cond-mat.stat-mech - 统计数学
cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 econ.EM - 计量经济学 econ.TH - 理论经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.FA - 泛函演算 math.OC - 优化与控制 math.ST - 统计理论 q-bio.NC - 神经元与认知 q-bio.PE - 人口与发展 q-bio.QM - 定量方法 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cond-mat.stat-mech]Machine-Learning Study using Improved Correlation Configuration and Application to Quantum Monte Carlo Simulation
• [cs.AI]Bayesian Inference by Symbolic Model Checking
• [cs.AI]Computing Optimal Decision Sets with SAT
• [cs.AI]Connecting actuarial judgment to probabilistic learning techniques with graph theory
• [cs.AI]Fairness-Aware Online Personalization
• [cs.AI]Improving probability selecting based weights for Satisfiability Problem
• [cs.AI]Social Choice Optimization
• [cs.CL]Exploiting stance hierarchies for cost-sensitive stance detection of Web documents
• [cs.CL]Leverage Unlabeled Data for Abstractive Speech Summarization with Self-Supervised Learning and Back-Summarization
• [cs.CL]Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification
• [cs.CL]MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering
• [cs.CL]Neural Modeling for Named Entities and Morphology (NEMO^2)
• [cs.CL]NeuralQA: A Usable Library for Question Answering (Contextual Query Expansion + BERT) on Large Datasets
• [cs.CL]Photon: A Robust Cross-Domain Text-to-SQL System
• [cs.CL]The Return of Lexical Dependencies: Neural Lexicalized PCFGs
• [cs.CL]The optimality of syntactic dependency distances
• [cs.CR]SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization
• [cs.CV]$grid2vec$: Learning Efficient Visual Representations via Flexible Grid-Graphs
• [cs.CV]A new Local Radon Descriptor for Content-Based Image Search
• [cs.CV]Action2Motion: Conditioned Generation of 3D Human Motions
• [cs.CV]An Improvement for Capsule Networks using Depthwise Separable Convolution
• [cs.CV]Benchmarking and Comparing Multi-exposure Image Fusion Algorithms
• [cs.CV]Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation
• [cs.CV]Contrastive Learning for Unpaired Image-to-Image Translation
• [cs.CV]Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval
• [cs.CV]Crowdsampling the Plenoptic Function
• [cs.CV]Deep Keypoint-Based Camera Pose Estimation with Geometric Constraints
• [cs.CV]Dense Scene Multiple Object Tracking with Box-Plane Matching
• [cs.CV]Detecting Suspicious Behavior: How to Deal with Visual Similarity through Neural Networks
• [cs.CV]Domain Adaptive Semantic Segmentation Using Weak Labels
• [cs.CV]Dynamic texture analysis for detecting fake faces in video sequences
• [cs.CV]Epipolar-Guided Deep Object Matching for Scene Change Detection
• [cs.CV]Event-based Stereo Visual Odometry
• [cs.CV]Foveation for Segmentation of Ultra-High Resolution Images
• [cs.CV]Fully Dynamic Inference with Deep Neural Networks
• [cs.CV]Generative Classifiers as a Basis for Trustworthy Computer Vision
• [cs.CV]Heatmap-based Vanishing Point boosts Lane Detection
• [cs.CV]Hierarchical Action Classification with Network Pruning
• [cs.CV]Infrastructure-based Multi-Camera Calibration using Radial Projections
• [cs.CV]Instance Selection for GANs
• [cs.CV]Key Frame Proposal Network for Efficient Pose Estimation in Videos
• [cs.CV]Label or Message: A Large-Scale Experimental Survey of Texts and Objects Co-Occurrence
• [cs.CV]Learning To Pay Attention To Mistakes
• [cs.CV]Learning from Few Samples: A Survey
• [cs.CV]LevelSet R-CNN: A Deep Variational Method for Instance Segmentation
• [cs.CV]Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation
• [cs.CV]Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge
• [cs.CV]NormalGAN: Learning Detailed 3D Human from a Single RGB-D Image
• [cs.CV]Outlier-Robust Estimation: Hardness, Minimally-Tuned Algorithms, and Applications
• [cs.CV]Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
• [cs.CV]Quantitative Distortion Analysis of Flattening Applied to the Scroll from En-Gedi
• [cs.CV]Rethinking Recurrent Neural Networks and other Improvements for Image Classification
• [cs.CV]Revisiting the Modifiable Areal Unit Problem in Deep Traffic Prediction with Visual Analytics
• [cs.CV]Rewriting a Deep Generative Model
• [cs.CV]Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound
• [cs.CV]SimPose: Effectively Learning DensePose and Surface Normals of People from Simulated Data
• [cs.CV]Single Image Cloud Detection via Multi-Image Fusion
• [cs.CV]The Blessing and the Curse of the Noise behind Facial Landmark Annotations
• [cs.CV]Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild
• [cs.CV]Unsupervised Continuous Object Representation Networks for Novel View Synthesis
• [cs.CV]Unsupervised Disentanglement GAN for Domain Adaptive Person Re-Identification
• [cs.CV]Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM
• [cs.CV]Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation
• [cs.CY]AI-based Monitoring and Response System for Hospital Preparedness towards COVID-19 in Southeast Asia
• [cs.CY]Developing a Novel Crowdsourcing Business Model for Micro-Mobility Ride-Sharing Systems: Methodology and Preliminary Results
• [cs.CY]GIS-AHP Multi-Decision-Criteria-Analysis for the Optimal Location of Solar Energy Plants at Indonesia
• [cs.CY]How Work From Home Affects Collaboration: A Large-Scale Study of Information Workers in a Natural Experiment During COVID-19
• [cs.CY]IIT Kanpur Consulting Group: Using Machine Learning and Management Consulting for Social Good
• [cs.DB]On the Nature and Types of Anomalies: A Review
• [cs.DC]Accelerating Multi-attribute Unsupervised Seismic Facies Analysis With RAPIDS
• [cs.DC]Implications of Dissemination Strategies on the Security of Distributed Ledgers
• [cs.DC]New approach to MPI program execution time prediction
• [cs.DC]Phase Transitions of the k-Majority Dynamics in a Biased Communication Model
• [cs.DL]Topics as Clusters of Citation Links to Highly Cited Sources: The Case of Research on International Relations
• [cs.DS]Efficient Tensor Decomposition
• [cs.DS]Local Conflict Coloring Revisited: Linial for Lists
• [cs.GT]Algorithmic Stability in Fair Allocation of Indivisible Goods Among Two Agents
• [cs.HC]A Flexible and Modular Body-Machine Interface for Individuals Living with Severe Disabilities
