cond-mat.mtrl-sci - 材料科学
cond-mat.soft - 软凝聚物质 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.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.LO - 计算逻辑 cs.NE - 神经与进化计算 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 econ.GN - 一般经济学 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.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.ao-ph - 大气和海洋物理 physics.ins-det - 仪器和探测器 q-bio.NC - 神经元与认知 q-bio.PE - 人口与发展 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
• [cond-mat.mtrl-sci]Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide
• [cond-mat.soft]Using Bayesian model selection to advise neutron reflectometry analysis from Langmuir-Blodgett monolayers
• [cs.AI]AnnaParser: Semantic Parsing for Tabular Data Analysis
• [cs.AI]Knowledge Map: Toward a New Approach Supporting the Knowledge Management in Distributed Data Mining
• [cs.AI]RTOP: A Conceptual and Computational Framework for General Intelligence
• [cs.CL]A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection
• [cs.CL]A practical two-stage training strategy for multi-stream end-to-end speech recognition
• [cs.CL]Capturing Greater Context for Question Generation
• [cs.CL]Controlling the Output Length of Neural Machine Translation
• [cs.CL]Correction of Automatic Speech Recognition with Transformer Sequence-to-sequence Model
• [cs.CL]Deja-vu: Double Feature Presentation in Deep Transformer Networks
• [cs.CL]Efficient Dynamic WFST Decoding for Personalized Language Models
• [cs.CL]IPOD: Corpus of 190,000 Industrial Occupations
• [cs.CL]Incremental Online Spoken Language Understanding
• [cs.CL]Instance-Based Model Adaptation For Direct Speech Translation
• [cs.CL]Kernel Graph Attention Network for Fact Verification
• [cs.CL]Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis
• [cs.CL]Opinion aspect extraction in Dutch childrens diary entries
• [cs.CL]Robust Neural Machine Translation for Clean and Noisy Speech Transcripts
• [cs.CL]Speaker Adaptive Training using Model Agnostic Meta-Learning
• [cs.CL]Speech-XLNet: Unsupervised Acoustic Model Pretraining For Self-Attention Networks
• [cs.CR]ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors
• [cs.CR]Deep learning guided Android malware and anomaly detection
• [cs.CV]Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction
• [cs.CV]Breast Anatomy Enriched Tumor Saliency Estimation
• [cs.CV]Deep Classification Network for Monocular Depth Estimation
• [cs.CV]Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation
• [cs.CV]Facial Expression Restoration Based on Improved Graph Convolutional Networks
• [cs.CV]Fast and Automatic Periacetabular Osteotomy Fragment Pose Estimation Using Intraoperatively Implanted Fiducials and Single-View Fluoroscopy
• [cs.CV]Identification of primary angle-closure on AS-OCT images with Convolutional Neural Networks
• [cs.CV]Iterative Matching Point
• [cs.CV]Occlusions for Effective Data Augmentation in Image Classification
• [cs.CV]Random 2.5D U-net for Fully 3D Segmentation
• [cs.CV]Region Based Adversarial Synthesis of Facial Action Units
• [cs.CV]Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detection
• [cs.CV]SalGaze: Personalizing Gaze Estimation Using Visual Saliency
• [cs.CV]Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT
• [cs.CV]Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis
• [cs.CV]Using Segmentation Masks in the ICCV 2019 Learning to Drive Challenge
• [cs.CV]Winning the ICCV 2019 Learning to Drive Challenge
• [cs.CY]Achieving Ethical Algorithmic Behaviour in the Internet-of-Things: a Review
• [cs.CY]An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision
• [cs.CY]Robot-Friendly Cities
• [cs.CY]Towards Robotic Things in Society
• [cs.DC]An Optimized, Parallel Computation of the Ghost Layer for Adaptive Hybrid Forest Meshes
• [cs.DC]Blockchain Methods for Trusted Avionics Systems
• [cs.DC]Divide and Scale: Formalization of Distributed Ledger Sharding Protocols
• [cs.DC]Train Where the Data is: A Case for Bandwidth Efficient Coded Training
• [cs.HC]On Automating Conversations
• [cs.HC]The Task Analysis Cell Assembly Perspective
• [cs.IR]BanditRank: Learning to Rank Using Contextual Bandits
• [cs.IR]Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval
• [cs.IR]Lucene for Approximate Nearest-Neighbors Search on Arbitrary Dense Vectors
• [cs.IR]Self-Attentive Document Interaction Networks for Permutation Equivariant Ranking
• [cs.IT]A New Method to Construct Gloay Complementary Set by Paraunitary Matrices and Hadamard Matrices
• [cs.IT]CNN-based Analog CSI Feedback in FDD MIMO-OFDM Systems
• [cs.IT]Circularly Pulse Shaped Orthogonal Time Frequency Space Modulation
• [cs.IT]Coded Caching with Linear Subpacketization is Possible in Multi-Antenna Communications
• [cs.IT]Distribution of the Sum of Fisher-Snedecor $\mathcal{F}$ Random Variables and Its Applications
• [cs.IT]Management and Orchestration of Virtual Network Functions via Deep Reinforcement Learning
• [cs.IT]New Construction of Complementary Sequence (or Array) Sets and Complete Complementary Codes (I)
