cs.AI - 人工智能

    cs.CE - 计算工程、 金融和科学 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.DL - 数字图书馆 cs.DM - 离散数学 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.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 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math-ph - 数学物理 math.FA - 泛函演算 math.ST - 统计理论 physics.soc-ph - 物理学与社会 q-bio.PE - 人口与发展 q-fin.GN - 通用财务 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]A literature review on current approaches and applications of fuzzy expert systems
    • [cs.AI]Human-In-The-Loop Learning of Qualitative Preference Models
    • [cs.AI]Learning Optimal and Near-Optimal Lexicographic Preference Lists
    • [cs.AI]Look, Read and Enrich. Learning from Scientific Figures and their Captions
    • [cs.AI]Robust Opponent Modeling via Adversarial Ensemble Reinforcement Learning in Asymmetric Imperfect-Information Games
    • [cs.CE]A Compressed Coding Scheme for Evolutionary Algorithms in Mixed-Integer Programming: A Case Study on Multi-Objective Constrained Portfolio Optimization
    • [cs.CL]A Corpus for Automatic Readability Assessment and Text Simplification of German
    • [cs.CL]A Random Gossip BMUF Process for Neural Language Modeling
    • [cs.CL]A Split-and-Recombine Approach for Follow-up Query Analysis
    • [cs.CL]ASU at TextGraphs 2019 Shared Task: Explanation ReGeneration using Language Models and Iterative Re-Ranking
    • [cs.CL]Alleviating Sequence Information Loss with Data Overlapping and Prime Batch Sizes
    • [cs.CL]An Edit-centric Approach for Wikipedia Article Quality Assessment
    • [cs.CL]Analysing Neural Language Models: Contextual Decomposition Reveals Default Reasoning in Number and Gender Assignment
    • [cs.CL]Argumentative Relation Classification as Plausibility Ranking
    • [cs.CL]CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots
    • [cs.CL]Characterizing Collective Attention via Descriptor Context in Public Discussions of Crisis Events
    • [cs.CL]CogniVal: A Framework for Cognitive Word Embedding Evaluation
    • [cs.CL]Cross-Lingual Contextual Word Embeddings Mapping With Multi-Sense Words In Mind
    • [cs.CL]Do We Need Neural Models to Explain Human Judgments of Acceptability?
    • [cs.CL]Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
    • [cs.CL]Exploring ways to incorporate additional knowledge to improve Natural Language Commonsense Question Answering
    • [cs.CL]Extracting Conceptual Knowledge from Natural Language Text Using Maximum Likelihood Principle
    • [cs.CL]How to Write Summaries with Patterns? Learning towards Abstractive Summarization through Prototype Editing
    • [cs.CL]Improving Generalization by Incorporating Coverage in Natural Language Inference
    • [cs.CL]Low-Resource Parsing with Crosslingual Contextualized Representations
    • [cs.CL]Made for Each Other: Broad-coverage Semantic Structures Meet Preposition Supersenses
    • [cs.CL]Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder
    • [cs.CL]Procedural Reasoning Networks for Understanding Multimodal Procedures
    • [cs.CL]RUN through the Streets: A New Dataset and Baseline Models for Realistic Urban Navigation
    • [cs.CL]Self-Training for End-to-End Speech Recognition
    • [cs.CL]Semantic Relatedness Based Re-ranker for Text Spotting
    • [cs.CL]Sentiment-Aware Recommendation System for Healthcare using Social Media
    • [cs.CL]Summary Level Training of Sentence Rewriting for Abstractive Summarization
    • [cs.CR]Adversarial Vulnerability Bounds for Gaussian Process Classification
    • [cs.CR]Barracuda: The Power of $\ell$-polling in Proof-of-Stake Blockchains
    • [cs.CR]Detecting malicious logins as graph anomalies
    • [cs.CR]Kinetic Song Comprehension: Deciphering Personal Listening Habits via Phone Vibrations
    • [cs.CR]VideoDP: A Universal Platform for Video Analytics with Differential Privacy
    • [cs.CV]A New Few-shot Segmentation Network Based on Class Representation
    • [cs.CV]Adaptively Aligned Image Captioning via Adaptive Attention Time
    • [cs.CV]Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Network
    • [cs.CV]Challenging deep image descriptors for retrieval in heterogeneous iconographic collections
    • [cs.CV]Class Feature Pyramids for Video Explanation
    • [cs.CV]ContCap: A comprehensive framework for continual image captioning
    • [cs.CV]Count, Crop and Recognise: Fine-Grained Recognition in the Wild
    • [cs.CV]Deep Latent Space Learning for Cross-modal Mapping of Audio and Visual Signals
    • [cs.CV]Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning
    • [cs.CV]Ensemble Knowledge Distillation for Learning Improved and Efficient Networks
    • [cs.CV]Grid Anchor based Image Cropping: A New Benchmark and An Efficient Model
    • [cs.CV]Large e-retailer image dataset for visual search and product classification
    • [cs.CV]Large-scale representation learning from visually grounded untranscribed speech
    • [cs.CV]Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift
    • [cs.CV]Localization with Limited Annotation
    • [cs.CV]Road Damage Detection Acquisition System based on Deep Neural Networks for Physical Asset Management
    • [cs.CV]Self-Supervised Learning of Depth and Motion Under Photometric Inconsistency
    • [cs.CV]Self-Supervised Monocular Depth Hints
    • [cs.CV]Slices of Attention in Asynchronous Video Job Interviews
    • [cs.CV]Social and Scene-Aware Trajectory Prediction in Crowded Spaces
    • [cs.CV]Transfer Learning using CNN for Handwritten Devanagari Character Recognition
    • [cs.CV]Wasserstein Distance Based Domain Adaptation for Object Detection
    • [cs.CY]Can WhatsApp Counter Misinformation by Limiting Message Forwarding?
    • [cs.DC]Accelerating Green Computing with Hybrid Asymmetric Multicore Architectures and Safe Parallelism
    • [cs.DC]Balsam: Automated Scheduling and Execution of Dynamic, Data-Intensive HPC Workflows