• [cs.HC]Between Subjectivity and Imposition: Power Dynamics in Data Annotation for Computer Vision
• [cs.HC]Mixed-Reality Robotic Games: Design Guidelines for Effective Entertainment with Consumer Robots
• [cs.HC]The BIRAFFE2 Experiment. Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems
• [cs.IR]A Heterogeneous Information Network based Cross Domain Insurance Recommendation System for Cold Start Users
• [cs.IR]A Hybrid Adaptive Educational eLearning Project based on Ontologies Matching and Recommendation System
• [cs.IR]Finding Local Experts for Dynamic Recommendations Using Lazy Random Walk
• [cs.IR]Improving Performance of Relation Extraction Algorithm via Leveled Adversarial PCNN and Database Expansion
• [cs.IR]Interpretable Contextual Team-aware Item Recommendation: Application in Multiplayer Online Battle Arena Games
• [cs.IR]Social Influences in Recommendation Systems
• [cs.IR]What does BERT know about books, movies and music? Probing BERT for Conversational Recommendation
• [cs.IT]A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future
• [cs.IT]Capacity of Remote Classification Over Wireless Channels
• [cs.IT]Determination of 2-Adic Complexity of Generalized Binary Sequences of Order 2
• [cs.IT]Minimum Feedback for Collison-Free Scheduling in Massive Random Access
• [cs.IT]Repairing Reed-Solomon Codes via Subspace Polynomials
• [cs.IT]kth Distance Distributions of n-Dimensional Matérn Cluster Process
• [cs.LG]Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models
• [cs.LG]Beyond $\mathcal{H}$-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence
• [cs.LG]Bilevel Continual Learning
• [cs.LG]Black-box Adversarial Sample Generation Based on Differential Evolution
• [cs.LG]CSER: Communication-efficient SGD with Error Reset
• [cs.LG]Communication-Efficient Federated Learning via Optimal Client Sampling
• [cs.LG]Data-efficient Hindsight Off-policy Option Learning
• [cs.LG]Deep Multi-View Spatiotemporal Virtual Graph Neural Network for Significant Citywide Ride-hailing Demand Prediction
• [cs.LG]DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs
• [cs.LG]Deriving Differential Target Propagation from Iterating Approximate Inverses
• [cs.LG]Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers
• [cs.LG]Dynamic Federated Learning Model for Identifying Adversarial Clients
• [cs.LG]Evolving Context-Aware Recommender Systems With Users in Mind
• [cs.LG]FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting
• [cs.LG]Fast, Structured Clinical Documentation via Contextual Autocomplete
• [cs.LG]Generalization Comparison of Deep Neural Networks via Output Sensitivity
• [cs.LG]Growing Efficient Deep Networks by Structured Continuous Sparsification
• [cs.LG]Improving Sample Eficiency with Normalized RBF Kernels
• [cs.LG]Label-Leaks: Membership Inference Attack with Label
• [cs.LG]Momentum Q-learning with Finite-Sample Convergence Guarantee
• [cs.LG]PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards
• [cs.LG]Prediction of hierarchical time series using structured regularization and its application to artificial neural networks
• [cs.LG]PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings
• [cs.LG]Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning
• [cs.LG]Regional Rainfall Prediction Using Support Vector Machine Classification of Large-Scale Precipitation Maps
• [cs.LG]Stable Learning via Causality-based Feature Rectification
• [cs.LG]Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry
• [cs.LG]SynergicLearning: Neural Network-Based Feature Extraction for Highly-Accurate Hyperdimensional Learning
• [cs.LG]The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise
• [cs.LG]Trade-offs in Top-k Classification Accuracies on Losses for Deep Learning
• [cs.LG]When are Neural ODE Solutions Proper ODEs?
• [cs.NE]On Representing (Anti)Symmetric Functions
• [cs.NE]Research on Fitness Function of Tow Evolution Algorithms Using for Neutron Spectrum Unfolding
• [cs.NI]Swarm Intelligence for Next-Generation Wireless Networks: Recent Advances and Applications
• [cs.RO]Bayesian Optimization for Developmental Robotics with Meta-Learning by Parameters Bounds Reduction
• [cs.RO]DroneLight: Drone Draws in the Air using Long Exposure Light Painting and ML
• [cs.RO]Learning Object-conditioned Exploration using Distributed Soft Actor Critic
• [cs.RO]Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation
• [cs.RO]Lifelong Navigation
• [cs.RO]Natural Gradient Shared Control
• [cs.RO]OrcVIO: Object residual constrained Visual-Inertial Odometry
• [cs.RO]Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination
• [cs.SI]Depressive, Drug Abusive, or Informative: Knowledge-aware Study of News Exposure during COVID-19 Outbreak
• [cs.SI]Sybil Resilient Money Minting
• [e
8e8
ess.AS]Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling
• [econ.EM]Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession
• [econ.TH]Learning what they think vs. learning what they to: The micro-foundations of vicarious learning
• [eess.AS]Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability
• [eess.AS]Exploiting Cross-Lingual Knowledge in Unsupervised Acoustic Modeling for Low-Resource Languages
• [eess.IV]Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients
• [eess.IV]Searching for Pneumothorax in Half a Million Chest X-Ray Images
• [eess.IV]Very Deep Super-Resolution of Remotely Sensed Images with Mean Square Error and Var-norm Estimators as Loss Functions
• [eess.SP]A Brain Emotional Learning-inspired Model For the Prediction of Geomagnetic Storms
• [eess.SP]Deep-Learning based Inverse Modeling Approaches: A Subsurface Flow Example
• [eess.SP]Dense Small Satellite Networks for Modern Terrestrial Communication Systems: Benefits, Infrastructure, and Technologies
• [eess.SP]Localization with One-Bit Passive Radars in Narrowband Internet-of-Things using Multivariate Polynomial Optimization
• [eess.SP]Unsupervised Event Detection, Clustering, and Use Case Exposition in Micro-PMU Measurements
• [math.FA]Approximation of Smoothness Classes by Deep ReLU Networks
• [math.OC]A PAC algorithm in relative precision for bandit problem with costly sampling
• [math.ST]A Power Analysis for Knockoffs with the Lasso Coefficient-Difference Statistic
