今日学术视野(2020.6.25)

astro-ph.HE - 高能天体物理现象

astro-ph.IM - 仪器仪表和天体物理学方法 cs.AI - 人工智能 cs.CE - 计算工程、 金融和科学 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.DS - 数据结构与算法 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PL - 编程语言 cs.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.DS - 动力系统 math.NT - 数论 math.OC - 优化与控制 math.ST - 统计理论 physics.comp-ph - 计算物理学 q-bio.NC - 神经元与认知 q-bio.PE - 人口与发展 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

• [astro-ph.HE]The GCE in a New Light: Disentangling the $γ$-ray Sky with Bayesian Graph Convolutional Neural Networks
• [astro-ph.IM]MANTRA: A Machine Learning reference lightcurve dataset for astronomical transient event recognition
• [cs.AI]A Framework for Fairness in Two-Sided Marketplaces
• [cs.AI]ELSIM: End-to-end learning of reusable skills through intrinsic motivation
• [cs.AI]Encoding Legal Balancing: Automating an Abstract Ethico-Legal Value Ontology in Preference Logic
• [cs.AI]Experience Replay with Likelihood-free Importance Weights
• [cs.AI]Logical Neural Networks
• [cs.AI]On the Relationship Between Active Inference and Control as Inference
• [cs.AI]Optimizing Interactive Systems via Data-Driven Objectives
• [cs.AI]PICO: Primitive Imitation for COntrol
• [cs.AI]The Effect of Multi-step Methods on Overestimation in Deep Reinforcement Learning
• [cs.AI]Towards Contrastive Explanations for Comparing the Ethics of Plans
• [cs.CE]Wavelet Augmented Regression Profiling (WARP): improved long-term estimation of travel time series with recurrent congestion
• [cs.CL]Can you tell? SSNet — a Sagittal Stratum-inspired Neural Network Framework for Sentiment Analysis
• [cs.CL]Combining Neural Language Models for WordSense Induction
• [cs.CL]Domain Adaptation for Semantic Parsing
• [cs.CL]Exploring Software Naturalness throughNeural Language Models
• [cs.CL]Improving Query Safety at Pinterest
• [cs.CL]Inductive Unsupervised Domain Adaptation for Few-Shot Classification via Clustering
• [cs.CL]Keyframe Segmentation and Positional Encoding for Video-guided Machine Translation Challenge 2020
• [cs.CL]NLPContributions: An Annotation Scheme for Machine Reading of Scholarly Contributions in Natural Language Processing Literature
• [cs.CL]Unsupervised Evaluation of Interactive Dialog with DialoGPT
• [cs.CR]Security and Privacy Preserving Deep Learning
• [cs.CV]A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence
• [cs.CV]AFDet: Anchor Free One Stage 3D Object Detection
• [cs.CV]Benchmarking features from different radiomics toolkits / toolboxes using Image Biomarkers Standardization Initiative
• [cs.CV]Boundary Regularized Building Footprint Extraction From Satellite Images Using Deep Neural Network
• [cs.CV]CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks
• [cs.CV]Calibrated Adversarial Refinement for Multimodal Semantic Segmentation
• [cs.CV]Contrastive Generative Adversarial Networks
• [cs.CV]DCNNs: A Transfer Learning comparison of Full Weapon Family threat detection forDual-Energy X-Ray Baggage Imagery
• [cs.CV]Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation
• [cs.CV]Discriminative Feature Alignment: ImprovingTransferability of Unsupervised DomainAdaptation by Gaussian-guided LatentAlignment
• [cs.CV]Distilling Object Detectors with Task Adaptive Regularization
• [cs.CV]Drive-Net: Convolutional Network for Driver Distraction Detection
• [cs.CV]Efficient Spatially Adaptive Convolution and Correlation
• [cs.CV]FNA++: Fast Network Adaptation via Parameter Remapping and Architecture Search
• [cs.CV]Facing the Hard Problems in FGVC
• [cs.CV]Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample
• [cs.CV]Increased-Range Unsupervised Monocular Depth Estimation
• [cs.CV]Instant 3D Object Tracking with Applications in Augmented Reality
• [cs.CV]Joint Detection and Multi-Object Tracking with Graph Neural Networks
• [cs.CV]LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation
• [cs.CV]Laplacian Mixture Model Point Based Registration
• [cs.CV]MSMD-Net: Deep Stereo Matching with Multi-scale and Multi-dimension Cost Volume
• [cs.CV]Modeling Lost Information in Lossy Image Compression
• [cs.CV]Motion Representation Using Residual Frames with 3D CNN
• [cs.CV]NeuralScale: Efficient Scaling of Neurons for Resource-Constrained Deep Neural Networks
• [cs.CV]Non-parametric spatially constrained local prior for scene parsing on real-world data
• [cs.CV]Object recognition through pose and shape estimation
• [cs.CV]ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects
• [cs.CV]PFGDF: Pruning Filter via Gaussian Distribution Feature for Deep Neural Networks Acceleration
• [cs.CV]PoseGAN: A Pose-to-Image Translation Framework for Camera Localization
• [cs.CV]Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network
• [cs.CV]RP2K: A Large-Scale Retail Product Dataset forFine-Grained Image Classification
• [cs.CV]Rotation Invariant Deep CBIR
• [cs.CV]SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection
• [cs.CV]Scribble2Label: Scribble-Supervised Cell Segmentation via Self-Generating Pseudo-Labels with Consistency
• [cs.CV]Single-Shot 3D Detection of Vehicles from Monocular RGB Images via Geometry Constrained Keypoints in Real-Time
• [cs.CV]Surpassing Real-World Source Training Data: Random 3D Characters for Generalizable Person Re-Identification
• [cs.CV]Towards Robust Sensor Fusion in Visual Perception
• [cs.CV]iffDetector: Inference-aware Feature Filtering for Object Detection
• [cs.CY]A Large-scale Analysis of App Inventor Projects
• [cs.CY]Effects of Non-Cognitive Factors on Post-Secondary Persistence of Deaf Students: An Agent-Based Modeling Approach
• [cs.CY]Lumos: A Library for Diagnosing Metric Regressions in Web-Scale Applications
• [cs.CY]Paratransit Agency Responses to the Adoption of Sub-contracted Services Using Secure Technologies
• [cs.CY]Successful implementation of discrete event simulation: the case of an Italian emergency department
• [cs.DC]Distributed Subgraph Enumeration via Backtracking-based Framework
• [cs.DC]Intermediate Value Linearizability: A Quantitative Correctness Criterion
• [cs.DC]Multiverse: Dynamic VM Provisioning for Virtualized High Performance Computing Clusters
• [cs.DC]On the Interoperability of Decentralized Exposure Notification Systems
• [cs.DC]Optimised allgatherv, reducescatter and allreduce communication in message-passing systems
• [cs.DC]PipeSim: Trace-driven Simulation of Large-Scale AI Operations Platforms
• [cs.DS]A Second-order Equilibrium in Nonconvex-Nonconcave Min-max Optimization: Existence and Algorithm
• [cs.DS]Approximation Algorithms for Sparse Principal Component Analysis
• [cs.DS]Similarity Search with Tensor Core Units
• [cs.IT]$C$-differential bent functions and perfect nonlinearity
• [cs.IT]Optimizing Downlink Resource Allocation in Multiuser MIMO Networks via Fractional Programming and the Hungarian Algorithm
• [cs.IT]Statistical Modeling of the Impact of Underwater Bubbles on an Optical Wireless Channel
• [cs.LG]A Dynamical Systems Approach for Convergence of the Bayesian EM Algorithm
• [cs.LG]A Multiscale Graph Convolutional Network Using Hierarchical Clustering
• [cs.LG]A Provably Convergent and Practical Algorithm for Min-max Optimization with Applications to GANs
• [cs.LG]Aligning Time Series on Incomparable Spaces
• [cs.LG]An Efficient Smoothing Proximal Gradient Algorithm for Convex Clustering
• [cs.LG]Automatic Data Augmentation for Generalization in Deep Reinforcement Learning
