cond-mat.mtrl-sci - 材料科学

    cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.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.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.ST - 统计理论 physics.soc-ph - 物理学与社会 q-bio.QM - 定量方法 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cond-mat.mtrl-sci]Leveraging Legacy Data to Accelerate Materials Design via Preference Learning
    • [cs.AI]Deep Reinforcement Learning in HOL4
    • [cs.CL]A Unified MRC Framework for Named Entity Recognition
    • [cs.CL]Attention Optimization for Abstractive Document Summarization
    • [cs.CL]Capacity, Bandwidth, and Compositionality in Emergent Language Learning
    • [cs.CL]DENS: A Dataset for Multi-class Emotion Analysis
    • [cs.CL]Evaluation of Sentence Representations in Polish
    • [cs.CL]Exploring Multilingual Syntactic Sentence Representations
    • [cs.CL]Generating a Common Question from Multiple Documents using Multi-source Encoder-Decoder Models
    • [cs.CL]L2RS: A Learning-to-Rescore Mechanism for Automatic Speech Recognition
    • [cs.CL]Machine Translation from Natural Language to Code using Long-Short Term Memory
    • [cs.CL]Measuring Conversational Fluidity in Automated Dialogue Agents
    • [cs.CL]Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection
    • [cs.CL]On the Cross-lingual Transferability of Monolingual Representations
    • [cs.CL]Predicting In-game Actions From the Language of NBA Players
    • [cs.CL]SpeechBERT: Cross-Modal Pre-trained Language Model for End-to-end Spoken Question Answering
    • [cs.CL]Stem-driven Language Models for Morphologically Rich Languages
    • [cs.CL]The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection
    • [cs.CR]Substra: a framework for privacy-preserving, traceable and collaborative Machine Learning
    • [cs.CV]A comparable study: Intrinsic difficulties of practical plant diagnosis from wide-angle images
    • [cs.CV]ALET (Automated Labeling of Equipment and Tools): A Dataset, a Baseline and a Usecase for Tool Detection in the Wild
    • [cs.CV]An End-to-End Foreground-Aware Network for Person Re-Identification
    • [cs.CV]An End-to-End Network for Co-Saliency Detection in One Single Image
    • [cs.CV]Attend to the Difference: Cross-Modality Person Re-identification via Contrastive Correlation
    • [cs.CV]ClsGAN: Selective Attribute Editing Based On Classification Adversarial Network
    • [cs.CV]CrevNet: Conditionally Reversible Video Prediction
    • [cs.CV]Deep Image Blending
    • [cs.CV]Gated Multi-layer Convolutional Feature Extraction Network for Robust Pedestrian Detection
    • [cs.CV]Hardware-aware One-Shot Neural Architecture Search in Coordinate Ascent Framework
    • [cs.CV]JRDB: A Dataset and Benchmark for Visual Perception for Navigation in Human Environments
    • [cs.CV]LPRNet: Lightweight Deep Network by Low-rank Pointwise Residual Convolution
    • [cs.CV]Learning an Uncertainty-Aware Object Detector for Autonomous Driving
    • [cs.CV]Learning to Localize Temporal Events in Large-scale Video Data
    • [cs.CV]Learning to Track Any Object
    • [cs.CV]Metric Classification Network in Actual Face Recognition Scene
    • [cs.CV]Progressive Unsupervised Person Re-identification by Tracklet Association with Spatio-Temporal Regularization
    • [cs.CV]Real-time Memory Efficient Large-pose Face Alignment via Deep Evolutionary Network
    • [cs.CV]Reducing Domain Gap via Style-Agnostic Networks
    • [cs.CV]RhythmNet: End-to-end Heart Rate Estimation from Face via Spatial-temporal Representation
    • [cs.CV]Self-supervised Learning of Detailed 3D Face Reconstruction
    • [cs.CV]Self-supervised Moving Vehicle Tracking with Stereo Sound
    • [cs.CV]TRB: A Novel Triplet Representation for Understanding 2D Human Body
    • [cs.CV]Team PFDet’s Methods for Open Images Challenge 2019
    • [cs.CV]Toward an Automatic System for Computer-Aided Assessment in Facial Palsy
    • [cs.CY]Assessing the Adoption of Virtual Learning Environments in Primary Schools: An Activity Oriented Study of Teacher’s Acceptance
    • [cs.DC]Massively Parallel Algorithms for String Matching with Wildcards
    • [cs.DC]Rare Event Simulation for non-Markovian repairable Fault Trees
    • [cs.DC]The Scalability for Parallel Machine Learning Training Algorithm: Dataset Matters
    • [cs.GT]Coalitional Games with Stochastic Characteristic Functions and Private Types
    • [cs.HC]A Robot’s Expressive Language Affects Human Strategy and Perceptions in a Competitive Game
    • [cs.HC]Mixing realities for sketch retrieval in Virtual Reality
    • [cs.IR]A Review of the End-to-End Methodologies for Clinical Concept Extraction
    • [cs.IR]Fast and Accurate Knowledge-Aware Document Representation Enhancement for News Recommendations
    • [cs.IT]Double-Sparsity Learning Based Channel-and-Signal Estimation in Massive MIMO with Generalized Spatial Modulation
    • [cs.IT]Peterson-Gorenstein-Zierler algorithm for differential convolutional codes
    • [cs.IT]Phase Retrieval of Low-Rank Matrices by Anchored Regression
    • [cs.LG]A Gegenbauer Neural Network with Regularized Weights Direct Determination for Classification
    • [cs.LG]A Simple Dynamic Learning Rate Tuning Algorithm For Automated Training of DNNs
    • [cs.LG]An End-to-End HW/SW Co-Design Methodology to Design Efficient Deep Neural Network Systems using Virtual Models
    • [cs.LG]BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
    • [cs.LG]Causal inference for climate change events from satellite image time series using computer vision and deep learning
    • [cs.LG]Deep 1D-Convnet for accurate Parkinson disease detection from gait
    • [cs.LG]Descriptive Dimensionality and Its Characterization of MDL-based Learning and Change Detection
    • [cs.LG]Fairness Sample Complexity and the Case for Human Intervention
    • [cs.LG]Fast Structured Decoding for Sequence Models
    • [cs.LG]Feature Selection and Extraction for Graph Neural Networks
    • [cs.LG]HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators
    • [cs.LG]Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling
    • [cs.LG]Human Action Recognition Using Deep Multilevel Multimodal (M2) Fusion of Depth and Inertial Sensors
    • [cs.LG]Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training?
    • [cs.LG]Learning Mixtures of Plackett-Luce Models from Structured Partial Orders
    • [cs.LG]Limits of Private Learning with Access to Public Data
    • [cs.LG]MediaEval 2019: Concealed FGSM Perturbations for Privacy Preservation
    • [cs.LG]Multi-scale Deep Neural Networks for Solving High Dimensional PDEs
    • [cs.LG]On the Tunability of Optimizers in Deep Learning
    • [cs.LG]Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations
    • [cs.LG]Platoon trajectories generation: A unidirectional interconnected LSTM-based car following model
    • [cs.LG]Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior
    • [cs.LG]Stabilizing DARTS with Amended Gradient Estimation on Architectural Parameters
    • [cs.LG]Strong Log-Concavity Does Not Imply Log-Submodularity
    • [cs.LG]Study of Deep Generative Models for Inorganic Chemical Compositions
    • [cs.LG]Toward a better trade-off between performance and fairness with kernel-based distribution matching
    • [cs.LG]Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets
    • [cs.LO]Simple Strategies in Multi-Objective MDPs (Technical Report)
    • [cs.NE]Improvement of the Izhikevich model based on the rat basolateral amygdala and hippocampus neurons, and recognition of their possible firing patterns
    • [cs.RO]AeroVR: Virtual Reality-based Teleoperation with Tactile Feedback for Aerial Manipulation
    • [cs.RO]Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning
    • [cs.RO]DQ Robotics: a Library for Robot Modeling and Control Using Dual Quaternion Algebra
    • [cs.RO]Learning Task-Oriented Grasping from Human Activity Datasets
    • [cs.RO]Retraction of Soft Growing Robots without Buckling
    • [cs.RO]Rhoban Football Club: RoboCup Humanoid KidSize 2019 Champion Team Paper
    • [cs.RO]Task-Motion Planning for Navigation in Belief Space
    • [cs.SD]Channel adversarial training for speaker verification and diarization
    • [cs.SD]SeCoST: Sequential Co-Supervision for Weakly Labeled Audio Event Detection
    • [cs.SI]Asymmetry in interdependence makes a multilayer system more robust against cascading failures
    • [cs.SI]Detecting Fake News with Weak Social Supervision
    • [cs.SI]Manipulating Node Similarity Measures in Network
    • [eess.AS]A Multi-Phase Gammatone Filterbank for Speech Separation via TasNet
    • [eess.AS]SPICE: Self-supervised Pitch Estimation
    • [eess.AS]Structural sparsification for Far-field Speaker Recognition with GNA
    • [eess.IV]DR$\vert$GRADUATE: uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images
    • [eess.SP]Classification of Mobile Services and Apps through Physical Channel Fingerprinting: a Deep Learning Approach
    • [eess.SP]Computation Efficiency Maximization in OFDMA-Based Mobile Edge Computing Networks
    • [eess.SP]Joint Source-Channel Coding and Bayesian Message Passing Detection for Grant-Free Radio Access in IoT
    • [eess.SP]Underwater Cooperative MIMO Communications using Hybrid Acoustic and Magnetic Induction Technique
    • [math.NA]Convergence Analysis of the Randomized Newton Method with Determinantal Sampling
    • [math.NA]Weighted Quasi Interpolant Spline Approximations: Properties and Applications
    • [math.OC]A distributed proximal-point algorithm for Nash equilibrium seeking under partial-decision information with geometric convergence
    • [math.OC]Information Flow Optimization in Inference Networks
    • [math.OC]Mirror Natural Evolution Strategies
    • [math.ST]Extremal clustering in non-stationary random sequences
    • [math.ST]Information Theoretic Limits for Phase Retrieval with Subsampled Haar Sensing Matrices
    • [math.ST]Joint estimation for volatility and drift parameters of ergodic jump diffusion processes via contrast function
    • [math.ST]On agnostic post hoc approaches to false positive control
    • [physics.soc-ph]Bayesian Modeling of Random Walker for Community Detection in Networks
    • [physics.soc-ph]Generating large scale-free networks with the Chung-Lu random graph model
    • [physics.soc-ph]Modeling vehicular mobility patterns using recurrent neural networks
    • [physics.soc-ph]Time Series Vector Autoregression Prediction of the Ecological Footprint based on Energy Parameters
    • [physics.soc-ph]Toward epidemic thresholds on temporal networks: a review and open questions
    • [q-bio.QM]Minimum Information guidelines for fluorescence microscopy: increasing the value, quality, and fidelity of image data
    • [stat.AP]A Simple Descriptive Method & Standard for Comparing Pairs of Stacked Bar Graphs
    • [stat.AP]Almost Politically Acceptable Criminal Justice Risk Assessment
    • [stat.AP]Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting
    • [stat.AP]Calibration of computer models with heteroscedastic errors and application to plant relative growth rates
    • [stat.ME]Bayesian epidemiological modeling over high-resolution network data
    • [stat.ME]Finite Mixtures of ERGMs for Ensembles of Networks
    • [stat.ME]Quantile Regression Modelling via Location and Scale Mixtures of Normal Distributions
    • [stat.ME]The covariate-adjusted residual estimator and its use in both randomized trials and observational settings
    • [stat.ME]Unified model selection approach based on minimum description length principle in Granger causality analysis
    • [stat.ML]Bias-Variance Tradeoff in a Sliding Window Implementation of the Stochastic Gradient Algorithm
    • [stat.ML]Calibration tests in multi-class classification: A unifying framework
    • [stat.ML]Online Gaussian LDA for Unsupervised Pattern Mining from Utility Usage Data
    • [stat.ML]Robust Principal Component Analysis Based On Maximum Correntropy Power Iterations
    • [stat.ML]Structured Prediction with Projection Oracles
    • [stat.ML]Towards Robust and Stable Deep Learning Algorithms for Forward Backward Stochastic Differential Equations
    • [stat.ML]Unsupervised Space-Time Clustering using Persistent Homology