• [math.ST]Adaptive nonparametric estimation of a component density in a two-class mixture model
• [math.ST]Covariance estimation with nonnegative partial correlations
• [math.ST]Fully distribution-free center-outward rank tests for multiple-output regression and MANOVA
• [math.ST]Learning interaction kernels in stochastic systems of interacting particles from multiple trajectories
• [math.ST]Multi-dimensional parameter estimation of heavy-tailed moving averages
• [math.ST]Outlier Robust Mean Estimation with Subgaussian Rates via Stability
• [q-bio.NC]A superconducting nanowire spiking element for neural networks
• [q-bio.PE]Correlation between COVID-19 morbidity and mortality rates in Japan and local population density, temperature and absolute humidity
• [q-bio.QM]Few shot domain adaptation for in situ macromolecule structural classification in cryo-electron tomograms
• [stat.AP]A Recipe for Accurate Estimation of Lifespan Brain Trajectories, Distinguishing Longitudinal and Cohort Effects
• [stat.AP]A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services
• [stat.AP]Change Sign Detection with Differential MDL Change Statistics and its Applications to COVID-19 Pandemic Analysis
• [stat.AP]Extreme-K categorical samples problem
• [stat.AP]Regression-based imputation of explanatory discrete missing data
• [stat.AP]Skewed link regression models for imbalanced binary response with applications to life insurance
• [stat.ME]A notion of depth for sparse functional data
• [stat.ME]Approximate inferences for nonlinear mixed effects models with scale mixtures of skew-normal distributions
• [stat.ME]Coloured Tobit Kalman Filter
• [stat.ME]Impulse Response Analysis for Sparse High-Dimensional Time Series
• [stat.ME]Localizing differences in smooths with simultaneous confidence bounds on the true discovery proportion
• [stat.ME]Non Uniform Sampling of Fixed Margin Uniform Matrices
• [stat.ME]Real-time detection of a change-point in a linear expectile model
• [stat.ML]Accuracy and stability of solar variable selection comparison under complicated dependence structures
• [stat.ML]Information-Theoretic Approximation to Causal Models
• [stat.ML]Learning Output Embeddings in Structured Prediction
• [stat.ML]On the Banach spaces associated with multi-layer ReLU networks: Function representation, approximation theory and gradient descent dynamics
• [stat.ML]Quantitative Understanding of VAE by Interpreting ELBO as Rate Distortion Cost of Transform Coding
• [stat.ML]Rademacher upper bounds for cross-validation errors with an application to the lasso
• [stat.ML]Random Forests for dependent data
• [stat.ML]Unnormalized Variational Bayes
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• [cond-mat.stat-mech]Machine-Learning Study using Improved Correlation Configuration and Application to Quantum Monte Carlo Simulation
Yusuke Tomita, Kenta Shiina, Yutaka Okabe, Hwee Kuan Lee
http://arxiv.org/abs/2007.15477v1
• [cs.AI]Bayesian Inference by Symbolic Model Checking
Bahare Salmani, Joost-Pieter Katoen
http://arxiv.org/abs/2007.15071v1
• [cs.AI]Computing Optimal Decision Sets with SAT
Jinqiang Yu, Alexey Ignatiev, Peter J. Stuckey, Pierre Le Bodic
http://arxiv.org/abs/2007.15140v1
• [cs.AI]Connecting actuarial judgment to probabilistic learning techniques with graph theory
Roland R. Ramsahai
http://arxiv.org/abs/2007.15475v1
• [cs.AI]Fairness-Aware Online Personalization
G Roshan Lal, Sahin Cem Geyik, Krishnaram Kenthapadi
http://arxiv.org/abs/2007.15270v1
• [cs.AI]Improving probability selecting based weights for Satisfiability Problem
Huimin Fu, Yang Xu, Jun Liu, Guanfeng Wu, Sutcliffe Geoff
http://arxiv.org/abs/2007.15185v1
• [cs.AI]Social Choice Optimization
Andrés García-Camino
http://arxiv.org/abs/2007.15393v1
• [cs.CL]Exploiting stance hierarchies for cost-sensitive stance detection of Web documents
Arjun Roy, Pavlos Fafalios, Asif Ekbal, Xiaofei Zhu, Stefan Dietze
http://arxiv.org/abs/2007.15121v1
• [cs.CL]Leverage Unlabeled Data for Abstractive Speech Summarization with Self-Supervised Learning and Back-Summarization
Paul Tardy, Louis de Seynes, François Hernandez, Vincent Nguyen, David Janiszek, Yannick Estève
http://arxiv.org/abs/2007.15296v1
• [cs.CL]Leveraging Adversarial Training in Self-Learning for Cross-Lingual Text Classification
Xin Dong, Yaxin Zhu, Yupeng Zhang, Zuohui Fu, Dongkuan Xu, Sen Yang, Gerard de Melo
http://arxiv.org/abs/2007.15072v1
• [cs.CL]MKQA: A Linguistically Diverse Benchmark for Multilingual Open Domain Question Answering
Shayne Longpre, Yi Lu, Joachim Daiber
http://arxiv.org/abs/2007.15207v1
• [cs.CL]Neural Modeling for Named Entities and Morphology (NEMO^2)
Dan Bareket, Reut Tsarfaty
http://arxiv.org/abs/2007.15620v1
• [cs.CL]NeuralQA: A Usable Library for Question Answering (Contextual Query Expansion + BERT) on Large Datasets
Victor Dibia
http://arxiv.org/abs/2007.15211v1
• [cs.CL]Photon: A Robust Cross-Domain Text-to-SQL System
Jichuan Zeng, Xi Victoria Lin, Caiming Xiong, Richard Socher, Michael R. Lyu, Irwin King, Steven C. H. Hoi
http://arxiv.org/abs/2007.15280v1
• [cs.CL]The Return of Lexical Dependencies: Neural Lexicalized PCFGs
Hao Zhu, Yonatan Bisk, Graham Neubig
http://arxiv.org/abs/2007.15135v1
• [cs.CL]The optimality of syntactic dependency distances
Ramon Ferrer-i-Cancho, Carlos Gómez-Rodríguez, Juan Luis Esteban, Lluís Alemany-Puig
http://arxiv.org/abs/2007.15342v1
• [cs.CR]SMAP: A Joint Dimensionality Reduction Scheme for Secure Multi-Party Visualization
Jiazhi Xia, Tianxiang Chen, Lei Zhang, Wei Chen, Yang Chen, Xiaolong Zhang, Cong Xie, Tobias Schreck
http://arxiv.org/abs/2007.15591v1
• [cs.CV]$grid2vec$: Learning Efficient Visual Representations via Flexible Grid-Graphs
Ali Hamdi, Du Yong Kim, Flora D. Salim
http://arxiv.org/abs/2007.15444v1
• [cs.CV]A new Local Radon Descriptor for Content-Based Image Search
Morteza Babaie, Hany Kashani, Meghana D. Kumar, Hamid. R. Tizhoosh
http://arxiv.org/abs/2007.15523v1
• [cs.CV]Action2Motion: Conditioned Generation of 3D Human Motions
Chuan Guo, Xinxin Zuo, Sen Wang, Shihao Zou, Qingyao Sun, Annan Deng, Minglun Gong, Li Cheng
http://arxiv.org/abs/2007.15240v1
• [cs.CV]An Improvement for Capsule Networks using Depthwise Separable Convolution
Nguyen Huu Phong, Bernardete Ribeiro