• [cs.LG]BETULA: Numerically Stable CF-Trees for BIRCH Clustering
• [cs.LG]Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation
• [cs.LG]C-SURE: Shrinkage Estimator and Prototype Classifier for Complex-Valued Deep Learning
• [cs.LG]Calibration of Neural Networks using Splines
• [cs.LG]Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning
• [cs.LG]Combinatorial Pure Exploration of Dueling Bandit
• [cs.LG]Correct Normalization Matters: Understanding the Effect of Normalization On Deep Neural Network Models For Click-Through Rate Prediction
• [cs.LG]Counterfactual Explanations of Concept Drift
• [cs.LG]Data Augmentation View on Graph Convolutional Network and the Proposal of Monte Carlo Graph Learning
• [cs.LG]Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning
• [cs.LG]Density-embedding layers: a general framework for adaptive receptive fields
• [cs.LG]Differentiable Segmentation of Sequences
• [cs.LG]Discrete Few-Shot Learning for Pan Privacy
• [cs.LG]Distance Correlation Sure Independence Screening for Accelerated Feature Selection in Parkinson’s Disease Vocal Data
• [cs.LG]Distributional Individual Fairness in Clustering
• [cs.LG]Environment Shaping in Reinforcement Learning using State Abstraction
• [cs.LG]Exact Support Recovery in Federated Regression with One-shot Communication
• [cs.LG]Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation
• [cs.LG]Extension of Direct Feedback Alignment to Convolutional and Recurrent Neural Network for Bio-plausible Deep Learning
• [cs.LG]Fairness without Demographics through Adversarially Reweighted Learning
• [cs.LG]Fast and Flexible Temporal Point Processes with Triangular Maps
• [cs.LG]Gaining insight into SARS-CoV-2 infection and COVID-19 severity using self-supervised edge features and Graph Neural Networks
• [cs.LG]Graph Neural Networks and Reinforcement Learning for Behavior Generation in Semantic Environments
• [cs.LG]Graph Prototypical Networks for Few-shot Learning on Attributed Networks
• [cs.LG]Hybrid Session-based News Recommendation using Recurrent Neural Networks
• [cs.LG]Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data
• [cs.LG]Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks
• [cs.LG]Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors
• [cs.LG]Long-Term Prediction of Lane Change Maneuver Through a Multilayer Perceptron
• [cs.LG]Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning
• [cs.LG]Multi-source Domain Adaptation via Weighted Joint Distributions Optimal Transport
• [cs.LG]Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction
• [cs.LG]On Compression Principle and Bayesian Optimization for Neural Networks
• [cs.LG]On Counterfactual Explanations under Predictive Multiplicity
• [cs.LG]On the Global Optimality of Model-Agnostic Meta-Learning
• [cs.LG]Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
• [cs.LG]Post-hoc Calibration of Neural Networks
• [cs.LG]Projective Latent Space Decluttering
• [cs.LG]Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
• [cs.LG]RayS: A Ray Searching Method for Hard-label Adversarial Attack
• [cs.LG]Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty
• [cs.LG]Rotation-Equivariant Neural Networks for Privacy Protection
• [cs.LG]Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
• [cs.LG]Show me the Way: Intrinsic Motivation from Demonstrations
• [cs.LG]Siamese Meta-Learning and Algorithm Selection with ‘Algorithm-Performance Personas’ [Proposal]
• [cs.LG]Simple and Effective VAE Training with Calibrated Decoders
• [cs.LG]Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
• [cs.LG]Spectral Evolution with Approximated Eigenvalue Trajectories for Link Prediction
• [cs.LG]Support Union Recovery in Meta Learning of Gaussian Graphical Models
• [cs.LG]Time Series Regression
• [cs.LO]A Constructive, Type-Theoretic Approach to Regression via Global Optimisation
• [cs.MA]Calibration of Shared Equilibria in General Sum Partially Observable Markov Games
• [cs.NE]Always-On, Sub-300-nW, Event-Driven Spiking Neural Network based on Spike-Driven Clock-Generation and
df6
Clock- and Power-Gating for an Ultra-Low-Power Intelligent Device
• [cs.NE]Efficient Hyperparameter Optimization in Deep Learning Using a Variable Length Genetic Algorithm
• [cs.NE]First Steps Towards a Runtime Analysis When Starting With a Good Solution
• [cs.NE]Inference with Artificial Neural Networks on the Analog BrainScaleS-2 Hardware
• [cs.NE]Learning Physical Constraints with Neural Projections
• [cs.NE]Maximizing Submodular or Monotone Functions under Partition Matroid Constraints by Multi-objective Evolutionary Algorithms
• [cs.NE]Particle Swarm Optimization for Energy Disaggregation in Industrial and Commercial Buildings
• [cs.NE]hxtorch: PyTorch for ANNs on BrainScaleS-2
• [cs.NI]Location-Aware Resource Allocation Algorithm in Satellite Ground Station Networks
• [cs.NI]Optimal Network Slicing for Service-Oriented Networks with Flexible Routing and Guaranteed E2E Latency
• [cs.PL]Information-theoretic User Interaction: Significant Inputs for Program Synthesis
• [cs.RO]Coverage Path Planning with Track Spacing Adaptation for Autonomous Underwater Vehicles
• [cs.RO]Feature Expansive Reward Learning: Rethinking Human Input
• [cs.RO]Generalized Grasping for Mechanical Grippers for Unknown Objects with Partial Point Cloud Representations
• [cs.RO]Grasp State Assessment of Deformable Objects Using Visual-Tactile Fusion Perception
• [cs.RO]Learning dynamics for improving control of overactuated flying systems
• [cs.RO]dm_control: Software and Tasks for Continuous Control
• [cs.SE]Technology Readiness Levels for Machine Learning Systems
• [cs.SI]Opinion Diffusion Software with Strategic Opinion Revelation and Unfriending
• [cs.SI]The Hawkes Edge Partition Model for Continuous-time Event-based Temporal Networks
• [cs.SI]Using graph theory and social media data to assess cultural ecosystem services in coastal areas: Method development and application
• [econ.EM]The Macroeconomy as a Random Forest
• [eess.AS]Articulatory-WaveNet: Autoregressive Model For Acoustic-to-Articulatory Inversion
• [eess.AS]Real Time Speech Enhancement in the Waveform Domain
• [eess.AS]Unsupervised Sound Separation Using Mixtures of Mixtures
• [eess.IV]3D Probabilistic Segmentation and Volumetry from 2D projection images
• [eess.IV]Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network
• [eess.IV]Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness
• [eess.IV]Deep Low-rank Prior in Dynamic MR Imaging
• [eess.IV]Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention
• [eess.IV]Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI
• [eess.IV]Semantic Features Aided Multi-Scale Reconstruction of Inter-Modality Magnetic Resonance Images
• [eess.IV]Semi-Supervised Learning for Fetal Brain MRI Quality Assessment with ROI consistency
• [eess.SP]Artificial Intelligence-Assisted Energy and Thermal Comfort Control for Sustainable Buildings: An Extended Representation of the Systematic Review
• [eess.SP]Deep Reinforcement Learning Control for Radar Detection and Tracking in Congested Spectral Environments
• [eess.SP]Fast Initial Access with Deep Learning for Beam Prediction in 5G mmWave Networks
• [eess.SP]Unsupervised ensembling of multiple software sensors: a new approach for electrocardiogram-derived respiration using one or two channels