    • [cs.DC]Low Diameter Graph Decompositions by Approximate Distance Computation
    • [cs.DC]When Two is Worse Than One
    • [cs.DL]Bibliothèque de la communauté assomptionniste : saisie informatique et classement Dewey
    • [cs.DM]Lower Bound for (Sum) Coloring Problem
    • [cs.HC]A High-Fidelity Open Embodied Avatar with Lip Syncing and Expression Capabilities
    • [cs.HC]Towards humane digitization: a wellbeing-driven process of personas creation
    • [cs.IR]BPMR: Bayesian Probabilistic Multivariate Ranking
    • [cs.IR]Understanding the Information needs of Social Scientists in Germany
    • [cs.IT]A Note on Decoding Order in Optimizing Multi-Cell NOMA
    • [cs.IT]A note on the quasiconvex Jensen divergences and the quasiconvex Bregman divergences derived thereof
    • [cs.IT]Coding for Optical Communications — Can We Approach the Shannon Limit With Low Complexity?
    • [cs.IT]Comments on “On Favorable Propagation in Massive MIMO Systems and Different Antenna Configurations” [1]
    • [cs.IT]Optimal Policies of Advanced Sleep Modes for Energy-Efficient 5G networks
    • [cs.IT]Optimization of Power Transfer Efficiency and Energy Efficiency for Wireless-Powered Systems with Massive MIMO
    • [cs.LG]Automobile Theft Detection by Clustering Owner Driver Data
    • [cs.LG]Corporate IT-support Help-Desk Process Hybrid-Automation Solution with Machine Learning Approach
    • [cs.LG]Highlighting Bias with Explainable Neural-Symbolic Visual Reasoning
    • [cs.LG]Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models
    • [cs.LG]Scalable Deep Unsupervised Clustering with Concrete GMVAEs
    • [cs.LG]Training Robust Deep Neural Networks via Adversarial Noise Propagation
    • [cs.LG]Voting with Random Classifiers (VORACE)
    • [cs.LO]Strong Equivalence for LPMLN Programs
    • [cs.NE]Evaluation of Deep Species Distribution Models using Environment and Co-occurrences
    • [cs.NI]Dynamic Bandwidth Allocation in Small-Cell Networks: An Economics Approach
    • [cs.NI]MACS: Deep Reinforcement Learning based SDN Controller Synchronization Policy Design
    • [cs.RO]Agent Prioritization for Autonomous Navigation
    • [cs.RO]Assembly of randomly placed parts realized by using only one robot arm with a general parallel-jaw gripper
    • [cs.RO]Finding Locomanipulation Plans Quickly in the Locomotion Constrained Manifold
    • [cs.RO]Flexible Disaster Response of Tomorrow — Final Presentation and Evaluation of the CENTAURO System
    • [cs.RO]Graph Neural Networks for Human-aware Social Navigation
    • [cs.RO]How to Evaluate Self-Driving Testing Ground? A Quantitative Approach
    • [cs.RO]Multi-Robot Deep Reinforcement Learning with Macro-Actions
    • [cs.RO]SL1M: Sparse L1-norm Minimization for contact planning on uneven terrain
    • [cs.RO]Vision-Based Proprioceptive Sensing for Soft Inflatable Actuators
    • [cs.SI]Community Detection Across Multiple Social Networks based on Overlapping Users
    • [cs.SI]DAOC: Stable Clustering of Large Networks
    • [cs.SI]Ensemble approach for generalized network dismantling
    • [cs.SI]Moments of Uniform Random Multigraphs with Fixed Degree Sequences
    • [eess.AS]WEnets: A Convolutional Framework for Evaluating Audio Waveforms
    • [eess.IV]Automated detection of oral pre-cancerous tongue lesions using deep learning for early diagnosis of oral cavity cancer
    • [eess.IV]Efficient Prealignment of CT Scans for Registration through a Bodypart Regressor
    • [eess.IV]Learning to Avoid Poor Images: Towards Task-aware C-arm Cone-beam CT Trajectories
    • [eess.IV]PgNN: Physics-guided Neural Network for Fourier Ptychographic Microscopy
    • [eess.IV]Prediction of overall survival and molecular markers in gliomas via analysis of digital pathology images using deep learning
    • [eess.IV]Quantitative Impact of Label Noise on the Quality of Segmentation of Brain Tumors on MRI scans
    • [eess.IV]Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer’s disease classification
    • [eess.SP]APIR-Net: Autocalibrated Parallel Imaging Reconstruction using a Neural Network
    • [eess.SY]On the observability of relative positions in left-invariant multi-agent control systems and its application to formation control
    • [math-ph]Perfect quantum state transfer on diamond fractal graphs
    • [math.FA]Almost Everywhere Generalized Phase Retrieval
    • [math.ST]Collective sampling through a Metropolis-Hastings like method: kinetic theory and numerical experiments
    • [math.ST]Generalized Resilience and Robust Statistics
    • [math.ST]Multivariate Rank-based Distribution-free Nonparametric Testing using Measure Transportation
    • [physics.soc-ph]Collapse of Social Engagement and its Prevention by Local Recruitments
    • [physics.soc-ph]Detecting social (in)stability in primates from their temporal co-presence network
    • [physics.soc-ph]Segregation Dynamics with Reinforcement Learning and Agent Based Modeling
    • [q-bio.PE]Improving inference for nonlinear state-space models of animal population dynamics given biased sequential life stage data
    • [q-fin.GN]Corruption Risk in Contracting Markets: A Network Science Perspective
    • [stat.ME]Bayesian Analysis of Multidimensional Functional Data
    • [stat.ME]Semantic and Cognitive Tools to Aid Statistical Inference: Replace Confidence and Significance by Compatibility and Surprise
    • [stat.ME]To Aid Statistical Inference, Emphasize Unconditional Descriptions of Statistics
    • [stat.ML]Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks
    • [stat.ML]Explaining Visual Models by Causal Attribution
    • [stat.ML]On Efficient Multilevel Clustering via Wasserstein Distances
    • [stat.ML]Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models
    • [stat.ML]Value function estimation in Markov reward processes: Instance-dependent $\ell_\infty$-bounds for policy evaluation