http://arxiv.org/abs/2007.15167v1
• [cs.CV]Benchmarking and Comparing Multi-exposure Image Fusion Algorithms
Xingchen Zhang
http://arxiv.org/abs/2007.15156v1
• [cs.CV]Cascaded Non-local Neural Network for Point Cloud Semantic Segmentation
Mingmei Cheng, Le Hui, Jin Xie, Jian Yang, Hui Kong
http://arxiv.org/abs/2007.15488v1
• [cs.CV]Contrastive Learning for Unpaired Image-to-Image Translation
Taesung Park, Alexei A. Efros, Richard Zhang, Jun-Yan Zhu
http://arxiv.org/abs/2007.15651v1
• [cs.CV]Cross-Modal Hierarchical Modelling for Fine-Grained Sketch Based Image Retrieval
Aneeshan Sain, Ayan Kumar Bhunia, Yongxin Yang, Tao Xiang, Yi-Zhe Song
http://arxiv.org/abs/2007.15103v1
• [cs.CV]Crowdsampling the Plenoptic Function
Zhengqi Li, Wenqi Xian, Abe Davis, Noah Snavely
http://arxiv.org/abs/2007.15194v1
• [cs.CV]Deep Keypoint-Based Camera Pose Estimation with Geometric Constraints
You-Yi Jau, Rui Zhu, Hao Su, Manmohan Chandraker
http://arxiv.org/abs/2007.15122v1
• [cs.CV]Dense Scene Multiple Object Tracking with Box-Plane Matching
Jinlong Peng, Yueyang Gu, Yabiao Wang, Chengjie Wang, Jilin Li, Feiyue Huang
http://arxiv.org/abs/2007.15576v1
• [cs.CV]Detecting Suspicious Behavior: How to Deal with Visual Similarity through Neural Networks
Guillermo A. Martínez-Mascorro, José C. Ortiz-Bayliss, Hugo Terashima-Marín
http://arxiv.org/abs/2007.15235v1
• [cs.CV]Domain Adaptive Semantic Segmentation Using Weak Labels
Sujoy Paul, Yi-Hsuan Tsai, Samuel Schulter, Amit K. Roy-Chowdhury, Manmohan Chandraker
http://arxiv.org/abs/2007.15176v1
• [cs.CV]Dynamic texture analysis for detecting fake faces in video sequences
Mattia Bonomi, Cecilia Pasquini, Giulia Boato
http://arxiv.org/abs/2007.15271v1
• [cs.CV]Epipolar-Guided Deep Object Matching for Scene Change Detection
Kento Doi, Ryuhei Hamaguchi, Shun Iwase, Rio Yokota, Yutaka Matsuo, Ken Sakurada
http://arxiv.org/abs/2007.15540v1
• [cs.CV]Event-based Stereo Visual Odometry
Yi Zhou, Guillermo Gallego, Shaojie Shen
http://arxiv.org/abs/2007.15548v1
• [cs.CV]Foveation for Segmentation of Ultra-High Resolution Images
Chen Jin, Ryutaro Tanno, Moucheng Xu, Thomy Mertzanidou, Daniel C. Alexander
http://arxiv.org/abs/2007.15124v1
• [cs.CV]Fully Dynamic Inference with Deep Neural Networks
Wenhan Xia, Hongxu Yin, Xiaoliang Dai, Niraj K. Jha
http://arxiv.org/abs/2007.15151v1
• [cs.CV]Generative Classifiers as a Basis for Trustworthy Computer Vision
Radek Mackowiak, Lynton Ardizzone, Ullrich Köthe, Carsten Rother
http://arxiv.org/abs/2007.15036v1
• [cs.CV]Heatmap-based Vanishing Point boosts Lane Detection
Yin-Bo Liu, Ming Zeng, Qing-Hao Meng
http://arxiv.org/abs/2007.15602v1
• [cs.CV]Hierarchical Action Classification with Network Pruning
Mahdi Davoodikakhki, KangKang Yin
http://arxiv.org/abs/2007.15244v1
• [cs.CV]Infrastructure-based Multi-Camera Calibration using Radial Projections
Yukai Lin, Viktor Larsson, Marcel Geppert, Zuzana Kukelova, Marc Pollefeys, Torsten Sattler
http://arxiv.org/abs/2007.15330v1
• [cs.CV]Instance Selection for GANs
Terrance DeVries, Michal Drozdzal, Graham W. Taylor
http://arxiv.org/abs/2007.15255v1
• [cs.CV]Key Frame Proposal Network for Efficient Pose Estimation in Videos
Yuexi Zhang, Yin Wang, Octavia Camps, Mario Sznaier
http://arxiv.org/abs/2007.15217v1
• [cs.CV]Label or Message: A Large-Scale Experimental Survey of Texts and Objects Co-Occurrence
Koki Takeshita, Juntaro Shioyama, Seiichi Uchida
http://arxiv.org/abs/2007.15381v1
• [cs.CV]Learning To Pay Attention To Mistakes
Mou-Cheng Xu, Neil Oxtoby, Daniel C. Alexander, Joseph Jacob
http://arxiv.org/abs/2007.15131v1
• [cs.CV]Learning from Few Samples: A Survey
Nihar Bendre, Hugo Terashima Marín, Peyman Najafirad
http://arxiv.org/abs/2007.15484v1
• [cs.CV]LevelSet R-CNN: A Deep Variational Method for Instance Segmentation
Namdar Homayounfar, Yuwen Xiong, Justin Liang, Wei-Chiu Ma, Raquel Urtasun
http://arxiv.org/abs/2007.15629v1
• [cs.CV]Linear Attention Mechanism: An Efficient Attention for Semantic Segmentation
Rui Li, Jianlin Su, Chenxi Duan, Shunyi Zheng
http://arxiv.org/abs/2007.14902v2
• [cs.CV]Multi-label Zero-shot Classification by Learning to Transfer from External Knowledge
He Huang, Yuanwei Chen, Wei Tang, Wenhao Zheng, Qing-Guo Chen, Yao hu, Philip Yu
http://arxiv.org/abs/2007.15610v1
• [cs.CV]NormalGAN: Learning Detailed 3D Human from a Single RGB-D Image
Lizhen Wang, Xiaochen Zhao, Tao Yu, Songtao Wang, Yebin Liu
http://arxiv.org/abs/2007.15340v1
• [cs.CV]Outlier-Robust Estimation: Hardness, Minimally-Tuned Algorithms, and Applications
Pasquale Antonante, Vasileios Tzoumas, Heng Yang, Luca Carlone
http://arxiv.org/abs/2007.15109v1
• [cs.CV]Perceiving 3D Human-Object Spatial Arrangements from a Single Image in the Wild
Jason Y. Zhang, Sam Pepose, Hanbyul Joo, Deva Ramanan, Jitendra Malik, Angjoo Kanazawa
http://arxiv.org/abs/2007.15649v1
• [cs.CV]Quantitative Distortion Analysis of Flattening Applied to the Scroll from En-Gedi
Clifford Seth Parker, William Brent Seales, Pnina Shor
http://arxiv.org/abs/2007.15551v1
• [cs.CV]Rethinking Recurrent Neural Networks and other Improvements for Image Classification
Nguyen Huu Phong, Bernardete Ribeiro
http://arxiv.org/abs/2007.15161v1
• [cs.CV]Revisiting the Modifiable Areal Unit Problem in Deep Traffic Prediction with Visual Analytics
Wei Zeng, Chengqiao Lin, Juncong Lin, Jincheng Jiang, Jiazhi Xia, Cagatay Turkay, Wei Chen
http://arxiv.org/abs/2007.15486v1
• [cs.CV]Rewriting a Deep Generative Model
David Bau, Steven Liu, Tongzhou Wang, Jun-Yan Zhu, Antonio Torralba
http://arxiv.org/abs/2007.15646v1
• [cs.CV]Searching Collaborative Agents for Multi-plane Localization in 3D Ultrasound
Yuhao Huang, Xin Yang, Rui Li, Jikuan Qian, Xiaoqiong Huang, Wenlong Shi, Haoran Dou, Chaoyu Chen, Yuanji Zhang, Huanjia Luo, Alejandro Frangi, Yi Xiong, Dong Ni
http://arxiv.org/abs/2007.15273v1
• [cs.CV]SimPose: Effectively Learning DensePose and Surface Normals of People from Simulated Data
Tyler Zhu, Per Karlsson, Christoph Bregler
http://arxiv.org/abs/2007.15506v1
• [cs.CV]Single Image Cloud Detection via Multi-Image Fusion
Scott Workman, M. Usman Rafique, Hunter Blanton, Connor Greenwell, Nathan Jacobs
http://arxiv.org/abs/2007.15144v1
• [cs.CV]The Blessing and the Curse of the Noise behind Facial Landmark Annotations