• [eess.SY]Online Multi-agent Reinforcement Learning for Decentralized Inverter-based Volt-VAR Control
• [eess.SY]Parameter Estimation Bounds Based on the Theory of Spectral Lines
• [math.DS]Inferring Causal Networks of Dynamical Systems through Transient Dynamics and Perturbation
• [math.NT]A Note on the Cross-Correlation of Costas Permutations
• [math.OC]A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse Problems
• [math.OC]Inexact Derivative-Free Optimization for Bilevel Learning
• [math.ST]An efficient Averaged Stochastic Gauss-Newtwon algorithm for estimating parameters of non linear regressions models
• [math.ST]Bootstrapping $\ell_p$-Statistics in High Dimensions
• [math.ST]Fitting inhomogeneous phase-type distributions to data: the univariate and the multivariate case
• [math.ST]Gromov-Wasserstein Distance based Object Matching: Asymptotic Inference
• [math.ST]Optimality of the max test for detecting sparse signals with Gaussian or heavier tail
• [physics.comp-ph]Phase space learning with neural networks
• [q-bio.NC]The principles of adaptation in organisms and machines II: Thermodynamics of the Bayesian brain
• [q-bio.PE]A self-supervised neural-analytic method to predict the evolution of COVID-19 in Romania
• [q-bio.QM]Deep Belief Network based representation learning for lncRNA-disease association prediction
• [quant-ph]Optimal Extensions of Resource Measures and their Applications
• [stat.AP]Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs
• [stat.AP]Effectiveness and Compliance to Social Distancing During COVID-19
• [stat.AP]Estimation of COVID-19 under-reporting in Brazilian States through SARI
• [stat.AP]Magnify Your Population: Statistical Downscaling to Augment the Spatial Resolution of Socioeconomic Census Data
• [stat.AP]Spatio-temporal evolution of global surface temperature distributions
• [stat.ME]A Causally Formulated Hazard Ratio Estimation through Backdoor Adjustment on Structural Causal Model
• [stat.ME]A Revisit to De-biased Lasso for Generalized Linear Models
• [stat.ME]An improved sample size calculation method for score tests in generalized linear models
• [stat.ME]Conditional independence testing via weighted partial copulas
• [stat.ME]Controlling for Unknown Confounders in Neuroimaging
• [stat.ME]Decoupling Shrinkage and Selection in Gaussian Linear Factor Analysis
• [stat.ME]Fast and Optimal Bayesian Approximations for Targeted Prediction
• [stat.ME]Min-Mid-Max Scaling, Limits of Agreement, and Agreement Score
• [stat.ME]Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020)
• [stat.ME]The role of swabs in modeling the COVID-19 outbreak in the most affected regions of Italy
• [stat.ME]Wasserstein Autoregressive Models for Density Time Series
• [stat.ML]A Comparative Study of Temporal Non-Negative Matrix Factorization with Gamma Markov Chains
• [stat.ML]ABID: Angle Based Intrinsic Dimensionality
• [stat.ML]Approximate Cross-Validation for Structured Models
• [stat.ML]Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data
• [stat.ML]Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures
• [stat.ML]Disentangling by Subspace Diffusion
• [stat.ML]Efficient Inference of Nonparametric Interaction in Spiking-neuron Networks
• [stat.ML]Fair Performance Metric Elicitation
• [stat.ML]Good linear classifiers are abundant in the interpolating regime
• [stat.ML]Limits of Transfer Learning
• [stat.ML]Normalizing Flows Across Dimensions
• [stat.ML]PAC-Bayes Analysis Beyond the Usual Bounds
• [stat.ML]Private Distributed Mean Estimation
• [stat.ML]SWAG: A Wrapper Method for Sparse Learning
• [stat.ML]Solving the Phantom Inventory Problem: Near-optimal Entry-wise Anomaly Detection
• [stat.ML]Statistical Mechanics of Generalization in Kernel Regression
• [stat.ML]The Generalized Lasso with Nonlinear Observations and Generative Priors
• [stat.ML]Variational Orthogonal Features
• [stat.ML]not-MIWAE: Deep Generative Modelling with Missing not at Random Data
·····································
• [astro-ph.HE]The GCE in a New Light: Disentangling the $γ$-ray Sky with Bayesian Graph Convolutional Neural Networks
_Florian List, Nicholas L. Rodd, Geraint F. Lewis, Ishaan Bhat
http://arxiv.org/abs/2006.12504v1
• [astro-ph.IM]MANTRA: A Machine Learning reference lightcurve dataset for astronomical transient event recognition
Mauricio Neira, Catalina Gómez, John F. Suárez-Pérez, Diego A. Gómez, Juan Pablo Reyes, Marcela Hernández Hoyos, Pablo Arbeláez, Jaime E. Forero-Romero
http://arxiv.org/abs/2006.13163v1
• [cs.AI]A Framework for Fairness in Two-Sided Marketplaces
Kinjal Basu, Cyrus DiCiccio, Heloise Logan, Noureddine El Karoui
http://arxiv.org/abs/2006.12756v1
• [cs.AI]ELSIM: End-to-end learning of reusable skills through intrinsic motivation
Arthur Aubret, Laetitia Matignon, Salima Hassas
http://arxiv.org/abs/2006.12903v1
• [cs.AI]Encoding Legal Balancing: Automating an Abstract Ethico-Legal Value Ontology in Preference Logic
Christoph Benzmüller, David Fuenmayor, Bertram Lomfeld
http://arxiv.org/abs/2006.12789v1
• [cs.AI]Experience Replay with Likelihood-free Importance Weights
Samarth Sinha, Jiaming Song, Animesh Garg, Stefano Ermon
http://arxiv.org/abs/2006.13169v1
• [cs.AI]Logical Neural Networks
Ryan Riegel, Alexander Gray, Francois Luus, Naweed Khan, Ndivhuwo Makondo, Ismail Yunus Akhalwaya, Haifeng Qian, Ronald Fagin, Francisco Barahona, Udit Sharma, Shajith Ikbal, Hima Karanam, Sumit Neelam, Ankita Likhyani, Santosh Srivastava
http://arxiv.org/abs/2006.13155v1
• [cs.AI]On the Relationship Between Active Inference and Control as Inference
Beren Millidge, Alexander Tschantz, Anil K Seth, Christopher L Buckley
http://arxiv.org/abs/2006.12964v1
• [cs.AI]Optimizing Interactive Systems via Data-Driven Objectives
Ziming Li, Julia Kiseleva, Alekh Agarwal, Maarten de Rijke, Ryen W. White
http://arxiv.org/abs/2006.12999v1
• [cs.AI]PICO: Primitive Imitation for COntrol
Corban G. Rivera, Katie M. Popek, Chace Ashcraft, Edward W. Staley, Kapil D. Katyal, Bart L. Paulhamus
http://arxiv.org/abs/2006.12551v1
• [cs.AI]The Effect of Multi-step Methods on Overestimation in Deep Reinforcement Learning
Lingheng Meng, Rob Gorbet, Dana Kulić
http://arxiv.org/abs/2006.12692v1
• [cs.AI]Towards Contrastive Explanations for Comparing the Ethics of Plans
Benjamin Krarup, Senka Krivic, Felix Lindner, Derek Long
http://arxiv.org/abs/2006.12632v1
• [cs.CE]Wavelet Augmented Regression Profiling (WARP): improved long-term estimation of travel time series with recurrent congestion
Alvaro Cabrejas Egea, Colm Connaughton
http://arxiv.org/abs/2006.13072v1
• [cs.CL]Can you tell? SSNet — a Sagittal Stratum-inspired Neural Network Framework for Sentiment Analysis
Apostol Vassilev, Munawar Hasan
http://arxiv.org/abs/2006.12958v1
• [cs.CL]Combining Neural Language Models for WordSense Induction
Nikolay Arefyev, Boris Sheludko, Tatiana Aleksashina
http://arxiv.org/abs/2006.13200v1
• [cs.CL]Domain Adaptation for Semantic Parsing
Zechang Li, Yuxuan Lai, Yansong Feng, Dongyan Zhao
http://arxiv.org/abs/2006.13071v1
• [cs.CL]Exploring Software Naturalness throughNeural Language Models
Luca Buratti, Saurabh Pujar, Mihaela Bornea, Scott McCarley, Yunhui Zheng, Gaetano Rossiello, Alessandro Morari, Jim Laredo, Veronika Thost, Yufan Zhuang, Giacomo Domeniconi
http://arxiv.org/abs/2006.12641v1
• [cs.CL]Improving Query Safety at Pinterest
Abhijit Mahabal, Yinrui Li, Rajat Raina, Daniel Sun, Revati Mahajan, Jure Leskovec