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    • [cs.AI]A literature review on current approaches and applications of fuzzy expert systems
    Mina Rajabi, Saeed Hossani, Fatemeh Dehghani
    http://arxiv.org/abs/1909.08794v1

    • [cs.AI]Human-In-The-Loop Learning of Qualitative Preference Models
    Joseph Allen, Ahmed Moussa, Xudong Liu
    http://arxiv.org/abs/1909.09064v1

    • [cs.AI]Learning Optimal and Near-Optimal Lexicographic Preference Lists
    Ahmed Moussa, Xudong Liu
    http://arxiv.org/abs/1909.09072v1

    • [cs.AI]Look, Read and Enrich. Learning from Scientific Figures and their Captions
    Jose Manuel Gomez-Perez, Raul Ortega
    http://arxiv.org/abs/1909.09070v1

    • [cs.AI]Robust Opponent Modeling via Adversarial Ensemble Reinforcement Learning in Asymmetric Imperfect-Information Games
    Macheng Shen, Jonathan P. How
    http://arxiv.org/abs/1909.08735v1

    • [cs.CE]A Compressed Coding Scheme for Evolutionary Algorithms in Mixed-Integer Programming: A Case Study on Multi-Objective Constrained Portfolio Optimization
    Yi Chen, Aimin Zhou, Swagatam Das
    http://arxiv.org/abs/1909.08748v1

    • [cs.CL]A Corpus for Automatic Readability Assessment and Text Simplification of German
    Alessia Battisti, Sarah Ebling
    http://arxiv.org/abs/1909.09067v1

    • [cs.CL]A Random Gossip BMUF Process for Neural Language Modeling
    Yiheng Huang, Jinchuan Tian, Lei Han, Guangsen Wang, Xingcheng Song, Dan Su, Dong Yu
    http://arxiv.org/abs/1909.09010v1

    • [cs.CL]A Split-and-Recombine Approach for Follow-up Query Analysis
    Qian Liu, Bei Chen, Haoyan Liu, Lei Fang, Jian-Guang Lou, Bin Zhou, Dongmei Zhang
    http://arxiv.org/abs/1909.08905v1

    • [cs.CL]ASU at TextGraphs 2019 Shared Task: Explanation ReGeneration using Language Models and Iterative Re-Ranking
    Pratyay Banerjee
    http://arxiv.org/abs/1909.08863v1

    • [cs.CL]Alleviating Sequence Information Loss with Data Overlapping and Prime Batch Sizes
    Noémien Kocher, Christian Scuito, Lorenzo Tarantino, Alexandros Lazaridis, Andreas Fischer, Claudiu Musat
    http://arxiv.org/abs/1909.08700v1

    • [cs.CL]An Edit-centric Approach for Wikipedia Article Quality Assessment
    Edison Marrese-Taylor, Pablo Loyola, Yutaka Matsuo
    http://arxiv.org/abs/1909.08880v1

    • [cs.CL]Analysing Neural Language Models: Contextual Decomposition Reveals Default Reasoning in Number and Gender Assignment
    Jaap Jumelet, Willem Zuidema, Dieuwke Hupkes
    http://arxiv.org/abs/1909.08975v1

    • [cs.CL]Argumentative Relation Classification as Plausibility Ranking
    Juri Opitz
    http://arxiv.org/abs/1909.09031v1

    • [cs.CL]CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots
    Arshit Gupta, Peng Zhang, Garima Lalwani, Mona Diab
    http://arxiv.org/abs/1909.08705v1

    • [cs.CL]Characterizing Collective Attention via Descriptor Context in Public Discussions of Crisis Events
    Ian Stewart, Diyi Yang, Jacob Eisenstein
    http://arxiv.org/abs/1909.08784v1

    • [cs.CL]CogniVal: A Framework for Cognitive Word Embedding Evaluation
    Nora Hollenstein, Antonio de la Torre, Nicolas Langer, Ce Zhang
    http://arxiv.org/abs/1909.09001v1

