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.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.HC - 人机接口 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.PF - 计算性能 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.RA - 环与代数 math.ST - 统计理论 physics.ao-ph - 大气和海洋物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]Extensional Higher-Order Paramodulation in Leo-III
• [cs.AI]Learning and T-Norms Theory
• [cs.AI]Probabilistic Approximate Logic and its Implementation in the Logical Imagination Engine
• [cs.CL]Deep Ranking Based Cost-sensitive Multi-label Learning for Distant Supervision Relation Extraction
• [cs.CL]DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks
• [cs.CL]Investigating Self-Attention Network for Chinese Word Segmentation
• [cs.CL]LINSPECTOR WEB: A Multilingual Probing Suite for Word Representations
• [cs.CL]On the Use/Misuse of the Term ‘Phoneme’
• [cs.CL]RoBERTa: A Robustly Optimized BERT Pretraining Approach
• [cs.CL]Time Masking: Leveraging Temporal Information in Spoken Dialogue Systems
• [cs.CL]Weakly Supervised Domain Detection
• [cs.CR]On the Round Complexity of Randomized Byzantine Agreement
• [cs.CR]Protocol for Asynchronous, Reliable, Secure and Efficient Consensus (PARSEC) Version 2.0
• [cs.CV]A Comparative Study of High-Recall Real-Time Semantic Segmentation Based on Swift Factorized Network
• [cs.CV]A Fully-Convolutional Neural Network for Background Subtraction of Unseen Videos
• [cs.CV]Context-Aware Multipath Networks
• [cs.CV]Context-Integrated and Feature-Refined Network for Lightweight Urban Scene Parsing
• [cs.CV]Cooperative image captioning
• [cs.CV]DCT-CompCNN: A Novel Image Classification Network Using JPEG Compressed DCT Coefficients
• [cs.CV]Deep Learning for Classification and Severity Estimation of Coffee Leaf Biotic Stress
• [cs.CV]Differential Scene Flow from Light Field Gradients
• [cs.CV]Improving Generalization via Attribute Selection on Out-of-the-box Data
• [cs.CV]LinearConv: Regenerating Redundancy in Convolution Filters as Linear Combinations for Parameter Reduction
• [cs.CV]MVB: A Large-Scale Dataset for Baggage Re-Identification and Merged Siamese Networks
• [cs.CV]Multi-level Domain Adaptive learning for Cross-Domain Detection
• [cs.CV]Multiple Human Association between Top and Horizontal Views by Matching Subjects’ Spatial Distributions
• [cs.CV]On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
• [cs.CV]Outfit Compatibility Prediction and Diagnosis with Multi-Layered Comparison Network
• [cs.CV]Product Image Recognition with Guidance Learning and Noisy Supervision
• [cs.CV]Report on UG^2+ Challenge Track 1: Assessing Algorithms to Improve Video Object Detection and Classification from Unconstrained Mobility Platforms
• [cs.CV]Semantic Deep Intermodal Feature Transfer: Transferring Feature Descriptors Between Imaging Modalities
• [cs.CV]Single Level Feature-to-Feature Forecasting with Deformable Convolutions
• [cs.CV]UGAN: Untraceable GAN for Multi-Domain Face Translation
• [cs.CV]Universal Pooling — A New Pooling Method for Convolutional Neural Networks
• [cs.CV]Unsupervised Learning Framework of Interest Point Via Properties Optimization
• [cs.CV]Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM
• [cs.CV]Using 3D Convolutional Neural Networks to Learn Spatiotemporal Features for Automatic Surgical Gesture Recognition in Video
• [cs.CY]Evaluating the Impact of Using GRASP Framework on Clinicians and Healthcare Professionals Decisions in Selecting Clinical Predictive Tools
• [cs.CY]Reducing malicious use of synthetic media research: Considerations and potential release practices for machine learning