http://arxiv.org/abs/2006.11511v2
• [cs.CL]Inductive Unsupervised Domain Adaptation for Few-Shot Classification via Clustering
Xin Cong, Bowen Yu, Tingwen Liu, Shiyao Cui, Hengzhu Tang, Bin Wang
http://arxiv.org/abs/2006.12816v1
• [cs.CL]Keyframe Segmentation and Positional Encoding for Video-guided Machine Translation Challenge 2020
Tosho Hirasawa, Zhishen Yang, Mamoru Komachi, Naoaki Okazaki
http://arxiv.org/abs/2006.12799v1
• [cs.CL]NLPContributions: An Annotation Scheme for Machine Reading of Scholarly Contributions in Natural Language Processing Literature
Jennifer D’Souza, Sören Auer
http://arxiv.org/abs/2006.12870v1
• [cs.CL]Unsupervised Evaluation of Interactive Dialog with DialoGPT
Shikib Mehri, Maxine Eskenazi
http://arxiv.org/abs/2006.12719v1
• [cs.CR]Security and Privacy Preserving Deep Learning
Saichethan Miriyala Reddy, Saisree Miriyala
http://arxiv.org/abs/2006.12698v1
• [cs.CV]A Survey on Deep Learning for Localization and Mapping: Towards the Age of Spatial Machine Intelligence
Changhao Chen, Bing Wang, Chris Xiaoxuan Lu, Niki Trigoni, Andrew Markham
http://arxiv.org/abs/2006.12567v1
• [cs.CV]AFDet: Anchor Free One Stage 3D Object Detection
Runzhou Ge, Zhuangzhuang Ding, Yihan Hu, Yu Wang, Sijia Chen, Li Huang, Yuan Li
http://arxiv.org/abs/2006.12671v1
• [cs.CV]Benchmarking features from different radiomics toolkits / toolboxes using Image Biomarkers Standardization Initiative
Mingxi Lei, Bino Varghese, Darryl Hwang, Steven Cen, Xiaomeng Lei, Afshin Azadikhah, Bhushan Desai, Assad Oberai, Vinay Duddalwar
http://arxiv.org/abs/2006.12761v1
• [cs.CV]Boundary Regularized Building Footprint Extraction From Satellite Images Using Deep Neural Network
Kang Zhao, Muhammad Kamran, Gunho Sohn
http://arxiv.org/abs/2006.13176v1
• [cs.CV]CIE XYZ Net: Unprocessing Images for Low-Level Computer Vision Tasks
Mahmoud Afifi, Abdelrahman Abdelhamed, Abdullah Abuolaim, Abhijith Punnappurath, Michael S. Brown
http://arxiv.org/abs/2006.12709v1
• [cs.CV]Calibrated Adversarial Refinement for Multimodal Semantic Segmentation
Elias Kassapis, Georgi Dikov, Deepak K. Gupta, Cedric Nugteren
http://arxiv.org/abs/2006.13144v1
• [cs.CV]Contrastive Generative Adversarial Networks
Minguk Kang, Jaesik Park
http://arxiv.org/abs/2006.12681v1
• [cs.CV]DCNNs: A Transfer Learning comparison of Full Weapon Family threat detection forDual-Energy X-Ray Baggage Imagery
A. Williamson, P. Dickinson, T. Lambrou, J. C. Murray
http://arxiv.org/abs/2006.13065v1
• [cs.CV]Deep Learning of Unified Region, Edge, and Contour Models for Automated Image Segmentation
Ali Hatamizadeh
http://arxiv.org/abs/2006.12706v1
• [cs.CV]Discriminative Feature Alignment: ImprovingTransferability of Unsupervised DomainAdaptation by Gaussian-guided LatentAlignment
Jing Wang, Jiahong Chen, Jianzhe Lin, Leonid Sigal, Clarence W. de Silva
http://arxiv.org/abs/2006.12770v1
• [cs.CV]Distilling Object Detectors with Task Adaptive Regularization
Ruoyu Sun, Fuhui Tang, Xiaopeng Zhang, Hongkai Xiong, Qi Tian
http://arxiv.org/abs/2006.13108v1
• [cs.CV]Drive-Net: Convolutional Network for Driver Distraction Detection
Mohammed S. Majdi, Sundaresh Ram, Jonathan T. Gill, Jeffery J. Rodriguez
http://arxiv.org/abs/2006.12586v1
• [cs.CV]Efficient Spatially Adaptive Convolution and Correlation
Thomas W. Mitchel, Benedict Brown, David Koller, Tim Weyrich, Szymon Rusinkiewicz, Michael Kazhdan
http://arxiv.org/abs/2006.13188v1
• [cs.CV]FNA++: Fast Network Adaptation via Parameter Remapping and Architecture Search
Jiemin Fang, Yuzhu Sun, Qian Zhang, Kangjian Peng, Yuan Li, Wenyu Liu, Xinggang Wang
http://arxiv.org/abs/2006.12986v1
• [cs.CV]Facing the Hard Problems in FGVC
Connor Anderson, Matt Gwilliam, Adam Teuscher, Andrew Merrill, Ryan Farrell
http://arxiv.org/abs/2006.13190v1
• [cs.CV]Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample
Shir Gur, Sagie Benaim, Lior Wolf
http://arxiv.org/abs/2006.12226v2
• [cs.CV]Increased-Range Unsupervised Monocular Depth Estimation
Saad Imran, Muhammad Umar Karim Khan, Sikander Bin Mukarram, Chong-Min Kyung
http://arxiv.org/abs/2006.12791v1
• [cs.CV]Instant 3D Object Tracking with Applications in Augmented Reality
Adel Ahmadyan, Tingbo Hou, Jianing Wei, Liangkai Zhang, Artsiom Ablavatski, Matthias Grundmann
http://arxiv.org/abs/2006.13194v1
• [cs.CV]Joint Detection and Multi-Object Tracking with Graph Neural Networks
Yongxin Wang, Xinshuo Weng, Kris Kitani
http://arxiv.org/abs/2006.13164v1
• [cs.CV]LAMP: Large Deep Nets with Automated Model Parallelism for Image Segmentation
Wentao Zhu, Can Zhao, Wenqi Li, Holger Roth, Ziyue Xu, Daguang Xu
http://arxiv.org/abs/2006.12575v1
• [cs.CV]Laplacian Mixture Model Point Based Registration
Mohammad Sadegh Majdi, Emad Fatemizadeh
http://arxiv.org/abs/2006.12582v1
• [cs.CV]MSMD-Net: Deep Stereo Matching with Multi-scale and Multi-dimension Cost Volume
Zhelun Shen, Yuchao Dai, Zhibo Rao
http://arxiv.org/abs/2006.12797v1
• [cs.CV]Modeling Lost Information in Lossy Image Compression
Yaolong Wang, Mingqing Xiao, Chang Liu, Shuxin Zheng, Tie-Yan Liu
http://arxiv.org/abs/2006.11999v2
• [cs.CV]Motion Representation Using Residual Frames with 3D CNN
Li Tao, Xueting Wang, Toshihiko Yamasaki
http://arxiv.org/abs/2006.13017v1
• [cs.CV]NeuralScale: Efficient Scaling of Neurons for Resource-Constrained Deep Neural Networks
Eugene Lee, Chen-Yi Lee
http://arxiv.org/abs/2006.12813v1
• [cs.CV]Non-parametric spatially constrained local prior for scene parsing on real-world data
Ligang Zhang
http://arxiv.org/abs/2006.12874v1
• [cs.CV]Object recognition through pose and shape estimation
Anitta D, Annis Fathima A
http://arxiv.org/abs/2006.12864v1
• [cs.CV]ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects
Dhruv Batra, Aaron Gokaslan, Aniruddha Kembhavi, Oleksandr Maksymets, Roozbeh Mottaghi, Manolis Savva, Alexander Toshev, Erik Wijmans
http://arxiv.org/abs/2006.13171v1
• [cs.CV]PFGDF: Pruning Filter via Gaussian Distribution Feature for Deep Neural Networks Acceleration
Jianrong Xu, Chao Li, Bifeng Cui, Kang Yang, Yongjun Xu
http://arxiv.org/abs/2006.12963v1
• [cs.CV]PoseGAN: A Pose-to-Image Translation Framework for Camera Localization
Kanglin Liu, Qing Li, Guoping Qiu
http://arxiv.org/abs/2006.12712v1
• [cs.CV]Probabilistic Crowd GAN: Multimodal Pedestrian Trajectory Prediction using a Graph Vehicle-Pedestrian Attention Network
Stuart Eiffert, Kunming Li, Mao Shan, Stewart Worrall, Salah Sukkarieh, Eduardo Nebot
http://arxiv.org/abs/2006.12906v1
• [cs.CV]RP2K: A Large-Scale Retail Product Dataset forFine-Grained Image Classification
Jingtian Peng, Chang Xiao, Xun Wei, Yifan Li
http://arxiv.org/abs/2006.12634v1
• [cs.CV]Rotation Invariant Deep CBIR
Subhadip Maji, Smarajit Bose
http://arxiv.org/abs/2006.13046v1
• [cs.CV]SLV: Spatial Likelihood Voting for Weakly Supervised Object Detection
Ze Chen, Zhihang Fu, Rongxin Jiang, Yaowu Chen, Xian-sheng Hua
http://arxiv.org/abs/2006.12884v1
• [cs.CV]Scribble2Label: Scribble-Supervised Cell Segmentation via Self-Generating Pseudo-Labels with Consistency
Hyeonsoo Lee, Won-Ki Jeong
http://arxiv.org/abs/2006.12890v1
• [cs.CV]Single-Shot 3D Detection of Vehicles from Monocular RGB Images via Geometry Constrained Keypoints in Real-Time
Nils Gählert, Jun-Jun Wan, Nicolas Jourdan, Jan Finkbeiner, Uwe Franke, Joachim Denzler
http://arxiv.org/abs/2006.13084v1
• [cs.CV]Surpassing Real-World Source Training Data: Random 3D Characters for Generalizable Person Re-Identification
