparse tensor decompositions
Pavel Kaloshin
http://arxiv.org/abs/2006.06443v1
• [cs.CV]Dance Revolution: Long Sequence Dance Generation with Music via Curriculum Learning
Ruozi Huang, Huang Hu, Wei Wu, Kei Sawada, Mi Zhang
http://arxiv.org/abs/2006.06119v1
• [cs.CV]Diagnosing Rarity in Human-Object Interaction Detection
Mert Kilickaya, Arnold Smeulders
http://arxiv.org/abs/2006.05728v1
• [cs.CV]Disentangled Non-Local Neural Networks
Minghao Yin, Zhuliang Yao, Yue Cao, Xiu Li, Zheng Zhang, Stephen Lin, Han Hu
http://arxiv.org/abs/2006.06668v1
• [cs.CV]DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders
Mangal Prakash, Alexander Krull, Florian Jug
http://arxiv.org/abs/2006.06072v1
• [cs.CV]Exploring Category-Agnostic Clusters for Open-Set Domain Adaptation
Yingwei Pan, Ting Yao, Yehao Li, Chong-Wah Ngo, Tao Mei
http://arxiv.org/abs/2006.06567v1
• [cs.CV]Exploring Weaknesses of VQA Models through Attribution Driven Insights
Shaunak Halbe
http://arxiv.org/abs/2006.06637v1
• [cs.CV]Fall Detector Adapted to Nursing Home Needs through an Optical-Flow based CNN
Alexy Carlier, Paul Peyramaure, Ketty Favre, Muriel Pressigout
http://arxiv.org/abs/2006.06201v1
• [cs.CV]Fast Coherent Point Drift
Xiang-Wei Feng, Da-Zheng Feng, Yun Zhu
http://arxiv.org/abs/2006.06281v1
• [cs.CV]Hypernetwork-Based Augmentation
Chih-Yang Chen, Che-Han Chang, Edward Y. Chang
http://arxiv.org/abs/2006.06320v1
• [cs.CV]Image Deconvolution via Noise-Tolerant Self-Supervised Inversion
Hirofumi Kobayashi, Ahmet Can Solak, Joshua Batson, Loic A. Royer
http://arxiv.org/abs/2006.06156v1
• [cs.CV]Improving Deep Metric Learning with Virtual Classes and Examples Mining
Pierre Jacob, David Picard, Aymeric Histace, Edouard Klein
http://arxiv.org/abs/2006.06611v1
• [cs.CV]JIT-Masker: Efficient Online Distillation for Background Matting
Jo Chuang, Qian Dong
http://arxiv.org/abs/2006.06185v1
• [cs.CV]Joint Training of Variational Auto-Encoder and Latent Energy-Based Model
Tian Han, Erik Nijkamp, Linqi Zhou, Bo Pang, Song-Chun Zhu, Ying Nian Wu
http://arxiv.org/abs/2006.06059v1
• [cs.CV]Kalman Filter Based Multiple Person Head Tracking
Mohib Ullah, Maqsood Mahmud, Habib Ullah, Kashif Ahmad, Ali Shariq Imran, Faouzi Alaya Cheikh
http://arxiv.org/abs/2006.06134v1
• [cs.CV]Large-Scale Adversarial Training for Vision-and-Language Representation Learning
Zhe Gan, Yen-Chun Chen, Linjie Li, Chen Zhu, Yu Cheng, Jingjing Liu
http://arxiv.org/abs/2006.06195v1
• [cs.CV]Learning a Unified Sample Weighting Network for Object Detection
Qi Cai, Yingwei Pan, Yu Wang, Jingen Liu, Ting Yao, Tao Mei
http://arxiv.org/abs/2006.06568v1
• [cs.CV]MOMS with Events: Multi-Object Motion Segmentation With Monocular Event Cameras
Chethan M. Parameshwara, Nitin J. Sanket, Arjun Gupta, Cornelia Fermuller, Yiannis Aloimonos
http://arxiv.org/abs/2006.06158v1
• [cs.CV]Map3D: Registration Based Multi-Object Tracking on 3D Serial Whole Slide Images
Ruining Deng, Haichun Yang, Aadarsh Jha, Yuzhe Lu, Peng Chu, Agnes Fogo, Yuankai Huo
http://arxiv.org/abs/2006.06038v1
• [cs.CV]MatchGAN: A Self-Supervised Semi-Supervised Conditional Generative Adversarial Network
Jiaze Sun, Binod Bhattarai, Tae-Kyun Kim
http://arxiv.org/abs/2006.06614v1
• [cs.CV]Minimum Potential Energy of Point Cloud for Robust Global Registration
Zijie Wu, Yaonan Wang, Qing Zhu, Jianxu Mao, Haotian Wu, Mingtao Feng, Ajmal mian
http://arxiv.org/abs/2006.06460v1
• [cs.CV]Morphing Attack Detection — Database, Evaluation Platform and Benchmarking
Kiran Raja, Matteo Ferrara, Annalisa Franco, Luuk Spreeuwers, Illias Batskos, Florens de Wit Marta Gomez-Barrero, Ulrich Scherhag, Daniel Fischer, Sushma Venkatesh, Jag Mohan Singh, Guoqiang Li, Loïc Bergeron, Sergey Isadskiy, Raghavendra Ramachandra, Christian Rathgeb, Dinusha Frings, Uwe Seidel, Fons Knopjes, Raymond Veldhuis, Davide Maltoni, Christoph Busch
http://arxiv.org/abs/2006.06458v1
• [cs.CV]Privacy-Aware Activity Classification from First Person Office Videos
Partho Ghosh, Md. Abrar Istiak, Nayeeb Rashid, Ahsan Habib Akash, Ridwan Abrar, Ankan Ghosh Dastider, Asif Shahriyar Sushmit, Taufiq Hasan
http://arxiv.org/abs/2006.06246v1
• [cs.CV]Privacy-Preserving Visual Feature Descriptors through Adversarial Affine Subspace Embedding
Mihai Dusmanu, Johannes L. Schönberger, Sudipta N. Sinha, Marc Pollefeys
http://arxiv.org/abs/2006.06634v1
• [cs.CV]Protecting Against Image Translation Deepfakes by Leaking Universal Perturbations from Black-Box Neural Networks
Nataniel Ruiz, Sarah Adel Bargal, Stan Sclaroff
http://arxiv.org/abs/2006.06493v1
• [cs.CV]Quasi-Dense Instance Similarity Learning
Jiangmiao Pang, Linlu Qiu, Haofeng Chen, Qi Li, Trevor Darrell, Fisher Yu
http://arxiv.org/abs/2006.06664v1
• [cs.CV]RTEX: A novel methodology for Ranking, Tagging, and Explanatory diagnostic captioning of radiography exams
Vasiliki Kougia, John Pavlopoulos, Panagiotis Papapetrou, Max Gordon
http://arxiv.org/abs/2006.06316v1
• [cs.CV]Rethinking the Truly Unsupervised Image-to-Image Translation
Kyungjune Baek, Yunjey Choi, Youngjung Uh, Jaejun Yoo, Hyunjung Shim
http://arxiv.org/abs/2006.06500v1