• [cs.CY]Validating and Updating GRASP: A New Evidence-Based Framework for Grading and Assessment of Clinical Predictive Tools
• [cs.DC]Edge User Allocation with Dynamic Quality of Service
• [cs.DC]Fog Computing Applications: Taxonomy and Requirements
• [cs.DC]Massively Scaling Seismic Processing on Sunway TaihuLight Supercomputer
• [cs.DC]ServerMix: Tradeoffs and Challenges of Serverless Data Analytics
• [cs.DS]Exhaustive Exact String Matching: The Analysis of the Full Human Genome
• [cs.HC]Personality is Revealed During Weekends: Towards Data Minimisation for Smartphone Based Personality Classification
• [cs.HC]Vocal Interactivity in Crowds, Flocks and Swarms: Implications for Voice User Interfaces
• [cs.IT]Achievable Rate Region for Iterative Multi-User Detection via Low-cost Gaussian Approximation
• [cs.IT]Neural Dynamic Successive Cancellation Flip Decoding of Polar Codes
• [cs.IT]Power Error Locating Pairs
• [cs.LG]A Frobenius norm regularization method for convolutional kernels to avoid unstable gradient problem
• [cs.LG]An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems
• [cs.LG]Bayesian Volumetric Autoregressive generative models for better semisupervised learning
• [cs.LG]Compressing deep quaternion neural networks with targeted regularization
• [cs.LG]DEAM: Accumulated Momentum with Discriminative Weight for Stochastic Optimization
• [cs.LG]Lexicographic Multiarmed Bandit
• [cs.LG]Making Neural Networks FAIR
• [cs.LG]Multi-Stage Prediction Networks for Data Harmonization
• [cs.LG]Scalable Semi-Supervised SVM via Triply Stochastic Gradients
• [cs.LG]Taming Momentum in a Distributed Asynchronous Environment
• [cs.LG]Towards meta-learning for multi-target regression problems
• [cs.LG]Training products of expert capsules with mixing by dynamic routing
• [cs.LG]Two-hidden-layer Feedforward Neural Networks are Universal Approximators: A Constructive Approach
• [cs.LO]Revisiting Explicit Negation in Answer Set Programming
• [cs.MA]Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
• [cs.NE]Autoencoding with a Learning Classifier System: Initial Results
• [cs.NE]Training capsules as a routing-weighted product of expert neurons
• [cs.NI]Data Aggregation Techniques for Internet of Things
• [cs.NI]Delay Analysis in Full-Duplex Heterogeneous Cellular Networks
• [cs.PF]Anonymity Mixes as (Partial) Assembly Queues: Modeling and Analysis
• [cs.RO]Feedback Control for Autonomous Riding of Hovershoes by a Cassie Bipedal Robot
• [cs.RO]Learning to Solve a Rubik’s Cube with a Dexterous Hand
• [cs.RO]Precise localization relative to 3D Automated Driving map using the Decentralized Kalman filter with Feedback
• [cs.RO]Vehicular Multi-object Tracking with Persistent Detector Failures
• [cs.SD]Interactive Lungs Auscultation with Reinforcement Learning Agent
• [cs.SE]An Empirical Analysis of the Python Package Index (PyPI)
• [cs.SI]Challenges in Community Discovery on Temporal Networks
• [cs.SI]Networks of Power: Analyzing World Leaders Interactions on Social Media
• [eess.AS]Correlation Distance Skip Connection Denoising Autoencoder (CDSK-DAE) for Speech Feature Enhancement
• [eess.IV]Adaptive Compressed Sensing MRI with Unsupervised Learning
• [eess.IV]Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images
• [eess.IV]As easy as 1, 2… 4? Uncertainty in counting tasks for medical imaging
• [eess.IV]Automatic Calcium Scoring in Cardiac and Chest CT Using DenseRAUnet
• [eess.IV]Image Enhancement by Recurrently-trained Super-resolution Network
• [eess.IV]Self-Adaptive 2D-3D Ensemble of Fully Convolutional Networks for Medical Image Segmentation
• [eess.SP]Detection of Malfunctioning Smart Electricity Meter
• [eess.SP]Online Subspace Tracking for Damage Propagation Modeling and Predictive Analytics: Big Data Perspective