Yanan Wang, Shengcai Liao, Ling Shao
http://arxiv.org/abs/2006.12774v1
• [cs.CV]Towards Robust Sensor Fusion in Visual Perception
Shaojie Wang, Tong Wu, Yevgeniy Vorobeychik
http://arxiv.org/abs/2006.13192v1
• [cs.CV]iffDetector: Inference-aware Feature Filtering for Object Detection
Mingyuan Mao, Yuxin Tian, Baochang Zhang, Qixiang Ye, Wanquan Liu, Guodong Guo, David Doermann
http://arxiv.org/abs/2006.12708v1
• [cs.CY]A Large-scale Analysis of App Inventor Projects
Nathalia da Cruz Alves, Christiane Gresse von Wangenheim, Jean Carlo Rossa Hauck
http://arxiv.org/abs/2006.11327v1
• [cs.CY]Effects of Non-Cognitive Factors on Post-Secondary Persistence of Deaf Students: An Agent-Based Modeling Approach
Marie Alaghband, Ivan Garibay
http://arxiv.org/abs/2006.12624v1
• [cs.CY]Lumos: A Library for Diagnosing Metric Regressions in Web-Scale Applications
Jamie Pool, Ebrahim Beyrami, Vishak Gopal, Ashkan Aazami, Jayant Gupchup, Jeff Rowland, Binlong Li, Pritesh Kanani, Ross Cutler, Johannes Gehrke
http://arxiv.org/abs/2006.12793v1
• [cs.CY]Paratransit Agency Responses to the Adoption of Sub-contracted Services Using Secure Technologies
Amari N. Lewis, Amelia C. Regan
http://arxiv.org/abs/2006.12628v1
• [cs.CY]Successful implementation of discrete event simulation: the case of an Italian emergency department
Arthur Kramer, Clio Dosi, Manuel Iori, Matteo Vignoli
http://arxiv.org/abs/2006.13062v1
• [cs.DC]Distributed Subgraph Enumeration via Backtracking-based Framework
Zhaokang Wang, Weiwei Hu, Chunfeng Yuan, Rong Gu, Yihua Huang
http://arxiv.org/abs/2006.12819v1
• [cs.DC]Intermediate Value Linearizability: A Quantitative Correctness Criterion
Arik Rinberg, Idit Keidar
http://arxiv.org/abs/2006.12889v1
• [cs.DC]Multiverse: Dynamic VM Provisioning for Virtualized High Performance Computing Clusters
Jashwant Raj Gunasekaran, Michael Cui, Prashanth Thinakaran, Josh Simons, Mahmut Taylan Kandemir, Chita R. Das
http://arxiv.org/abs/2006.12560v1
• [cs.DC]On the Interoperability of Decentralized Exposure Notification Systems
Marko Vukolic
http://arxiv.org/abs/2006.13087v1
• [cs.DC]Optimised allgatherv, reduce_scatter and allreduce communication in message-passing systems
Andreas Jocksch, Noe Ohana, Emmanuel Lanti, Vasileios Karakasis, Laurent Villard
http://arxiv.org/abs/2006.13112v1
• [cs.DC]PipeSim: Trace-driven Simulation of Large-Scale AI Operations Platforms
Thomas Rausch, Waldemar Hummer, Vinod Muthusamy
http://arxiv.org/abs/2006.12587v1
• [cs.DS]A Second-order Equilibrium in Nonconvex-Nonconcave Min-max Optimization: Existence and Algorithm
Oren Mangoubi, Nisheeth K. Vishnoi
http://arxiv.org/abs/2006.12363v2
• [cs.DS]Approximation Algorithms for Sparse Principal Component Analysis
Agniva Chowdhury, Petros Drineas, David P. Woodruff, Samson Zhou
http://arxiv.org/abs/2006.12748v1
• [cs.DS]Similarity Search with Tensor Core Units
Thomas D. Ahle, Francesco Silvestri
http://arxiv.org/abs/2006.12608v1
• [cs.IT]$C$-differential bent functions and perfect nonlinearity
Pantelimon Stanica, Sugata Gangopadhyay, Aaron Geary, Constanza Riera, Anton Tkachenko
http://arxiv.org/abs/2006.12535v1
• [cs.IT]Optimizing Downlink Resource Allocation in Multiuser MIMO Networks via Fractional Programming and the Hungarian Algorithm
Ahmad Ali Khan, Raviraj Adve, Wei Yu
http://arxiv.org/abs/2006.12549v1
• [cs.IT]Statistical Modeling of the Impact of Underwater Bubbles on an Optical Wireless Channel
Myoungkeun Shin, Ki-Hong Park, Mohamed-Slim Alouini
http://arxiv.org/abs/2006.12787v1
• [cs.LG]A Dynamical Systems Approach for Convergence of the Bayesian EM Algorithm
Orlando Romero, Subhro Das, Pin-Yu Chen, Sérgio Pequito
http://arxiv.org/abs/2006.12690v1
• [cs.LG]A Multiscale Graph Convolutional Network Using Hierarchical Clustering
Alex Lipov, Pietro Liò
http://arxiv.org/abs/2006.12542v1
• [cs.LG]A Provably Convergent and Practical Algorithm for Min-max Optimization with Applications to GANs
Oren Mangoubi, Sushant Sachdeva, Nisheeth K. Vishnoi
http://arxiv.org/abs/2006.12376v2
• [cs.LG]Aligning Time Series on Incomparable Spaces
Samuel Cohen, Giulia Luise, Alexander Terenin, Brandon Amos, Marc Peter Deisenroth
http://arxiv.org/abs/2006.12648v1
• [cs.LG]An Efficient Smoothing Proximal Gradient Algorithm for Convex Clustering
Xin Zhou, Chunlei Du, Xiaodong Cai
http://arxiv.org/abs/2006.12592v1
• [cs.LG]Automatic Data Augmentation for Generalization in Deep Reinforcement Learning
Roberta Raileanu, Max Goldstein, Denis Yarats, Ilya Kostrikov, Rob Fergus
http://arxiv.org/abs/2006.12862v1
• [cs.LG]BETULA: Numerically Stable CF-Trees for BIRCH Clustering
Andreas Lang, Erich Schubert
http://arxiv.org/abs/2006.12881v1
• [cs.LG]Bridging the Theoretical Bound and Deep Algorithms for Open Set Domain Adaptation
Li Zhong, Zhen Fang, Feng Liu, Bo Yuan, Guangquan Zhang, Jie Lu
http://arxiv.org/abs/2006.13022v1
• [cs.LG]C-SURE: Shrinkage Estimator and Prototype Classifier for Complex-Valued Deep Learning
Yifei Xing, Rudrasis Chakraborty, Minxuan Duan, Stella Yu
http://arxiv.org/abs/2006.12590v1
• [cs.LG]Calibration of Neural Networks using Splines
Kartik Gupta, Amir Rahimi, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley
http://arxiv.org/abs/2006.12800v1
• [cs.LG]Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning
Tuan A. Nguyen, Hyewon Jeong, Eunho Yang, Sung Ju Hwang
http://arxiv.org/abs/2006.12777v1
• [cs.LG]Combinatorial Pure Exploration of Dueling Bandit
Wei Chen, Yihan Du, Longbo Huang, Haoyu Zhao
http://arxiv.org/abs/2006.12772v1
• [cs.LG]Correct Normalization Matters: Understanding the Effect of Normalization On Deep Neural Network Models For Click-Through Rate Prediction
Zhiqiang Wang, Qingyun She, PengTao Zhang, Junlin Zhang
http://arxiv.org/abs/2006.12753v1
• [cs.LG]Counterfactual Explanations of Concept Drift
Fabian Hinder, Barbara Hammer
http://arxiv.org/abs/2006.12822v1
• [cs.LG]Data Augmentation View on Graph Convolutional Network and the Proposal of Monte Carlo Graph Learning
Hande Dong, Zhaolin Ding, Xiangnan He, Fuli Feng, Shuxian Bi
http://arxiv.org/abs/2006.13090v1
• [cs.LG]Deep Implicit Coordination Graphs for Multi-agent Reinforcement Learning
Sheng Li, Jayesh K. Gupta, Peter Morales, Ross Allen, Mykel J. Kochenderfer
http://arxiv.org/abs/2006.11438v1
• [cs.LG]Density-embedding layers: a general framework for adaptive receptive fields
Francesco Cicala, Luca Bortolussi
http://arxiv.org/abs/2006.12779v1
• [cs.LG]Differentiable Segmentation of Sequences
Erik Scharwächter, Jonathan Lennartz, Emmanuel Müller
http://arxiv.org/abs/2006.13105v1
• [cs.LG]Discrete Few-Shot Learning for Pan Privacy
Roei Gelbhart, Benjamin I. P. Rubinstein
http://arxiv.org/abs/2006.13120v1
• [cs.LG]Distance Correlation Sure Independence Screening for Accelerated Feature Selection in Parkinson’s Disease Vocal Data
Dan Schellhas, Bishal Neupane, Deepak Thammineni, Bhargav Kanumuri, Robert C. Green II
http://arxiv.org/abs/2006.12919v1
• [cs.LG]Distributional Individual Fairness in Clustering
Nihesh Anderson, Suman K. Bera, Syamantak Das, Yang Liu
http://arxiv.org/abs/2006.12589v1
• [cs.LG]Environment Shaping in Reinforcement Learning using State Abstraction
Parameswaran Kamalaruban, Rati Devidze, Volkan Cevher, Adish Singla
http://arxiv.org/abs/2006.13160v1
• [cs.LG]Exact Support Recovery in Federated Regression with One-shot Communication
Adarsh Barik, Jean Honorio
http://arxiv.org/abs/2006.12583v1