• [cs.CV]Revisiting visual-inertial structure from motion for odometry and SLAM initialization
Georgios Evangelidis, Branislav Micusik
http://arxiv.org/abs/2006.06017v1
• [cs.CV]Robust Multi-object Matching via Iterative Reweighting of the Graph Connection Laplacian
Yunpeng Shi, Shaohan Li, Gilad Lerman
http://arxiv.org/abs/2006.06658v1
• [cs.CV]SLIC-UAV: A Method for monitoring recovery in tropical restoration projects through identification of signature species using UAVs
Jo
c49
nathan Williams, Carola-Bibiane Schönlieb, Tom Swinfield, Bambang Irawan, Eva Achmad, Muhammad Zudhi, Habibi, Elva Gemita, David A. Coomes
http://arxiv.org/abs/2006.06624v1
• [cs.CV]Spectral Image Segmentation with Global Appearance Modeling
Jeova F. S. Rocha Neto, Pedro F. Felzenszwalb
http://arxiv.org/abs/2006.06573v1
• [cs.CV]Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker
http://arxiv.org/abs/2006.06015v1
• [cs.CV]Telling Left from Right: Learning Spatial Correspondence between Sight and Sound
Karren Yang, Bryan Russell, Justin Salamon
http://arxiv.org/abs/2006.06175v1
• [cs.CV]Towards Robust Fine-grained Recognition by Maximal Separation of Discriminative Features
Krishna Kanth Nakka, Mathieu Salzmann
http://arxiv.org/abs/2006.06028v1
• [cs.CV]Transferring and Regularizing Prediction for Semantic Segmentation
Yiheng Zhang, Zhaofan Qiu, Ting Yao, Chong-Wah Ngo, Dong Liu, Tao Mei
http://arxiv.org/abs/2006.06570v1
• [cs.CV]Understanding Human Hands in Contact at Internet Scale
Dandan Shan, Jiaqi Geng, Michelle Shu, David F. Fouhey
http://arxiv.org/abs/2006.06669v1
• [cs.CV]VirTex: Learning Visual Representations from Textual Annotations
Karan Desai, Justin Johnson
http://arxiv.org/abs/2006.06666v1
• [cs.CV]What makes instance discrimination good for transfer learning?
Nanxuan Zhao, Zhirong Wu, Rynson W. H. Lau, Stephen Lin
http://arxiv.org/abs/2006.06606v1
• [cs.CY]2020 UK Lockdown Cyber Narratives: the Secure, the Insecure and the Worrying
Karen Renaud, Paul van Schaik, Alastair Irons, Sara Wilford
http://arxiv.org/abs/2006.06340v1
• [cs.CY]Analyzing Power Grid, ICT, and Market Without Domain Knowledge Using Distributed Artificial Intelligence
Eric MSP Veith, Stephan Balduin, Nils Wenninghoff, Martin Tröschel, Lars Fischer, Astrid Nieße, Thomas Wolgast, Richard Sethmann, Bastian Fraune, Torben Woltjen
http://arxiv.org/abs/2006.06074v1
• [cs.CY]Design Considerations for High Impact, Automated Echocardiogram Analysis
Wiebke Toussaint, Dave Van Veen, Courtney Irwin, Yoni Nachmany, Manuel Barreiro-Perez, Elena Díaz-Peláez, Sara Guerreiro de Sousa, Liliana Millán, Pedro L. Sánchez, Antonio Sánchez-Puente, Jesús Sampedro-Gómez, P. Ignacio Dorado-Díaz, Víctor Vicente-Palacios
http://arxiv.org/abs/2006.06292v1
• [cs.CY]Montreal AI Ethics Institute’s Response to Scotland’s AI Strategy
Abhishek Gupta
http://arxiv.org/abs/2006.06300v1
• [cs.CY]SECure: A Social and Environmental Certificate for AI Systems
Abhishek Gupta, Camylle Lanteigne, Sara Kingsley
http://arxiv.org/abs/2006.06217v1
• [cs.CY]System to Integrate Fairness Transparently: An Industry Approach
Emily Dodwell, Cheryl Flynn, Balachander Krishnamurthy, Subhabrata Majumdar, Ritwik Mitra
http://arxiv.org/abs/2006.06082v1
• [cs.DB]TableQA: a Large-Scale Chinese Text-to-SQL Dataset for Table-Aware SQL Generation
Ningyuan Sun, Xuefeng Yang, Yunfeng Liu
http://arxiv.org/abs/2006.06434v1
• [cs.DC]Efficient Partial Snapshot Implementations
Nikolaos D. Kallimanis, Eleni Kanellou, Charidimos Kiosterakis
http://arxiv.org/abs/2006.06048v1
• [cs.DC]GNNAdvisor: An Efficient Runtime System for GNN Acceleration on GPUs
Yuke Wang, Boyuan Feng, Gushu Li, Shuangchen Li, Lei Deng, Yuan Xie, Yufei Ding
http://arxiv.org/abs/2006.06608v1
• [cs.DL]PeopleMap: Visualization Tool for Mapping Out Researchers using Natural Language Processing
Jon Saad-Falcon, Omar Shaikh, Zijie J. Wang, Austin P. Wright, Sasha Richardson, Duen Horng Chau
http://arxiv.org/abs/2006.06105v1
• [cs.GT]Online Learning in Iterated Prisoner’s Dilemma to Mimic Human Behavior
Baihan Lin, Djallel Bouneffouf, Guillermo Cecchi
http://arxiv.org/abs/2006.06580v1
• [cs.GT]Optimally Deceiving a Learning Leader in Stackelberg Games
Georgios Birmpas, Jiarui Gan, Alexandros Hollender, Francisco J. Marmolejo-Cossío, Ninad Rajgopal, Alexandros A. Voudouris
http://arxiv.org/abs/2006.06566v1
• [cs.HC]Affective Movement Generation using Laban Effort and Shape and Hidden Markov Models
Ali Samadani, Rob Gorbet, Dana Kulic
http://arxiv.org/abs/2006.06071v1
• [cs.HC]Creating a Robot Coach for Mindfulness and Wellbeing: A Longitudinal Study
Indu P. Bodala, Nikhil Churamani, Hatice Gunes
http://arxiv.org/abs/2006.05289v2
• [cs.HC]Mental Workload and Language Production in Non-Native Speaker IPA Interaction
Yunhan Wu, Justin Edwards, Orla Cooney, Anna Bleakley, Philip R. Doyle, Leigh Clark, Daniel Rough, Benjamin R. Cowan
http://arxiv.org/abs/2006.06331v1
• [cs.HC]See what I’m saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers
Yunhan Wu, Daniel Rough, Anna Bleakley, Justin Edwards, Orla Cooney, Philip R. Doyle, Leigh Clark, Benjamin R. Cowan
http://arxiv.org/abs/2006.06328v1
• [cs.HC]Transparency in Language Generation: Levels of Automation