• [eess.SP]Towards the Enhancement of Body Standing Balance Recovery by Means of a Wireless Audio-Biofeedback System
• [math.NA]A bisector line field approach to interpolation of orientation fields
• [math.OC]Incremental Methods for Weakly Convex Optimization
• [math.OC]Using positive spanning sets to achieve stationarity with the Boosted DC Algorithm
• [math.PR]Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity
• [math.RA]Rational Motions with Generic Trajectories of Low Degree
• [math.ST]Adaptive regression with Brownian path covariate
• [math.ST]An asymptotically optimal transform of Pearson’s correlation statistic
• [math.ST]Double Bayesian Smoothing as Message Passing
• [math.ST]Notes on Computational Hardness of Hypothesis Testing: Predictions using the Low-Degree Likelihood Ratio
• [math.ST]Phase Transition Unbiased Estimation in High Dimensional Settings
• [math.ST]Robust multivariate mean estimation: the optimality of trimmed mean
• [math.ST]Subexponential-Time Algorithms for Sparse PCA
• [physics.ao-ph]Analog forecasting of extreme-causing weather patterns using deep learning
• [stat.AP]Adjusting for Spatial Effects in Genomic Prediction
• [stat.AP]Comparative Analysis of User Behavior of Dock-Based vs. Dockless Bikeshare and Scootershare in Washington, D.C
• [stat.AP]Decision Tree Learning for Uncertain Clinical Measurements
• [stat.AP]Exploiting new forms of data to study the private rented sector: strengths and limitations of a database of rental listings
• [stat.CO]Analyzing MCMC Output
• [stat.ME]A memory-free spatial additive mixed modeling for big spatial data
• [stat.ME]Measurement error and precision medicine: error-prone tailoring covariates in dynamic treatment regimes
• [stat.ME]On the variability of regression shrinkage methods for clinical prediction models: simulation study on predictive performance
• [stat.ME]Some examples of application for predicting of compressive sensing method
• [stat.ML]A close-up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation
• [stat.ML]Doubly-Robust Lasso Bandit
• [stat.ML]Graph Informer Networks for Molecules
• [stat.ML]Sequential Learning of Active Subspaces
• [stat.ML]Towards Scalable Gaussian Process Modeling
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• [cs.AI]Extensional Higher-Order Paramodulation in Leo-III
Alexander Steen, Christoph Benzmüller
http://arxiv.org/abs/1907.11501v1
• [cs.AI]Learning and T-Norms Theory
Giuseppe Marra, Francesco Giannini, Michelangelo Diligenti, Marco Maggini, Marco Gori
http://arxiv.org/abs/1907.11468v1
• [cs.AI]Probabilistic Approximate Logic and its Implementation in the Logical Imagination Engine
Mark-Oliver Stehr, Minyoung Kim, Carolyn L. Talcott, Merrill Knapp, Akos Vertes
http://arxiv.org/abs/1907.11321v1
• [cs.CL]Deep Ranking Based Cost-sensitive Multi-label Learning for Distant Supervision Relation Extraction
Hai Ye, Zhunchen Luo
http://arxiv.org/abs/1907.11521v1
• [cs.CL]DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks
Lin Zehui, Pengfei Liu, Luyao Huang, Junkun Chen, Xipeng Qiu, Xuanjing Huang
http://arxiv.org/abs/1907.11065v2
• [cs.CL]Investigating Self-Attention Network for Chinese Word Segmentation
Leilei Gan, Yue Zhang
http://arxiv.org/abs/1907.11512v1
• [cs.CL]LINSPECTOR WEB: A Multilingual Probing Suite for Word Representations
Max Eichler, Gözde Gül Şahin, Iryna Gurevych
http://arxiv.org/abs/1907.11438v1
• [cs.CL]On the Use/Misuse of the Term ‘Phoneme’
Roger K. Moore, Lucy Skidmore
http://arxiv.org/abs/1907.11640v1
• [cs.CL]RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, Veselin Stoyanov
http://arxiv.org/abs/1907.11692v1