• [cs.LG]Expert-Supervised Reinforcement Learning for Offline Policy Learning and Evaluation
Aaron Sonabend W, Junwei Lu, Leo A. Celi, Tianxi Cai, Peter Szolovits
http://arxiv.org/abs/2006.13189v1
• [cs.LG]Extension of Direct Feedback Alignment to Convolutional and Recurrent Neural Network for Bio-plausible Deep Learning
Donghyeon Han, Gwangtae Park, Junha Ryu, Hoi-jun Yoo
http://arxiv.org/abs/2006.12830v1
• [cs.LG]Fairness without Demographics through Adversarially Reweighted Learning
Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi
http://arxiv.org/abs/2006.13114v1
• [cs.LG]Fast and Flexible Temporal Point Processes with Triangular Maps
Oleksandr Shchur, Nicholas Gao, Marin Biloš, Stephan Günnemann
http://arxiv.org/abs/2006.12631v1
• [cs.LG]Gaining insight into SARS-CoV-2 infection and COVID-19 severity using self-supervised edge features and Graph Neural Networks
Arijit Sehanobish, Neal G. Ravindra, David van Dijk
http://arxiv.org/abs/2006.12971v1
• [cs.LG]Graph Neural Networks and Reinforcement Learning for Behavior Generation in Semantic Environments
Patrick Hart, Alois Knoll
http://arxiv.org/abs/2006.12576v1
• [cs.LG]Graph Prototypical Networks for Few-shot Learning on Attributed Networks
Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, Huan Liu
http://arxiv.org/abs/2006.12739v1
• [cs.LG]Hybrid Session-based News Recommendation using Recurrent Neural Networks
Gabriel de Souza P. Moreira, Dietmar Jannach, Adilson Marques da Cunha
http://arxiv.org/abs/2006.13063v1
• [cs.LG]Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data
Rui Dai, Shenkun Xu, Qian Gu, Chenguang Ji, Kaikui Liu
http://arxiv.org/abs/2006.12715v1
• [cs.LG]Just How Toxic is Data Poisoning? A Unified Benchmark for Backdoor and Data Poisoning Attacks
Avi Schwarzschild, Micah Goldblum, Arjun Gupta, John P Dickerson, Tom Goldstein
http://arxiv.org/abs/2006.12557v1
• [cs.LG]Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors
Karl Pertsch, Oleh Rybkin, Frederik Ebert, Chelsea Finn, Dinesh Jayaraman, Sergey Levine
http://arxiv.org/abs/2006.13205v1
• [cs.LG]Long-Term Prediction of Lane Change Maneuver Through a Multilayer Perceptron
Zhenyu Shou, Ziran Wang, Kyungtae Han, Yongkang Liu, Prashant Tiwari, Xuan Di
http://arxiv.org/abs/2006.12769v1
• [cs.LG]Multi-Class Uncertainty Calibration via Mutual Information Maximization-based Binning
Kanil Patel, William Beluch, Bin Yang, Michael Pfeiffer, Dan Zhang
http://arxiv.org/abs/2006.13092v1
• [cs.LG]Multi-source Domain Adaptation via Weighted Joint Distributions Optimal Transport
Rosanna Turrisi, Rémi Flamary, Alain Rakotomamonjy, Massimiliano Pontil
http://arxiv.org/abs/2006.12938v1
• [cs.LG]Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction
Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D Boyer, Egemen Kolemen, Jeff Schneider
http://arxiv.org/abs/2006.12682v1
• [cs.LG]On Compression Principle and Bayesian Optimization for Neural Networks
Michael Tetelman
http://arxiv.org/abs/2006.12714v1
• [cs.LG]On Counterfactual Explanations under Predictive Multiplicity
Martin Pawelczyk, Klaus Broelemann, Gjergji Kasneci
http://arxiv.org/abs/2006.13132v1
• [cs.LG]On the Global Optimality of Model-Agnostic Meta-Learning
Lingxiao Wang, Qi Cai, Zhuoran Yang, Zhaoran Wang
http://arxiv.org/abs/2006.13182v1
• [cs.LG]Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
Cassidy Laidlaw, Sahil Singla, Soheil Feizi
http://arxiv.org/abs/2006.12655v1
• [cs.LG]Post-hoc Calibration of Neural Networks
Amir Rahimi, Kartik Gupta, Thalaiyasingam Ajanthan, Thomas Mensink, Cristian Sminchisescu, Richard Hartley
http://arxiv.org/abs/2006.12807v1
• [cs.LG]Projective Latent Space Decluttering
Andreas Hinterreiter, Marc Streit, Bernhard Kainz
http://arxiv.org/abs/2006.12902v1
• [cs.LG]Provably Efficient Reinforcement Learning for Discounted MDPs with Feature Mapping
Dongruo Zhou, Jiafan He, Quanquan Gu
http://arxiv.org/abs/2006.13165v1
• [cs.LG]RayS: A Ray Searching Method for Hard-label Adversarial Attack
Jinghui Chen, Quanquan Gu
http://arxiv.org/abs/2006.12792v1
• [cs.LG]Risk-Sensitive Reinforcement Learning: a Martingale Approach to Reward Uncertainty
Nelson Vadori, Sumitra Ganesh, Prashant Reddy, Manuela Veloso
http://arxiv.org/abs/2006.12686v1
• [cs.LG]Rotation-Equivariant Neural Networks for Privacy Protection
Hao Zhang, Yiting Chen, Haotian Ma, Xu Cheng, Qihan Ren, Liyao Xiang, Jie Shi, Quanshi Zhang
http://arxiv.org/abs/2006.13016v1
• [cs.LG]Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
Aleksei Petrenko, Zhehui Huang, Tushar Kumar, Gaurav Sukhatme, Vladlen Koltun
http://arxiv.org/abs/2006.11751v2
• [cs.LG]Show me the Way: Intrinsic Motivation from Demonstrations
Léonard Hussenot, Robert Dadashi, Matthieu Geist, Olivier Pietquin
http://arxiv.org/abs/2006.12917v1
• [cs.LG]Siamese Meta-Learning and Algorithm Selection with ‘Algorithm-Performance Personas’ [Proposal]**
Joeran Beel, Bryan Tyrell, Edward Bergman, Andrew Collins, Shahad Nagoor
http://arxiv.org/abs/2006.12328v2
• [cs.LG]Simple and Effective VAE Training with Calibrated Decoders
Oleh Rybkin, Kostas Daniilidis, Sergey Levine
http://arxiv.org/abs/2006.13202v1
• [cs.LG]Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks
Francesco Croce, Maksym Andriushchenko, Naman D. Singh, Nicolas Flammarion, Matthias Hein
http://arxiv.org/abs/2006.12834v1
• [cs.LG]Spectral Evolution with Approximated Eigenvalue Trajectories for Link Prediction
Miguel Romero, Jorge Finke, Camilo Rocha, Luis Tobón
http://arxiv.org/abs/2006.12657v1
• [cs.LG]Support Union Recovery in Meta Learning of Gaussian Graphical Models
Qian Zhang, Yilin Zheng, Jean Honorio
http://arxiv.org/abs/2006.12598v1
• [cs.LG]Time Series Regression
Chang Wei Tan, Christoph Bergmeir, Francois Petitjean, Geoffrey I. Webb
http://arxiv.org/abs/2006.12672v1
• [cs.LO]A Constructive, Type-Theoretic Approach to Regression via Global Optimisation
Dan R. Ghica, Todd Waugh Ambridge
http://arxiv.org/abs/2006.12868v1
• [cs.MA]Calibration of Shared Equilibria in General Sum Partially Observable Markov Games
Nelson Vadori, Sumitra Ganesh, Manuela Veloso
http://arxiv.org/abs/2006.13085v1
• [cs.NE]Always-On, Sub-300-nW, Event-Driven Spiking Neural Network based on Spike-Driven Clock-Generation and
df6
Clock- and Power-Gating for an Ultra-Low-Power Intelligent Device
Dewei Wang, Pavan Kumar Chundi, Sung Justin Kim, Minhao Yang, Joao Pedro Cerqueira, Joonsung Kang, Seungchul Jung, Sangjoon Kim, Mingoo Seok
http://arxiv.org/abs/2006.12314v2
• [cs.NE]Efficient Hyperparameter Optimization in Deep Learning Using a Variable Length Genetic Algorithm
Xueli Xiao, Ming Yan, Sunitha Basodi, Chunyan Ji, Yi Pan
http://arxiv.org/abs/2006.12703v1
• [cs.NE]First Steps Towards a Runtime Analysis When Starting With a Good Solution
Denis Antipov, Maxim Buzdalov, Benjamin Doerr
http://arxiv.org/abs/2006.12161v2
• [cs.NE]Inference with Artificial Neural Networks on the Analog BrainScaleS-2 Hardware
Johannes Weis, Philipp Spilger, Sebastian Billaudelle, Yannik Stradmann, Arne Emmel, Eric Müller, Oliver Breitwieser, Andreas Grübl, Joscha Ilmberger, Vitali Karasenko, Mitja Kleider, Christian Mauch, Korbinian Schreiber, Johannes Schemmel
http://arxiv.org/abs/2006.13177v1
• [cs.NE]Learning Physical Constraints with Neural Projections
Shuqi Yang, Xingzhe He, Bo Zhu
http://arxiv.org/abs/2006.12745v1
• [cs.NE]Maximizing Submodular or Monotone Functions under Partition Matroid Constraints by Multi-objective Evolutionary Algorithms