• [cs.IT]New Construction of Complementary Sequence (or Array) Sets and Complete Complementary Codes (II)
• [cs.IT]On the Bee-Identification Error Exponent with Absentee Bees
• [cs.IT]Trainable Projected Gradient Detector for Sparsely Spread Code Division Multiple Access
• [cs.LG]A Unifying Framework of Bilinear LSTMs
• [cs.LG]A Useful Taxonomy for Adversarial Robustness of Neural Networks
• [cs.LG]Better Approximate Inference for Partial Likelihood Models with a Latent Structure
• [cs.LG]Bottom-Up Meta-Policy Search
• [cs.LG]Complex Transformer: A Framework for Modeling Complex-Valued Sequence
• [cs.LG]Contrastive Representation Distillation
• [cs.LG]Deep Learning at the Edge
• [cs.LG]Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output
• [cs.LG]EdgeAI: A Vision for Deep Learning in IoT Era
• [cs.LG]Efficient Decoupled Neural Architecture Search by Structure and Operation Sampling
• [cs.LG]Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
• [cs.LG]Feature Selection and Extraction for Graph Neural Networks
• [cs.LG]Federated Evaluation of On-device Personalization
• [cs.LG]Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating
• [cs.LG]Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment
• [cs.LG]Interpreting Basis Path Set in Neural Networks
• [cs.LG]Learning Partial Differential Equations from Data Using Neural Networks
• [cs.LG]MLAT: Metric Learning for kNN in Streaming Time Series
• [cs.LG]Online Meta-Learning on Non-convex Setting
• [cs.LG]Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation
• [cs.LG]Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning
• [cs.LG]Recurrent Attention Walk for Semi-supervised Classification
• [cs.LG]Restless Hidden Markov Bandits with Linear Rewards
• [cs.LG]Robust Domain Randomization for Reinforcement Learning
• [cs.LG]Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles
• [cs.LG]Self-Attention for Raw Optical Satellite Time Series Classification
• [cs.LG]Stabilising priors for robust Bayesian deep learning
• [cs.LG]State2vec: Off-Policy Successor Features Approximators
• [cs.LG]Strategic Adaptation to Classifiers: A Causal Perspective
• [cs.LG]USTAR: Online Multimodal Embedding for Modeling User-Guided Spatiotemporal Activity
• [cs.LG]Weighted Distributed Differential Privacy ERM: Convex and Non-convex
• [cs.LO]Knowledge of Uncertain Worlds: Programming with Logical Constraints
• [cs.NE]A Novel Generalized Artificial Neural Network for Mining Two-Class Datasets
• [cs.NE]Autoencoding with XCSF
• [cs.NE]Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis
• [cs.RO]An Analytical Lidar Sensor Model Based on Ray Path Information
• [cs.RO]Closed-Form Full Map Posteriors for Robot Localization with Lidar Sensors
• [cs.RO]Impact-Aware Online Motion Planning for Fully-Actuated Bipedal Robot Walking
• [cs.RO]Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control
• [cs.RO]Learning Humanoid Robot Running Skills through Proximal Policy Optimization
• [cs.RO]Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans
• [cs.RO]Teach Biped Robots to Walk via Gait Principles and Reinforcement Learning with Adversarial Critics
• [cs.RO]gradSLAM: Dense SLAM meets Automatic Differentiation
• [cs.SD]Filterbank design for end-to-end speech separation
• [cs.SD]Learning the helix topology of musical pitch
• [cs.SE]Kuksa: A Cloud-Native Architecture for Enabling Continuous Delivery in the Automotive Domain
• [cs.SI]Network2Vec Learning Node Representation Based on Space Mapping in Networks
• [econ.GN]Beating the House: Identifying Inefficiencies in Sports Betting Markets
• [eess.AS]A Transformer with Interleaved Self-attention and Convolution for Hybrid Acoustic Models
• [eess.IV]A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images
• [eess.IV]Deep Clustering of Compressed Variational Embeddings
• [eess.IV]Deep Learning Supersampled Scanning Transmission Electron Microscopy
• [eess.IV]Deep generative model-driven multimodal prostate segmentation in radiotherapy
• [eess.IV]Divide-and-Conquer Adversarial Learning for High-Resolution Image and Video Enhancement
• [eess.IV]INTEL-TAU: A Color Constancy Dataset
• [eess.IV]Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
• [eess.IV]Photoshopping Colonoscopy Video Frames
• [eess.IV]Semantic Segmentation of Skin Lesions using a Small Data Set
• [eess.IV]Stain Style Transfer using Transitive Adversarial Networks
• [eess.IV]Towards an Intelligent Microscope: adaptively learned illumination for optimal sample classification
• [eess.SP]New RLL Code with Improved Error Performance for Visible Light Communication
• [eess.SY]Decentralized Runtime Synthesis of Shields for Multi-Agent Systems
• [eess.SY]Prioritized Inverse Kinematics: Desired Task Trajectories in Nonsingular Task Spaces
• [math.NA]Kernel Methods for Bayesian Elliptic Inverse Problems on Manifolds
• [math.OC]Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
• [math.ST]How well can we learn large factor models without assuming strong factors?