    ·····································

    • [cond-mat.mtrl-sci]Leveraging Legacy Data to Accelerate Materials Design via Preference Learning
    Xiaolin Sun, Zhufeng Hou, Masato Sumita, Shinsuke Ishihara, Ryo Tamura, Koji Tsuda
    http://arxiv.org/abs/1910.11516v1

    • [cs.AI]Deep Reinforcement Learning in HOL4
    Thibault Gauthier
    http://arxiv.org/abs/1910.11797v1

    • [cs.CL]A Unified MRC Framework for Named Entity Recognition
    Xiaoya Li, Jingrong Feng, Yuxian Meng, Qinghong Han, Fei Wu, Jiwei Li
    http://arxiv.org/abs/1910.11476v1

    • [cs.CL]Attention Optimization for Abstractive Document Summarization
    Min Gui, Junfeng Tian, Rui Wang, Zhenglu Yang
    http://arxiv.org/abs/1910.11491v1

    • [cs.CL]Capacity, Bandwidth, and Compositionality in Emergent Language Learning
    Cinjon Resnick, Abhinav Gupta, Jakob Foerster, Andrew M. Dai, Kyunghyun Cho
    http://arxiv.org/abs/1910.11424v1

    • [cs.CL]DENS: A Dataset for Multi-class Emotion Analysis
    Chen Liu, Muhammad Osama, Anderson de Andrade
    http://arxiv.org/abs/1910.11769v1

    • [cs.CL]Evaluation of Sentence Representations in Polish
    Sławomir Dadas, Michał Perełkiewicz, Rafał Poświata
    http://arxiv.org/abs/1910.11834v1

    • [cs.CL]Exploring Multilingual Syntactic Sentence Representations
    Chen Liu, Anderson de Andrade, Muhammad Osama
    http://arxiv.org/abs/1910.11768v1

    • [cs.CL]Generating a Common Question from Multiple Documents using Multi-source Encoder-Decoder Models
    Woon Sang Cho, Yizhe Zhang, Sudha Rao, Chris Brockett, Sungjin Lee
    http://arxiv.org/abs/1910.11483v1

    • [cs.CL]L2RS: A Learning-to-Rescore Mechanism for Automatic Speech Recognition
    Yuanfeng Song, Di Jiang, Xuefang Zhao, Qian Xu, Raymond Chi-Wing Wong, Lixin Fan, Qiang Yang
    http://arxiv.org/abs/1910.11496v1

    • [cs.CL]Machine Translation from Natural Language to Code using Long-Short Term Memory
    K. M. Tahsin Hassan Rahit, Rashidul Hasan Nabil, Md Hasibul Huq
    http://arxiv.org/abs/1910.11471v1

    • [cs.CL]Measuring Conversational Fluidity in Automated Dialogue Agents
    Keith Vella, Massimo Poesio, Michael Sigamani, Cihan Dogan, Aimore Dutra, Dimitrios Dimakopoulos, Alfredo Gemma, Ella Walters
    http://arxiv.org/abs/1910.11790v1

    • [cs.CL]Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection
    Shumin Deng, Ningyu Zhang, Jiaojian Kang, Yichi Zhang, Wei Zhang, Huajun Chen
    http://arxiv.org/abs/1910.11621v1

    • [cs.CL]On the Cross-lingual Transferability of Monolingual Representations
    Mikel Artetxe, Sebastian Ruder, Dani Yogatama
    http://arxiv.org/abs/1910.11856v1

    • [cs.CL]Predicting In-game Actions From the Language of NBA Players
    Nadav Oved, Amir Feder, Roi Reichart
    http://arxiv.org/abs/1910.11292v2

    • [cs.CL]SpeechBERT: Cross-Modal Pre-trained Language Model for End-to-end Spoken Question Answering
    Yung-Sung Chuang, Chi-Liang Liu, Hung-Yi Lee
    http://arxiv.org/abs/1910.11559v1

    • [cs.CL]Stem-driven Language Models for Morphologically Rich Languages
    Yash Shah, Ishan Tarunesh, Harsh Deshpande, Preethi Jyothi
    http://arxiv.org/abs/1910.11536v1

    • [cs.CL]The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection
    Arya D. McCarthy, Ekaterina Vylomova, Shijie Wu, Chaitanya Malaviya, Lawrence Wolf-Sonkin, Garrett Nicolai, Christo Kirov, Miikka Silfverberg, Sebastian J. Mielke, Jeffrey Heinz, Ryan Cotterell, Mans Hulden
    http://arxiv.org/abs/1910.11493v1