Anh Viet Do, Frank Neumann
http://arxiv.org/abs/2006.12773v1
• [cs.NE]Particle Swarm Optimization for Energy Disaggregation in Industrial and Commercial Buildings
Karoline Brucke, Stefan Arens, Jan-Simon Telle, Sunke~Schlüters, Benedikt Hanke, Karsten von Maydell, Carsten Agert
http://arxiv.org/abs/2006.12940v1
• [cs.NE]hxtorch: PyTorch for ANNs on BrainScaleS-2
Philipp Spilger, Eric Müller, Arne Emmel, Aron Leibfried, Christian Mauch, Christian Pehle, Johannes Weis, Oliver Breitwieser, Sebastian Billaudelle, Sebastian Schmitt, Timo C. Wunderlich, Yannik Stradmann, Johannes Schemmel
http://arxiv.org/abs/2006.13138v1
• [cs.NI]Location-Aware Resource Allocation Algorithm in Satellite Ground Station Networks
Xiangqiang Gao, Rongke liu, Aryan Kaushik
http://arxiv.org/abs/2006.12727v1
• [cs.NI]Optimal Network Slicing for Service-Oriented Networks with Flexible Routing and Guaranteed E2E Latency
Wei-Kun Chen, Ya-Feng Liu, Antonio De Domenico, Zhi-Quan Luo, Yu-Hong Dai
http://arxiv.org/abs/2006.13019v1
• [cs.PL]Information-theoretic User Interaction: Significant Inputs for Program Synthesis
Ashish Tiwari, Arjun Radhakrishna, Sumit Gulwani, Daniel Perelman
http://arxiv.org/abs/2006.12638v1
• [cs.RO]Coverage Path Planning with Track Spacing Adaptation for Autonomous Underwater Vehicles
Veronika Yordanova, Bart Gips
http://arxiv.org/abs/2006.12896v1
• [cs.RO]Feature Expansive Reward Learning: Rethinking Human Input
Andreea Bobu, Marius Wiggert, Claire Tomlin, Anca D. Dragan
http://arxiv.org/abs/2006.13208v1
• [cs.RO]Generalized Grasping for Mechanical Grippers for Unknown Objects with Partial Point Cloud Representations
Michael Hegedus, Kamal Gupta, Mehran Mehrandezh
http://arxiv.org/abs/2006.12676v1
• [cs.RO]Grasp State Assessment of Deformable Objects Using Visual-Tactile Fusion Perception
Shaowei Cui, Rui Wang, Junhang Wei, Fanrong Li, Shuo Wang
http://arxiv.org/abs/2006.12729v1
• [cs.RO]Learning dynamics for improving control of overactuated flying systems
Weixuan Zhang, Maximilian Brunner, Lionel Ott, Mina Kamel, Roland Siegwart, Juan Nieto
http://arxiv.org/abs/2006.13153v1
• [cs.RO]dm_control: Software and Tasks for Continuous Control
Yuval Tassa, Saran Tunyasuvunakool, Alistair Muldal, Yotam Doron, Siqi Liu, Steven Bohez, Josh Merel, Tom Erez, Timothy Lillicrap, Nicolas Heess
http://arxiv.org/abs/2006.12983v1
• [cs.SE]Technology Readiness Levels for Machine Learning Systems
Alexander Lavin, Gregory Renard
http://arxiv.org/abs/2006.12497v1
• [cs.SI]Opinion Diffusion Software with Strategic Opinion Revelation and Unfriending
Patrick Shepherd, Mia Weaver, Judy Goldsmith
http://arxiv.org/abs/2006.12572v1
• [cs.SI]The Hawkes Edge Partition Model for Continuous-time Event-based Temporal Networks
Sikun Yang, Heinz Koeppl
http://arxiv.org/abs/2006.12952v1
• [cs.SI]Using graph theory and social media data to assess cultural ecosystem services in coastal areas: Method development and application
Ana Ruiz-Frau, Andres Ospina-Alvarez, Sebastián Villasante, Pablo Pita, Isidro Maya-Jariego, Silvia de Juan Mohan
http://arxiv.org/abs/2006.12495v1
• [econ.EM]The Macroeconomy as a Random Forest
Philippe Goulet Coulombe
http://arxiv.org/abs/2006.12724v1
• [eess.AS]Articulatory-WaveNet: Autoregressive Model For Acoustic-to-Articulatory Inversion
Narjes Bozorg, Michael T. Johnson
http://arxiv.org/abs/2006.12594v1
• [eess.AS]Real Time Speech Enhancement in the Waveform Domain
Alexandre Defossez, Gabriel Synnaeve, Yossi Adi
http://arxiv.org/abs/2006.12847v1
• [eess.AS]Unsupervised Sound Separation Using Mixtures of Mixtures
Scott Wisdom, Efthymios Tzinis, Hakan Erdogan, Ron J. Weiss, Kevin Wilson, John R. Hershey
http://arxiv.org/abs/2006.12701v1
• [eess.IV]3D Probabilistic Segmentation and Volumetry from 2D projection images
Athanasios Vlontzos, Samuel Budd, Benjamin Hou, Daniel Rueckert, Bernhard Kainz
http://arxiv.org/abs/2006.12809v1
• [eess.IV]Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural Network
Qing Lyu, Hongming Shan, Yibin Xie, Debiao Li, Ge Wang
http://arxiv.org/abs/2006.12700v1
• [eess.IV]Deep Attentive Wasserstein Generative Adversarial Networks for MRI Reconstruction with Recurrent Context-Awareness
Yifeng Guo, Chengjia Wang, Heye Zhang, Guang Yang
http://arxiv.org/abs/2006.12915v1
• [eess.IV]Deep Low-rank Prior in Dynamic MR Imaging
Ziwen Ke, Wenqi Huang, Jing Cheng, Sen Jia, Haifeng Wang, Xin Liu, Hairong Zheng, Leslie Ying, Yanjie Zhu, Dong Liang
http://arxiv.org/abs/2006.12090v2
• [eess.IV]Joint Left Atrial Segmentation and Scar Quantification Based on a DNN with Spatial Encoding and Shape Attention
Lei Li, Xin Weng, Julia A. Schnabel, Xiahai Zhuang
http://arxiv.org/abs/2006.13011v1
• [eess.IV]Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI
Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab
http://arxiv.org/abs/2006.12852v1
• [eess.IV]Semantic Features Aided Multi-Scale Reconstruction of Inter-Modality Magnetic Resonance Images
Preethi Srinivasan, Prabhjot Kaur, Aditya Nigam, Arnav Bhavsar
http://arxiv.org/abs/2006.12585v1
• [eess.IV]Semi-Supervised Learning for Fetal Brain MRI Quality Assessment with ROI consistency
Junshen Xu, Sayeri Lala, Borjan Gagoski, Esra Abaci Turk, P. Ellen Grant, Polina Golland, Elfar Adalsteinsson
http://arxiv.org/abs/2006.12704v1
• [eess.SP]Artificial Intelligence-Assisted Energy and Thermal Comfort Control for Sustainable Buildings: An Extended Representation of the Systematic Review
Ghezlane Halhoul Merabet, Mohamed Essaaidi, Mohamed Ben-Haddou, Basheer Qolomany, Junaid Qadir, Muhammad Anan, Ala Al-Fuqaha, Riduan Mohamed Abid, Driss Benhaddou
http://arxiv.org/abs/2006.12559v1
• [eess.SP]Deep Reinforcement Learning Control for Radar Detection and Tracking in Congested Spectral Environments
Charles E. Thornton, Mark A. Kozy, R. Michael Buehrer, Anthony F. Martone, Kelly D. Sherbondy
http://arxiv.org/abs/2006.13173v1
• [eess.SP]Fast Initial Access with Deep Learning for Beam Prediction in 5G mmWave Networks
Tarun S. Cousik, Vijay K. Shah, Jeffrey H. Reed, Tugba Erpek, Yalin E. Sagduyu
http://arxiv.org/abs/2006.12653v1
• [eess.SP]Unsupervised ensembling of multiple software sensors: a new approach for electrocardiogram-derived respiration using one or two channels
John Malik, Yu-Ting Lin, Ronen Talmon, Hau-Tieng Wu
http://arxiv.org/abs/2006.13054v1
• [eess.SY]Online Multi-agent Reinforcement Learning for Decentralized Inverter-based Volt-VAR Control
Haotian Liu, Wenchuan Wu
http://arxiv.org/abs/2006.12841v1
• [eess.SY]Parameter Estimation Bounds Based on the Theory of Spectral Lines
Arnab Sarker, Joseph E. Gaudio, Anuradha M. Annaswamy
http://arxiv.org/abs/2006.12687v1
• [math.DS]Inferring Causal Networks of Dynamical Systems through Transient Dynamics and Perturbation
George Stepaniants, Bingni W. Brunton, J. Nathan Kutz
http://arxiv.org/abs/2006.13154v1
• [math.NT]A Note on the Cross-Correlation of Costas Permutations
Domingo Gomez-Perez, Arne Winterhof
http://arxiv.org/abs/2006.12820v1
• [math.OC]A Fast Stochastic Plug-and-Play ADMM for Imaging Inverse Problems
Junqi Tang, Mike Davies
http://arxiv.org/abs/2006.11630v2
• [math.OC]Inexact Derivative-Free Optimization for Bilevel Learning
Matthias J. Ehrhardt, Lindon Roberts
http://arxiv.org/abs/2006.12674v1
• [math.ST]An efficient Averaged Stochastic Gauss-Newtwon algorithm for estimating parameters of non linear regressions models
Peggy Cénac, Antoine Godichon-Baggioni, Bruno Portier