Xiaoyu Xiang, Yang Cheng, Shaoyuan Xu, Qian Lin, Jan Allebach
http://arxiv.org/abs/2007.15269v1
• [cs.CV]Unselfie: Translating Selfies to Neutral-pose Portraits in the Wild
Liqian Ma, Zhe Lin, Connelly Barnes, Alexei A. Efros, Jingwan Lu
http://arxiv.org/abs/2007.15068v1
• [cs.CV]Unsupervised Continuous Object Representation Networks for Novel View Synthesis
Nicolai Häni, Selim Engin, Jun-Jee Chao, Volkan Isler
http://arxiv.org/abs/2007.15627v1
• [cs.CV]Unsupervised Disentanglement GAN for Domain Adaptive Person Re-Identification
Yacine Khraimeche, Guillaume-Alexandre Bilodeau, David Steele, Harshad Mahadik
http://arxiv.org/abs/2007.15560v1
• [cs.CV]Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM
Guohao Yu, Alina Zare, Weihuang Xu, Roser Matamala, Joel Reyes-Cabrera, Felix B. Fritschi, Thomas E. Juenger
http://arxiv.org/abs/2007.15243v1
• [cs.CV]Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation
Kazuya Nishimura, Junya Hayashida, Chenyang Wang, Dai Fei Elmer Ker, Ryoma Bise
http://arxiv.org/abs/2007.15258
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v1)
• [cs.CY]AI-based Monitoring and Response System for Hospital Preparedness towards COVID-19 in Southeast Asia
Tushar Goswamy, Naishadh Parmar, Ayush Gupta, Vatsalya Tandon, Raunak Shah, Varun Goyal, Sanyog Gupta, Karishma Laud, Shivam Gupta, Sudhanshu Mishra, Ashutosh Modi
http://arxiv.org/abs/2007.15619v1
• [cs.CY]Developing a Novel Crowdsourcing Business Model for Micro-Mobility Ride-Sharing Systems: Methodology and Preliminary Results
Mohammed Elhenawy, MD Mostafizur Rahman Komol, Huthaifa I. Ashqar, Mohammed Hamad Almannaa, Mahmoud Masoud, Hesham A. Rakha, Andry Rakotonirainy
http://arxiv.org/abs/2007.15585v1
• [cs.CY]GIS-AHP Multi-Decision-Criteria-Analysis for the Optimal Location of Solar Energy Plants at Indonesia
H. S. Ruiz, A. Sunarso, K. Ibrahim-bathis, S. A. Murti, I. Budiarto
http://arxiv.org/abs/2007.15351v1
• [cs.CY]How Work From Home Affects Collaboration: A Large-Scale Study of Information Workers in a Natural Experiment During COVID-19
Longqi Yang, Sonia Jaffe, David Holtz, Siddharth Suri, Shilpi Sinha, Jeffrey Weston, Connor Joyce, Neha Shah, Kevin Sherman, CJ Lee, Brent Hecht, Jaime Teevan
http://arxiv.org/abs/2007.15584v1
• [cs.CY]IIT Kanpur Consulting Group: Using Machine Learning and Management Consulting for Social Good
Tushar Goswamy, Vatsalya Tandon, Naishadh Parmar, Raunak Shah, Ayush Gupta
http://arxiv.org/abs/2007.15628v1
• [cs.DB]On the Nature and Types of Anomalies: A Review
Ralph Foorthuis
http://arxiv.org/abs/2007.15634v1
• [cs.DC]Accelerating Multi-attribute Unsupervised Seismic Facies Analysis With RAPIDS
Otávio O. Napoli, Vanderson Martins do Rosario, João Paulo Navarro, Pedro Mário Cruz e Silva, Edson Borin
http://arxiv.org/abs/2007.15152v1
• [cs.DC]Implications of Dissemination Strategies on the Security of Distributed Ledgers
Luca Serena, Gabriele D’Angelo, Stefano Ferretti
http://arxiv.org/abs/2007.15260v1
• [cs.DC]New approach to MPI program execution time prediction
A. Chupakhin, A. Kolosov, R. Smeliansky, V. Antonenko, G. Ishelev
http://arxiv.org/abs/2007.15338v1
• [cs.DC]Phase Transitions of the k-Majority Dynamics in a Biased Communication Model
Emilio Cruciani, Hlafo Alfie Mimun, Matteo Quattropani, Sara Rizzo
http://arxiv.org/abs/2007.15306v1
• [cs.DL]Topics as Clusters of Citation Links to Highly Cited Sources: The Case of Research on International Relations
Frank Havemann
http://arxiv.org/abs/2007.15254v1
• [cs.DS]Efficient Tensor Decomposition
Aravindan Vijayaraghavan
http://arxiv.org/abs/2007.15589v1
• [cs.DS]Local Conflict Coloring Revisited: Linial for Lists
Yannic Maus, Tigran Tonoyan
http://arxiv.org/abs/2007.15251v1
• [cs.GT]Algorithmic Stability in Fair Allocation of Indivisible Goods Among Two Agents
Vijay Menon, Kate Larson
http://arxiv.org/abs/2007.15203v1
• [cs.HC]A Flexible and Modular Body-Machine Interface for Individuals Living with Severe Disabilities
Cheikh Latyr Fall, Ulysse Côté-Allard, Quentin Mascret, Alexandre Campeau-Lecours, Mounir Boukadoum, Clément Gosselin, Benoit Gosselin
http://arxiv.org/abs/2007.15032v1
• [cs.HC]Between Subjectivity and Imposition: Power Dynamics in Data Annotation for Computer Vision
Milagros Miceli, Martin Schuessler, Tianling Yang
http://arxiv.org/abs/2007.14886v2
• [cs.HC]Mixed-Reality Robotic Games: Design Guidelines for Effective Entertainment with Consumer Robots
F. Gabriele Pratticò, Fabrizio Lamberti
http://arxiv.org/abs/2007.15538v1
• [cs.HC]The BIRAFFE2 Experiment. Study in Bio-Reactions and Faces for Emotion-based Personalization for AI Systems
Krzysztof Kutt, Dominika Drążyk, Maciej Szelążek, Szymon Bobek, Grzegorz J. Nalepa
http://arxiv.org/abs/2007.15048v1
• [cs.IR]A Heterogeneous Information Network based Cross Domain Insurance Recommendation System for Cold Start Users
Ye Bi, Liqiang Song, Mengqiu Yao, Zhenyu Wu, Jianming Wang, Jing Xiao
http://arxiv.org/abs/2007.15293v1
• [cs.IR]A Hybrid Adaptive Educational eLearning Project based on Ontologies Matching and Recommendation System
Vasiliki Demertzi, Konstantinos Demertzis
http://arxiv.org/abs/2007.14771v2
• [cs.IR]Finding Local Experts for Dynamic Recommendations Using Lazy Random Walk
Diyah Puspitaningrum, Julio Fernando, Edo Afriando, Ferzha Putra Utama, Rina Rahmadini, Y. Pinata
http://arxiv.org/abs/2007.15091v1
• [cs.IR]Improving Performance of Relation Extraction Algorithm via Leveled Adversarial PCNN and Database Expansion
Diyah Puspitaningrum
http://arxiv.org/abs/2007.15084v1
• [cs.IR]Interpretable Contextual Team-aware Item Recommendation: Application in Multiplayer Online Battle Arena Games
Andrés Villa, Vladimir Araujo, Francisca Cattan, Denis Parra
http://arxiv.org/abs/2007.15236v1
• [cs.IR]Social Influences in Recommendation Systems
Diyah Puspitaningrum
http://arxiv.org/abs/2007.15104v1
• [cs.IR]What does BERT know about books, movies and music? Probing BERT for Conversational Recommendation
Gustavo Penha, Claudia Hauff
http://arxiv.org/abs/2007.15356v1
• [cs.IT]A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future
Gunes Kurt, Mohammad G. Khoshkholgh, Safwan Alfattani, Ahmed Ibrahim, Tasneem S. J. Darwish, Md Sahabul Alam, Halim Yanikomeroglu, Abbas Yongacoglu
http://arxiv.org/abs/2007.15088v1