    • [cs.CL]Cross-Lingual Contextual Word Embeddings Mapping With Multi-Sense Words In Mind
    Zheng Zhang, Ruiqing Yin, Jun Zhu, Pierre Zweigenbaum
    http://arxiv.org/abs/1909.08681v1

    • [cs.CL]Do We Need Neural Models to Explain Human Judgments of Acceptability?
    Wang Jing, M. A. Kelly, David Reitter
    http://arxiv.org/abs/1909.08663v1

    • [cs.CL]Espresso: A Fast End-to-end Neural Speech Recognition Toolkit
    Yiming Wang, Tongfei Chen, Hainan Xu, Shuoyang Ding, Hang Lv, Yiwen Shao, Nanyun Peng, Lei Xie, Shinji Watanabe, Sanjeev Khudanpur
    http://arxiv.org/abs/1909.08723v1

    • [cs.CL]Exploring ways to incorporate additional knowledge to improve Natural Language Commonsense Question Answering
    Arindam Mitra, Pratyay Banerjee, Kuntal Kumar Pal, Swaroop Mishra, Chitta Baral
    http://arxiv.org/abs/1909.08855v1

    • [cs.CL]Extracting Conceptual Knowledge from Natural Language Text Using Maximum Likelihood Principle
    Shipra Sharma, Balwinder Sodhi
    http://arxiv.org/abs/1909.08927v1

    • [cs.CL]How to Write Summaries with Patterns? Learning towards Abstractive Summarization through Prototype Editing
    Shen Gao, Xiuying Chen, Piji Li, Zhangming Chan, Dongyan Zhao, Rui Yan
    http://arxiv.org/abs/1909.08837v1

    • [cs.CL]Improving Generalization by Incorporating Coverage in Natural Language Inference
    Nafise Sadat Moosavi, Prasetya Ajie Utama, Andreas Rücklé, Iryna Gurevych
    http://arxiv.org/abs/1909.08940v1

    • [cs.CL]Low-Resource Parsing with Crosslingual Contextualized Representations
    Phoebe Mulcaire, Jungo Kasai, Noah A. Smith
    http://arxiv.org/abs/1909.08744v1

    • [cs.CL]Made for Each Other: Broad-coverage Semantic Structures Meet Preposition Supersenses
    Jakob Prange, Nathan Schneider, Omri Abend
    http://arxiv.org/abs/1909.08796v1

    • [cs.CL]Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder
    Li Du, Xiao Ding, Ting Liu, Zhongyang Li
    http://arxiv.org/abs/1909.08824v1

    • [cs.CL]Procedural Reasoning Networks for Understanding Multimodal Procedures
    Mustafa Sercan Amac, Semih Yagcioglu, Aykut Erdem, Erkut Erdem
    http://arxiv.org/abs/1909.08859v1

    • [cs.CL]RUN through the Streets: A New Dataset and Baseline Models for Realistic Urban Navigation
    Tzuf Paz-Argaman, Reut Tsarfaty
    http://arxiv.org/abs/1909.08970v1

    • [cs.CL]Self-Training for End-to-End Speech Recognition
    Jacob Kahn, Ann Lee, Awni Hannun
    http://arxiv.org/abs/1909.09116v1

    • [cs.CL]Semantic Relatedness Based Re-ranker for Text Spotting
    Ahmed Sabir, Francesc Moreno-Noguer, Lluís Padró
    http://arxiv.org/abs/1909.07950v2

    • [cs.CL]Sentiment-Aware Recommendation System for Healthcare using Social Media
    Alan Aipe, Mukuntha Narayanan Sundararaman, Asif Ekbal
    http://arxiv.org/abs/1909.08686v1

    • [cs.CL]Summary Level Training of Sentence Rewriting for Abstractive Summarization
    Sanghwan Bae, Taeuk Kim, Jihoon Kim, Sang-goo Lee
    http://arxiv.org/abs/1909.08752v1

    • [cs.CR]Adversarial Vulnerability Bounds for Gaussian Process Classification
    Michael Thomas Smith, Kathrin Grosse, Michael Backes, Mauricio A Alvarez
    http://arxiv.org/abs/1909.08864v1

    • [cs.CR]Barracuda: The Power of $\ell$-polling in Proof-of-Stake Blockchains
    Giulia Fanti, Jiantao Jiao, Ashok Makkuva, Sewoong Oh, Ranvir Rana, Pramod Viswanath
    http://arxiv.org/abs/1909.08719v1

    • [cs.CR]Detecting malicious logins as graph anomalies
    Brian A. Powell
    http://arxiv.org/abs/1909.09047v1

    • [cs.CR]Kinetic Song Comprehension: Deciphering Personal Listening Habits via Phone Vibrations
    Richard Matovu, Isaac Griswold-Steiner, Abdul Serwadda
    http://arxiv.org/abs/1909.09123v1

    • [cs.CR]VideoDP: A Universal Platform for Video Analytics with Differential Privacy
    Han Wang, Shangyu Xie, Yuan Hong
    http://arxiv.org/abs/1909.08729v1

    • [cs.CV]A New Few-shot Segmentation Network Based on Class Representation
    Yuwei Yang, Fanman Meng, Hongliang Li, King N. Ngan, Qingbo Wu
    http://arxiv.org/abs/1909.08754v1

    • [cs.CV]Adaptively Aligned Image Captioning via Adaptive Attention Time
    Lun Huang, Wenmin Wang, Yaxian Xia, Jie Chen
    http://arxiv.org/abs/1909.09060v1

