cond-mat.dis-nn - 无序系统与神经网络

    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.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.FL - 形式语言与自动机理论 cs.GR - 计算机图形学 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.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.acc-ph - 加速器物理学 physics.comp-ph - 计算物理学 physics.med-ph - 医学物理学 q-bio.GN - 基因组学 q-bio.QM - 定量方法 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.dis-nn]Gaussian-Spherical Restricted Boltzmann Machines
    • [cs.AI]Bayesian causal inference via probabilistic program synthesis
    • [cs.AI]FutureMapping 2: Gaussian Belief Propagation for Spatial AI
    • [cs.AI]Lexical Learning as an Online Optimal Experiment: Building Efficient Search Engines through Human-Machine Collaboration
    • [cs.AI]Towards A Logical Account of Epistemic Causality
    • [cs.CL]A Neural Topic-Attention Model for Medical Term Abbreviation Disambiguation
    • [cs.CL]A neural document language modeling framework for spoken document retrieval
    • [cs.CL]Adversarial NLI: A New Benchmark for Natural Language Understanding
    • [cs.CL]Attention Is All You Need for Chinese Word Segmentation
    • [cs.CL]Building an Application Independent Natural Language Interface
    • [cs.CL]Can adversarial training learn image captioning ?
    • [cs.CL]Cascaded LSTMs based Deep Reinforcement Learning for Goal-driven Dialogue
    • [cs.CL]Contextual Text Denoising with Masked Language Models
    • [cs.CL]DiaNet: BERT and Hierarchical Attention Multi-Task Learning of Fine-Grained Dialect
    • [cs.CL]Discourse-Aware Neural Extractive Model for Text Summarization
    • [cs.CL]Do Multi-hop Readers Dream of Reasoning Chains?
    • [cs.CL]Document-level Neural Machine Translation with Inter-Sentence Attention
    • [cs.CL]Fill in the Blanks: Imputing Missing Sentences for Larger-Context Neural Machine Translation
    • [cs.CL]Great New Design: How Do We Talk about Media Architecture in Social Media
    • [cs.CL]Harnessing the richness of the linguistic signal in predicting pragmatic inferences
    • [cs.CL]How does Grammatical Gender Affect Noun Representations in Gender-Marking Languages?
    • [cs.CL]LIMIT-BERT : Linguistic Informed Multi-Task BERT
    • [cs.CL]Learning to Customize Language Model for Generation-based dialog systems
    • [cs.CL]Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness
    • [cs.CL]Multi-scale Octave Convolutions for Robust Speech Recognition
    • [cs.CL]Naver Labs Europe’s Systems for the Document-Level Generation and Translation Task at WNGT 2019
    • [cs.CL]Positional Attention-based Frame Identification with BERT: A Deep Learning Approach to Target Disambiguation and Semantic Frame Selection
    • [cs.CL]Predicting Discourse Structure using Distant Supervision from Sentiment
    • [cs.CL]Probabilistic Bias Mitigation in Word Embeddings
    • [cs.CL]Pseudolikelihood Reranking with Masked Language Models
    • [cs.CL]Toward Gender-Inclusive Coreference Resolution
    • [cs.CL]Towards Generalizable Neuro-Symbolic Systems for Commonsense Question Answering
    • [cs.CL]Transfer Learning from Transformers to Fake News Challenge Stance Detection (FNC-1) Task
    • [cs.CL]Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning
    • [cs.CL]What Question Answering can Learn from Trivia Nerds
    • [cs.CR]A machine-learning approach to Detect users’ suspicious behaviour through the Facebook wall
    • [cs.CR]Quantifying (Hyper) Parameter Leakage in Machine Learning
    • [cs.CR]Robust and Undetectable White-Box Watermarks for Deep Neural Networks
    • [cs.CV]A Review of methods for Textureless Object Recognition
    • [cs.CV]A Self Validation Network for Object-Level Human Attention Estimation
    • [cs.CV]AQUALOC: An Underwater Dataset for Visual-Inertial-Pressure Localization
    • [cs.CV]Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?
    • [cs.CV]Automatic Cobb Angle Detection using Vertebra Detector and Vertebra Corners Regression
    • [cs.CV]Co-Generation with GANs using AIS based HMC
    • [cs.CV]Cross-Domain Face Synthesis using a Controllable GAN
    • [cs.CV]Distilling Pixel-Wise Feature Similarities for Semantic Segmentation
    • [cs.CV]Dynamic Regularizer with an Informative Prior
    • [cs.CV]Generalizing Energy-based Generative ConvNets from Particle Evolution Perspective
    • [cs.CV]Hidden State Guidance: Improving Image Captioning using An Image Conditioned Autoencoder
    • [cs.CV]LiDAR-Flow: Dense Scene Flow Estimation from Sparse LiDAR and Stereo Images
    • [cs.CV]Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors
    • [cs.CV]On the Interaction Between Deep Detectors and Siamese Trackers in Video Surveillance
    • [cs.CV]Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos
    • [cs.CV]TAB-VCR: Tags and Attributes based VCR Baselines
    • [cs.CV]Universal Adversarial Perturbations Against Person Re-Identification
    • [cs.CV]Very high resolution Airborne PolSAR Image Classification using Convolutional Neural Networks