• [cs.IT]Capacity of Remote Classification Over Wireless Channels
Qiao Lan, Yuqing Du, Petar Popovski, Kaibin Huang
http://arxiv.org/abs/2007.15480v1
• [cs.IT]Determination of 2-Adic Complexity of Generalized Binary Sequences of Order 2
Minghui Yang, Keqin Feng
http://arxiv.org/abs/2007.15327v1
• [cs.IT]Minimum Feedback for Collison-Free Scheduling in Massive Random Access
Justin Singh Kang, Wei Yu
http://arxiv.org/abs/2007.15497v1
• [cs.IT]Repairing Reed-Solomon Codes via Subspace Polynomials
Hoang Dau, Dinh Thi Xinh, Han Mao Kiah, Tran Thi Luong, Olgica Milenkovic
http://arxiv.org/abs/2007.15253v1
• [cs.IT]kth Distance Distributions of n-Dimensional Matérn Cluster Process
Kaushlendra Pandey, Abhishek K. Gupta
http://arxiv.org/abs/2007.15233v1
• [cs.LG]Anomaly Detection at Scale: The Case for Deep Distributional Time Series Models
Fadhel Ayed, Lorenzo Stella, Tim Januschowski, Jan Gasthaus
http://arxiv.org/abs/2007.15541v1
• [cs.LG]Beyond $\mathcal{H}$-Divergence: Domain Adaptation Theory With Jensen-Shannon Divergence
Changjian Shui, Qi Chen, Jun Wen, Fan Zhou, Christian Gagné, Boyu Wang
http://arxiv.org/abs/2007.15567v1
• [cs.LG]Bilevel Continual Learning
Quang Pham, Doyen Sahoo, Chenghao Liu, Steven C. H Hoi
http://arxiv.org/abs/2007.15553v1
• [cs.LG]Black-box Adversarial Sample Generation Based on Differential Evolution
Junyu Lin, Lei Xu, Yingqi Liu, Xiangyu Zhang
http://arxiv.org/abs/2007.15310v1
• [cs.LG]CSER: Communication-efficient SGD with Error Reset
Cong Xie, Shuai Zheng, Oluwasanmi Koyejo, Indranil Gupta, Mu Li, Haibin Lin
http://arxiv.org/abs/2007.13221v2
• [cs.LG]Communication-Efficient Federated Learning via Optimal Client Sampling
Monica Ribero, Haris Vikalo
http://arxiv.org/abs/2007.15197v1
• [cs.LG]Data-efficient Hindsight Off-policy Option Learning
Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala, Noah Siegel, Nicolas Heess, Martin Riedmiller
http://arxiv.org/abs/2007.15588v1
• [cs.LG]Deep Multi-View Spatiotemporal Virtual Graph Neural Network for Significant Citywide Ride-hailing Demand Prediction
Guangyin Jin, Zhexu Xi, Hengyu Sha, Yanghe Feng, Jincai Huang
http://arxiv.org/abs/2007.15189v1
• [cs.LG]DeepPeep: Exploiting Design Ramifications to Decipher the Architecture of Compact DNNs
Nandan Kumar Jha, Sparsh Mittal, Binod Kumar, Govardhan Mattela
http://arxiv.org/abs/2007.15248v1
• [cs.LG]Deriving Differential Target Propagation from Iterating Approximate Inverses
Yoshua Bengio
http://arxiv.org/abs/2007.15139v1
• [cs.LG]Detecting Anomalous Inputs to DNN Classifiers By Joint Statistical Testing at the Layers
Jayaram Raghuram, Varun Chandrasekaran, Somesh Jha, Suman Banerjee
http://arxiv.org/abs/2007.15147v1
• [cs.LG]Dynamic Federated Learning Model for Identifying Adversarial Clients
Nuria Rodríguez-Barroso, Eugenio Martínez-Cámara, M. Victoria Luzón, Gerardo González Seco, Miguel Ángel Veganzones, Francisco Herrera
http://arxiv.org/abs/2007.15030v1
• [cs.LG]Evolving Context-Aware Recommender Systems With Users in Mind
Amit Livne, Eliad Shem Tov, Adir Solomon, Achiya Elyasaf, Bracha Shapira, Lior Rokach
http://arxiv.org/abs/2007.15409v1
• [cs.LG]FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting
Boris N. Oreshkin, Arezou Amini, Lucy Coyle, Mark J. Coates
http://arxiv.org/abs/2007.15531v1
• [cs.LG]Fast, Structured Clinical Documentation via Contextual Autocomplete
Divya Gopinath, Monica Agrawal, Luke Murray, Steven Horng, David Karger, David Sontag
http://arxiv.org/abs/2007.15153v1
• [cs.LG]Generalization Comparison of Deep Neural Networks via Output Sensitivity
Mahsa Forouzesh, Farnood Salehi, Patrick Thiran
http://arxiv.org/abs/2007.15378v1
• [cs.LG]Growing Efficient Deep Networks by Structured Continuous Sparsification
Xin Yuan, Pedro Savarese, Michael Maire
http://arxiv.org/abs/2007.15353v1
• [cs.LG]Improving Sample Eficiency with Normalized RBF Kernels
Sebastian Pineda-Arango, David Obando-Paniagua, Alperen Dedeoglu, Philip Kurzendörfer, Friedemann Schestag, Randolf Scholz
http://arxiv.org/abs/2007.15397v1
• [cs.LG]Label-Leaks: Membership Inference Attack with Label
Zheng Li, Yang Zhang
http://arxiv.org/abs/2007.15528v1
• [cs.LG]Momentum Q-learning with Finite-Sample Convergence Guarantee
Bowen Weng, Huaqing Xiong, Lin Zhao, Yingbin Liang, Wei Zhang
http://arxiv.org/abs/2007.15418v1
• [cs.LG]PixL2R: Guiding Reinforcement Learning Using Natural Language by Mapping Pixels to Rewards
Prasoon Goyal, Scott Niekum, Raymond J. Mooney
http://arxiv.org/abs/2007.15543v1
• [cs.LG]Prediction of hierarchical time series using structured regularization and its application to artificial neural networks
Tomokaze Shiratori, Ken Kobayashi, Yuichi Takano
http://arxiv.org/abs/2007.15159v1
• [cs.LG]PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings
Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Sahand Sharifzadeh, Volker Tresp, Jens Lehmann
http://arxiv.org/abs/2007.14175v2
• [cs.LG]Quantity vs. Quality: On Hyperparameter Optimization for Deep Reinforcement Learning
Lars Hertel, Pierre Baldi, Daniel L. Gillen
http://arxiv.org/abs/2007.14604v2
• [cs.LG]Regional Rainfall Prediction Using Support Vector Machine Classification of Large-Scale Precipitation Maps
Eslam A. Hussein, Mehrdad Ghaziasgar, Christopher Thron
http://arxiv.org/abs/2007.15404v1
• [cs.LG]Stable Learning via Causality-based Feature Rectification
Zhengxu Yu, Pengfei Wang, Junkai Xu, Liang Xie, Zhongming Jin, Jianqiang Huang, Xiaofei He, Deng Cai, Xian-Sheng Hua
http://arxiv.org/abs/2007.15241v1
• [cs.LG]Stopping Criterion Design for Recursive Bayesian Classification: Analysis and Decision Geometry
Aziz Kocanaogullari, Murat Akcakaya, Deniz Erdogmus
http://arxiv.org/abs/2007.15568v1
• [cs.LG]SynergicLearning: Neural Network-Based Feature Extraction for Highly-Accurate Hyperdimensional Learning
Mahdi Nazemi, Amirhossein Esmaili, Arash Fayyazi, Massoud Pedram
http://arxiv.org/abs/2007.15222v1
• [cs.LG]The Complexity of Adversarially Robust Proper Learning of Halfspaces with Agnostic Noise
Ilias Diakonikolas, Daniel M. Kane, Pasin Manurangsi
http://arxiv.org/abs/2007.15220v1
• [cs.LG]Trade-offs in Top-k Classification Accuracies on Losses for Deep Learning
Azusa Sawada, Eiji Kaneko, Kazutoshi Sagi
http://arxiv.org/abs/2007.15359v1
• [cs.LG]When are Neural ODE Solutions Proper ODEs?