    • [cs.CV]Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Network
    Anjith George, Zohreh Mostaani, David Geissenbuhler, Olegs Nikisins, Andre Anjos, Sebastien Marcel
    http://arxiv.org/abs/1909.08848v1

    • [cs.CV]Challenging deep image descriptors for retrieval in heterogeneous iconographic collections
    Dimitri Gominski, Martyna Poreba, Valérie Gouet-Brunet, Liming Chen
    http://arxiv.org/abs/1909.08866v1

    • [cs.CV]Class Feature Pyramids for Video Explanation
    Alexandros Stergiou, Georgios Kapidis, Grigorios Kalliatakis, Christos Chrysoulas, Ronald Poppe, Remco Veltkamp
    http://arxiv.org/abs/1909.08611v1

    • [cs.CV]ContCap: A comprehensive framework for continual image captioning
    Giang Nguyen, Tae Joon Jun, Trung Tran, Daeyoung Kim
    http://arxiv.org/abs/1909.08745v1

    • [cs.CV]Count, Crop and Recognise: Fine-Grained Recognition in the Wild
    Max Bain, Arsha Nagrani, Daniel Schofield, Andrew Zisserman
    http://arxiv.org/abs/1909.08950v1

    • [cs.CV]Deep Latent Space Learning for Cross-modal Mapping of Audio and Visual Signals
    Shah Nawaz, Muhammad Kamran Janjua, Ignazio Gallo, Arif Mahmood, Alessandro Calefati
    http://arxiv.org/abs/1909.08685v1

    • [cs.CV]Dual Encoder-Decoder based Generative Adversarial Networks for Disentangled Facial Representation Learning
    Cong Hu, Zhen-Hua Feng, Xiao-Jun Wu, Josef Kittler
    http://arxiv.org/abs/1909.08797v1

    • [cs.CV]Ensemble Knowledge Distillation for Learning Improved and Efficient Networks
    Umar Asif, Jianbin Tang, Stefan Harrer
    http://arxiv.org/abs/1909.08097v2

    • [cs.CV]Grid Anchor based Image Cropping: A New Benchmark and An Efficient Model
    Hui Zeng, Lida Li, Zisheng Cao, Lei Zhang
    http://arxiv.org/abs/1909.08989v1

    • [cs.CV]Large e-retailer image dataset for visual search and product classification
    Arnaud Bellétoile
    http://arxiv.org/abs/1909.08612v1

    • [cs.CV]Large-scale representation learning from visually grounded untranscribed speech
    Gabriel Ilharco, Yuan Zhang, Jason Baldridge
    http://arxiv.org/abs/1909.08782v1

    • [cs.CV]Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift
    Titus Leistner, Hendrik Schilling, Radek Mackowiak, Stefan Gumhold, Carsten Rother
    http://arxiv.org/abs/1909.09059v1

    • [cs.CV]Localization with Limited Annotation
    Eyal Rozenberg, Daniel Freedman, Alex Bronstein
    http://arxiv.org/abs/1909.08842v1

    • [cs.CV]Road Damage Detection Acquisition System based on Deep Neural Networks for Physical Asset Management
    A. A. Angulo, J. A. Vega-Fernández, L. M. Aguilar-Lobo, S. Natraj, G Ochoa-Ruiz
    http://arxiv.org/abs/1909.08991v1

    • [cs.CV]Self-Supervised Learning of Depth and Motion Under Photometric Inconsistency
    Tianwei Shen, Lei Zhou, Zixin Luo, Yao Yao, Shiwei Li, Jiahui Zhang, Tian Fang, Long Quan
    http://arxiv.org/abs/1909.09115v1

    • [cs.CV]Self-Supervised Monocular Depth Hints
    Jamie Watson, Michael Firman, Gabriel J. Brostow, Daniyar Turmukhambetov
    http://arxiv.org/abs/1909.09051v1

    • [cs.CV]Slices of Attention in Asynchronous Video Job Interviews
    Léo Hemamou, Ghazi Felhi, Jean-Claude Martin, Chloé Clavel
    http://arxiv.org/abs/1909.08845v1

    • [cs.CV]Social and Scene-Aware Trajectory Prediction in Crowded Spaces
    Matteo Lisotto, Pasquale Coscia, Lamberto Ballan
    http://arxiv.org/abs/1909.08840v1

    • [cs.CV]Transfer Learning using CNN for Handwritten Devanagari Character Recognition
    Nagender Aneja, Sandhya Aneja
    http://arxiv.org/abs/1909.08774v1

    • [cs.CV]Wasserstein Distance Based Domain Adaptation for Object Detection
    Pengcheng Xu, Prudhvi Gurram, Gene Whipps, Rama Chellappa
    http://arxiv.org/abs/1909.08675v1

    • [cs.CY]Can WhatsApp Counter Misinformation by Limiting Message Forwarding?
    Philipe de Freitas Melo, Carolina Coimbra Vieira, Kiran Garimella, Pedro O. S. Vaz de Melo, Fabrício Benevenuto
    http://arxiv.org/abs/1909.08740v1

    • [cs.DC]Accelerating Green Computing with Hybrid Asymmetric Multicore Architectures and Safe Parallelism
    Hope Mogale, Michael Esiefarienrhe, Naison Gasela, Lucia Letlonkane
    http://arxiv.org/abs/1909.08978v1