http://arxiv.org/abs/2006.12920v1
• [math.ST]Bootstrapping $\ell_p$-Statistics in High Dimensions
Alexander Giessing, Jianqing Fan
http://arxiv.org/abs/2006.13099v1
• [math.ST]Fitting inhomogeneous phase-type distributions to data: the univariate and the multivariate case
Hansjoerg Albrecher, Mogens Bladt, Jorge Yslas
http://arxiv.org/abs/2006.13003v1
• [math.ST]Gromov-Wasserstein Distance based Object Matching: Asymptotic Inference
Christoph Alexander Weitkamp, Katharina Proksch, Carla Tameling, Axel Munk
http://arxiv.org/abs/2006.12287v2
• [math.ST]Optimality of the max test for detecting sparse signals with Gaussian or heavier tail
Xiao Li, William Fithian
http://arxiv.org/abs/2006.12489v1
• [physics.comp-ph]Phase space learning with neural networks
Jaime Lopez Garcia, Angel Rivero Jimenez
http://arxiv.org/abs/2006.12599v1
• [q-bio.NC]The principles of adaptation in organisms and machines II: Thermodynamics of the Bayesian brain
Hideaki Shimazaki
http://arxiv.org/abs/2006.13158v1
• [q-bio.PE]A self-supervised neural-analytic method to predict the evolution of COVID-19 in Romania
Radu D. Stochiţoiu, Traian Rebedea, Ionel Popescu, Marius Leordeanu
http://arxiv.org/abs/2006.12926v1
• [q-bio.QM]Deep Belief Network based representation learning for lncRNA-disease association prediction
Manu Madhavan, Gopakumar G
http://arxiv.org/abs/2006.12534v1
• [quant-ph]Optimal Extensions of Resource Measures and their Applications
Gilad Gour, Marco Tomamichel
http://arxiv.org/abs/2006.12408v2
• [stat.AP]Adding flexibility to clinical trial designs: an example-based guide to the practical use of adaptive designs
Thomas Burnett, Pavel Mozgunov, Philip Pallmann, Sofia S. Villar, Graham M. Wheeler, Thomas Jaki
http://arxiv.org/abs/2006.12811v1
• [stat.AP]Effectiveness and Compliance to Social Distancing During COVID-19
Kristi Bushman, Konstantinos Pelechrinis, Alexandros Labrinidis
http://arxiv.org/abs/2006.12720v1
• [stat.AP]Estimation of COVID-19 under-reporting in Brazilian States through SARI
Balthazar Paixão, Lais Baroni, Rebecca Salles, Luciana Escobar, Carlos de Sousa, Marcel Pedroso, Raphael Saldanha, Rafaelli Coutinho, Fabio Porto, Eduardo Ogasawara
http://arxiv.org/abs/2006.12759v1
• [stat.AP]Magnify Your Population: Statistical Downscaling to Augment the Spatial Resolution of Socioeconomic Census Data
Giulia Carella, Andy Eschbacher, Dongjie Fan, Miguel Álvarez, Álvaro Arredondo, Alejandro Polvillo Hall, Javier Pérez Trufero, Javier de la Torre
http://arxiv.org/abs/2006.13152v1
• [stat.AP]Spatio-temporal evolution of global surface temperature distributions
Federico Amato, Fabian Guignard, Vincent Humphrey, Mikhail Kanevski
http://arxiv.org/abs/2006.12386v2
• [stat.ME]A Causally Formulated Hazard Ratio Estimation through Backdoor Adjustment on Structural Causal Model
Riddhiman Adib, Paul Griffin, Sheikh Iqbal Ahamed, Mohammad Adibuzzaman
http://arxiv.org/abs/2006.12573v1
• [stat.ME]A Revisit to De-biased Lasso for Generalized Linear Models
Lu Xia, Bin Nan, Yi Li
http://arxiv.org/abs/2006.12778v1
• [stat.ME]An improved sample size calculation method for score tests in generalized linear models
Yongqiang Tang, Liang Zhu, Jiezhun Gu
http://arxiv.org/abs/2006.13104v1
• [stat.ME]Conditional independence testing via weighted partial copulas
Pascal Bianchi, Kevin Elgui, François Portier
http://arxiv.org/abs/2006.12839v1
• [stat.ME]Controlling for Unknown Confounders in Neuroimaging
Sebastian Pölsterl, Christian Wachinger
http://arxiv.org/abs/2006.13135v1
• [stat.ME]Decoupling Shrinkage and Selection in Gaussian Linear Factor Analysis
Henrique Bolfarine, Carlos M. Carvalho, Hedibert F. Lopes, Jared S. Murray
http://arxiv.org/abs/2006.11908v2
• [stat.ME]Fast and Optimal Bayesian Approximations for Targeted Prediction
Daniel R. Kowal
http://arxiv.org/abs/2006.13107v1
• [stat.ME]Min-Mid-Max Scaling, Limits of Agreement, and Agreement Score
Veli Safak
http://arxiv.org/abs/2006.12904v1
• [stat.ME]Seeded intervals and noise level estimation in change point detection: A discussion of Fryzlewicz (2020)
Solt Kovács, Housen Li, Peter Bühlmann
http://arxiv.org/abs/2006.12806v1
• [stat.ME]The role of swabs in modeling the COVID-19 outbreak in the most affected regions of Italy
Claudia Furlan, Cinzia Mortarino
http://arxiv.org/abs/2006.13094v1
• [stat.ME]Wasserstein Autoregressive Models for Density Time Series
Chao Zhang, Piotr Kokoszka, Alexander Petersen
http://arxiv.org/abs/2006.12640v1
• [stat.ML]A Comparative Study of Temporal Non-Negative Matrix Factorization with Gamma Markov Chains
Louis Filstroff, Olivier Gouvert, Cédric Févotte, Olivier Cappé
http://arxiv.org/abs/2006.12843v1
• [stat.ML]ABID: Angle Based Intrinsic Dimensionality
Erik Thordsen, Erich Schubert
http://arxiv.org/abs/2006.12880v1
• [stat.ML]Approximate Cross-Validation for Structured Models
Soumya Ghosh, William T. Stephenson, Tin D. Nguyen, Sameer K. Deshpande, Tamara Broderick
http://arxiv.org/abs/2006.12669v1
• [stat.ML]Byzantine-Resilient High-Dimensional SGD with Local Iterations on Heterogeneous Data
Deepesh Data, Suhas Diggavi
http://arxiv.org/abs/2006.13041v1
• [stat.ML]Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures
Julien Launay, Iacopo Poli, François Boniface, Florent Krzakala
http://arxiv.org/abs/2006.12878v1
• [stat.ML]Disentangling by Subspace Diffusion
David Pfau, Irina Higgins, Aleksandar Botev, Sébastien Racanière
http://arxiv.org/abs/2006.12982v1
• [stat.ML]Efficient Inference of Nonparametric Interaction in Spiking-neuron Networks
Feng Zhou, Yixuan Zhang, Jun Zhu
http://arxiv.org/abs/2006.12845v1
• [stat.ML]Fair Performance Metric Elicitation
Gaurush Hiranandani, Harikrishna Narasimhan, Oluwasanmi Koyejo
http://arxiv.org/abs/2006.12732v1
• [stat.ML]Good linear classifiers are abundant in the interpolating regime
Ryan Theisen, Jason M. Klusowski, Michael W. Mahoney
http://arxiv.org/abs/2006.12625v1
• [stat.ML]Limits of Transfer Learning
Jake Williams, Abel Tadesse, Tyler Sam, Huey Sun, George D. Montanez
http://arxiv.org/abs/2006.12694v1
• [stat.ML]Normalizing Flows Across Dimensions
Edmond Cunningham, Renos Zabounidis, Abhinav Agrawal, Ina Fiterau, Daniel Sheldon
http://arxiv.org/abs/2006.13070v1
• [stat.ML]PAC-Bayes Analysis Beyond the Usual Bounds
Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvari, John Shawe-Taylor
http://arxiv.org/abs/2006.13057v1
• [stat.ML]Private Distributed Mean Estimation
Lun Wang, Ruoxi Jia
http://arxiv.org/abs/2006.13039v1
• [stat.ML]SWAG: A Wrapper Method for Sparse Learning
Roberto Molinari, Gaetan Bakalli, Stéphane Guerrier, Cesare Miglioli, Samuel Orso, Olivier Scaillet
http://arxiv.org/abs/2006.12837v1
• [stat.ML]Solving the Phantom Inventory Problem: Near-optimal Entry-wise Anomaly Detection
Vivek F. Farias, Andrew A. Li, Tianyi Peng
http://arxiv.org/abs/2006.13126v1
• [stat.ML]Statistical Mechanics of Generalization in Kernel Regression
Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan
http://arxiv.org/abs/2006.13198v1
• [stat.ML]The Generalized Lasso with Nonlinear Observations and Generative Priors
Zhaoqiang Liu, Jonathan Scarlett
http://arxiv.org/abs/2006.12415v2
• [stat.ML]Variational Orthogonal Features
David R. Burt, Carl Edward Rasmussen, Mark van der Wilk
http://arxiv.org/abs/2006.13170v1
• [stat.ML]not-MIWAE: Deep Generative Modelling with Missing not at Random Data
Niels Bruun Ipsen, Pierre-Alexandre Mattei, Jes Frellsen
http://arxiv.org/abs/2006.12871v1