• [math.ST]Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression
• [math.ST]Multiple outlier detection tests for parametric models
• [math.ST]Objective Bayesian Analysis of a Cokriging Model for Hierarchical Multifidelity Codes
• [math.ST]On the behavior of the DFA and DCCA in trend-stationary processes
• [physics.ao-ph]Tropical Cyclone Track Forecasting using Fused Deep Learning from Aligned Reanalysis Data
• [physics.ins-det]Towards Fast Displaced Vertex Finding
• [q-bio.NC]Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks
• [q-bio.PE]Inference with selection, varying population size and evolving population structure: Application of ABC to a forward-backward coalescent process with interactions
• [stat.AP]An inverse problem approach to the probabilistic reconstruction of particle tracks on a censored and closed surface
• [stat.AP]Double-Counting Problem of the Bonus-Malus System
• [stat.AP]Statistical Modeling for Spatio-Temporal Data from Physical Convection-Diffusion Processes
• [stat.CO]Event-scheduling algorithms with Kalikow decomposition for simulating potentially infinite neuronal networks
• [stat.ME]A Stochastic Block Model for Multilevel Networks: Application to the Sociology of Organisations
• [stat.ME]Bayesian nonparametric temporal dynamic clustering via autoregressive Dirichlet priors
• [stat.ME]Doubly robust treatment effect estimation with missing attributes
• [stat.ME]Flexible Bayesian modelling in dichotomous item response theory using mixtures of skewed item curves
• [stat.ME]Nested Conformal Prediction and the Generalized Jackknife+
• [stat.ML]Deterministic tensor completion with hypergraph expanders
• [stat.ML]Global Capacity Measures for Deep ReLU Networks via Path Sampling
• [stat.ML]Leveraging directed causal discovery to detect latent common causes
• [stat.ML]Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules
• [stat.ML]Neural Execution of Graph Algorithms
• [stat.ML]Sparse Orthogonal Variational Inference for Gaussian Processes
• [stat.ML]Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales
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• [cond-mat.mtrl-sci]Machine Learning Inter-Atomic Potentials Generation Driven by Active Learning: A Case Study for Amorphous and Liquid Hafnium dioxide
Ganesh Sivaraman, Anand Narayanan Krishnamoorthy, Matthias Baur, Christian Holm, Marius Stan, Gabor Csányi, Chris Benmore, Álvaro Vázquez-Mayagoitia
http://arxiv.org/abs/1910.10254v1
• [cond-mat.soft]Using Bayesian model selection to advise neutron reflectometry analysis from Langmuir-Blodgett monolayers
Andrew R. McCluskey, Thomas Arnold, Joshaniel F. K. Cooper, Tim Snow
http://arxiv.org/abs/1910.10581v1
• [cs.AI]AnnaParser: Semantic Parsing for Tabular Data Analysis
Yan Gao, Jian-Guang Lou, Dongmei Zhang
http://arxiv.org/abs/1910.10363v1
• [cs.AI]Knowledge Map: Toward a New Approach Supporting the Knowledge Management in Distributed Data Mining
Nhien-An Le-Khac, Lamine M. Aouad, M-Tahar Kechadi
http://arxiv.org/abs/1910.10547v1
• [cs.AI]RTOP: A Conceptual and Computational Framework for General Intelligence
Shilpesh Garg
http://arxiv.org/abs/1910.10393v1
• [cs.CL]A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection
Kurt Espinosa, Makoto Miwa, Sophia Ananiadou
http://arxiv.org/abs/1910.10281v1
• [cs.CL]A practical two-stage training strategy for multi-stream end-to-end speech recognition
Ruizhi Li, Gregory Sell, Xiaofei Wang, Shinji Watanabe, Hynek Hermansky
http://arxiv.org/abs/1910.10671v1
• [cs.CL]Capturing Greater Context for Question Generation
Luu Anh Tuan, Darsh J Shah, Regina Barzilay
http://arxiv.org/abs/1910.10274v1
• [cs.CL]Controlling the Output Length of Neural Machine Translation
Surafel Melaku Lakew, Mattia Di Gangi, Marcello Federico
http://arxiv.org/abs/1910.10408v1
• [cs.CL]Correction of Automatic Speech Recognition with Transformer Sequence-to-sequence Model
Oleksii Hrinchuk, Mariya Popova, Boris Ginsburg
http://arxiv.org/abs/1910.10697v1
• [cs.CL]Deja-vu: Double Feature Presentation in Deep Transformer Networks
Andros Tjandra, Chunxi Liu, Frank Zhang, Xiaohui Zhang, Yongqiang Wang, Gabriel Synnaeve, Satoshi Nakamura, Geoffrey Zweig
http://arxiv.org/abs/1910.10324v1
• [cs.CL]Efficient Dynamic WFST Decoding for Personalized Language Models
Jun Liu, Jiedan Zhu, Vishal Kathuria, Fuchun Peng
http://arxiv.org/abs/1910.10670v1
• [cs.CL]IPOD: Corpus of 190,000 Industrial Occupations
Junhua Liu, Chu Guo, Yung Chuen Ng, Kristin L. Wood, Kwan Hui Lim
http://arxiv.org/abs/1910.10495v1
• [cs.CL]Incremental Online Spoken Language Understanding
Prashanth Gurunath Shivakumar, Naveen Kumar, Panayiotis Georgiou, Shrikanth Narayanan
http://arxiv.org/abs/1910.10287v1
• [cs.CL]Instance-Based Model Adaptation For Direct Speech Translation