    • [cs.DC]Balsam: Automated Scheduling and Execution of Dynamic, Data-Intensive HPC Workflows
    Michael A. Salim, Thomas D. Uram, J. Taylor Childers, Prasanna Balaprakash, Venkatram Vishwanath, Michael E. Papka
    http://arxiv.org/abs/1909.08704v1

    • [cs.DC]Low Diameter Graph Decompositions by Approximate Distance Computation
    Ruben Becker, Yuval Emek, Christoph Lenzen
    http://arxiv.org/abs/1909.09002v1

    • [cs.DC]When Two is Worse Than One
    R. Guerin
    http://arxiv.org/abs/1909.08969v1

    • [cs.DL]Bibliothèque de la communauté assomptionniste : saisie informatique et classement Dewey
    Benoit Soubeyran
    http://arxiv.org/abs/1909.08756v1

    • [cs.DM]Lower Bound for (Sum) Coloring Problem
    Alexandre Gondran, Vincent Duchamp, Laurent Moalic
    http://arxiv.org/abs/1909.08906v1

    • [cs.HC]A High-Fidelity Open Embodied Avatar with Lip Syncing and Expression Capabilities
    Deepali Aneja, Daniel McDuff, Shital Shah
    http://arxiv.org/abs/1909.08766v1

    • [cs.HC]Towards humane digitization: a wellbeing-driven process of personas creation
    Irawan Nurhas, Jan Pawlowski, Stefan Geisler
    http://arxiv.org/abs/1909.08839v1

    • [cs.IR]BPMR: Bayesian Probabilistic Multivariate Ranking
    Nan Wang, Hongning Wang
    http://arxiv.org/abs/1909.08737v1

    • [cs.IR]Understanding the Information needs of Social Scientists in Germany
    Dagmar Kern, Daniel Hienert
    http://arxiv.org/abs/1909.08876v1

    • [cs.IT]A Note on Decoding Order in Optimizing Multi-Cell NOMA
    Lei You, Di Yuan
    http://arxiv.org/abs/1909.08651v1

    • [cs.IT]A note on the quasiconvex Jensen divergences and the quasiconvex Bregman divergences derived thereof
    Frank Nielsen, Gaëtan Hadjeres
    http://arxiv.org/abs/1909.08857v1

    • [cs.IT]Coding for Optical Communications — Can We Approach the Shannon Limit With Low Complexity?
    Alexandre Graell i Amat, Gianluigi Liva, Fabian Steiner
    http://arxiv.org/abs/1909.09092v1

    • [cs.IT]Comments on “On Favorable Propagation in Massive MIMO Systems and Different Antenna Configurations” [1]**
    S. Loyka, M. Khojastehnia
    http://arxiv.org/abs/1909.08726v1

    • [cs.IT]Optimal Policies of Advanced Sleep Modes for Energy-Efficient 5G networks
    Fatma Ezzahra Salem, Tijani Chahed, Eitan Altman, Azeddine Gati, Zwi Altman
    http://arxiv.org/abs/1909.09011v1

    • [cs.IT]Optimization of Power Transfer Efficiency and Energy Efficiency for Wireless-Powered Systems with Massive MIMO
    Talha Ahmed Khan, Ali Yazdan, Robert W. Heath Jr
    http://arxiv.org/abs/1909.08652v1

    • [cs.LG]Automobile Theft Detection by Clustering Owner Driver Data
    Yong Goo Kang, Kyung Ho Park, Huy Kang Kim
    http://arxiv.org/abs/1909.08929v1

    • [cs.LG]Corporate IT-support Help-Desk Process Hybrid-Automation Solution with Machine Learning Approach
    Kuruparan Shanmugalingam, Nisal Chandrasekara, Calvin Hindle, Gihan Fernando, Chanaka Gunawardhana
    http://arxiv.org/abs/1909.09018v1

    • [cs.LG]Highlighting Bias with Explainable Neural-Symbolic Visual Reasoning
    Adrien Bennetot, Jean-Luc Laurent, Raja Chatila, Natalia Díaz-Rodríguez
    http://arxiv.org/abs/1909.09065v1

    • [cs.LG]Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models
    Farhad Shakerin
    http://arxiv.org/abs/1909.09017v1

    • [cs.LG]Scalable Deep Unsupervised Clustering with Concrete GMVAEs
    Mark Collier, Hector Urdiales
    http://arxiv.org/abs/1909.08994v1

    • [cs.LG]Training Robust Deep Neural Networks via Adversarial Noise Propagation
    Aishan Liu, Xianglong Liu, Chongzhi Zhang, Hang Yu, Qiang Liu, Junfeng He
    http://arxiv.org/abs/1909.09034v1

    • [cs.LG]Voting with Random Classifiers (VORACE)
    Cristina Cornelio, Michele Donini, Andrea Loreggia, Maria Silvia Pini, Francesca Rossi
    http://arxiv.org/abs/1909.08996v1

    • [cs.LO]Strong Equivalence for LPMLN Programs
    Joohyung Lee, Man Luo
    http://arxiv.org/abs/1909.08998v1

    • [cs.NE]Evaluation of Deep Species Distribution Models using Environment and Co-occurrences
    Benjamin Deneu, Maximilien Servajean, Christophe Botella, Alexis Joly
    http://arxiv.org/abs/1909.08825v1