• [cs.CL]Time Masking: Leveraging Temporal Information in Spoken Dialogue Systems
Rylan Conway, Lambert Mathias
http://arxiv.org/abs/1907.11315v1
• [cs.CL]Weakly Supervised Domain Detection
Yumo Xu, Mirella Lapata
http://arxiv.org/abs/1907.11499v1
• [cs.CR]On the Round Complexity of Randomized Byzantine Agreement
Ran Cohen, Iftach Haitner, Nikolaos Makriyannis, Matan Orland, Alex Samorodnitsky
http://arxiv.org/abs/1907.11329v1
• [cs.CR]Protocol for Asynchronous, Reliable, Secure and Efficient Consensus (PARSEC) Version 2.0
Pierre Chevalier, Bartlomiej Kaminski, Fraser Hutchison, Qi Ma, Spandan Sharma, Andreas Fackler, William J Buchanan
http://arxiv.org/abs/1907.11445v1
• [cs.CV]A Comparative Study of High-Recall Real-Time Semantic Segmentation Based on Swift Factorized Network
Kaite Xiang, Kaiwei Wang, Kailun Yang
http://arxiv.org/abs/1907.11394v1
• [cs.CV]A Fully-Convolutional Neural Network for Background Subtraction of Unseen Videos
M. Ozan Tezcan, Janusz Konrad, Prakash Ishwar
http://arxiv.org/abs/1907.11371v1
• [cs.CV]Context-Aware Multipath Networks
Dumindu Tissera, Kumara Kahatapitiya, Rukshan Wijesinghe, Subha Fernando, Ranga Rodrigo
http://arxiv.org/abs/1907.11519v1
• [cs.CV]Context-Integrated and Feature-Refined Network for Lightweight Urban Scene Parsing
Bin Jiang, Wenxuan Tu, Chao Yang, Junsong Yuan
http://arxiv.org/abs/1907.11474v1
• [cs.CV]Cooperative image captioning
Gilad Vered, Gal Oren, Yuval Atzmon, Gal Chechik
http://arxiv.org/abs/1907.11565v1
• [cs.CV]DCT-CompCNN: A Novel Image Classification Network Using JPEG Compressed DCT Coefficients
Bulla Rajesh, Mohammed Javed, Ratnesh, Shubham Srivastava
http://arxiv.org/abs/1907.11503v1
• [cs.CV]Deep Learning for Classification and Severity Estimation of Coffee Leaf Biotic Stress
J. G. M. Esgario, R. A. Krohling, J. A. Ventura
http://arxiv.org/abs/1907.11561v1
• [cs.CV]Differential Scene Flow from Light Field Gradients
Sizhuo Ma, Brandon M. Smith, Mohit Gupta
http://arxiv.org/abs/1907.11637v1
• [cs.CV]Improving Generalization via Attribute Selection on Out-of-the-box Data
Xiaofeng Xu, Ivor W. Tsang, Chuancai Liu
http://arxiv.org/abs/1907.11397v1
• [cs.CV]LinearConv: Regenerating Redundancy in Convolution Filters as Linear Combinations for Parameter Reduction
Kumara Kahatapitiya, Ranga Rodrigo
http://arxiv.org/abs/1907.11432v1
• [cs.CV]MVB: A Large-Scale Dataset for Baggage Re-Identification and Merged Siamese Networks
Zhulin Zhang, Dong Li, Jinhua Wu, Yunda Sun, Li Zhang
http://arxiv.org/abs/1907.11366v1
• [cs.CV]Multi-level Domain Adaptive learning for Cross-Domain Detection
Rongchang Xie, Fei Yu, Jiachao Wang, Yizhou Wang, Li Zhang
http://arxiv.org/abs/1907.11484v1
• [cs.CV]Multiple Human Association between Top and Horizontal Views by Matching Subjects’ Spatial Distributions
Ruize Han, Yujun Zhang, Wei Feng, Chenxing Gong, Xiaoyu Zhang, Jiewen Zhao, Liang Wan, Song Wang
http://arxiv.org/abs/1907.11458v1
• [cs.CV]On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method
Pu Zhao, Sijia Liu, Pin-Yu Chen, Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, Xue Lin
http://arxiv.org/abs/1907.11684v1
• [cs.CV]Outfit Compatibility Prediction and Diagnosis with Multi-Layered Comparison Network
Xin Wang, Bo Wu, Yun Ye, Yueqi Zhong
http://arxiv.org/abs/1907.11496v1
• [cs.CV]Product Image Recognition with Guidance Learning and Noisy Supervision
Qing Li, Xiaojiang Peng, Liangliang Cao, Wenbin Du, Hao Xing, Yu Qiao
http://arxiv.org/abs/1907.11384v1
• [cs.CV]Report on UG^2+ Challenge Track 1: Assessing Algorithms to Improve Video Object Detection and Classification from Unconstrained Mobility Platforms
Sreya Banerjee, Rosaura G. VidalMata, Zhangyang Wang, Walter J. Scheirer
http://arxiv.org/abs/1907.11529v1