Mattia Antonino Di Gangi, Viet-Nhat Nguyen, Matteo Negri, Marco Turchi
http://arxiv.org/abs/1910.10663v1
• [cs.CL]Kernel Graph Attention Network for Fact Verification
Zhenghao Liu, Chenyan Xiong, Maosong Sun
http://arxiv.org/abs/1910.09796v2
• [cs.CL]Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis
Eric Battenberg, RJ Skerry-Ryan, Soroosh Mariooryad, Daisy Stanton, David Kao, Matt Shannon, Tom Bagby
http://arxiv.org/abs/1910.10288v1
• [cs.CL]Opinion aspect extraction in Dutch childrens diary entries
Hella Haanstra, Maaike H. T. de Boer
http://arxiv.org/abs/1910.10502v1
• [cs.CL]Robust Neural Machine Translation for Clean and Noisy Speech Transcripts
Mattia Antonino Di Gangi, Robert Enyedi, Alessandra Brusadin, Marcello Federico
http://arxiv.org/abs/1910.10238v1
• [cs.CL]Speaker Adaptive Training using Model Agnostic Meta-Learning
Ondřej Klejch, Joachim Fainberg, Peter Bell, Steve Renals
http://arxiv.org/abs/1910.10605v1
• [cs.CL]Speech-XLNet: Unsupervised Acoustic Model Pretraining For Self-Attention Networks
Xingchen Song, Guangsen Wang, Zhiyong Wu, Yiheng Huang, Dan Su, Dong Yu, Helen Meng
http://arxiv.org/abs/1910.10387v1
• [cs.CR]ASNM Datasets: A Collection of Network Traffic Features for Testing of Adversarial Classifiers and Network Intrusion Detectors
Ivan Homoliak, Petr Hanacek
http://arxiv.org/abs/1910.10528v1
• [cs.CR]Deep learning guided Android malware and anomaly detection
Nikola Milosevic, Junfan Huang
http://arxiv.org/abs/1910.10660v1
• [cs.CV]Accurate 6D Object Pose Estimation by Pose Conditioned Mesh Reconstruction
Pedro Castro, Anil Armagan, Tae-Kyun Kim
http://arxiv.org/abs/1910.10653v1
• [cs.CV]Breast Anatomy Enriched Tumor Saliency Estimation
Fei Xu, Yingtao Zhang, Min Xian, H. D. Cheng, Boyu Zhang, Jianrui Ding, Chunping Ning, Ying Wang
http://arxiv.org/abs/1910.10652v1
• [cs.CV]Deep Classification Network for Monocular Depth Estimation
Azeez Oluwafemi, Yang Zou, B. V. K. Vijaya Kumar
http://arxiv.org/abs/1910.10369v1
• [cs.CV]Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation
Fabio Pizzati, Raoul de Charette, Michela Zaccaria, Pietro Cerri
http://arxiv.org/abs/1910.10563v1
• [cs.CV]Facial Expression Restoration Based on Improved Graph Convolutional Networks
Zhilei Liu, Le Li, Yunpeng Wu, Cuicui Zhang
http://arxiv.org/abs/1910.10344v1
• [cs.CV]Fast and Automatic Periacetabular Osteotomy Fragment Pose Estimation Using Intraoperatively Implanted Fiducials and Single-View Fluoroscopy
Robert Grupp, Ryan Murphy, Rachel Hegeman, Clayton Alexander, Mathias Unberath, Yoshito Otake, Benjamin McArthur, Mehran Armand, Russell Taylor
http://arxiv.org/abs/1910.10187v1
• [cs.CV]Identification of primary angle-closure on AS-OCT images with Convolutional Neural Networks
Chenglang Yuan, Cheng Bian, Hongjian Kang, Shu Liang, Kai Ma, Yefeng Zheng
http://arxiv.org/abs/1910.10414v1
• [cs.CV]Iterative Matching Point
Jiahao Li, Changhao Zhang
http://arxiv.org/abs/1910.10328v1
• [cs.CV]Occlusions for Effective Data Augmentation in Image Classification
Ruth Fong, Andrea Vedaldi
http://arxiv.org/abs/1910.10651v1
• [cs.CV]Random 2.5D U-net for Fully 3D Segmentation
Christoph Angermann, Markus Haltmeier
http://arxiv.org/abs/1910.10398v1
• [cs.CV]Region Based Adversarial Synthesis of Facial Action Units
Zhilei Liu, Diyi Liu, Yunpeng Wu
http://arxiv.org/abs/1910.10323v1
• [cs.CV]Relation Modeling with Graph Convolutional Networks for Facial Action Unit Detection
Zhilei Liu, Jiahui Dong, Cuicui Zhang, Longbiao Wang, Jianwu Dang
http://arxiv.org/abs/1910.10334v1
• [cs.CV]SalGaze: Personalizing Gaze Estimation Using Visual Saliency
Zhuoqing Chang, Matias Di Martino, Qiang Qiu, Steven Espinosa, Guillermo Sapiro
http://arxiv.org/abs/1910.10603v1
• [cs.CV]Semi-supervised Multi-domain Multi-task Training for Metastatic Colon Lymph Node Diagnosis From Abdominal CT
Saskia Glaser, Gabriel Maicas, Sergei Bedrikovetski, Tarik Sammour, Gustavo Carneiro
http://arxiv.org/abs/1910.10371v1
• [cs.CV]Unsupervised Robust Disentangling of Latent Characteristics for Image Synthesis
Patrick Esser, Johannes Haux, Björn Ommer
http://arxiv.org/abs/1910.10223v1
• [cs.CV]Using Segmentation Masks in the ICCV 2019 Learning to Drive Challenge
Antonia Lovjer, Minsu Yeom, Benedikt D. Schifferer, Iddo Drori
http://arxiv.org/abs/1910.10317v1
• [cs.CV]Winning the ICCV 2019 Learning to Drive Challenge
Michael Diodato, Yu Li, Manik Goyal, Iddo Drori
http://arxiv.org/abs/1910.10318v1
• [cs.CY]Achieving Ethical Algorithmic Behaviour in the Internet-of-Things: a Review
Seng W. Loke
http://arxiv.org/abs/1910.10241v1
• [cs.CY]An Empirical Study on Learning Fairness Metrics for COMPAS Data with Human Supervision
Hanchen Wang, Nina Grgic-Hlaca, Preethi Lahoti, Krishna P. Gummadi, Adrian Weller