Justin Edwards, Allison Perrone, Philip R. Doyle
http://arxiv.org/abs/2006.06295v1
• [cs.IR]Embed2Detect: Temporally Clustered Embedded Words for Event Detection in Social Media
Hansi Hettiarachchi, Mariam Adedoyin-Olowe, Jagdev Bhogal, Mohamed Medhat Gaber
http://arxiv.org/abs/2006.05908v2
• [cs.IT]AoI-optimal Joint Sampling and Updating for Wireless Powered Communication Systems
Mohamed A. Abd-Elmagid, Harpreet S. Dhillon, Nikolaos Pappas
http://arxiv.org/abs/2006.06339v1
• [cs.IT]Codes with locality from cyclic extensions of Deligne-Lusztig curves
Gretchen L. Matthews, Fernando L. Piñero
http://arxiv.org/abs/2006.06397v1
• [cs.IT]Combinatorics with Copula for Code based Post-Quantum Cryptography
Kelechi Chuwkunonyerem Emerole, Said Boussakta
http://arxiv.org/abs/2006.06598v1
• [cs.IT]On Decoding Fountain Codes with Erroneous Received Symbols
Xuan He, Kui Cai
http://arxiv.org/abs/2006.06492v1
• [cs.IT]Relay Aided Intelligent Reconfigurable Surfaces: Achieving the Potential Without So Many Antennas
Xiaoyan Ying, Umut Demirhan, Ahmed Alkhateeb
http://arxiv.org/abs/2006.06644v1
• [cs.IT]Sample-Efficient Low Rank Phase Retrieval
Seyedehsara Nayer, Namrata Vaswani
http://arxiv.org/abs/2006.06198v1
• [cs.IT]The block mutual coherence property condition for signal recovery
Jianwen Huang, Hailin Wang, Feng Zhang, Jianjun Wang
http://arxiv.org/abs/2006.06160v1
• [cs.IT]The high-order block RIP for non-convex block-sparse compressed sensing
Jianwen Huang, Xinling Liu, Jinyao Hou, Jianjun Wang
http://arxiv.org/abs/2006.06344v1
• [cs.IT]The perturbation analysis of nonconvex low-rank matrix robust recovery
Jianwen Huang, Wendong Wang, Feng Zhang, Jianjun Wang
http://arxiv.org/abs/2006.06283v1
• [cs.IT]Uplink and Downlink MIMO-NOMA with Simultaneous Triangularization
Aravindh Krishnamoorthy, Robert Schober
http://arxiv.org/abs/2006.06471v1
• [cs.LG]A Class of Algorithms for General Instrumental Variable Models
Niki Kilbertus, Matt J. Kusner, Ricardo Silva
http://arxiv.org/abs/2006.06366v1
• [cs.LG]A Generalised Linear Model Framework for Variational Autoencoders based on Exponential Dispersion Families
Robert Sicks, Ralf Korn, Stefanie Schwaar
http://arxiv.org/abs/2006.06267v1
• [cs.LG]A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning
Sijia Liu, Pin-Yu Chen, Bhavya Kailkhura, Gaoyuan Zhang, Alfred Hero, Pramod K. Varshney
http://arxiv.org/abs/2006.06224v1
• [cs.LG]A multi-objective-based approach for Fair Principal Component Analysis
Guilherme D. Pelegrina, Renan D. B. Brotto, Leonardo T. Duarte, João M. T. Romano, Romis Attux
http://arxiv.org/abs/2006.06137v1
• [cs.LG]Achieving robustness in classification using optimal transport with hinge regularization
Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio
http://arxiv.org/abs/2006.06520v1
• [cs.LG]AdaS: Adaptive Scheduling of Stochastic Gradients
Mahdi S. Hosseini, Konstantinos N. Plataniotis
http://arxiv.org/abs/2006.06587v1
• [cs.LG]Adaptation Strategies for Automated Machine Learning on Evolving Data
Bilge Celik, Joaquin Vanschoren
http://arxiv.org/abs/2006.06480v1
• [cs.LG]Adaptive Reward-Free Exploration
Emilie Kaufmann, Pierre Ménard, Omar Darwiche Domingues, Anders Jonsson, Edouard Leurent, Michal Valko
http://arxiv.org/abs/2006.06294v1
• [cs.LG]Bandit Samplers for Training Graph Neural Networks
Ziqi Liu, Zhengwei Wu, Zhiqiang Zhang, Jun Zhou, Shuang Yang, Le Song, Yuan Qi
http://arxiv.org/abs/2006.05806v2
• [cs.LG]Blissful Ignorance: Anti-Transfer Learning for Task Invariance
Eric Guizzo, Tillman Weyde, Giacomo Tarroni
http://arxiv.org/abs/2006.06494v1
• [cs.LG]Cumulant GAN
Yannis Pantazis, Dipjyoti Paul, Michail Fasoulakis, Yannis Stylianou, Markos Katsoulakis
http://arxiv.org/abs/2006.06625v1
• [cs.LG]DFraud3- Multi-Component Fraud Detection freeof Cold-start
Saeedreza Shehnepoor, Roberto Togneri, Wei Liu, Mohammed Bennamoun
http://arxiv.org/abs/2006.05718v2
• [cs.LG]DNF-Net: A Neural Architecture for Tabular Data
Ami Abutbul, Gal Elidan, Liran Katzir, Ran El-Yaniv
http://arxiv.org/abs/2006.06465v1
• [cs.LG]Deep Differential System Stability — Learning advanced computations from examples
François Charton, Amaury Hayat, Guillaume Lample
http://arxiv.org/abs/2006.06462v1
• [cs.LG]Deep Learning Requires Explicit Regularization for Reliable Predictive Probability
Taejong Joo, Uijung Chung
http://arxiv.org/abs/2006.06399v1
• [cs.LG]Deep Learning for Stable Monotone Dynamical Systems
Yu Wang, Qitong Gao, Miroslav Pajic
http://arxiv.org/abs/2006.06417v1
• [cs.LG]Demystifying Self-Supervised Learning: An Information-Theoretical Framework
Yao-Hung Hubert Tsai, Yue Wu, Ruslan Salakhutdinov, Louis-Philippe Morency
http://arxiv.org/abs/2006.05576v2
• [cs.LG]Deterministic Gaussian Averaged Neural Networks
Ryan Campbell, Chris Finlay, Adam M Oberman
http://arxiv.org/abs/2006.06061v1
• [cs.LG]Diagnosis and Analysis of Celiac Disease and Environmental Enteropathy on Biopsy Images using Deep Learning Approaches
Kamran Kowsari
http://arxiv.org/abs/2006.06627v1
• [cs.LG]Directional convergence and alignment in deep learning
Ziwei Ji, Matus Telgarsky
http://arxiv.org/abs/2006.06657v1