Katharina Ott, Prateek Katiyar, Philipp Hennig, Michael Tiemann
http://arxiv.org/abs/2007.15386v1
• [cs.NE]On Representing (Anti)Symmetric Functions
Marcus Hutter
http://arxiv.org/abs/2007.15298v1
• [cs.NE]Research on Fitness Function of Tow Evolution Algorithms Using for Neutron Spectrum Unfolding
Rui Li, Jianbo Yang, Xianguo Tuo, Rui Shi
http://arxiv.org/abs/2007.15206v1
• [cs.NI]Swarm Intelligence for Next-Generation Wireless Networks: Recent Advances and Applications
Quoc-Viet Pham, Dinh C. Nguyen, Seyedali Mirjalili, Dinh Thai Hoang, Diep N. Nguyen, Pubudu N. Pathirana, Won-Joo Hwang
http://arxiv.org/abs/2007.15221v1
• [cs.RO]Bayesian Optimization for Developmental Robotics with Meta-Learning by Parameters Bounds Reduction
Maxime Petit, Emmanuel Dellandrea, Liming Chen
http://arxiv.org/abs/2007.15375v1
• [cs.RO]DroneLight: Drone Draws in the Air using Long Exposure Light Painting and ML
Roman Ibrahimov, Nikolay Zherdev, Dzmitry Tsetserukou
http://arxiv.org/abs/2007.15171v1
• [cs.RO]Learning Object-conditioned Exploration using Distributed Soft Actor Critic
Ayzaan Wahid, Austin Stone, Kevin Chen, Brian Ichter, Alexander Toshev
http://arxiv.org/abs/2007.14545v2
• [cs.RO]Learning RGB-D Feature Embeddings for Unseen Object Instance Segmentation
Yu Xiang, Christopher Xie, Arsalan Mousavian, Dieter Fox
http://arxiv.org/abs/2007.15157v1
• [cs.RO]Lifelong Navigation
Bo Liu, Xuesu Xiao, Peter Stone
http://arxiv.org/abs/2007.14486v2
• [cs.RO]Natural Gradient Shared Control
Yoojin Oh, Shao-Wen Wu, Marc Toussaint, Jim Mainprice
http://arxiv.org/abs/2007.15308v1
• [cs.RO]OrcVIO: Object residual constrained Visual-Inertial Odometry
Mo Shan, Qiaojun Feng, Nikolay Atanasov
http://arxiv.org/abs/2007.15107v1
• [cs.RO]Toward Agile Maneuvers in Highly Constrained Spaces: Learning from Hallucination
Xuesu Xiao, Bo Liu, Garrett Warnell, Peter Stone
http://arxiv.org/abs/2007.14479v2
• [cs.SI]Depressive, Drug Abusive, or Informative: Knowledge-aware Study of News Exposure during COVID-19 Outbreak
Amanuel Alambo, Manas Gaur, Krishnaprasad Thirunarayan
http://arxiv.org/abs/2007.15209v1
• [cs.SI]Sybil Resilient Money Minting
Ouri Poupko, Nimrod Talmon
http://arxiv.org/abs/2007.15536v1
• [e
8e8
ess.AS]Music FaderNets: Controllable Music Generation Based On High-Level Features via Low-Level Feature Modelling
Hao Hao Tan, Dorien Herremans
http://arxiv.org/abs/2007.15474v1
• [econ.EM]Measuring the Effectiveness of US Monetary Policy during the COVID-19 Recession
Martin Feldkircher, Florian Huber, Michael Pfarrhofer
http://arxiv.org/abs/2007.15419v1
• [econ.TH]Learning what they think vs. learning what they to: The micro-foundations of vicarious learning
Sanghyun Park, Phanish Puranam
http://arxiv.org/abs/2007.15264v1
• [eess.AS]Developing RNN-T Models Surpassing High-Performance Hybrid Models with Customization Capability
Jinyu Li, Rui Zhao, Zhong Meng, Yanqing Liu, Wenning Wei, Sarangarajan Parthasarathy, Vadim Mazalov, Zhenghao Wang, Lei He, Sheng Zhao, Yifan Gong
http://arxiv.org/abs/2007.15188v1
• [eess.AS]Exploiting Cross-Lingual Knowledge in Unsupervised Acoustic Modeling for Low-Resource Languages
Siyuan Feng
http://arxiv.org/abs/2007.15074v1
• [eess.IV]Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients
Sofie Tilborghs, Ine Dirks, Lucas Fidon, Siri Willems, Tom Eelbode, Jeroen Bertels, Bart Ilsen, Arne Brys, Adriana Dubbeldam, Nico Buls, Panagiotis Gonidakis, Sebastián Amador Sánchez, Annemiek Snoeckx, Paul M. Parizel, Johan de Mey, Dirk Vandermeulen, Tom Vercauteren, David Robben, Dirk Smeets, Frederik Maes, Jef Vandemeulebroucke, Paul Suetens
http://arxiv.org/abs/2007.15546v1
• [eess.IV]Searching for Pneumothorax in Half a Million Chest X-Ray Images
Antonio Sze-To, Hamid Tizhoosh
http://arxiv.org/abs/2007.15429v1
• [eess.IV]Very Deep Super-Resolution of Remotely Sensed Images with Mean Square Error and Var-norm Estimators as Loss Functions
Antigoni Panagiotopoulou, Lazaros Grammatikopoulos, Eleni Charou, Emmanuel Bratsolis, Nicholas Madamopoulos, John Petrogonas
http://arxiv.org/abs/2007.15417v1
• [eess.SP]A Brain Emotional Learning-inspired Model For the Prediction of Geomagnetic Storms
Mahboobeh Parsapoor
http://arxiv.org/abs/2007.15579v1
• [eess.SP]Deep-Learning based Inverse Modeling Approaches: A Subsurface Flow Example
Nanzhe Wanga, Haibin Changa, Dongxiao Zhang
http://arxiv.org/abs/2007.15580v1
• [eess.SP]Dense Small Satellite Networks for Modern Terrestrial Communication Systems: Benefits, Infrastructure, and Technologies
Naveed UL Hassan, Chongwen Huang, Chau Yuen, Ayaz Ahmad, Yan Zhang
http://arxiv.org/abs/2007.15377v1
• [eess.SP]Localization with One-Bit Passive Radars in Narrowband Internet-of-Things using Multivariate Polynomial Optimization
Saeid Sedighi, Kumar Vijay Mishra, M. R. Bhavani Shankar, Björn Ottersten
http://arxiv.org/abs/2007.15108v1
• [eess.SP]Unsupervised Event Detection, Clustering, and Use Case Exposition in Micro-PMU Measurements
Armin Aligholian, Alireza Shahsavari, Emma Stewart, Ed Cortez, Hamed Mohsenian-Rad
http://arxiv.org/abs/2007.15237v1
• [math.FA]Approximation of Smoothness Classes by Deep ReLU Networks
Mazen Ali, Anthony Nouy
http://arxiv.org/abs/2007.15645v1
• [math.OC]A PAC algorithm in relative precision for bandit problem with costly sampling
Marie Billaud-Friess, Arthur Macherey, Anthony Nouy, Clémentine Prieur
http://arxiv.org/abs/2007.15331v1
• [math.ST]A Power Analysis for Knockoffs with the Lasso Coefficient-Difference Statistic