    • [cs.CV]Visual Appearance Based Person Retrieval in Unconstrained Environment Videos
    • [cs.CV]Weakly Supervised Tracklet Person Re-Identification by Deep Feature-wise Mutual Learning
    • [cs.CY]Blockchain and the Common Good Reimagined
    • [cs.CY]Methodological Blind Spots in Machine Learning Fairness: Lessons from the Philosophy of Science and Computer Science
    • [cs.CY]Which Factors Impact Engagement on News Articles on Facebook?
    • [cs.DC]A Self-Repairing Hardware Architecture for Safety-Critical Cyber-Physical-Systems
    • [cs.DC]Byzantine Lattice Agreement in Synchronous Systems
    • [cs.DC]Decomposing Collectives for Exploiting Multi-lane Communication
    • [cs.DC]Run-time Parameter Sensitivity Analysis Optimizations
    • [cs.DL]Towards a Predictive Patent Analytics and Evaluation Platform
    • [cs.DS]Improved Local Computation Algorithm for Set Cover via Sparsification
    • [cs.FL]An Abstraction-Based Framework for Neural Network Verification
    • [cs.GR]LaplacianNet: Learning on 3D Meshes with Laplacian Encoding and Pooling
    • [cs.IR]Graph Neural News Recommendation with Long-term and Short-term Interest Modeling
    • [cs.IR]Multi-Stage Document Ranking with BERT
    • [cs.IT]Age-Based Scheduling Policy for Federated Learning in Mobile Edge Networks
    • [cs.IT]Anisotropic compressed sensing for non-Cartesian MRI acquisitions
    • [cs.IT]Channel Capacity Optimization Using Reconfigurable Intelligent Surfaces in Indoor mmWave Environments
    • [cs.IT]Differentially low uniform permutations from known 4-uniform functions
    • [cs.IT]Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-user Communications: Achievable Rates with Limited Discrete Phase Shifts
    • [cs.IT]Intelligent Reflecting Surface Aided Network: Power Control for Physical-Layer Broadcasting
    • [cs.IT]Joint Communication and Computation Optimization for Wireless Powered Mobile Edge Computing with D2D Offloading
    • [cs.IT]MmWave Amplify-and-Forward MIMO Relay Networks with Hybrid Precoding/Combining Design
    • [cs.IT]Multi-resolution CSI Feedback with deep learning in Massive MIMO System
    • [cs.IT]Rate Distortion Study for Time-Varying Autoregressive Gaussian Process
    • [cs.IT]Robust Beamforming Design for OTFS-NOMA
    • [cs.IT]Spatially Coupled Generalized LDPC Codes: Asymptotic Analysis and Finite Length Scaling
    • [cs.IT]Structured Channel Covariance Estimation from Limited Samples in Massive MIMO
    • [cs.LG]A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
    • [cs.LG]BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems
    • [cs.LG]Certifiable Robustness to Graph Perturbations
    • [cs.LG]Continual Unsupervised Representation Learning
    • [cs.LG]Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods
    • [cs.LG]Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators
    • [cs.LG]Energy-Inspired Models: Learning with Sampler-Induced Distributions
    • [cs.LG]Explainable Prediction of Adverse Outcomes Using Clinical Notes
    • [cs.LG]Graph Structured Prediction Energy Networks
    • [cs.LG]Image-Conditioned Graph Generation for Road Network Extraction
    • [cs.LG]In-Place Zero-Space Memory Protection for CNN
    • [cs.LG]Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization
    • [cs.LG]Iterative Hessian Sketch in Input Sparsity Time
    • [cs.LG]Learning Disentangled Representations for Recommendation
    • [cs.LG]Learning Fairness in Multi-Agent Systems
    • [cs.LG]Lsh-sampling Breaks the Computation Chicken-and-egg Loop in Adaptive Stochastic Gradient Estimation
    • [cs.LG]Meta-Learning to Cluster
    • [cs.LG]Multivariate Uncertainty in Deep Learning
    • [cs.LG]NAT: Neural Architecture Transformer for Accurate and Compact Architectures
    • [cs.LG]Neural Assistant: Joint Action Prediction, Response Generation, and Latent Knowledge Reasoning
    • [cs.LG]Neural networks trained with WiFi traces to predict airport passenger behavior
    • [cs.LG]Object-oriented state editing for HRL
    • [cs.LG]On the Convergence of Local Descent Methods in Federated Learning
    • [cs.LG]On the Regularization Properties of Structured Dropout
    • [cs.LG]Parameter Sharing Decoder Pair for Auto Composing
    • [cs.LG]Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control
    • [cs.LG]Policy Continuation with Hindsight Inverse Dynamics
    • [cs.LG]RLINK: Deep Reinforcement Learning for User Identity Linkage
    • [cs.LG]Robust and Computationally-Efficient Anomaly Detection using Powers-of-Two Networks
    • [cs.LG]Sample Complexity of Learning Mixtures of Sparse Linear Regressions
    • [cs.LG]Sobolev Independence Criterion
    • [cs.LG]Solving NMF with smoothness and sparsity constraints using PALM
    • [cs.LG]Transport Model for Feature Extraction
    • [cs.LG]Understanding Isomorphism Bias in Graph Data Sets
    • [cs.LG]Unsupervised Star Galaxy Classification with Cascade Variational Auto-Encoder
    • [cs.LG]VASE: Variational Assorted Surprise Exploration for Reinforcement Learning
    • [cs.LG]What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers
    • [cs.LO]Belief revision and 3-valued logics: Characterization of 19,683 belief change operators
    • [cs.NE]An Automatic Design Framework of Swarm Pattern Formation based on Multi-objective Genetic Programming
    • [cs.NE]Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
    • [cs.NE]Sharp Bounds for Genetic Drift in EDAs
    • [cs.RO]CALC2.0: Combining Appearance, Semantic and Geometric Information for Robust and Efficient Visual Loop Closure
    • [cs.RO]Crop Height and Plot Estimation from Unmanned Aerial Vehicles using 3D LiDAR
    • [cs.RO]Duckiefloat: a Collision-Tolerant Resource-Constrained Blimp for Long-Term Autonomy in Subterranean Environments
    • [cs.RO]Dynamic Cloth Manipulation with Deep Reinforcement Learning
    • [cs.RO]Interactive Gibson: A Benchmark for Interactive Navigation in Cluttered Environments
    • [cs.RO]S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes
    • [cs.RO]Team NCTU: Toward AI-Driving for Autonomous Surface Vehicles — From Duckietown to RobotX
    • [cs.RO]Towards vision-based robotic skins: a data-driven, multi-camera tactile sensor
    • [cs.SE]Selecting Reliable Blockchain Peers via Hybrid Blockchain Reliability Prediction
    • [cs.SI]Semi-supervisedly Co-embedding Attributed Networks
    • [eess.AS]End-to-end Microphone Permutation and Number Invariant Multi-channel Speech Separation
    • [eess.IV]Conditional Denoising of Remote Sensing Imagery Using Cycle-Consistent Deep Generative Models
    • [eess.IV]Flash X-ray diffraction imaging in 3D: a proposed analysis pipeline
    • [eess.IV]Image-Guided Depth Upsampling via Hessian and TV Priors
    • [eess.IV]Multi-defect microscopy image restoration under limited data conditions
    • [eess.IV]On the Proof of Fixed-Point Convergence for Plug-and-Play ADMM
    • [eess.SP]Geometric Sequence Decomposition with $k$-simplexes Transform
    • [eess.SY]Recurrent averaging inequalities, opinion formation and distributed algorithms
    • [math.NA]Spectral properties of kernel matrices in the flat limit
    • [math.OC]A Decentralized Proximal Point-type Method for Saddle Point Problems
    • [math.OC]Mixing of Stochastic Accelerated Gradient Descent
    • [math.PR]Phase Transitions for Detecting Latent Geometry in Random Graphs
    • [math.ST]Multiplicative noise in Bayesian inverse problems: Well-posedness and consistency of MAP estimators
    • [math.ST]Rate of convergence for geometric inference based on the empirical Christoffel function
    • [physics.acc-ph]Machine learning for design optimization of storage ring nonlinear dynamics
    • [physics.comp-ph]Connecting exciton diffusion with surface roughness via deep learning
    • [physics.comp-ph]Evaluation of Surrogate Models for Multi-fin Flapping Propulsion Systems
    • [physics.med-ph]The importance of evaluating the complete automated knowledge-based planning pipeline
    • [q-bio.GN]Assessment of Multiple-Biomarker Classifiers: fundamental principles and a proposed strategy
    • [q-bio.QM]Precision disease networks (PDN)
    • [stat.AP]Accounting for Location Measurement Error in Atomic Resolution Images of Crystalline Materials
    • [stat.AP]Change Point Detection for Nonparametric Regression under Strongly Mixing Process
    • [stat.AP]EnergyStar++: Towards more accurate and explanatory building energy benchmarking
    • [stat.AP]Horvitz-Thompson-like estimation with distance-based detection probabilities for circular plot sampling of forests
    • [stat.CO]”multiColl”: An R package to detect multicollinearity
    • [stat.CO]Bayesian nonstationary Gaussian process modeling: the BayesNSGP package for R
    • [stat.CO]Combined parameter and state inference with automatically calibrated ABC
    • [stat.CO]Evaluation of Granger causality measures for constructing networks from multivariate time series
    • [stat.CO]Parameter elimination in particle Gibbs sampling
    • [stat.ME]A Semiparametric Approach to Model-based Sensitivity Analysis in Observational Studies
    • [stat.ME]Connecting population-level AUC and latent scale-invariant $R^2$ via Semiparametric Gaussian Copula and rank correlations
    • [stat.ME]New weighted $L^2$-type tests for the inverse Gaussian distribution
    • [stat.ME]Order Determination for Spiked Models
    • [stat.ME]Probabilistic Detection and Estimation of Conic Sections from Noisy Data
    • [stat.ML]A study of data and label shift in the LIME framework
    • [stat.ML]Enhancing Certifiable Robustness via a Deep Model Ensemble
    • [stat.ML]Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning
    • [stat.ML]Investigating Under and Overfitting in Wasserstein Generative Adversarial Networks
    • [stat.ML]Kernel-Guided Training of Implicit Generative Models with Stability Guarantees
    • [stat.ML]Learn-By-Calibrating: Using Calibration as a Training Objective
    • [stat.ML]Recovering Bandits
    • [stat.ML]SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization
    • [stat.ML]Unsupervised inference approach to facial attractiveness