• [cs.LG]Distributed Reinforcement Learning in Multi-Agent Networked Systems
Yiheng Lin, Guannan Qu, Longbo Huang, Adam Wierman
http://arxiv.org/abs/2006.06555v1
• [cs.LG]Distribution Regression for Continuous-Time Processes via the Expected Signature
Maud Lemercier, Cristopher Salvi, Theodoros Damoulas, Edwin V. Bonilla, Terry Lyons
http://arxiv.org/abs/2006.05805v2
• [cs.LG]Dynamical mean-field theory for stochastic gradient descent in Gaussian mixture classification
Francesca Mignacco, Florent Krzakala, Pierfrancesco Urbani, Lenka Zdeborová
http://arxiv.org/abs/2006.06098v1
• [cs.LG]Dynamically Stable Infinite-Width Limits of Neural Classifiers
Eugene A. Golikov
http://arxiv.org/abs/2006.06574v1
• [cs.LG]Efficient Contextual Bandits with Continuous Actions
Maryam Majzoubi, Chicheng Zhang, Rajan Chari, Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins
http://arxiv.org/abs/2006.06040v1
• [cs.LG]Embed Me If You Can: A Geometric Perceptron
Pavlo Melnyk, Michael Felsberg, Mårten Wadenbäck
http://arxiv.org/abs/2006.06507v1
• [cs.LG]Exploration by Maximizing Rényi Entropy for Zero-Shot Meta RL
Chuheng Zhang, Yuanying Cai, Longbo Huang, Jian Li
http://arxiv.org/abs/2006.06193v1
• [cs.LG]Fair Data Integration
Sainyam Galhotra, Karthikeyan Shanmugam, Prasanna Sattigeri, Kush R. Varshney
http://arxiv.org/abs/2006.06053v1
• [cs.LG]G5: A Universal GRAPH-BERT for Graph-to-Graph Transfer and Apocalypse Learning
Jiawei Zhang
http://arxiv.org/abs/2006.06183v1
• [cs.LG]GAIT-prop: A biologically plausible learning rule derived from backpropagation of error
Nasir Ahmad, Marcel A. J. van Gerven, Luca Ambrogioni
http://arxiv.org/abs/2006.06438v1
• [cs.LG]GANgster: A Fraud Review Detector based on Regulated GAN with Data Augmentation
Saeedreza Shehnepoor, Roberto Togneri, Wei Liu, Mohammed Bennamoun
http://arxiv.org/abs/2006.06561v1
• [cs.LG]How Interpretable and Trustworthy are GAMs?
Chun-Hao Chang, Sarah Tan, Ben Lengerich, Anna Goldenberg, Rich Caruana
http://arxiv.org/abs/2006.06466v1
• [cs.LG]Implicit Kernel Attention
Kyungwoo Song, Yohan Jung, Dongjun Kim, Il-Chul Moon
http://arxiv.org/abs/2006.06147v1
• [cs.LG]Improved Algorithms for Convex-Concave Minimax Optimization
Yuanhao Wang, Jian Li
http://arxiv.org/abs/2006.06359v1
• [cs.LG]Interpretable Visualizations with Differentiating Embedding Networks
Isaac Robinson
http://arxiv.org/abs/2006.06640v1
• [cs.LG]Latent Transformations for Discrete-Data Normalising Flows
Rob Hesselink, Wilker Aziz
http://arxiv.org/abs/2006.06346v1
• [cs.LG]Learning Continuous-Time Dynamics by Stochastic Differential Networks
Yingru Liu, Yucheng Xing, Xuewen Yang, Xin Wang, Di Jin, Jing Shi
http://arxiv.org/abs/2006.06145v1
• [cs.LG]Learning Halfspaces with Tsybakov Noise
Ilias Diakonikolas, Vasilis Kontonis, Christos Tzamos, Nikos Zarifis
http://arxiv.org/abs/2006.06467v1
• [cs.LG]Learning Individually Inferred Communication for Multi-Agent Cooperation
Ziluo Ding, Tiejun Huang, Zongqing Lu
http://arxiv.org/abs/2006.06455v1
• [cs.LG]Learning Navigation Costs from Demonstration with Semantic Observations
Tianyu Wang, Vikas Dhiman, Nikolay Atanasov
http://arxiv.org/abs/2006.05043v2
• [cs.LG]Learning normalizing flows from Entropy-Kantorovich potentials
Chris Finlay, Augusto Gerolin, Adam M Oberman, Aram-Alexandre Pooladian
http://arxiv.org/abs/2006.06033v1
• [cs.LG]Learning to Extrapolate Knowledge: Transductive Few-shot Out-of-Graph Link Prediction
Jinheon Baek, Dong Bok Lee, Sung Ju Hwang
http://arxiv.org/abs/2006.06648v1
• [cs.LG]Learning to Incentivize Other Learning Agents
Jiachen Yang, Ang Li, Mehrdad Farajtabar, Peter Sunehag, Edward Hughes, Hongyuan Zha
http://arxiv.org/abs/2006.06051v1
• [cs.LG]Learning to Infer 3D Object Models from Images
Chang Chen, Fei Deng, Sungjin Ahn
http://arxiv.org/abs/2006.06130v1
• [cs.LG]Model-Size Reduction for Reservoir Computing by Concatenating Internal States Through Time
Yusuke Sakemi, Kai Morino, Timothée Leleu, Kazuyuki Aihara
http://arxiv.org/abs/2006.06218v1
• [cs.LG]NADS: Neural Architecture Distribution Search for Uncertainty Awareness
Randy Ardywibowo, Shahin Boluki, Xinyu Gong, Zhangyang Wang, Xiaoning Qian
http://arxiv.org/abs/2006.06646v1
• [cs.LG]NanoFlow: Scalable Normalizing Flows with Sublinear Parameter Complexity
Sang-gil Lee, Sungwon Kim, Sungroh Yoon
http://arxiv.org/abs/2006.06280v1
• [cs.LG]Neural Methods for Point-wise Dependency Estimation
Yao-Hung Hubert Tsai, Han Zhao, Makoto Yamada, Louis-Philippe Morency, Ruslan Salakhutdinov
http://arxiv.org/abs/2006.05553v2
• [cs.LG]On Coresets For Regularized Regression
Rachit Chhaya, Anirban Dasgupta, Supratim Shit
http://arxiv.org/abs/2006.05440v2
• [cs.LG]On Mixup Regularization
Luigi Carratino, Moustapha Cissé, Rodolphe Jenatton, Jean-Philippe Vert
http://arxiv.org/abs/2006.06049v1
• [cs.LG]On Noise Injection in Generative Adversarial Networks
Ruili Feng, Deli Zhao, Zhengjun Zha
http://arxiv.org/abs/2006.05891v2
• [cs.LG]On the Maximum Mutual Information Capacity of Neural Architectures
Brandon Foggo, Nanpeng Yu
http://arxiv.org/abs/2006.06037v1
• [cs.LG]PAC Bounds for Imitation and Model-based Batch Learning of Contextual Markov Decision Processes