http://arxiv.org/abs/1910.10255v1
• [cs.CY]Robot-Friendly Cities
Seng W. Loke
http://arxiv.org/abs/1910.10258v1
• [cs.CY]Towards Robotic Things in Society
Seng W. Loke
http://arxiv.org/abs/1910.10253v1
• [cs.DC]An Optimized, Parallel Computation of the Ghost Layer for Adaptive Hybrid Forest Meshes
Johannes Holke, David Knapp, Carsten Burstedde
http://arxiv.org/abs/1910.10641v1
• [cs.DC]Blockchain Methods for Trusted Avionics Systems
Erik Blasch, Ronghua Xu, Yu Chen, Genshe Chen, Dan Shen
http://arxiv.org/abs/1910.10638v1
• [cs.DC]Divide and Scale: Formalization of Distributed Ledger Sharding Protocols
Georgia Avarikioti, Eleftherios Kokoris-Kogias, Roger Wattenhofer
http://arxiv.org/abs/1910.10434v1
• [cs.DC]Train Where the Data is: A Case for Bandwidth Efficient Coded Training
Zhifeng Lin, Krishna Giri Narra, Mingchao Yu, Salman Avestimehr, Murali Annavaram
http://arxiv.org/abs/1910.10283v1
• [cs.HC]On Automating Conversations
Ting-Hao ‘Kenneth’ Huang
http://arxiv.org/abs/1910.09621v2
• [cs.HC]The Task Analysis Cell Assembly Perspective
Dan Diaper, Chris Huyck
http://arxiv.org/abs/1910.10481v1
• [cs.IR]BanditRank: Learning to Rank Using Contextual Bandits
Phanideep Gampa, Sumio Fujita
http://arxiv.org/abs/1910.10410v1
• [cs.IR]Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval
Zhuyun Dai, Jamie Callan
http://arxiv.org/abs/1910.10687v1
• [cs.IR]Lucene for Approximate Nearest-Neighbors Search on Arbitrary Dense Vectors
Tommaso Teofili, Jimmy Lin
http://arxiv.org/abs/1910.10208v1
• [cs.IR]Self-Attentive Document Interaction Networks for Permutation Equivariant Ranking
Rama Kumar Pasumarthi, Xuanhui Wang, Michael Bendersky, Marc Najork
http://arxiv.org/abs/1910.09676v2
• [cs.IT]A New Method to Construct Gloay Complementary Set by Paraunitary Matrices and Hadamard Matrices
Zilong Wang, Gaofei Wu, Dongxu Ma
http://arxiv.org/abs/1910.10302v1
• [cs.IT]CNN-based Analog CSI Feedback in FDD MIMO-OFDM Systems
Mahdi Boloursaz Mashhadi, Qianqian Yang, Deniz Gunduz
http://arxiv.org/abs/1910.10428v1
• [cs.IT]Circularly Pulse Shaped Orthogonal Time Frequency Space Modulation
Shashank Tiwari, Suvra Sekhar Das
http://arxiv.org/abs/1910.10457v1
• [cs.IT]Coded Caching with Linear Subpacketization is Possible in Multi-Antenna Communications
MohammadJavad Salehi, Antti Tölli, Seyed Pooya Shariatpanahi
http://arxiv.org/abs/1910.10384v1
• [cs.IT]Distribution of the Sum of Fisher-Snedecor $\mathcal{F}$ Random Variables and Its Applications
Hongyang Du, Jiayi Zhang, Julian Cheng, Bo Ai
http://arxiv.org/abs/1910.10565v1
• [cs.IT]Management and Orchestration of Virtual Network Functions via Deep Reinforcement Learning
Joan S Pujol Roig, David M. Gutierrez-Estevez, Deniz Gündüz
http://arxiv.org/abs/1910.10695v1
• [cs.IT]New Construction of Complementary Sequence (or Array) Sets and Complete Complementary Codes (I)
Zilong Wang, Dongxu Ma, Guang Gong
http://arxiv.org/abs/1910.10304v1
• [cs.IT]New Construction of Complementary Sequence (or Array) Sets and Complete Complementary Codes (II)
Zilong Wang, Dongxu Ma, Erzhong Xue, Guang Gong, Srdjan Budisin
http://arxiv.org/abs/1910.10310v1
• [cs.IT]On the Bee-Identification Error Exponent with Absentee Bees
Anshoo Tandon, Vincent Y. F. Tan, Lav R. Varshney
http://arxiv.org/abs/1910.10333v1
• [cs.IT]Trainable Projected Gradient Detector for Sparsely Spread Code Division Multiple Access
Satoshi Takabe, Yuki Yamauchi, Tadashi Wadayama
http://arxiv.org/abs/1910.10336v1
• [cs.LG]A Unifying Framework of Bilinear LSTMs
Mohit Rajpal, Bryan Kian Hsiang Low
http://arxiv.org/abs/1910.10294v1
• [cs.LG]A Useful Taxonomy for Adversarial Robustness of Neural Networks
Leslie N. Smith
http://arxiv.org/abs/1910.10679v1
• [cs.LG]Better Approximate Inference for Partial Likelihood Models with a Latent Structure
Amrith Setlur, Barnabás Póczós
http://arxiv.org/abs/1910.10211v1
• [cs.LG]Bottom-Up Meta-Policy Search
Luckeciano C. Melo, Marcos R. O. A. Maximo, Adilson Marques da Cunha
http://arxiv.org/abs/1910.10232v1
• [cs.LG]Complex Transformer: A Framework for Modeling Complex-Valued Sequence
Muqiao Yang, Martin Q. Ma, Dongyu Li, Yao-Hung Hubert Tsai, Ruslan Salakhutdinov
http://arxiv.org/abs/1910.10202v1
• [cs.LG]Contrastive Representation Distillation
Yonglong Tian, Dilip Krishnan, Phillip Isola
http://arxiv.org/abs/1910.10699v1
• [cs.LG]Deep Learning at the Edge
Sahar Voghoei, Navid Hashemi Tonekaboni, Jason G. Wallace, Hamid R. Arabnia
http://arxiv.org/abs/1910.10231v1
• [cs.LG]Detecting Out-of-Distribution Inputs in Deep Neural Networks Using an Early-Layer Output
Vahdat Abdelzad, Krzysztof Czarnecki, Rick Salay, Taylor Denounden, Sachin Vernekar, Buu Phan
http://arxiv.org/abs/1910.10307v1
• [cs.LG]EdgeAI: A Vision for Deep Learning in IoT Era