    • [cs.CR]Substra: a framework for privacy-preserving, traceable and collaborative Machine Learning
    Mathieu N Galtier, Camille Marini
    http://arxiv.org/abs/1910.11567v1

    • [cs.CV]A comparable study: Intrinsic difficulties of practical plant diagnosis from wide-angle images
    Katsumasa Suwa, Quan Huu Cap, Ryunosuke Kotani, Hiroyuki Uga, Satoshi Kagiwada, Hitoshi Iyatomi
    http://arxiv.org/abs/1910.11506v1

    • [cs.CV]ALET (Automated Labeling of Equipment and Tools): A Dataset, a Baseline and a Usecase for Tool Detection in the Wild
    Fatih Can Kurnaz, Burak Hocaoğlu, Mert Kaan Yılmaz, İdil Sülo, Sinan Kalkan
    http://arxiv.org/abs/1910.11713v1

    • [cs.CV]An End-to-End Foreground-Aware Network for Person Re-Identification
    Yiheng Liu, Wengang Zhou, Jianzhuang Liu, Guojun Qi, Qi Tian, Houqiang Li
    http://arxiv.org/abs/1910.11547v1

    • [cs.CV]An End-to-End Network for Co-Saliency Detection in One Single Image
    Yuanhao Yue, Qin Zou, Hongkai Yu, Qian Wang, Song Wang
    http://arxiv.org/abs/1910.11819v1

    • [cs.CV]Attend to the Difference: Cross-Modality Person Re-identification via Contrastive Correlation
    Shizhou Zhang, Yifei Yang, Peng Wang, Xiuwei Zhang, Yanning Zhang
    http://arxiv.org/abs/1910.11656v1

    • [cs.CV]ClsGAN: Selective Attribute Editing Based On Classification Adversarial Network
    Liu Ying, Heng Fan, Fuchuan Ni, Jinhai Xiang
    http://arxiv.org/abs/1910.11764v1

    • [cs.CV]CrevNet: Conditionally Reversible Video Prediction
    Wei Yu, Yichao Lu, Steve Easterbrook, Sanja Fidler
    http://arxiv.org/abs/1910.11577v1

    • [cs.CV]Deep Image Blending
    Lingzhi Zhang, Tarmily Wen, Jianbo Shi
    http://arxiv.org/abs/1910.11495v1

    • [cs.CV]Gated Multi-layer Convolutional Feature Extraction Network for Robust Pedestrian Detection
    Tianrui Liu, Jun-Jie Huang, Tianhong Dai, Guangyu Ren, Tania Stathaki
    http://arxiv.org/abs/1910.11761v1

    • [cs.CV]Hardware-aware One-Shot Neural Architecture Search in Coordinate Ascent Framework
    Li Lyna Zhang, Yuqing Yang, Yuhang Jiang, Wenwu Zhu, Yunxin Liu
    http://arxiv.org/abs/1910.11609v1

    • [cs.CV]JRDB: A Dataset and Benchmark for Visual Perception for Navigation in Human Environments
    Roberto Martín-Martín, Hamid Rezatofighi, Abhijeet Shenoi, Mihir Patel, JunYoung Gwak, Nathan Dass, Alan Federman, Patrick Goebel, Silvio Savarese
    http://arxiv.org/abs/1910.11792v1

    • [cs.CV]LPRNet: Lightweight Deep Network by Low-rank Pointwise Residual Convolution
    Bin Sun, Jun Li, Ming Shao, Yun Fu
    http://arxiv.org/abs/1910.11853v1

    • [cs.CV]Learning an Uncertainty-Aware Object Detector for Autonomous Driving
    Gregory P. Meyer, Niranjan Thakurdesai
    http://arxiv.org/abs/1910.11375v1

    • [cs.CV]Learning to Localize Temporal Events in Large-scale Video Data
    Mikel Bober-Irizar, Miha Skalic, David Austin
    http://arxiv.org/abs/1910.11631v1

    • [cs.CV]Learning to Track Any Object
    Achal Dave, Pavel Tokmakov, Cordelia Schmid, Deva Ramanan
    http://arxiv.org/abs/1910.11844v1

    • [cs.CV]Metric Classification Network in Actual Face Recognition Scene
    Jian Li, Yan Wang, Xiubao Zhang, Weihong Deng, Haifeng Shen
    http://arxiv.org/abs/1910.11563v1

    • [cs.CV]Progressive Unsupervised Person Re-identification by Tracklet Association with Spatio-Temporal Regularization
    Qiaokang Xie, Wengang Zhou, Guo-Jun Qi, Qi Tian, Houqiang Li
    http://arxiv.org/abs/1910.11560v1

    • [cs.CV]Real-time Memory Efficient Large-pose Face Alignment via Deep Evolutionary Network
    Bin Sun, Ming Shao, Siyu Xia, Yun Fu
    http://arxiv.org/abs/1910.11818v1

    • [cs.CV]Reducing Domain Gap via Style-Agnostic Networks
    Hyeonseob Nam, HyunJae Lee, Jongchan Park, Wonjun Yoon, Donggeun Yoo
    http://arxiv.org/abs/1910.11645v1

    • [cs.CV]RhythmNet: End-to-end Heart Rate Estimation from Face via Spatial-temporal Representation
    Xuesong Niu, Hu Han, Shiguang Shan, Xilin Chen
    http://arxiv.org/abs/1910.11515v1

    • [cs.CV]Self-supervised Learning of Detailed 3D Face Reconstruction
    Yajing Chen, Fanzi Wu, Zeyu Wang, Yibing Song, Yonggen Ling, Linchao Bao
    http://arxiv.org/abs/1910.11791v1