• [cs.CV]Semantic Deep Intermodal Feature Transfer: Transferring Feature Descriptors Between Imaging Modalities
Sebastian P. Kleinschmidt, Bernardo Wagner
http://arxiv.org/abs/1907.11436v1
• [cs.CV]Single Level Feature-to-Feature Forecasting with Deformable Convolutions
Josip Šarić, Marin Oršić, Tonći Antunović, Sacha Vražić, Siniša Šegvić
http://arxiv.org/abs/1907.11475v1
• [cs.CV]UGAN: Untraceable GAN for Multi-Domain Face Translation
Defa Zhu, Si Liu, Wentao Jiang, Chen Gao, Tianyi Wu, Guodong Guo
http://arxiv.org/abs/1907.11418v1
• [cs.CV]Universal Pooling — A New Pooling Method for Convolutional Neural Networks
Junhyuk Hyun, Hongje Seong, Euntai Kim
http://arxiv.org/abs/1907.11440v1
• [cs.CV]Unsupervised Learning Framework of Interest Point Via Properties Optimization
Pei Yan, Yihua Tan, Yuan Xiao, Yuan Tai, Cai Wen
http://arxiv.org/abs/1907.11375v1
• [cs.CV]Unsupervised Learning for Optical Flow Estimation Using Pyramid Convolution LSTM
Shuosen Guan, Haoxin Li, Wei-Shi Zheng
http://arxiv.org/abs/1907.11628v1
• [cs.CV]Using 3D Convolutional Neural Networks to Learn Spatiotemporal Features for Automatic Surgical Gesture Recognition in Video
Isabel Funke, Sebastian Bodenstedt, Florian Oehme, Felix von Bechtolsheim, Jürgen Weitz, Stefanie Speidel
http://arxiv.org/abs/1907.11454v1
• [cs.CY]Evaluating the Impact of Using GRASP Framework on Clinicians and Healthcare Professionals Decisions in Selecting Clinical Predictive Tools
Mohamed Khalifa, Farah Magrabi, Blanca Gallego
http://arxiv.org/abs/1907.11523v1
• [cs.CY]Reducing malicious use of synthetic media research: Considerations and potential release practices for machine learning
Aviv Ovadya, Jess Whittlestone
http://arxiv.org/abs/1907.11274v1
• [cs.CY]Validating and Updating GRASP: A New Evidence-Based Framework for Grading and Assessment of Clinical Predictive Tools
Mohamed Khalifa, Farah Magrabi, Blanca Gallego
http://arxiv.org/abs/1907.11524v1
• [cs.DC]Edge User Allocation with Dynamic Quality of Service
Phu Lai, Qiang He, Guangming Cui, Xiaoyu Xia, Mohamed Abdelrazek, Feifei Chen, John Hosking, John Grundy, Yun Yang
http://arxiv.org/abs/1907.11580v1
• [cs.DC]Fog Computing Applications: Taxonomy and Requirements
Arif Ahmed, HamidReza Arkian, Davaadorj Battulga, Ali J. Fahs, Mozhdeh Farhadi, Dimitrios Giouroukis, Adrien Gougeon, Felipe Oliveira Gutierrez, Guillaume Pierre, Paulo R. Souza Jr, Mulugeta Ayalew Tamiru, Li Wu
http://arxiv.org/abs/1907.11621v1
• [cs.DC]Massively Scaling Seismic Processing on Sunway TaihuLight Supercomputer
Yongmin Hu, Hailong Yang, Zhongzhi Luan, Depei Qian
http://arxiv.org/abs/1907.11678v1
• [cs.DC]ServerMix: Tradeoffs and Challenges of Serverless Data Analytics
Pedro García-López, Marc Sánchez-Artigas, Simon Shillaker, Peter Pietzuch, David Breitgand, Gil Vernik, Pierre Sutra, Tristan Tarrant, Ana Juan Ferrer
http://arxiv.org/abs/1907.11465v1
• [cs.DS]Exhaustive Exact String Matching: The Analysis of the Full Human Genome
Konstantinos F. Xylogiannopoulos
http://arxiv.org/abs/1907.11232v1
• [cs.HC]Personality is Revealed During Weekends: Towards Data Minimisation for Smartphone Based Personality Classification
Mohammed Khwaja, Aleksandar Matic
http://arxiv.org/abs/1907.11498v1
• [cs.HC]Vocal Interactivity in Crowds, Flocks and Swarms: Implications for Voice User Interfaces
Roger K. Moore
http://arxiv.org/abs/1907.11656v1
• [cs.IT]Achievable Rate Region for Iterative Multi-User Detection via Low-cost Gaussian Approximation
Xiaojie Wang, Chulong Liang, Li Ping, Stephan ten Brink
http://arxiv.org/abs/1907.11518v1
• [cs.IT]Neural Dynamic Successive Cancellation Flip Decoding of Polar Codes
Nghia Doan, Seyyed Ali Hashemi, Furkan Ercan, Thibaud Tonnellier, Warren Gross