Yash Nair, Finale Doshi-Velez
http://arxiv.org/abs/2006.06352v1
• [cs.LG]Probabilistic Auto-Encoder
Vanessa Böhm, Uroš Seljak
http://arxiv.org/abs/
847
2006.05479v1
847
2006.05479v1)
• [cs.LG]Real-Time Video Inference on Edge Devices via Adaptive Model Streaming
Mehrdad Khani, Pouya Hamadanian, Arash Nasr-Esfahany, Mohammad Alizadeh
http://arxiv.org/abs/2006.06628v1
• [cs.LG]Recovery and Generalization in Over-Realized Dictionary Learning
Jeremias Sulam, Chong You, Zhihui Zhu
http://arxiv.org/abs/2006.06179v1
• [cs.LG]Robust model training and generalisation with Studentising flows
Simon Alexanderson, Gustav Eje Henter
http://arxiv.org/abs/2006.06599v1
• [cs.LG]STL-SGD: Speeding Up Local SGD with Stagewise Communication Period
Shuheng Shen, Yifei Cheng, Jingchang Liu, Linli Xu
http://arxiv.org/abs/2006.06377v1
• [cs.LG]Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation
Devavrat Shah, Dogyoon Song, Zhi Xu, Yuzhe Yang
http://arxiv.org/abs/2006.06135v1
• [cs.LG]Scalable Partial Explainability in Neural Networks via Flexible Activation Functions
Schyler C. Sun, Chen Li, Zhuangkun Wei, Antonios Tsourdos, Weisi Guo
http://arxiv.org/abs/2006.06057v1
• [cs.LG]Self-Supervised Reinforcement Learning for Recommender Systems
Xin Xin, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose
http://arxiv.org/abs/2006.05779v2
• [cs.LG]Smoothed Geometry for Robust Attribution
Zifan Wang, Haofan Wang, Shakul Ramkumar, Matt Fredrikson, Piotr Mardziel, Anupam Datta
http://arxiv.org/abs/2006.06643v1
• [cs.LG]TS-UCB: Improving on Thompson Sampling With Little to No Additional Computation
Jackie Baek, Vivek F. Farias
http://arxiv.org/abs/2006.06372v1
• [cs.LG]The Backbone Method for Ultra-High Dimensional Sparse Machine Learning
Dimitris Bertsimas, Vassilis Digalakis Jr
http://arxiv.org/abs/2006.06592v1
• [cs.LG]Understanding Regularisation Methods for Continual Learning
Frederik Benzing
http://arxiv.org/abs/2006.06357v1
• [cs.LG]Wide and Deep Graph Neural Networks with Distributed Online Learning
Zhan Gao, Fernando Gama, Alejandro Ribeiro
http://arxiv.org/abs/2006.06376v1
• [cs.LG]Zeroth-Order Supervised Policy Improvement
Hao Sun, Ziping Xu, Yuhang Song, Meng Fang, Jiechao Xiong, Bo Dai, Zhengyou Zhang, Bolei Zhou
http://arxiv.org/abs/2006.06600v1
• [cs.LO]A framework for step-wise explaining how to solve constraint satisfaction problems
Bart Bogaerts, Emilio Gamba, Tias Guns
http://arxiv.org/abs/2006.06343v1
• [cs.MS]Accelerating linear solvers for large-scale Stokes problems with C++ metaprogramming
Denis Demidov, Lin Mu, Bin Wang
http://arxiv.org/abs/2006.06052v1
• [cs.NE]A Novel Meta-Heuristic Optimization Algorithm Inspired by the Spread of Viruses
Zhixi Li, Vincent Tam
http://arxiv.org/abs/2006.06282v1
• [cs.NE]Growing Artificial Neural Networks
John Mixter, Ali Akoglu
http://arxiv.org/abs/2006.06629v1
• [cs.NE]Hardware Implementation of Spiking Neural Networks Using Time-To-First-Spike Encoding
Seongbin Oh, Dongseok Kwon, Gyuho Yeom, Won-Mook Kang, Soochang Lee, Sung Yun Woo, Jang Saeng Kim, Min Kyu Park, Jong-Ho Lee
http://arxiv.org/abs/2
2000
006.05033v1
2000
006.05033v1)
• [cs.NE]Sensorimotor Visual Perception on Embodied System Using Free Energy Principle
Kanako Esaki, Tadayuki Matsumura, Kiyoto Ito, Hiroyuki Mizuno
http://arxiv.org/abs/2006.06192v1
• [cs.NE]Towards Dynamic Algorithm Selection for Numerical Black-Box Optimization: Investigating BBOB as a Use Case
Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck
http://arxiv.org/abs/2006.06586v1
• [cs.NI]On the Feasibility of Perfect Resilience with Local Fast Failover
Klaus-Tycho Foerster, Juho Hirvonen, Yvonne-Anne Pignolet, Stefan Schmid, Gilles Tredan
http://arxiv.org/abs/2006.06513v1
• [cs.NI]Recurrent Neural Networks for Handover Management in Next-Generation Self-Organized Networks
Zoraze Ali, Marco Miozzo, Lorenza Giupponi, Paolo Dini, Stojan Denic, Stavroula Vassaki
http://arxiv.org/abs/2006.06526v1
• [cs.RO]Complementary Visual Neuronal Systems Model for Collision Sensing
Qinbing Fu, Shigang Yue
http://arxiv.org/abs/2006.06431v1
• [cs.RO]Deep Drone Acrobatics
Elia Kaufmann, Antonio Loquercio, René Ranftl, Matthias Müller, Vladlen Koltun, Davide Scaramuzza
http://arxiv.org/abs/2006.05768v2
• [cs.RO]Ergodic Specifications for Flexible Swarm Control: From User Commands to Persistent Adaptation
Ahalya Prabhakar, Ian Abraham, Annalisa Taylor, Millicent Schlafly, Katarina Popovic, Giovani Diniz, Brendan Teich, Borislava Simidchieva, Shane Clark, Todd Murphey
http://arxiv.org/abs/2006.06081v1
• [cs.RO]From proprioception to long-horizon planning in novel environments: A hierarchical RL model
Nishad Gothoskar, Miguel Lázaro-Gredilla, Dileep George
http://arxiv.org/abs/2006.06620v1
• [cs.RO]Geometric Solutions for General Actuator Routing on Inflated-Beam Soft Growing Robots
Laura H Blumenschein, Margaret Koehler, Nathan S. Usevitch, Elliot W. Hawkes, D. Caleb Rucker, Allison M. Okamura
http://arxiv.org/abs/2006.06117v1
• [cs.RO]Geometric and Stiffness Modeling and Design of Calibration Experiments for the 7 dof Serial Manipulator KUKA iiwa 14 R820
Sami Sellami, Victor Massagué Respall