    • [cs.CV]Self-supervised Moving Vehicle Tracking with Stereo Sound
    Chuang Gan, Hang Zhao, Peihao Chen, David Cox, Antonio Torralba
    http://arxiv.org/abs/1910.11760v1

    • [cs.CV]TRB: A Novel Triplet Representation for Understanding 2D Human Body
    Haodong Duan, KwanYee Lin, Sheng Jin, Wentao Liu, Chen Qian, Wanli Ouyang
    http://arxiv.org/abs/1910.11535v1

    • [cs.CV]Team PFDet’s Methods for Open Images Challenge 2019
    Yusuke Niitani, Toru Ogawa, Shuji Suzuki, Takuya Akiba, Tommi Kerola, Kohei Ozaki, Shotaro Sano
    http://arxiv.org/abs/1910.11534v1

    • [cs.CV]Toward an Automatic System for Computer-Aided Assessment in Facial Palsy
    Diego L. Guarin, Yana Yunusova, Babak Taati, Joseph R Dusseldorp, Suresh Mohan, Joana Tavares, Martinus M. van Veen, Emily Fortier, Tessa A. Hadlock, Nate Jowett
    http://arxiv.org/abs/1910.11497v1

    • [cs.CY]Assessing the Adoption of Virtual Learning Environments in Primary Schools: An Activity Oriented Study of Teacher’s Acceptance
    Elena Codreanu, Christine Michel, Marc-Eric Bobillier-Chaumon, Olivier Vigneau
    http://arxiv.org/abs/1910.11601v1

    • [cs.DC]Massively Parallel Algorithms for String Matching with Wildcards
    MohammadTaghi Hajiaghayi, Hamed Saleh, Saeed Seddighin, Xiaorui Sun
    http://arxiv.org/abs/1910.11829v1

    • [cs.DC]Rare Event Simulation for non-Markovian repairable Fault Trees
    Carlos E. Budde, Marco Biagi, Raúl E. Monti, Pedro R. D’Argenio, Mariëlle Stoelinga
    http://arxiv.org/abs/1910.11672v1

    • [cs.DC]The Scalability for Parallel Machine Learning Training Algorithm: Dataset Matters
    Cheng Daning, Zhang Hanping, Xia Fen, Li Shigang, Zhang Yunquan
    http://arxiv.org/abs/1910.11510v1

    • [cs.GT]Coalitional Games with Stochastic Characteristic Functions and Private Types
    Dengji Zhao, Yiqing Huang, Liat Cohen, Tal Grinshpoun
    http://arxiv.org/abs/1910.11737v1

    • [cs.HC]A Robot’s Expressive Language Affects Human Strategy and Perceptions in a Competitive Game
    Aaron M. Roth, Samantha Reig, Umang Bhatt, Jonathan Shulgach, Tamara Amin, Afsaneh Doryab, Fei Fang, Manuela Veloso
    http://arxiv.org/abs/1910.11459v1

    • [cs.HC]Mixing realities for sketch retrieval in Virtual Reality
    Daniele Giunchi, Stuart james, Donald Degraen, Anthony Steed
    http://arxiv.org/abs/1910.11637v1

    • [cs.IR]A Review of the End-to-End Methodologies for Clinical Concept Extraction
    Sunyang Fu, David Chen, Sijia Liu, Sungrim Moon, Kevin J Peterson, Feichen Shen, Yanshan Wang, Liwei Wang, Andrew Wen, Yiqing Zhao, Sunghwan Sohn, Hongfang Liu
    http://arxiv.org/abs/1910.11377v1

    • [cs.IR]Fast and Accurate Knowledge-Aware Document Representation Enhancement for News Recommendations
    Danyang Liu, Jianxun Lian, Ying Qiao, Jiun-Hung Chen, Guangzhong Sun, Xing Xie
    http://arxiv.org/abs/1910.11494v1

    • [cs.IT]Double-Sparsity Learning Based Channel-and-Signal Estimation in Massive MIMO with Generalized Spatial Modulation
    Xiaoyan Kuai, Xiaojun Yuan, Wenjing Yan, Hang Liu, Ying Jun, Zhang
    http://arxiv.org/abs/1910.11504v1

    • [cs.IT]Peterson-Gorenstein-Zierler algorithm for differential convolutional codes
    José Gómez-Torrecillas, F. J. Lobillo, Gabriel Navarro, José Patricio Sánchez-Hernández
    http://arxiv.org/abs/1910.11574v1

    • [cs.IT]Phase Retrieval of Low-Rank Matrices by Anchored Regression
    Kiryung Lee, Sohail Bahmani, Yonina Eldar, Justin Romberg
    http://arxiv.org/abs/1910.11477v1

    • [cs.LG]A Gegenbauer Neural Network with Regularized Weights Direct Determination for Classification
    Jie He, Tao Chen, Zhijun Zhang
    http://arxiv.org/abs/1910.11552v1

    • [cs.LG]A Simple Dynamic Learning Rate Tuning Algorithm For Automated Training of DNNs
    Koyel Mukherjee, Alind Khare, Ashish Verma
    http://arxiv.org/abs/1910.11605v1

    • [cs.LG]An End-to-End HW/SW Co-Design Methodology to Design Efficient Deep Neural Network Systems using Virtual Models
    Michael J. Klaiber, Sebastian Vogel, Axel Acosta, Robert Korn, Leonardo Ecco, Kristine Back, Andre Guntoro, Ingo Feldner
    http://arxiv.org/abs/1910.11632v1

    • [cs.LG]BANANAS: Bayesian Optimization with Neural Architectures for Neural Architecture Search
    Colin White, Willie Neiswanger, Yash Savani
    http://arxiv.org/abs/1910.11858v1