http://arxiv.org/abs/1907.11563v1
• [cs.IT]Power Error Locating Pairs
Alain Couvreur, Isabella Panaccione
http://arxiv.org/abs/1907.11658v1
• [cs.LG]A Frobenius norm regularization method for convolutional kernels to avoid unstable gradient problem
Pei-Chang Guo
http://arxiv.org/abs/1907.11235v1
• [cs.LG]An Information-theoretic On-line Learning Principle for Specialization in Hierarchical Decision-Making Systems
Heinke Hihn, Sebastian Gottwald, Daniel A. Braun
http://arxiv.org/abs/1907.11452v1
• [cs.LG]Bayesian Volumetric Autoregressive generative models for better semisupervised learning
Guilherme Pombo, Robert Gray, Tom Varsavsky, John Ashburner, Parashkev Nachev
http://arxiv.org/abs/1907.11559v1
• [cs.LG]Compressing deep quaternion neural networks with targeted regularization
Riccardo Vecchi, Simone Scardapane, Danilo Comminiello, Aurelio Uncini
http://arxiv.org/abs/1907.11546v1
• [cs.LG]DEAM: Accumulated Momentum with Discriminative Weight for Stochastic Optimization
Jiyang Bai, Jiawei Zhang
http://arxiv.org/abs/1907.11307v1
• [cs.LG]Lexicographic Multiarmed Bandit
Alihan Hüyük, Cem Tekin
http://arxiv.org/abs/1907.11605v1
• [cs.LG]Making Neural Networks FAIR
Anna Nguyen, Tobias Weller, York Sure-Vetter
http://arxiv.org/abs/1907.11569v1
• [cs.LG]Multi-Stage Prediction Networks for Data Harmonization
Stefano B. Blumberg, Marco Palombo, Can Son Khoo, Chantal M. W. Tax, Ryutaro Tanno, Daniel C. Alexander
http://arxiv.org/abs/1907.11629v1
• [cs.LG]Scalable Semi-Supervised SVM via Triply Stochastic Gradients
Xiang Geng, Bin Gu, Xiang Li, Wanli Shi, Guansheng Zheng, Heng Huang
http://arxiv.org/abs/1907.11584v1
• [cs.LG]Taming Momentum in a Distributed Asynchronous Environment
Ido Hakimi, Saar Barkai, Moshe Gabel, Assaf Schuster
http://arxiv.org/abs/1907.11612v1
• [cs.LG]Towards meta-learning for multi-target regression problems
Gabriel Jonas Aguiar, Everton José Santana, Saulo Martiello Mastelini, Rafael Gomes Mantovani, Sylvio Barbon Jr
http://arxiv.org/abs/1907.11277v1
• [cs.LG]Training products of expert capsules with mixing by dynamic routing
Michael Hauser
http://arxiv.org/abs/1907.11643v1
• [cs.LG]Two-hidden-layer Feedforward Neural Networks are Universal Approximators: A Constructive Approach
Rocio Gonzalez-Diaz, Miguel A. Gutiérrez-Naranjo, Eduardo Paluzo-Hidalgo
http://arxiv.org/abs/1907.11457v1
• [cs.LO]Revisiting Explicit Negation in Answer Set Programming
Felicidad Aguado, Pedro Cabalar, Jorge Fandinno, David Pearce, Gilberto Perez, Concepcion Vidal
http://arxiv.org/abs/1907.11467v1
• [cs.MA]Action Semantics Network: Considering the Effects of Actions in Multiagent Systems
Weixun Wang, Tianpei Yang Yong Liu, Jianye Hao, Xiaotian Hao, Yujing Hu, Yingfeng Chen, Changjie Fan, Yang Gao
http://arxiv.org/abs/1907.11461v1
• [cs.NE]Autoencoding with a Learning Classifier System: Initial Results
Larry Bull
http://arxiv.org/abs/1907.11554v1
• [cs.NE]Training capsules as a routing-weighted product of expert neurons
Michael Hauser
http://arxiv.org/abs/1907.11639v1
• [cs.NI]Data Aggregation Techniques for Internet of Things
Sunny Sanyal
http://arxiv.org/abs/1907.11367v1
• [cs.NI]Delay Analysis in Full-Duplex Heterogeneous Cellular Networks
Leila Marandi, Mansour Naslcheraghi, Seyed Ali Ghorashi, Mohammad Shikh-Bahaei
http://arxiv.org/abs/1907.11264v1
• [cs.PF]Anonymity Mixes as (Partial) Assembly Queues: Modeling and Analysis
Mehmet Fatih Aktas, Emina Soljanin
http://arxiv.org/abs/1907.11603v1
• [cs.RO]Feedback Control for Autonomous Riding of Hovershoes by a Cassie Bipedal Robot
Shuxiao Chen, Jonathan Rogers, Bike Zhang, Koushil Sreenath
http://arxiv.org/abs/1907.11353v1
• [cs.RO]Learning to Solve a Rubik’s Cube with a Dexterous Hand