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    • [cond-mat.dis-nn]Gaussian-Spherical Restricted Boltzmann Machines
    Aurélien Decelle, Cyril Furtlehner
    http://arxiv.org/abs/1910.14544v1

    • [cs.AI]Bayesian causal inference via probabilistic program synthesis
    Sam Witty, Alexander Lew, David Jensen, Vikash Mansinghka
    http://arxiv.org/abs/1910.14124v1

    • [cs.AI]FutureMapping 2: Gaussian Belief Propagation for Spatial AI
    Andrew J. Davison, Joseph Ortiz
    http://arxiv.org/abs/1910.14139v1

    • [cs.AI]Lexical Learning as an Online Optimal Experiment: Building Efficient Search Engines through Human-Machine Collaboration
    Jacopo Tagliabue, Reuben Cohn-Gordon
    http://arxiv.org/abs/1910.14164v1

    • [cs.AI]Towards A Logical Account of Epistemic Causality
    Shakil M. Khan, Mikhail Soutchanski
    http://arxiv.org/abs/1910.14217v1

    • [cs.CL]A Neural Topic-Attention Model for Medical Term Abbreviation Disambiguation
    Irene Li, Michihiro Yasunaga, Muhammed Yavuz Nuzumlalı, Cesar Caraballo, Shiwani Mahajan, Harlan Krumholz, Dragomir Radev
    http://arxiv.org/abs/1910.14076v1

    • [cs.CL]A neural document language modeling framework for spoken document retrieval
    Li-Phen Yen, Zhen-Yu Wu, Kuan-Yu Chen
    http://arxiv.org/abs/1910.14286v1