    • [cs.LG]Causal inference for climate change events from satellite image time series using computer vision and deep learning
    Vikas Ramachandra
    http://arxiv.org/abs/1910.11492v1

    • [cs.LG]Deep 1D-Convnet for accurate Parkinson disease detection from gait
    Imanne El Maachi, Guillaume-Alexandre Bilodeau, Wassim Bouachir
    http://arxiv.org/abs/1910.11509v1

    • [cs.LG]Descriptive Dimensionality and Its Characterization of MDL-based Learning and Change Detection
    Kenji Yamanishi
    http://arxiv.org/abs/1910.11540v1

    • [cs.LG]Fairness Sample Complexity and the Case for Human Intervention
    Ananth Balashankar, Alyssa Lees
    http://arxiv.org/abs/1910.11452v1

    • [cs.LG]Fast Structured Decoding for Sequence Models
    Zhiqing Sun, Zhuohan Li, Haoqing Wang, Zi Lin, Di He, Zhi-Hong Deng
    http://arxiv.org/abs/1910.11555v1

    • [cs.LG]Feature Selection and Extraction for Graph Neural Networks
    Deepak Bhaskar Acharya, Dr. Huaming Zhang
    http://arxiv.org/abs/1910.10682v2

    • [cs.LG]HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators
    Chengshu Li, Fei Xia, Roberto Martin-Martin, Silvio Savarese
    http://arxiv.org/abs/1910.11432v1

    • [cs.LG]Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling
    Filippo Maria Bianchi, Daniele Grattarola, Lorenzo Livi, Cesare Alippi
    http://arxiv.org/abs/1910.11436v1

    • [cs.LG]Human Action Recognition Using Deep Multilevel Multimodal (M2) Fusion of Depth and Inertial Sensors
    Zeeshan Ahmad, Naimul Khan
    http://arxiv.org/abs/1910.11482v1

    • [cs.LG]Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training?
    Ali Shafahi, Amin Ghiasi, Furong Huang, Tom Goldstein
    http://arxiv.org/abs/1910.11585v1

    • [cs.LG]Learning Mixtures of Plackett-Luce Models from Structured Partial Orders
    Zhibing Zhao, Lirong Xia
    http://arxiv.org/abs/1910.11721v1

    • [cs.LG]Limits of Private Learning with Access to Public Data
    Noga Alon, Raef Bassily, Shay Moran
    http://arxiv.org/abs/1910.11519v1

    • [cs.LG]MediaEval 2019: Concealed FGSM Perturbations for Privacy Preservation
    Panagiotis Linardos, Suzanne Little, Kevin McGuinness
    http://arxiv.org/abs/1910.11603v1

    • [cs.LG]Multi-scale Deep Neural Networks for Solving High Dimensional PDEs
    Wei Cai, Zhi-Qin John Xu
    http://arxiv.org/abs/1910.11710v1

    • [cs.LG]On the Tunability of Optimizers in Deep Learning
    Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret
    http://arxiv.org/abs/1910.11758v1

    • [cs.LG]Over Parameterized Two-level Neural Networks Can Learn Near Optimal Feature Representations
    Cong Fang, Hanze Dong, Tong Zhang
    http://arxiv.org/abs/1910.11508v1

    • [cs.LG]Platoon trajectories generation: A unidirectional interconnected LSTM-based car following model
    Yangxin Lin, Ping Wang, Yang Zhou, Fan Ding, Chen Wang, Huachun Tan
    http://arxiv.org/abs/1910.11843v1

    • [cs.LG]Rationally Inattentive Inverse Reinforcement Learning Explains YouTube Commenting Behavior
    William Hoiles, Vikram Krishnamurthy, Kunal Pattanayak
    http://arxiv.org/abs/1910.11703v1

    • [cs.LG]Stabilizing DARTS with Amended Gradient Estimation on Architectural Parameters
    Kaifeng Bi, Changping Hu, Lingxi Xie, Xin Chen, Longhui Wei, Qi Tian
    http://arxiv.org/abs/1910.11831v1

    • [cs.LG]Strong Log-Concavity Does Not Imply Log-Submodularity
    Alkis Gotovos
    http://arxiv.org/abs/1910.11544v1

    • [cs.LG]Study of Deep Generative Models for Inorganic Chemical Compositions
    Yoshihide Sawada, Koji Morikawa, Mikiya Fujii
    http://arxiv.org/abs/1910.11499v1

    • [cs.LG]Toward a better trade-off between performance and fairness with kernel-based distribution matching
    Flavien Prost, Hai Qian, Qiuwen Chen, Ed H. Chi, Jilin Chen, Alex Beutel
    http://arxiv.org/abs/1910.11779v1

    • [cs.LG]Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets
    Esma Balkir, Masha Naslidnyk, Dave Palfrey, Arpit Mittal
    http://arxiv.org/abs/1910.11583v1

    • [cs.LO]Simple Strategies in Multi-Objective MDPs (Technical Report)
    Florent Delgrange, Joost-Pieter Katoen, Tim Quatmann, Mickael Randour
    http://arxiv.org/abs/1910.11024v2

    • [cs.NE]Improvement of the Izhikevich model based on the rat basolateral amygdala and hippocampus neurons, and recognition of their possible firing patterns
    Sahar Hojjatinia, Mahdi Aliyari Shoorehdeli, Zahra Fatahi, Zeinab Hojjatinia, Abbas Haghparast
    http://arxiv.org/abs/1910.11380v1

    • [cs.RO]AeroVR: Virtual Reality-based Teleoperation with Tactile Feedback for Aerial Manipulation
    Grigoriy A. Yashin, Daria Trinitatova, Ruslan T. Agishev, Roman Ibrahimov, Dzmitry Tsetserukou
    http://arxiv.org/abs/1910.11604v1