Tingguang Li, Weitao Xi, Meng Fang, Jia Xu, Max Qing-Hu Meng
http://arxiv.org/abs/1907.11388v1
• [cs.RO]Precise localization relative to 3D Automated Driving map using the Decentralized Kalman filter with Feedback
Koba Natroshvili, Kai Storr, Fabian Oboril, Kay-Ulrich Scholl
http://arxiv.org/abs/1907.11237v1
• [cs.RO]Vehicular Multi-object Tracking with Persistent Detector Failures
Michael Motro, Joydeep Ghosh
http://arxiv.org/abs/1907.11306v1
• [cs.SD]Interactive Lungs Auscultation with Reinforcement Learning Agent
Tomasz Grzywalski, Riccardo Belluzzo, Szymon Drgas, Agnieszka Cwalinska, Honorata Hafke-Dys
http://arxiv.org/abs/1907.11238v1
• [cs.SE]An Empirical Analysis of the Python Package Index (PyPI)
Ethan Bommarito, Michael Bommarito
http://arxiv.org/abs/1907.11073v2
• [cs.SI]Challenges in Community Discovery on Temporal Networks
Remy Cazabet, Giulio Rossetti
http://arxiv.org/abs/1907.11435v1
• [cs.SI]Networks of Power: Analyzing World Leaders Interactions on Social Media
Evgeniia Iakhnis, Adam Badawy
http://arxiv.org/abs/1907.11283v1
• [eess.AS]Correlation Distance Skip Connection Denoising Autoencoder (CDSK-DAE) for Speech Feature Enhancement
Alzahra Badi, Sangwook Park, David K. Han, Hanseok Ko
http://arxiv.org/abs/1907.11361v1
• [eess.IV]Adaptive Compressed Sensing MRI with Unsupervised Learning
Cagla D. Bahadir, Adrian V. Dalca, Mert R. Sabuncu
http://arxiv.org/abs/1907.11374v1
• [eess.IV]Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images
Fei Yu, Jie Zhao, Yanjun Gong, Zhi Wang, Yuxi Li, Fan Yang, Bin Dong, Quanzheng Li, Li Zhang
http://arxiv.org/abs/1907.11483v1
• [eess.IV]As easy as 1, 2… 4? Uncertainty in counting tasks for medical imaging
Zach Eaton-Rosen, Thomas Varsavsky, Sebastien Ourselin, M. Jorge Cardoso
http://arxiv.org/abs/1907.11555v1
• [eess.IV]Automatic Calcium Scoring in Cardiac and Chest CT Using DenseRAUnet
Jiechao Ma, Rongguo Zhang
http://arxiv.org/abs/1907.11392v1
• [eess.IV]Image Enhancement by Recurrently-trained Super-resolution Network
Saem Park, Nojun Kwak
http://arxiv.org/abs/1907.11341v1
• [eess.IV]Self-Adaptive 2D-3D Ensemble of Fully Convolutional Networks for Medical Image Segmentation
Maria G. Baldeon Calisto, Susana K. Lai-Yuen
http://arxiv.org/abs/1907.11587v1
• [eess.SP]Detection of Malfunctioning Smart Electricity Meter
Ming Liu, Dongpeng Liu, Guangyu Sun, Yi Zhao, Duolin Wang, Fangxing Liu, Xiang Fang, Qing He, Dong Xu
http://arxiv.org/abs/1907.11377v1
• [eess.SP]Online Subspace Tracking for Damage Propagation Modeling and Predictive Analytics: Big Data Perspective
Farhan Khan
http://arxiv.org/abs/1907.11477v1
• [eess.SP]Towards the Enhancement of Body Standing Balance Recovery by Means of a Wireless Audio-Biofeedback System
Giovanni Costantini, Daniele Casali, Fabio Paolizzo, Marco Alessandrini, Alessandro Micarelli, Andrea Viziano, Giovanni Saggio
http://arxiv.org/abs/1907.11542v1
• [math.NA]A bisector line field approach to interpolation of orientation fields
Nicolas Boizot, Ludovic Sacchelli
http://arxiv.org/abs/1907.11449v1
• [math.OC]Incremental Methods for Weakly Convex Optimization
Xiao Li, Zhihui Zhu, Anthony Man-Cho So, Jason D Lee
http://arxiv.org/abs/1907.11687v1
• [math.OC]Using positive spanning sets to achieve stationarity with the Boosted DC Algorithm
Francisco J. Aragón Artacho, Rubén Campoy, Quoc Tran-Dinh, Phan T. Vuong
http://arxiv.org/abs/1907.11471v1
• [math.PR]Improved Bounds for Discretization of Langevin Diffusions: Near-Optimal Rates without Convexity
Wenlong Mou, Nicolas Flammarion, Martin J. Wainwright, Peter L. Bartlett
http://arxiv.org/abs/1907.11331v1
• [math.RA]Rational Motions with Generic Trajectories of Low Degree