http://arxiv.org/abs/2006.06314v1
• [cs.RO]Graph Neural Networks for Motion Planning
Arbaaz Khan, Alejandro Ribeiro, Vijay Kumar, Anthony G. Francis
http://arxiv.org/abs/2006.06248v1
• [cs.RO]The Role of Modularity and Neuro-Regulation for the Production of Multiple Behaviors
Victor Massagué Respall
http://arxiv.org/abs/2006.06310v1
• [cs.RO]Tuning-Free Contact-Implicit Trajectory Optimization
Aykut Ozgun Onol, Radu Corcodel, Philip Long, Taskin Padir
http://arxiv.org/abs/2006.06176v1
• [cs.SD]Perceiving Music Quality with GANs
Agrin Hilmkil, Carl Thomé, Anders Arpteg
http://arxiv.org/abs/2006.06287v1
• [cs.SI]A Toolkit for Analyzing and Visualizing Online Users via Reshare Cascade Modeling
Quyu Kong, Rohit Ram, Marian-Andrei Rizoiu
http://arxiv.org/abs/2006.06167v1
• [cs.SI]Extracting and categorising the reactions to COVID-19 by the South African public — A social media study
Vukosi Marivate, Avashlin Moodley, Athandiwe Saba
http://arxiv.org/abs/2006.06336v1
• [cs.SI]Fair Clustering for Diverse and Experienced Groups
Ilya Amburg, Nate Veldt, Austin R. Benson
http://arxiv.org/abs/2006.05645v2
• [cs.SI]Forming an Electoral College for a Graph: a Heuristic Semi-supervised Learning Framework
Chen Li, Xutan Peng, Hao Peng, Jianxin Li, Lihong Wang, Philip S. Yu
http://arxiv.org/abs/2006.06469v1
• [cs.SI]Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps
Xianfeng Tang, Yozen Liu, Neil Shah, Xiaolin Shi, Prasenjit Mitra, Suhang Wang
http://arxiv.org/abs/2006.06427v1
• [cs.SI]Modeling and Simulation of COVID-19 Pandemic for Cincinnati Tri-State Area
Michael Rechtin, Vince Feldman, Sam Klare, Nathan Riddle, Rajnikant Sharma
http://arxiv.org/abs/2006.06021v1
• [cs.SI]Robust Detection of Adaptive Spammers by Nash Reinforcement Learning
Yingtong Dou, Guixiang Ma, Philip S. Yu, Sihong Xie
http://arxiv.org/abs/2006.06069v1
• [cs.SI]Understanding the Dynamics of Information Flow During Disaster Response Using Absorbing Markov Chains
Yitong Li, Wenying Ji
http://arxiv.org/abs/2006.06510v1
• [eess.AS]Deep generative models for musical audio synthesis
M. Huzaifah, L. Wyse
http://arxiv.org/abs/2006.06426v1
• [eess.AS]Investigating Robustness of Adversarial Samples Detection for Automatic Speaker Verification
Xu Li, Na Li, Jinghua Zhong, Xixin Wu, Xunying Liu, Dan Su, Dong Yu, Helen Meng
http://arxiv.org/abs/2006.06186v1
• [eess.AS]XiaoiceSing: A High-Quality and Integrated Singing Voice Synthesis System
Peiling Lu, Jie Wu, Jian Luan, Xu Tan, Li Zhou
http://arxiv.org/abs/2006.06261v1
• [eess.IV]COVID-19-CT-CXR: a freely accessible and weakly labeled chest X-ray and CT image collection on COVID-19 from biomedical literature
Yifan Peng, Yu-Xing Tang, Sungwon Lee, Yingying Zhu, Ronald M. Summers, Zhiyong Lu
http://arxiv.org/abs/2006.06177v1
• [eess.IV]DSU-net: Dense SegU-net for automatic head-and-neck tumor segmentation in MR images
Pin Tang, Chen Zu, Mei Hong, Rui Yan, Xingchen Peng, Jianghong Xiao, Xi Wu, Jiliu Zhou, Luping Zhou, Yan Wang
http://arxiv.org/abs/2006.06278v1
• [eess.IV]Fully-automated deep learning slice-based muscle estimation from CT images for sarcopenia assessment
Fahdi Kanavati, Shah Islam, Zohaib Arain, Eric O. Aboagye, Andrea Rockall
http://arxiv.org/abs/2006.06432v1
• [eess.IV]Interpreting CNN for Low Complexity Learned Sub-pixel Motion Compensation in Video Coding
Luka Murn, Saverio Blasi, Alan F. Smeaton, Noel E. O’Connor, Marta Mrak
http://arxiv.org/abs/2006.06392v1
• [eess.IV]TensorFlow with user friendly Graphical Framework for object detection API
Heemoon Yoon, Sang-Hee Lee, Mira Park
http://arxiv.org/abs/2006.06385v1
• [eess.IV]W-net: Simultaneous segmentation of multi-anatomical retinal structures using a multi-task deep neural network
Hongwei Zhao, Chengtao Peng, Lei Liu, Bin Li
http://arxiv.org/abs/2006.06277v1
• [eess.SP]A PDD Decoder for Binary Linear Codes With Neural Check Polytope Projection
Yi Wei, Ming-Min Zhao, Min-Jian Zhao, Ming Lei
http://arxiv.org/abs/2006.06240v1
• [eess.SP]A Primer on Large Intelligent Surface (LIS) for Wireless Sensing in an Industrial Setting
Cristian J. Vaca-Rubio, Pablo Ramirez-Espinosa, Robin Jess Williams, Kimmo Kansanen, Zheng-Hua Tan, Elisabeth de Carvalho, Petar Popovski
http://arxiv.org/abs/2006.06563v1
• [eess.SP]A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers
Niccolò Antonello, Philip N. Garner
http://arxiv.org/abs/2006.05389v2
• [eess.SP]Energy-Efficient Fixed-Gain AF Relay Assisted OFDM with Index Modulation
Jiusi Zhou, Shuping Dang, Basem Shihada, Mohamed-Slim Alouini
http://arxiv.org/abs/2006.04926v1
• [eess.SP]On Matched Filtering for Statistical Change Point Detection
Kevin C. Cheng, Shuchin Aeron, Michael C. Hughes, Eric L. Miller
http://arxiv.org/abs/org/abs/2006.05539v1
• [eess.SP]User Cooperation for IRS-aided Secure SWIPT MIMO: Active Attacks and Passive Eavesdropping
Gui Zhou, Cunhua Pan, Hong Ren, Kezhi Wang, Arumugam Nallanathan, Kai-Kit Wong
http://arxiv.org/abs/2006.05347v1
• [eess.SY]Data-driven Thermal Model Inference with ARMAX, in Smart Environments, based on Normalized Mutual Information
Zhanhong Jiang, Jonathan Francis, Anit Kumar Sahu, Sirajum Munir, Charles Shelton, Anthony Rowe, Mario Bergés