Kartikeya Bhardwaj, Naveen Suda, Radu Marculescu
http://arxiv.org/abs/1910.10356v1
• [cs.LG]Efficient Decoupled Neural Architecture Search by Structure and Operation Sampling
Heung-Chang Lee, Do-Guk Kim, Bohyung Han
http://arxiv.org/abs/1910.10397v1
• [cs.LG]Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, Peter J. Liu
http://arxiv.org/abs/1910.10683v1
• [cs.LG]Feature Selection and Extraction for Graph Neural Networks
Deepak Bhaskar Acharya, Dr. Huaming Zhang
http://arxiv.org/abs/1910.10682v1
• [cs.LG]Federated Evaluation of On-device Personalization
Kangkang Wang, Rajiv Mathews, Chloé Kiddon, Hubert Eichner, Françoise Beaufays, Daniel Ramage
http://arxiv.org/abs/1910.10252v1
• [cs.LG]Federated Learning with Unbiased Gradient Aggregation and Controllable Meta Updating
Xin Yao, Tianchi Huang, Rui-Xiao Zhang, Ruiyu Li, Lifeng Sun
http://arxiv.org/abs/1910.08234v2
• [cs.LG]Generalized Domain Adaptation with Covariate and Label Shift CO-ALignment
Shuhan Tan, Xingchao Peng, Kate Saenko
http://arxiv.org/abs/1910.10320v1
• [cs.LG]Interpreting Basis Path Set in Neural Networks
Juanping Zhu, Qi Meng, Wei Chen, Zhi-ming Ma
http://arxiv.org/abs/1910.09402v1
• [cs.LG]Learning Partial Differential Equations from Data Using Neural Networks
Ali Hasan, João M. Pereira, Robert Ravier, Sina Farsiu, Vahid Tarokh
http://arxiv.org/abs/1910.10262v1
• [cs.LG]MLAT: Metric Learning for kNN in Streaming Time Series
Dongmin Park, Susik Yoon, Hwanjun Song, Jae-Gil Lee
http://arxiv.org/abs/1910.10368v1
• [cs.LG]Online Meta-Learning on Non-convex Setting
Zhenxun Zhuang, Yunlong Wang, Kezi Yu, Songtao Lu
http://arxiv.org/abs/1910.10196v1
• [cs.LG]Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation
Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Man-Chung Yue, Daniel Kuhn, Wolfram Wiesemann
http://arxiv.org/abs/1910.10583v1
• [cs.LG]Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning
Anis Elgabli, Jihong Park, Amrit S. Bedi, Mehdi Bennis, Vaneet Aggarwal
http://arxiv.org/abs/1910.10453v1
• [cs.LG]Recurrent Attention Walk for Semi-supervised Classification
Uchenna Akujuobi, Qiannan Zhang, Han Yufei, Xiangliang Zhang
http://arxiv.org/abs/1910.10266v1
• [cs.LG]Restless Hidden Markov Bandits with Linear Rewards
Michal Yemini, Amir Leshem, Anelia Somekh-Baruch
http://arxiv.org/abs/1910.10271v1
• [cs.LG]Robust Domain Randomization for Reinforcement Learning
Reda Bahi Slaoui, William R. Clements, Jakob N. Foerster, Sébastien Toth
http://arxiv.org/abs/1910.10537v1
• [cs.LG]Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles
Aditya Modi, Nan Jiang, Ambuj Tewari, Satinder Singh
http://arxiv.org/abs/1910.10597v1
• [cs.LG]Self-Attention for Raw Optical Satellite Time Series Classification
Marc Rußwurm, Marco Körner
http://arxiv.org/abs/1910.10536v1
• [cs.LG]Stabilising priors for robust Bayesian deep learning
Felix McGregor, Arnu Pretorius, Johan du Preez, Steve Kroon
http://arxiv.org/abs/1910.10386v1
• [cs.LG]State2vec: Off-Policy Successor Features Approximators
Sephora Madjiheurem, Laura Toni
http://arxiv.org/abs/1910.10277v1
• [cs.LG]Strategic Adaptation to Classifiers: A Causal Perspective
John Miller, Smitha Milli, Moritz Hardt
http://arxiv.org/abs/1910.10362v1
• [cs.LG]USTAR: Online Multimodal Embedding for Modeling User-Guided Spatiotemporal Activity
Amila Silva, Shanika Karunasekera, Christopher Leckie, Ling Luo
http://arxiv.org/abs/1910.10335v1
• [cs.LG]Weighted Distributed Differential Privacy ERM: Convex and Non-convex
Yilin Kang, Yong Liu, Weiping Wang
http://arxiv.org/abs/1910.10308v1
• [cs.LO]Knowledge of Uncertain Worlds: Programming with Logical Constraints
Yanhong A. Liu, Scott D. Stoller
http://arxiv.org/abs/1910.10346v1
• [cs.NE]A Novel Generalized Artificial Neural Network for Mining Two-Class Datasets
Wei-Chang Yeh
http://arxiv.org/abs/1910.10461v1
• [cs.NE]Autoencoding with XCSF
Richard J. Preen, Stewart W. Wilson, Larry Bull
http://arxiv.org/abs/1910.10579v1
• [cs.NE]Genetic Programming for Evolving Similarity Functions for Clustering: Representations and Analysis
Andrew Lensen, Bing Xue, Mengjie Zhang
http://arxiv.org/abs/1910.10264v1
• [cs.RO]An Analytical Lidar Sensor Model Based on Ray Path Information
Alexander Schaefer, Lukas Luft, Wolfram Burgard
http://arxiv.org/abs/1910.10469v1
• [cs.RO]Closed-Form Full Map Posteriors for Robot Localization with Lidar Sensors
Lukas Luft, Alexander Schaefer, Tobias Schubert, Wolfram Burgard
http://arxiv.org/abs/1910.10493v1
• [cs.RO]Impact-Aware Online Motion Planning for Fully-Actuated Bipedal Robot Walking
Yuan Gao, Xingye Da, Yan Gu
http://arxiv.org/abs/1910.10633v1
• [cs.RO]Learning Deep Parameterized Skills from Demonstration for Re-targetable Visuomotor Control