Johannes Siegele, Daniel F. Scharler, Hans-Peter Schröcker
http://arxiv.org/abs/1907.11525v1
• [math.ST]Adaptive regression with Brownian path covariate
Karine Bertin, Nicolas Klutchnikoff
http://arxiv.org/abs/1907.11284v1
• [math.ST]An asymptotically optimal transform of Pearson’s correlation statistic
Iosif Pinelis
http://arxiv.org/abs/1907.11579v1
• [math.ST]Double Bayesian Smoothing as Message Passing
Pasquale Di Viesti, Giorgio M. Vitetta, Emilio Sirignano
http://arxiv.org/abs/1907.11547v1
• [math.ST]Notes on Computational Hardness of Hypothesis Testing: Predictions using the Low-Degree Likelihood Ratio
Dmitriy Kunisky, Alexander S. Wein, Afonso S. Bandeira
http://arxiv.org/abs/1907.11636v1
• [math.ST]Phase Transition Unbiased Estimation in High Dimensional Settings
Stéphane Guerrier, Mucyo Karemera, Samuel Orso, Maria-Pia Victoria-Feser
http://arxiv.org/abs/1907.11541v1
• [math.ST]Robust multivariate mean estimation: the optimality of trimmed mean
Gabor Lugosi, Shahar Mendelson
http://arxiv.org/abs/1907.11391v1
• [math.ST]Subexponential-Time Algorithms for Sparse PCA
Yunzi Ding, Dmitriy Kunisky, Alexander S. Wein, Afonso S. Bandeira
http://arxiv.org/abs/1907.11635v1
• [physics.ao-ph]Analog forecasting of extreme-causing weather patterns using deep learning
Ashesh Chattopadhyay, Ebrahim Nabizadeh, Pedram Hassanzadeh
http://arxiv.org/abs/1907.11617v1
• [stat.AP]Adjusting for Spatial Effects in Genomic Prediction
Xiaojun Mao, Somak Dutta, Raymond K. W. Wong, Dan Nettleton
http://arxiv.org/abs/1907.11581v1
• [stat.AP]Comparative Analysis of User Behavior of Dock-Based vs. Dockless Bikeshare and Scootershare in Washington, D.C
Kiana Roshan Zamir, Iryna Bondarenko, Arefeh Nasri, Stefanie Brodie, Kimberly Lucas
http://arxiv.org/abs/1907.11526v1
• [stat.AP]Decision Tree Learning for Uncertain Clinical Measurements
Cecília Nunes, Hélène Langet, Mathieu De Craene, Oscar Camara, Bart Bijnens, Anders Jonsson
http://arxiv.org/abs/1907.11325v1
• [stat.AP]Exploiting new forms of data to study the private rented sector: strengths and limitations of a database of rental listings
Mark Livingston, Francesca Pannullo, Adrian Bowman, Marian Scott, Nick Bailey
http://arxiv.org/abs/1907.11447v1
• [stat.CO]Analyzing MCMC Output
Dootika Vats, Nathan Robertson, James M Flegal, Galin L Jones
http://arxiv.org/abs/1907.11680v1
• [stat.ME]A memory-free spatial additive mixed modeling for big spatial data
Daisuke Murakami, Daniel A. Griffith
http://arxiv.org/abs/1907.11369v1
• [stat.ME]Measurement error and precision medicine: error-prone tailoring covariates in dynamic treatment regimes
Dylan Spicker, Michael Wallace
http://arxiv.org/abs/1907.11659v1
• [stat.ME]On the variability of regression shrinkage methods for clinical prediction models: simulation study on predictive performance
Ben Van Calster, Maarten van Smeden, Ewout W. Steyerberg
http://arxiv.org/abs/1907.11493v1
• [stat.ME]Some examples of application for predicting of compressive sensing method
Nicholas Rowe
http://arxiv.org/abs/1907.11508v1
• [stat.ML]A close-up comparison of the misclassification error distance and the adjusted Rand index for external clustering evaluation
José E. Chacón
http://arxiv.org/abs/1907.11505v1
• [stat.ML]Doubly-Robust Lasso Bandit
Gi-Soo Kim, Myunghee Cho Paik
http://arxiv.org/abs/1907.11362v1
• [stat.ML]Graph Informer Networks for Molecules
Jaak Simm, Adam Arany, Edward De Brouwer, Yves Moreau
http://arxiv.org/abs/1907.11318v1
• [stat.ML]Sequential Learning of Active Subspaces
Nathan Wycoff, Mickael Binois, Stefan M. Wild
http://arxiv.org/abs/1907.11572v1
• [stat.ML]Towards Scalable Gaussian Process Modeling
Piyush Pandita, Jesper Kristensen, Liping Wang
http://arxiv.org/abs/1907.11313v1