http://arxiv.org/abs/2006.06088v1
• [eess.SY]Stochastic properties of an inverted pendulum on a wheel on a soft surface
O. M. Kiselev
http://arxiv.org/abs/2006.06222v1
• [eess.SY]The Effects of Driver Coupling and Automation Impedance on Emergency Steering Interventions
Akshay Bhardwaj, Yidu Lu, Selina Pan, Nadine Sarter, Brent Gillespie
http://arxiv.org/abs/2006.06093v1
• [math.FA]Tight frames over the quaternions and equiangular lines
Shayne Waldron
http://arxiv.org/abs/2006.06126v1
• [math.OC]Ensuring smoothly navigable approximation sets by Bezier curve parameterizations in evolutionary bi-objective optimization — applied to brachytherapy treatment planning for prostate cancer
S. C. Maree, T. Alderliesten, P. A. N. Bosman
http://arxiv.org/abs/2006.06449v1
• [math.OC]Revisiting the Continuity of Rotation Representations in Neural Networks
Sitao Xiang, Hao Li
http://arxiv.org/abs/2006.06234v1
• [math.OC]Scalable Multi-Agent Reinforcement Learning for Networked Systems with Average Reward
Guannan Qu, Yiheng Lin, Adam Wierman, Na Li
http://arxiv.org/abs/2006.06626v1
• [math.ST]Asymptotics of Ridge(less) Regression under General Source Condition
Dominic Richards, Jaouad Mourtada, Lorenzo Rosasco
http://arxiv.org/abs/2006.06386v1
• [math.ST]Convergence of Pseudo-Bayes Factors in Forward and Inverse Regression Problems
Debashis Chatterjee, Sourabh Bhattacharya
http://arxiv.org/abs/2006.06020v1
• [math.ST]Exact and asymptotic properties of $δ$-records in the linear drift model
Raúl Gouet, Miguel Lafuente, F. Javier López, Gerardo Sanz
http://arxiv.org/abs/2006.05458v2
• [math.ST]Fast increased fidelity approximate Gibbs samplers for Bayesian Gaussian process regression
Kelly R. Moran, Matthew W. Wheeler
http://arxiv.org/abs/2006.06537v1
• [math.ST]How simplifying and flexible is the simplifying assumption in pair-copula constructions — some analytic answers in dimension three and beyond
Thomas Mroz, Sebastian Fuchs, Wolfgang Trutschnig
http://arxiv.org/abs/2006.06542v1
• [math.ST]Some More Properties of the Unit-Gompertz Distribution
M. Z. Anis, Debsurya De
http://arxiv.org/abs/2006.06439v1
• [nlin.AO]Deep Time-Delay Reservoir Computing: Dynamics and Memory Capacity
Mirko Goldmann, Felix Köster, Kathy Lüdge, Serhiy Yanchuk
http://arxiv.org/abs/2006.06322v1
• [nlin.CD]Stabilization of the wheeled inverted pendulum on a soft surface
O. M. Kiselev
http://arxiv.org/abs/2006.05450v1
• [physics.acc-ph]Superconducting radio-frequency cavity fault classification using machine learning at Jefferson Laboratory
Chris Tennant, Adam Carpenter, Tom Powers, Anna Shabalina Solopova, Lasitha Vidyaratne, Khan Iftekharuddin
http://arxiv.org/abs/2006.06562v1
• [physics.app-ph]FBG-Based Triaxial Force Sensor Integrated with an Eccentrically Configured Imaging Probe for Endoluminal Optical Biopsy
Zicong Wu, Anzhu Gao, Ning Liu, Zhu Jin, Guang-Zhong Yang
http://arxiv.org/abs/2006.06210v1
• [physics.app-ph]Machine learning model to cluster and map tribocorrosion regimes in feature space
Rahul Ramachandran
http://arxiv.org/abs/2006.06252v1
• [physics.comp-ph]Enabling Nonlinear Manifold Projection Reduced-Order Models by Extending Convolutional Neural Networks to Unstructured Data
John Tencer, Kevin Potter
http://arxiv.org/abs/2006.06154v1
• [physics.med-ph]Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation
Jonas Teuwen, Nikita Moriakov, Christian Fedon, Marco Caballo, Ingrid Reiser, Pedrag Bakic, Eloy García, Oliver Diaz, Koen Michielsen, Ioannis Sechopoulos
http://arxiv.org/abs/2006.06508v1
• [physics.soc-ph]Analysis of node2vec random walks on networks
Lingqi Meng, Naoki Masuda
http://arxiv.org/abs/2006.04904v1
• [quant-ph]Binary Classification with Classical Instances and Quantum Labels
Matthias C. Caro
http://arxiv.org/abs/2006.06005v1
• [stat.AP]On a Multi-Year Microlevel Collective Risk Model
Rosy Oh, Himchan Jeong, Jae Youn Ahn, Emiliano A. Valdez
http://arxiv.org/abs/2006.06151v1
• [stat.AP]What Drives Inflation and How: Evidence from Additive Mixed Models Selected by cAIC
Philipp Baumann, Enzo Rossi, Alexander Volkmann
http://arxiv.org/abs/2006.06274v1
• [stat.ME]A Bayesian Time-Varying Autoregressive Model for Improved Short- and Long-Term Prediction
Christoph Berninger, Almond Stöcker, David Rügamer
http://arxiv.org/abs/863
s/2006.05750v1
s/2006.05750v1)
• [stat.ME]A Bridge between Cross-validation Bayes Factors and Geometric Intrinsic Bayes Factors
Yekun Wang, Luis Pericchi
http://arxiv.org/abs/2006.06495v1
• [stat.ME]Bayesian Eigenvalue Regularization via Cumulative Shrinkage Process
Masahiro Tanaka
http://arxiv.org/abs/2006.06220v1
• [stat.ME]Conformal Inference of Counterfactuals and Individual Treatment Effects
Lihua Lei, Emmanuel J. Candès
http://arxiv.org/abs/2006.06138v1
• [stat.ME]Grouped GEE Analysis for Longitudinal Data
Tsubasa Ito, Shonosuke Sugasawa
http://arxiv.org/abs/2006.06180v1
• [stat.ME]Higher-order interactions in statistical physics and machine learning: A non-parametric solution to the inverse problem
Sjoerd Viktor Beentjes, Ava Khamseh
http://arxiv.org/abs/2006.06010v1
• [stat.ME]Modeling high-dimensional dependence among astronomical data