Jonathan Chang, Nishanth Kumar, Sean Hastings, Aaron Gokaslan, Diego Romeres, Devesh Jha, Daniel Nikovski, George Konidaris, Stefanie Tellex
http://arxiv.org/abs/1910.10628v1
• [cs.RO]Learning Humanoid Robot Running Skills through Proximal Policy Optimization
Luckeciano C. Melo, Marcos R. O. A. Maximo
http://arxiv.org/abs/1910.10620v1
• [cs.RO]Long-Term Urban Vehicle Localization Using Pole Landmarks Extracted from 3-D Lidar Scans
Alexander Schaefer, Daniel Büscher, Johan Vertens, Lukas Luft, Wolfram Burgard
http://arxiv.org/abs/1910.10550v1
• [cs.RO]Teach Biped Robots to Walk via Gait Principles and Reinforcement Learning with Adversarial Critics
Kuangen Zhang, Zhimin Hou, Clarence W. de Silva, Haoyong Yu, Chenglong Fu
http://arxiv.org/abs/1910.10194v1
• [cs.RO]gradSLAM: Dense SLAM meets Automatic Differentiation
Krishna Murthy Jatavallabhula, Ganesh Iyer, Liam Paull
http://arxiv.org/abs/1910.10672v1
• [cs.SD]Filterbank design for end-to-end speech separation
Manuel Pariente, Samuele Cornell, Antoine Deleforge, Emmanuel Vincent
http://arxiv.org/abs/1910.10400v1
• [cs.SD]Learning the helix topology of musical pitch
Vincent Lostanlen, Sripathi Sridhar, Brian McFee, Andrew Farnsworth, Juan Pablo Bello
http://arxiv.org/abs/1910.10246v1
• [cs.SE]Kuksa: A Cloud-Native Architecture for Enabling Continuous Delivery in the Automotive Domain
Ahmad Banijamali, Pooyan Jamshidi, Pasi Kuvaja, Markku Oivo
http://arxiv.org/abs/1910.10190v1
• [cs.SI]Network2Vec Learning Node Representation Based on Space Mapping in Networks
Huang Zhenhua, Wang Zhenyu, Zhang Rui, Zhao Yangyang, Xie Xiaohui, Sharad Mehrotra
http://arxiv.org/abs/1910.10379v1
• [econ.GN]Beating the House: Identifying Inefficiencies in Sports Betting Markets
Sathya Ramesh, Ragib Mostofa, Marco Bornstein, John Dobelman
http://arxiv.org/abs/1910.08858v2
• [eess.AS]A Transformer with Interleaved Self-attention and Convolution for Hybrid Acoustic Models
Liang Lu
http://arxiv.org/abs/1910.10352v1
• [eess.IV]A Deep Learning based Pipeline for Efficient Oral Cancer Screening on Whole Slide Images
Jiahao Lu, Nataša Sladoje, Christina Runow Stark, Eva Darai Ramqvist, Jan-Michaél Hirsch, Joakim Lindblad
http://arxiv.org/abs/1910.10549v1
• [eess.IV]Deep Clustering of Compressed Variational Embeddings
Suya Wu, Enmao Diao, Jie Ding, Vahid Tarokh
http://arxiv.org/abs/1910.10341v1
• [eess.IV]Deep Learning Supersampled Scanning Transmission Electron Microscopy
Jeffrey M. Ede
http://arxiv.org/abs/1910.10467v1
• [eess.IV]Deep generative model-driven multimodal prostate segmentation in radiotherapy
Kibrom Berihu Girum, Gilles Créhange, Raabid Hussain, Paul Michael Walker, Alain Lalande
http://arxiv.org/abs/1910.10542v1
• [eess.IV]Divide-and-Conquer Adversarial Learning for High-Resolution Image and Video Enhancement
Zhiwu Huang, Danda Pani Paudel, Guanju Li, Jiqing Wu, Radu Timofte, Luc Van Gool
http://arxiv.org/abs/1910.10455v1
• [eess.IV]INTEL-TAU: A Color Constancy Dataset
Firas Laakom, Jenni Raitoharju, Alexandros Iosifidis, Jarno Nikkanen, Moncef Gabbouj
http://arxiv.org/abs/1910.10404v1
• [eess.IV]Neural Ordinary Differential Equations for Semantic Segmentation of Individual Colon Glands
Hans Pinckaers, Geert Litjens
http://arxiv.org/abs/1910.10470v1
• [eess.IV]Photoshopping Colonoscopy Video Frames
Yuyuan Liu, Yu Tian, Gabriel Maicas, Leonardo Z. C. T. Pu, Rajvinder Singh, Johan W. Verjans, Gustavo Carneiro
http://arxiv.org/abs/1910.10345v1
• [eess.IV]Semantic Segmentation of Skin Lesions using a Small Data Set
Beril Sirmacek, Max Kivits
http://arxiv.org/abs/1910.10534v1
• [eess.IV]Stain Style Transfer using Transitive Adversarial Networks
Shaojin Cai, Yuyang Xue3 Qinquan Gao, Min Du, Gang Chen, Hejun Zhang, Tong Tong
http://arxiv.org/abs/1910.10330v1
• [eess.IV]Towards an Intelligent Microscope: adaptively learned illumination for optimal sample classification
Amey Chaware, Colin L. Cooke, Kanghyun Kim, Roarke Horstmeyer
http://arxiv.org/abs/1910.10209v1
• [eess.SP]New RLL Code with Improved Error Performance for Visible Light Communication
Vitalio Alfonso Reguera
http://arxiv.org/abs/1910.10079v2
• [eess.SY]Decentralized Runtime Synthesis of Shields for Multi-Agent Systems
Dhananjay Raju, Suda Bharadwaj, Ufuk Topcu
http://arxiv.org/abs/1910.10380v1
• [eess.SY]Prioritized Inverse Kinematics: Desired Task Trajectories in Nonsingular Task Spaces
Sang-ik An, Dongheui Lee
http://arxiv.org/abs/1910.10300v1
• [math.NA]Kernel Methods for Bayesian Elliptic Inverse Problems on Manifolds
John Harlim, Daniel Sanz-Alonso, Ruiyi Yang
http://arxiv.org/abs/1910.10669v1
• [math.OC]Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks
Jinming Xu, Ye Tian, Ying Sun, Gesualdo Scutari
http://arxiv.org/abs/1910.10666v1
• [math.ST]How well can we learn large factor models without assuming strong factors?