    • [cs.NI]Dynamic Bandwidth Allocation in Small-Cell Networks: An Economics Approach
    Lin Cheng, Bernardo A. Huberman
    http://arxiv.org/abs/1909.08656v1

    • [cs.NI]MACS: Deep Reinforcement Learning based SDN Controller Synchronization Policy Design
    Ziyao Zhang, Liang Ma, Konstantinos Poularakis, Kin K. Leung, Jeremy Tucker, Ananthram Swami
    http://arxiv.org/abs/1909.09063v1

    • [cs.RO]Agent Prioritization for Autonomous Navigation
    Khaled S. Refaat, Kai Ding, Natalia Ponomareva, Stéphane Ross
    http://arxiv.org/abs/1909.08792v1

    • [cs.RO]Assembly of randomly placed parts realized by using only one robot arm with a general parallel-jaw gripper
    Jie Zhao, Xin Jiang, Xiaoman Wang, Shengfan Wang, Yunhui Liu
    http://arxiv.org/abs/1909.08862v1

    • [cs.RO]Finding Locomanipulation Plans Quickly in the Locomotion Constrained Manifold
    Steven Jens Jorgensen, Mihir Vedantam, Ryan Gupta, Henry Cappel, Luis Sentis
    http://arxiv.org/abs/1909.08804v1

    • [cs.RO]Flexible Disaster Response of Tomorrow — Final Presentation and Evaluation of the CENTAURO System
    Tobias Klamt, Diego Rodriguez, Lorenzo Baccelliere, Xi Chen, Domenico Chiaradia, Torben Cichon, Massimiliano Gabardi, Paolo Guria, Karl Holmquist, Malgorzata Kamedula, Hakan Karaoguz, Navvab Kashiri, Arturo Laurenzi, Christian Lenz, Daniele Leonardis, Enrico Mingo Hoffman, Luca Muratore, Dmytro Pavlichenko, Francesco Porcini, Zeyu Ren, Fabian Schilling, Max Schwarz, Massimiliano Solazzi, Michael Felsberg, Antonio Frisoli, Michael Gustmann, Patric Jensfelt, Klas Nordberg, Jürgen Roßmann, Uwe Süss, Nikos G. Tsagarakis, Sven Behnke
    http://arxiv.org/abs/1909.08812v1

    • [cs.RO]Graph Neural Networks for Human-aware Social Navigation
    Luis J. Manso, Ronit R. Jorvekar, Diego R. Faria, Pablo Bustos, Pilar Bachiller
    http://arxiv.org/abs/1909.09003v1

    • [cs.RO]How to Evaluate Self-Driving Testing Ground? A Quantitative Approach
    Rui Chen, Mansur Arief, Weiyang Zhang, Ding Zhao
    http://arxiv.org/abs/1909.09079v1

    • [cs.RO]Multi-Robot Deep Reinforcement Learning with Macro-Actions
    Yuchen Xiao, Joshua Hoffman, Tian Xia, Christopher Amato
    http://arxiv.org/abs/1909.08776v1

    • [cs.RO]SL1M: Sparse L1-norm Minimization for contact planning on uneven terrain
    Steve Tonneau, Daeun Song, Pierre Fernbach, Nicolas Mansard, Michel Taix, Andrea Del Prete
    http://arxiv.org/abs/1909.09044v1

    • [cs.RO]Vision-Based Proprioceptive Sensing for Soft Inflatable Actuators
    Peter Werner, Matthias Hofer, Carmelo Sferrazza, Raffaello D’Andrea
    http://arxiv.org/abs/1909.09096v1

    • [cs.SI]Community Detection Across Multiple Social Networks based on Overlapping Users
    Ziqing Zhu, Tao Zhou, Chenghao Jia, Jiawei Liu, Jiuxin Cao
    http://arxiv.org/abs/1909.09007v1

    • [cs.SI]DAOC: Stable Clustering of Large Networks
    Artem Lutov, Mourad Khayati, Philippe Cudré-Mauroux
    http://arxiv.org/abs/1909.08786v1

    • [cs.SI]Ensemble approach for generalized network dismantling
    Xiao-Long Ren, Nino Antulov-Fantulin
    http://arxiv.org/abs/1909.09016v1

    • [cs.SI]Moments of Uniform Random Multigraphs with Fixed Degree Sequences
    Philip S. Chodrow
    http://arxiv.org/abs/1909.09037v1

    • [eess.AS]WEnets: A Convolutional Framework for Evaluating Audio Waveforms
    Andrew A. Catellier, Stephen D. Voran
    http://arxiv.org/abs/1909.09024v1

    • [eess.IV]Automated detection of oral pre-cancerous tongue lesions using deep learning for early diagnosis of oral cavity cancer
    Mohammed Zubair M. Shamim, Sadatullah Syed, Mohammad Shiblee, Mohammed Usman, Syed Ali
    http://arxiv.org/abs/1909.08987v1

    • [eess.IV]Efficient Prealignment of CT Scans for Registration through a Bodypart Regressor
    Hans Meine, Alessa Hering
    http://arxiv.org/abs/1909.08898v1

    • [eess.IV]Learning to Avoid Poor Images: Towards Task-aware C-arm Cone-beam CT Trajectories
    Jan-Nico Zaech, Cong Gao, Bastian Bier, Russell Taylor, Andreas Maier, Nassir Navab, Mathias Unberath
    http://arxiv.org/abs/1909.08868v1