    • [cs.CL]Adversarial NLI: A New Benchmark for Natural Language Understanding
    Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, Douwe Kiela
    http://arxiv.org/abs/1910.14599v1

    • [cs.CL]Attention Is All You Need for Chinese Word Segmentation
    Sufeng Duan, Hai Zhao
    http://arxiv.org/abs/1910.14537v1

    • [cs.CL]Building an Application Independent Natural Language Interface
    Sahisnu Mazumder, Bing Liu, Shuai Wang, Sepideh Esmaeilpour
    http://arxiv.org/abs/1910.14084v1

    • [cs.CL]Can adversarial training learn image captioning ?
    Jean-Benoit Delbrouck, Bastien Vanderplaetse, Stéphane Dupont
    http://arxiv.org/abs/1910.14609v1

    • [cs.CL]Cascaded LSTMs based Deep Reinforcement Learning for Goal-driven Dialogue
    Yue Ma, Xiaojie Wang, Zhenjiang Dong, Hong Chen
    http://arxiv.org/abs/1910.14229v1

    • [cs.CL]Contextual Text Denoising with Masked Language Models
    Yifu Sun, Haoming Jiang
    http://arxiv.org/abs/1910.14080v1

    • [cs.CL]DiaNet: BERT and Hierarchical Attention Multi-Task Learning of Fine-Grained Dialect
    Muhammad Abdul-Mageed, Chiyu Zhang, AbdelRahim Elmadany, Arun Rajendran, Lyle Ungar
    http://arxiv.org/abs/1910.14243v1

    • [cs.CL]Discourse-Aware Neural Extractive Model for Text Summarization
    Jiacheng Xu, Zhe Gan, Yu Cheng, Jingjing Liu
    http://arxiv.org/abs/1910.14142v1

    • [cs.CL]Do Multi-hop Readers Dream of Reasoning Chains?
    Haoyu Wang, Mo Yu, Xiaoxiao Guo, Rajarshi Das, Wenhan Xiong, Tian Gao
    http://arxiv.org/abs/1910.14520v1

    • [cs.CL]Document-level Neural Machine Translation with Inter-Sentence Attention
    Shu Jiang, Rui Wang, Zuchao Li, Masao Utiyama, Kehai Chen, Eiichiro Sumita, Hai Zhao, Bao-liang Lu
    http://arxiv.org/abs/1910.14528v1

    • [cs.CL]Fill in the Blanks: Imputing Missing Sentences for Larger-Context Neural Machine Translation
    Sébastien Jean, Ankur Bapna, Orhan Firat
    http://arxiv.org/abs/1910.14075v1

    • [cs.CL]Great New Design: How Do We Talk about Media Architecture in Social Media
    Selena Savic
    http://arxiv.org/abs/1910.14395v1

    • [cs.CL]Harnessing the richness of the linguistic signal in predicting pragmatic inferences
    Sebastian Schuster, Yuxing Chen, Judith Degen
    http://arxiv.org/abs/1910.14254v1

    • [cs.CL]How does Grammatical Gender Affect Noun Representations in Gender-Marking Languages?
    Hila Gonen, Yova Kementchedjhieva, Yoav Goldberg
    http://arxiv.org/abs/1910.14161v1

    • [cs.CL]LIMIT-BERT : Linguistic Informed Multi-Task BERT
    Junru Zhou, Zhuosheng Zhang, Hai Zhao
    http://arxiv.org/abs/1910.14296v1

    • [cs.CL]Learning to Customize Language Model for Generation-based dialog systems
    Yiping Song, Zequn Liu, Wei Bi, Rui Yan, Ming Zhang
    http://arxiv.org/abs/1910.14326v1

    • [cs.CL]Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness
    Alexandre Bérard, Ioan Calapodescu, Marc Dymetman, Claude Roux, Jean-Luc Meunier, Vassilina Nikoulina
    http://arxiv.org/abs/1910.14589v1

    • [cs.CL]Multi-scale Octave Convolutions for Robust Speech Recognition
    Joanna Rownicka, Peter Bell, Steve Renals
    http://arxiv.org/abs/1910.14443v1

    • [cs.CL]Naver Labs Europe’s Systems for the Document-Level Generation and Translation Task at WNGT 2019
    Fahimeh Saleh, Alexandre Bérard, Ioan Calapodescu, Laurent Besacier
    http://arxiv.org/abs/1910.14539v1