Yinchu Zhu
http://arxiv.org/abs/1910.10382v1
• [math.ST]Minimax Rate Optimal Adaptive Nearest Neighbor Classification and Regression
Puning Zhao, Lifeng Lai
http://arxiv.org/abs/1910.10513v1
• [math.ST]Multiple outlier detection tests for parametric models
Vilijandas Bagdonavicius, Linas Petkevicius
http://arxiv.org/abs/1910.10426v1
• [math.ST]Objective Bayesian Analysis of a Cokriging Model for Hierarchical Multifidelity Codes
Pulong Ma
http://arxiv.org/abs/1910.10225v1
• [math.ST]On the behavior of the DFA and DCCA in trend-stationary processes
Taiane Schaedler Prass, Guilherme Pumi
http://arxiv.org/abs/1910.10589v1
• [physics.ao-ph]Tropical Cyclone Track Forecasting using Fused Deep Learning from Aligned Reanalysis Data
Sophie Giffard-Roisin, Mo Yang, Guillaume Charpiat, Christina Kumler-Bonfanti, Balázs Kégl, Claire Monteleoni
http://arxiv.org/abs/1910.10566v1
• [physics.ins-det]Towards Fast Displaced Vertex Finding
Kim Albertsson, Federico Meloni
http://arxiv.org/abs/1910.10508v1
• [q-bio.NC]Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks
Roman Pogodin, Dane Corneil, Alexander Seeholzer, Joseph Heng, Wulfram Gerstner
http://arxiv.org/abs/1910.10559v1
• [q-bio.PE]Inference with selection, varying population size and evolving population structure: Application of ABC to a forward-backward coalescent process with interactions
Clotilde Lepers, Sylvain Billiard, Matthieu Porte, Sylvie Méléard, Viet Chi Tran
http://arxiv.org/abs/1910.10201v1
• [stat.AP]An inverse problem approach to the probabilistic reconstruction of particle tracks on a censored and closed surface
Yunjiao Lu, Pierre Hodara, Charles Kervrann, Alain Trubuil
http://arxiv.org/abs/1910.10432v1
• [stat.AP]Double-Counting Problem of the Bonus-Malus System
Rosy Oh, Kyung Suk Lee, Sojung C. Park, Jae Youn Ahn
http://arxiv.org/abs/1910.10313v1
• [stat.AP]Statistical Modeling for Spatio-Temporal Data from Physical Convection-Diffusion Processes
Xiao Liu, Kyongmin Yeo, Siyuan Lu
http://arxiv.org/abs/1910.10375v1
• [stat.CO]Event-scheduling algorithms with Kalikow decomposition for simulating potentially infinite neuronal networks
Tien Cuong Phi, Alexandre Muzy, Patricia Reynaud-Bouret
http://arxiv.org/abs/1910.10576v1
• [stat.ME]A Stochastic Block Model for Multilevel Networks: Application to the Sociology of Organisations
Saint-Clair Chabert-Liddell, Pierre Barbillon, Sophie Donnet, Emmanuel Lazega
http://arxiv.org/abs/1910.10512v1
• [stat.ME]Bayesian nonparametric temporal dynamic clustering via autoregressive Dirichlet priors
Maria De Iorio, Stefano Favaro, Alessandra Guglielmi, Lifeng Ye
http://arxiv.org/abs/1910.10443v1
• [stat.ME]Doubly robust treatment effect estimation with missing attributes
Imke Mayer, Stefan Wager, Tobias Gauss, Jean-Denis Moyer, Julie Josse
http://arxiv.org/abs/1910.10624v1
• [stat.ME]Flexible Bayesian modelling in dichotomous item response theory using mixtures of skewed item curves
Flávio B. Gonçalves, Juliane Venturelli, Rosangela H. Loschi
http://arxiv.org/abs/1910.10233v1
• [stat.ME]Nested Conformal Prediction and the Generalized Jackknife+
Arun K. Kuchibhotla, Aaditya K. Ramdas
http://arxiv.org/abs/1910.10562v1
• [stat.ML]Deterministic tensor completion with hypergraph expanders
Kameron Decker Harris, Yizhe Zhu
http://arxiv.org/abs/1910.10692v1
• [stat.ML]Global Capacity Measures for Deep ReLU Networks via Path Sampling
Ryan Theisen, Jason M. Klusowski, Huan Wang, Nitish Shirish Keskar, Caiming Xiong, Richard Socher
http://arxiv.org/abs/1910.10245v1
• [stat.ML]Leveraging directed causal discovery to detect latent common causes
Ciarán M. Lee, Christopher Hart, Jonathan G. Richens, Saurabh Johri
http://arxiv.org/abs/1910.10174v1
• [stat.ML]Machine Learning for Scent: Learning Generalizable Perceptual Representations of Small Molecules
Benjamin Sanchez-Lengeling, Jennifer N. Wei, Brian K. Lee, Richard C. Gerkin, Alán Aspuru-Guzik, Alexander B. Wiltschko
http://arxiv.org/abs/1910.10685v1
• [stat.ML]Neural Execution of Graph Algorithms
Petar Veličković, Rex Ying, Matilde Padovano, Raia Hadsell, Charles Blundell
http://arxiv.org/abs/1910.10593v1
• [stat.ML]Sparse Orthogonal Variational Inference for Gaussian Processes
Jiaxin Shi, Michalis K. Titsias, Andriy Mnih
http://arxiv.org/abs/1910.10596v1
• [stat.ML]Unifying Variational Inference and PAC-Bayes for Supervised Learning that Scales
Sanjay Thakur, Herke Van Hoof, Gunshi Gupta, David Meger
http://arxiv.org/abs/1910.10367v1