    • [cs.RO]Collision Avoidance in Pedestrian-Rich Environments with Deep Reinforcement Learning
    Michael Everett, Yu Fan Chen, Jonathan P. How
    http://arxiv.org/abs/1910.11689v1

    • [cs.RO]DQ Robotics: a Library for Robot Modeling and Control Using Dual Quaternion Algebra
    Bruno Vilhena Adorno, Murilo Marques Marinho
    http://arxiv.org/abs/1910.11612v1

    • [cs.RO]Learning Task-Oriented Grasping from Human Activity Datasets
    Mia Kokic, Danica Kragic, Jeannette Bohg
    http://arxiv.org/abs/1910.11669v1

    • [cs.RO]Retraction of Soft Growing Robots without Buckling
    Margaret M. Coad, Rachel P. Thomasson, Laura H. Blumenschein, Nathan S. Usevitch, Elliot W. Hawkes, Allison M. Okamura
    http://arxiv.org/abs/1910.11863v1

    • [cs.RO]Rhoban Football Club: RoboCup Humanoid KidSize 2019 Champion Team Paper
    Loic Gondry, Ludovic Hofer, Patxi Laborde-Zubieta, Olivier Ly, Lucie Mathé, Grégoire Passault, Antoine Pirrone, Antun Skuric
    http://arxiv.org/abs/1910.11744v1

    • [cs.RO]Task-Motion Planning for Navigation in Belief Space
    Antony Thomas, Fulvio Mastrogiovanni, Marco Baglietto
    http://arxiv.org/abs/1910.11683v1

    • [cs.SD]Channel adversarial training for speaker verification and diarization
    Chau Luu, Peter Bell, Steve Renals
    http://arxiv.org/abs/1910.11643v1

    • [cs.SD]SeCoST: Sequential Co-Supervision for Weakly Labeled Audio Event Detection
    Anurag Kumar, Vamsi Krishna Ithapu
    http://arxiv.org/abs/1910.11789v1

    • [cs.SI]Asymmetry in interdependence makes a multilayer system more robust against cascading failures
    Run-Ran Liu, Chun-Xiao Jia, Ying-Cheng Lai
    http://arxiv.org/abs/1910.11417v1

    • [cs.SI]Detecting Fake News with Weak Social Supervision
    Kai Shu, Ahmed Hassan Awadallah, Susan Dumais, Huan Liu
    http://arxiv.org/abs/1910.11430v1

    • [cs.SI]Manipulating Node Similarity Measures in Network
    Palash Dey, Sourav Medya
    http://arxiv.org/abs/1910.11529v1

    • [eess.AS]A Multi-Phase Gammatone Filterbank for Speech Separation via TasNet
    David Ditter, Timo Gerkmann
    http://arxiv.org/abs/1910.11615v1

    • [eess.AS]SPICE: Self-supervised Pitch Estimation
    Beat Gfeller, Christian Frank, Dominik Roblek, Matt Sharifi, Marco Tagliasacchi, Mihajlo Velimirović
    http://arxiv.org/abs/1910.11664v1

    • [eess.AS]Structural sparsification for Far-field Speaker Recognition with GNA
    Jingchi Zhang, Jonathan Huang, Michael Deisher, Hai Li, Yiran Chen
    http://arxiv.org/abs/1910.11488v1

    • [eess.IV]DR$\vert$GRADUATE: uncertainty-aware deep learning-based diabetic retinopathy grading in eye fundus images
    Teresa Araújo, Guilherme Aresta, Luís Mendonça, Susana Penas, Carolina Maia, Ângela Carneiro, Ana Maria Mendonça, Aurélio Campilho
    http://arxiv.org/abs/1910.11777v1

    • [eess.SP]Classification of Mobile Services and Apps through Physical Channel Fingerprinting: a Deep Learning Approach
    Hoang Duy Trinh, Angel Fernandez Gambin, Lorenza Giupponi, Paolo Dini
    http://arxiv.org/abs/1910.11617v1

    • [eess.SP]Computation Efficiency Maximization in OFDMA-Based Mobile Edge Computing Networks
    Yuhang Wu, Yuhao Wang, Fuhui Zhou, Rose Qingyang Hu
    http://arxiv.org/abs/1910.11439v1

    • [eess.SP]Joint Source-Channel Coding and Bayesian Message Passing Detection for Grant-Free Radio Access in IoT
    Johannes Dommel, Zoran Utkovski, Slawomir Stanczak, Osvaldo Simeone
    http://arxiv.org/abs/1910.11704v1

    • [eess.SP]Underwater Cooperative MIMO Communications using Hybrid Acoustic and Magnetic Induction Technique
    Zhangyu Li, Soham Desai, Vaishnendr D Sudev, Pu Wang, Jinsong Han, Zhi Sun
    http://arxiv.org/abs/1910.11378v1

    • [math.NA]Convergence Analysis of the Randomized Newton Method with Determinantal Sampling
    Mojmír Mutný, Michał Dereziński, Andreas Krause
    http://arxiv.org/abs/1910.11561v1

    • [math.NA]Weighted Quasi Interpolant Spline Approximations: Properties and Applications
    Andrea Raffo, Silvia Biasotti
    http://arxiv.org/abs/1910.11826v1

    • [math.OC]A distributed proximal-point algorithm for Nash equilibrium seeking under partial-decision information with geometric convergence
    Mattia Bianchi, Giuseppe Belgioioso, Sergio Grammatico
    http://arxiv.org/abs/1910.11613v1

    • [math.OC]Information Flow Optimization in Inference Networks
    Aditya Deshmukh, Jing Liu, Venugopal V. Veeravalli, Gunjan Verma
    http://arxiv.org/abs/1910.11451v1