Asaf Weinstein, Weijie J. Su, Małgorzata Bogdan, Rina F. Barber, Emmanuel J. Candès
http://arxiv.org/abs/2007.15346v1
• [math.ST]Adaptive nonparametric estimation of a component density in a two-class mixture model
Gaelle Chagny, Antoine Channarond, Van Ha Hoang, Angelina Roche
http://arxiv.org/abs/2007.15518v1
• [math.ST]Covariance estimation with nonnegative partial correlations
Jake A. Soloff, Adityanand Guntuboyina, Michael I. Jordan
http://arxiv.org/abs/2007.15252v1
• [math.ST]Fully distribution-free center-outward rank tests for multiple-output regression and MANOVA
Marc Hallin, Daniel Hlubinka, Šárka Hudecová
http://arxiv.org/abs/2007.15496v1
• [math.ST]Learning interaction kernels in stochastic systems of interacting particles from multiple trajectories
Fei Lu, Mauro Maggioni, Sui Tang
http://arxiv.org/abs/2007.15174v1
• [math.ST]Multi-dimensional parameter estimation of heavy-tailed moving averages
Mathias Mørck Ljungdahl, Mark Podolskij
http://arxiv.org/abs/2007.15301v1
• [math.ST]Outlier Robust Mean Estimation with Subgaussian Rates via Stability
Ilias Diakonikolas, Daniel M. Kane, Ankit Pensia
http://arxiv.org/abs/2007.15618v1
• [q-bio.NC]A superconducting nanowire spiking element for neural networks
Emily Toomey, Ken Segall, Matteo Castellani, Marco Colangelo, Nancy Lynch, Karl K. Berggren
http://arxiv.org/abs/2007.15101v1
• [q-bio.PE]Correlation between COVID-19 morbidity and mortality rates in Japan and local population density, temperature and absolute humidity
Sachiko Kodera, Essam A. Rashed, Akimasa Hirata
http://arxiv.org/abs/2007.14065v2
• [q-bio.QM]Few shot domain adaptation for in situ macromolecule structural classification in cryo-electron tomograms
Liangyong Yu, Ran Li, Xiangrui Zeng, Hongyi Wang, Jie Jin, Ge Yang, Rui Jiang, Min Xu
http://arxiv.org/abs/2007.15422v1
• [stat.AP]A Recipe for Accurate Estimation of Lifespan Brain Trajectories, Distinguishing Longitudinal and Cohort Effects
Øystein Sørensen, Kristine B Walhovd, Anders M Fjell
http://arxiv.org/abs/2007.13446v1
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• [stat.AP]A Recommendation and Risk Classification System for Connecting Rough Sleepers to Essential Outreach Services
Harrison Wilde, Lucia Lushi Chen, Austin Nguyen, Zoe Kimpel, Joshua Sidgwick, Adolfo De Unanue, Davide Veronese, Bilal Mateen, Rayid Ghani, Sebastian Vollmer
http://arxiv.org/abs/2007.15326v1
• [stat.AP]Change Sign Detection with Differential MDL Change Statistics and its Applications to COVID-19 Pandemic Analysis
Kenji Yamanishi, Linchuan Xu, Ryo Yuki, Shintaro Fukushima, Chuan-hao Lin
http://arxiv.org/abs/2007.15179v1
• [stat.AP]Extreme-K categorical samples problem
Elizabeth Chou, Catie McVey, Yin-Chen Hsieh, Sabrina Enriquez, Fushing Hsieh
http://arxiv.org/abs/2007.15039v1
• [stat.AP]Regression-based imputation of explanatory discrete missing data
Gilma Hernández-Herrera, Albert Navarro, David Moriña
http://arxiv.org/abs/2007.15031v1
• [stat.AP]Skewed link regression models for imbalanced binary response with applications to life insurance
Shuang Yin, Dipak K. Dey, Emiliano A. Valdez, Guojun Gan, Jeyaraj Vadiveloo
http://arxiv.org/abs/2007.15172v1
• [stat.ME]A notion of depth for sparse functional data
Carlo Sguera, Sara López-Pintado
http://arxiv.org/abs/2007.15413v1
• [stat.ME]Approximate inferences for nonlinear mixed effects models with scale mixtures of skew-normal distributions
Fernanda L. Schumacher, Dipak K. Dey, Victor H. Lachos
http://arxiv.org/abs/2007.15086v1
• [stat.ME]Coloured Tobit Kalman Filter
Kostas Loumponias
http://arxiv.org/abs/2007.15335v1
• [stat.ME]Impulse Response Analysis for Sparse High-Dimensional Time Series
Jonas Krampe, Efstathios Paparoditis, Carsten Trenkler
http://arxiv.org/abs/2007.15535v1
• [stat.ME]Localizing differences in smooths with simultaneous confidence bounds on the true discovery proportion
David Swanson
http://arxiv.org/abs/2007.15445v1
• [stat.ME]Non Uniform Sampling of Fixed Margin Uniform Matrices
Alex Fout, Bailey Fosdick, Matthew P. Hitt
http://arxiv.org/abs/2007.15043v1
• [stat.ME]Real-time detection of a change-point in a linear expectile model
Gabriela Ciuperca
http://arxiv.org/abs/2007.15137v1
• [stat.ML]Accuracy and stability of solar variable selection comparison under complicated dependence structures
Ning Xu
http://arxiv.org/abs/2007.15614v1
• [stat.ML]Information-Theoretic Approximation to Causal Models
Peter Gmeiner
http://arxiv.org/abs/2007.15047v1
• [stat.ML]Learning Output Embeddings in Structured Prediction
Luc Brogat-Motte, Alessandro Rudi, Céline Brouard, Juho Rousu, Florence d’Alché-Buc
http://arxiv.org/abs/2007.14703v2
• [stat.ML]On the Banach spaces associated with multi-layer ReLU networks: Function representation, approximation theory and gradient descent dynamics
Weinan E, Stephan Wojtowytsch
http://arxiv.org/abs/2007.15623v1
• [stat.ML]Quantitative Understanding of VAE by Interpreting ELBO as Rate Distortion Cost of Transform Coding
Akira Nakagawa, Keizo Kato
http://arxiv.org/abs/2007.15190v1
• [stat.ML]Rademacher upper bounds for cross-validation errors with an application to the lasso
Ning Xu, Timothy C. G. Fisher, Jian Hong
http://arxiv.org/abs/2007.15598v1
• [stat.ML]Random Forests for dependent data
Arkajyoti Saha, Sumanta Basu, Abhirup Datta
http://arxiv.org/abs/2007.15421v1
• [stat.ML]Unnormalized Variational Bayes
Saeed Saremi
http://arxiv.org/abs/2007.15130v1
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