Roberto Vio, Thomas W. Nagler, Paola Andreani
http://arxiv.org/abs/2006.06268v1
• [stat.ME]Probabilistic Best Subset Selection by Gradient-Based Optimization
Mingzhang Yin, Nhat Ho, Bowei Yan, Xiaoning Qian, Mingyuan Zhou
http://arxiv.org/abs/2006.06448v1
• [stat.ME]Study on estimators of the PDF and CDF of the one parameter polynomial exponential distribution
Indrani Mukherjee, Sudhansu S. Maiti, Vijay Vir Singh
http://arxiv.org/abs/2006.06272v1
• [stat.ME]The Limits to Learning an SIR Process: Granular Forecasting for Covid-19
Jackie Baek, Vivek F. Farias, Andreea Georgescu, Retsef Levi, Tianyi Peng, Deeksha Sinha, Joshua Wilde, Andrew Zheng
http://arxiv.org/abs/2006.06373v1
• [stat.ME]Wilks’ theorem for semiparametric regressions with weakly dependent data
Marie Du Roy de Chaumaray, Matthieu Marbac, Valentin Patilea
http://arxiv.org/abs/2006.06350v1
• [stat.ML]A Variational Approach to Privacy and Fairness
Borja Rodríguez-Gálvez, Ragnar Thobaben, Mikael Skoglund
http://arxiv.org/abs/2006.06332v1
• [stat.ML]Asymptotic Errors for Teacher-Student Convex Generalized Linear Models (or : How to Prove Kabashima’s Replica Formula)
Cedric Gerbelot, Alia Abbara, Florent Krzakala
http://arxiv.org/abs/2006.06581v1
• [stat.ML]Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning
Qing Li, Siyuan Huang, Yining Hong, Yixin Chen, Ying Nian Wu, Song-Chun Zhu
http://arxiv.org/abs/2006.06649v1
• [stat.ML]CoinPress: Practical Private Mean and Covariance Estimation
Sourav Biswas, Yihe Dong, Gautam Kamath, Jonathan Ullman
http://arxiv.org/abs/2006.06618v1
• [stat.ML]Convergence of adaptive algorithms for weakly convex constrained optimization
Ahmet Alacaoglu, Yura Malitsky, Volkan Cevher
http://arxiv.org/abs/2006.06650v1
• [stat.ML]Deep Structural Causal Models for Tractable Counterfactual Inference
Nick Pawlowski, Daniel C. Castro, Ben Glocker
http://arxiv.org/abs/2006.06485v1
• [stat.ML]Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization
Benjamin Aubin, Florent Krzakala, Yue M. Lu, Lenka Zdeborová
http://arxiv.org/abs/2006.06560v1
• [stat.ML]Improved Design of Quadratic Discriminant Analysis Classifier in Unbalanced Settings
Amine Bejaoui, Khalil Elkhalil, Abla Kammoun, Mohamed Slim Alouni, Tarek Alnaffouri
http://arxiv.org/abs/2006.06355v1
• [stat.ML]Interpretable, similarity-driven multi-view embeddings from high-dimensional biomedical data
Brian B. Avants, Nicholas J. Tustison, James R. Stone
http://arxiv.org/abs/2006.06545v1
• [stat.ML]Mixup Training as the Complexity Reduction
Masanari Kimura
http://arxiv.org/abs/2006.06231v1
• [stat.ML]Modeling Shared Responses in Neuroimaging Studies through MultiView ICA
Hugo Richard, Luigi Gresele, Aapo Hyvärinen, Bertrand Thirion, Alexandre Gramfort, Pierre Ablin
http://arxiv.org/abs/2006.06635v1
• [stat.ML]Multi-index Antithetic Stochastic Gradient Algorithm
Mateusz B. Majka, Marc Sabate-Vidales, Łukasz Szpruch
http://arxiv.org/abs/2006.06102v1
• [stat.ML]Multiplicative noise and heavy tails in stochastic optimization
Liam Hodgkinson, Michael W. Mahoney
http://arxiv.org/abs/2006.06293v1
• [stat.ML]Neural Ordinary Differential Equations on Manifolds
Luca Falorsi, Patrick Forré
http://arxiv.org/abs/2006.06663v1
• [stat.ML]On mistakes we made in prior Computational Psychiatry Data driven approach projects and how they jeopardize translation of those findings in clinical practice
Milena Čukić Radenković, David Pokrajac, Victoria Lopez
http://arxiv.org/abs/2006.06418v1
• [stat.ML]Pointer Graph Networks
Petar Veličković, Lars Buesing, Matthew C. Overlan, Razvan Pascanu, Oriol Vinyals, Charles Blundell
http://arxiv.org/abs/2006.06380v1
• [stat.ML]Robust Grouped Variable Selection Using Distributionally Robust Optimization
Ruidi Chen, Ioannis Ch. Paschalidis
http://arxiv.org/abs/2006.06094v1
• [stat.ML]Robustified Multivariate Regression and Classification Using Distributionally Robust Optimization under the Wasserstein Metric
Ruidi Chen, Ioannis Ch. Paschalidis
http://arxiv.org/abs/2006.06090v1
• [stat.ML]Similarity-based Classification: Connecting Similarity Learning to Binary Classification
Han Bao, Takuya Shimada, Liyuan Xu, Issei Sato, Masashi Sugiyama
http://arxiv.org/abs/2006.06207v1
• [stat.ML]Sparse recovery by reduced variance stochastic approximation
Anatoli Juditsky, Andrei Kulunchakov, Hlib Tsyntseus
http://arxiv.org/abs/2006.06365v1
• [stat.ML]Stanza: A Nonlinear State Space Model for Probabilistic Inference in Non-Stationary Time Series
Anna K. Yanchenko, Sayan Mukherjee
http://arxiv.org/abs/2006.06553v1
• [stat.ML]Statistical Efficiency of Thompson Sampling for Combinatorial Semi-Bandits
Pierre Perrault, Etienne Boursier, Vianney Perchet, Michal Valko
http://arxiv.org/abs/2006.06613v1
• [stat.ML]Variance reduction for Langevin Monte Carlo in high dimensional sampling problems
Zhiyan Ding, Qin Li
http://arxiv.org/abs/2006.06068v1
• [stat.ML]Weighted Lasso Estimates for Sparse Logistic Regression: Non-asymptotic Properties with Measurement Error
Huamei Huang, Yujing Gao, Huiming Zhang, Bo Li
http://arxiv.org/abs/2006.06136v1
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