    • [eess.IV]PgNN: Physics-guided Neural Network for Fourier Ptychographic Microscopy
    Yongbing Zhang, Yangzhe Liu, Xiu Li, Shaowei Jiang, Krishna Dixit, Xinfeng Zhang, Xiangyang Ji
    http://arxiv.org/abs/1909.08869v1

    • [eess.IV]Prediction of overall survival and molecular markers in gliomas via analysis of digital pathology images using deep learning
    Saima Rathore, Muhammad Aksam Iftikhar, Zissimos Mourelatos
    http://arxiv.org/abs/1909.09124v1

    • [eess.IV]Quantitative Impact of Label Noise on the Quality of Segmentation of Brain Tumors on MRI scans
    Michał Marcinkiewicz, Grzegorz Mrukwa
    http://arxiv.org/abs/1909.08959v1

    • [eess.IV]Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer’s disease classification
    Fabian Eitel, Kerstin Ritter
    http://arxiv.org/abs/1909.08856v1

    • [eess.SP]APIR-Net: Autocalibrated Parallel Imaging Reconstruction using a Neural Network
    Chaoping Zhang, Florian Dubost, Marleen de Bruijne, Stefan Klein, Dirk H. J. Poot
    http://arxiv.org/abs/1909.09006v1

    • [eess.SY]On the observability of relative positions in left-invariant multi-agent control systems and its application to formation control
    Leonardo Colombo, Hector Garcia de Marina, María Barbero Liñán, David Martín de Diego
    http://arxiv.org/abs/1909.08914v1

    • [math-ph]Perfect quantum state transfer on diamond fractal graphs
    Maxim Derevyagin, Gerald V. Dunne, Gamal Mograby, Alexander Teplyaev
    http://arxiv.org/abs/1909.08668v1

    • [math.FA]Almost Everywhere Generalized Phase Retrieval
    Meng Huang, Yi Rong, Yang Wang, Zhiqiang Xu
    http://arxiv.org/abs/1909.08874v1

    • [math.ST]Collective sampling through a Metropolis-Hastings like method: kinetic theory and numerical experiments
    Grégoire Clarté, Antoine Diez
    http://arxiv.org/abs/1909.08988v1

    • [math.ST]Generalized Resilience and Robust Statistics
    Banghua Zhu, Jiantao Jiao, Jacob Steinhardt
    http://arxiv.org/abs/1909.08755v1

    • [math.ST]Multivariate Rank-based Distribution-free Nonparametric Testing using Measure Transportation
    Nabarun Deb, Bodhisattva Sen
    http://arxiv.org/abs/1909.08733v1

    • [physics.soc-ph]Collapse of Social Engagement and its Prevention by Local Recruitments
    Shang-Nan Wang, Luan Cheng, Hai-Jun Zhou
    http://arxiv.org/abs/1909.08926v1

    • [physics.soc-ph]Detecting social (in)stability in primates from their temporal co-presence network
    Valeria Gelardi, Joël Fagot, Alain Barrat, Nicolas Claidière
    http://arxiv.org/abs/1909.09090v1

    • [physics.soc-ph]Segregation Dynamics with Reinforcement Learning and Agent Based Modeling
    Egemen Sert, Yaneer Bar-Yam, Alfredo J. Morales
    http://arxiv.org/abs/1909.08711v1

    • [q-bio.PE]Improving inference for nonlinear state-space models of animal population dynamics given biased sequential life stage data
    Leo Polansky, Ken B. Newman, Lara Mitchell
    http://arxiv.org/abs/1909.09111v1

    • [q-fin.GN]Corruption Risk in Contracting Markets: A Network Science Perspective
    Johannes Wachs, Mihály Fazekas, János Kertész
    http://arxiv.org/abs/1909.08664v1

    • [stat.ME]Bayesian Analysis of Multidimensional Functional Data
    John Shamshoian, Damla Senturk, Shafali Jeste, Donatello Telesca
    http://arxiv.org/abs/1909.08763v1

    • [stat.ME]Semantic and Cognitive Tools to Aid Statistical Inference: Replace Confidence and Significance by Compatibility and Surprise
    Zad R. Chow, Sander Greenland
    http://arxiv.org/abs/1909.08579v2

    • [stat.ME]To Aid Statistical Inference, Emphasize Unconditional Descriptions of Statistics
    Sander Greenland, Zad R. Chow
    http://arxiv.org/abs/1909.08583v2

    • [stat.ML]Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks
    Sekitoshi Kanai, Yasutoshi Ida, Yasuhiro Fujiwara, Masanori Yamada, Shuichi Adachi
    http://arxiv.org/abs/1909.08830v1

    • [stat.ML]Explaining Visual Models by Causal Attribution
    Álvaro Parafita, Jordi Vitrià
    http://arxiv.org/abs/1909.08891v1

    • [stat.ML]On Efficient Multilevel Clustering via Wasserstein Distances
    Viet Huynh, Nhat Ho, Nhan Dam, XuanLong Nguyen, Mikhail Yurochkin, Hung Bui, and Dinh Phung
    http://arxiv.org/abs/1909.08787v1

    • [stat.ML]Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models
    Vincent Le Guen, Nicolas Thome
    http://arxiv.org/abs/1909.09020v1

    • [stat.ML]Value function estimation in Markov reward processes: Instance-dependent $\ell_\infty$-bounds for policy evaluation
    Ashwin Pananjady, Martin J. Wainwright
    http://arxiv.org/abs/1909.08749v1