    • [math.OC]Mirror Natural Evolution Strategies
    Haishan Ye, Tong Zhang
    http://arxiv.org/abs/1910.11490v1

    • [math.ST]Extremal clustering in non-stationary random sequences
    Graeme Auld, Ioannis Papastathopoulos
    http://arxiv.org/abs/1910.11660v1

    • [math.ST]Information Theoretic Limits for Phase Retrieval with Subsampled Haar Sensing Matrices
    Rishabh Dudeja, Junjie Ma, Arian Maleki
    http://arxiv.org/abs/1910.11849v1

    • [math.ST]Joint estimation for volatility and drift parameters of ergodic jump diffusion processes via contrast function
    Chiara Amorino, Arnaud Gloter
    http://arxiv.org/abs/1910.11602v1

    • [math.ST]On agnostic post hoc approaches to false positive control
    Gilles Blanchard, Pierre Neuvial, Etienne Roquain
    http://arxiv.org/abs/1910.11575v1

    • [physics.soc-ph]Bayesian Modeling of Random Walker for Community Detection in Networks
    Takafumi J. Suzuki
    http://arxiv.org/abs/1910.11587v1

    • [physics.soc-ph]Generating large scale-free networks with the Chung-Lu random graph model
    Dario Fasino, Arianna Tonetto, Francesco Tudisco
    http://arxiv.org/abs/1910.11341v1

    • [physics.soc-ph]Modeling vehicular mobility patterns using recurrent neural networks
    Kevin O’Keeffe, Paolo Santi, Carlo Ratti
    http://arxiv.org/abs/1910.11851v1

    • [physics.soc-ph]Time Series Vector Autoregression Prediction of the Ecological Footprint based on Energy Parameters
    Radmila Janković, Ivan Mihajlović, Alessia Amelio
    http://arxiv.org/abs/1910.11800v1

    • [physics.soc-ph]Toward epidemic thresholds on temporal networks: a review and open questions
    Jack Leitch, Kathleen A. Alexander, Srijan Sengupta
    http://arxiv.org/abs/1910.11474v1

    • [q-bio.QM]Minimum Information guidelines for fluorescence microscopy: increasing the value, quality, and fidelity of image data
    Maximiliaan Huisman, Mathias Hammer, Alex Rigano, Renu Gopinathan, Carlas Smith, David Grunwald, Caterina Strambio-De-Castillia
    http://arxiv.org/abs/1910.11370v1

    • [stat.AP]A Simple Descriptive Method & Standard for Comparing Pairs of Stacked Bar Graphs
    Ronaldo Vigo
    http://arxiv.org/abs/1910.11524v1

    • [stat.AP]Almost Politically Acceptable Criminal Justice Risk Assessment
    Richard A. Berk, Ayya A. Elzarka
    http://arxiv.org/abs/1910.11410v1

    • [stat.AP]Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting
    The Tien Mai, Jukka Corander
    http://arxiv.org/abs/1910.11743v1

    • [stat.AP]Calibration of computer models with heteroscedastic errors and application to plant relative growth rates
    Chih-Li Sung, Beau David Barber, Berkley J. Walker
    http://arxiv.org/abs/1910.11518v1

    • [stat.ME]Bayesian epidemiological modeling over high-resolution network data
    Stefan Engblom, Robin Eriksson, Stefan Widgren
    http://arxiv.org/abs/1910.11720v1

    • [stat.ME]Finite Mixtures of ERGMs for Ensembles of Networks
    Fan Yin, Weining Shen, Carter T. Butts
    http://arxiv.org/abs/1910.11445v1

    • [stat.ME]Quantile Regression Modelling via Location and Scale Mixtures of Normal Distributions
    Haim Y. Bar, James G. Booth, Martin T. Wells
    http://arxiv.org/abs/1910.11479v1

    • [stat.ME]The covariate-adjusted residual estimator and its use in both randomized trials and observational settings
    Stephen A. Lauer, Nicholas G. Reich, Laura B. Balzer
    http://arxiv.org/abs/1910.11397v1

    • [stat.ME]Unified model selection approach based on minimum description length principle in Granger causality analysis
    Fei Li, Xuewei Wang, Qiang Lin, Zhenghui Hu
    http://arxiv.org/abs/1910.11537v1

    • [stat.ML]Bias-Variance Tradeoff in a Sliding Window Implementation of the Stochastic Gradient Algorithm
    Yakup Ceki Papo
    http://arxiv.org/abs/1910.11868v1

    • [stat.ML]Calibration tests in multi-class classification: A unifying framework
    David Widmann, Fredrik Lindsten, Dave Zachariah
    http://arxiv.org/abs/1910.11385v1

    • [stat.ML]Online Gaussian LDA for Unsupervised Pattern Mining from Utility Usage Data
    Saad Mohamad, Abdelhamid Bouchachia
    http://arxiv.org/abs/1910.11599v1

    • [stat.ML]Robust Principal Component Analysis Based On Maximum Correntropy Power Iterations
    Jean P. Chereau, Bruno Scalzo Dees, Danilo P. Mandic
    http://arxiv.org/abs/1910.11374v1

    • [stat.ML]Structured Prediction with Projection Oracles
    Mathieu Blondel
    http://arxiv.org/abs/1910.11369v1

    • [stat.ML]Towards Robust and Stable Deep Learning Algorithms for Forward Backward Stochastic Differential Equations
    Batuhan Güler, Alexis Laignelet, Panos Parpas
    http://arxiv.org/abs/1910.11623v1

    • [stat.ML]Unsupervised Space-Time Clustering using Persistent Homology
    Umar Islambekov, Yulia Gel
    http://arxiv.org/abs/1910.11525v1