    • [cs.CL]Positional Attention-based Frame Identification with BERT: A Deep Learning Approach to Target Disambiguation and Semantic Frame Selection
    Sang-Sang Tan, Jin-Cheon Na
    http://arxiv.org/abs/1910.14549v1

    • [cs.CL]Predicting Discourse Structure using Distant Supervision from Sentiment
    Patrick Huber, Giuseppe Carenini
    http://arxiv.org/abs/1910.14176v1

    • [cs.CL]Probabilistic Bias Mitigation in Word Embeddings
    Hailey James-Sorenson, David Alvarez-Melis
    http://arxiv.org/abs/1910.14497v1

    • [cs.CL]Pseudolikelihood Reranking with Masked Language Models
    Julian Salazar, Davis Liang, Toan Q. Nguyen, Katrin Kirchhoff
    http://arxiv.org/abs/1910.14659v1

    • [cs.CL]Toward Gender-Inclusive Coreference Resolution
    Yang Trista Cao, Hal Daumé III
    http://arxiv.org/abs/1910.13913v2

    • [cs.CL]Towards Generalizable Neuro-Symbolic Systems for Commonsense Question Answering
    Kaixin Ma, Jonathan Francis, Quanyang Lu, Eric Nyberg, Alessandro Oltramari
    http://arxiv.org/abs/1910.14087v1

    • [cs.CL]Transfer Learning from Transformers to Fake News Challenge Stance Detection (FNC-1) Task
    Valeriya Slovikovskaya
    http://arxiv.org/abs/1910.14353v1

    • [cs.CL]Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning
    Zheng Li, Xin Li, Ying Wei, Lidong Bing, Yu Zhang, Qiang Yang
    http://arxiv.org/abs/1910.14192v1

    • [cs.CL]What Question Answering can Learn from Trivia Nerds
    Jordan Boyd-Graber
    http://arxiv.org/abs/1910.14464v1

    • [cs.CR]A machine-learning approach to Detect users’ suspicious behaviour through the Facebook wall
    Aimilia Panagiotou, Bogdan Ghita, Stavros Shiaeles, Keltoum Bendiab
    http://arxiv.org/abs/1910.14417v1

    • [cs.CR]Quantifying (Hyper) Parameter Leakage in Machine Learning
    Vasisht Duddu, D. Vijay Rao
    http://arxiv.org/abs/1910.14409v1

    • [cs.CR]Robust and Undetectable White-Box Watermarks for Deep Neural Networks
    Tianhao Wang, Florian Kerschbaum
    http://arxiv.org/abs/1910.14268v1

    • [cs.CV]A Review of methods for Textureless Object Recognition
    Frincy Clement, Kirtan Shah, Dhara Pancholi
    http://arxiv.org/abs/1910.14255v1

    • [cs.CV]A Self Validation Network for Object-Level Human Attention Estimation
    Zehua Zhang, Chen Yu, David Crandall
    http://arxiv.org/abs/1910.14260v1

    • [cs.CV]AQUALOC: An Underwater Dataset for Visual-Inertial-Pressure Localization
    Maxime Ferrera, Vincent Creuze, Julien Moras, Pauline Trouvé-Peloux
    http://arxiv.org/abs/1910.14532v1

    • [cs.CV]Are Out-of-Distribution Detection Methods Effective on Large-Scale Datasets?
    Ryne Roady, Tyler L. Hayes, Ronald Kemker, Ayesha Gonzales, Christopher Kanan
    http://arxiv.org/abs/1910.14034v1

    • [cs.CV]Automatic Cobb Angle Detection using Vertebra Detector and Vertebra Corners Regression
    Bidur Khanal, Lavsen Dahal, Prashant Adhikari, Bishesh Khanal
    http://arxiv.org/abs/1910.14202v1

    • [cs.CV]Co-Generation with GANs using AIS based HMC
    Tiantian Fang, Alexander G. Schwing
    http://arxiv.org/abs/1910.14673v1

    • [cs.CV]Cross-Domain Face Synthesis using a Controllable GAN
    Fania Mokhayeri, Kaveh Kamali, Eric Granger
    http://arxiv.org/abs/1910.14247v1

    • [cs.CV]Distilling Pixel-Wise Feature Similarities for Semantic Segmentation
    Yuhu Shan
    http://arxiv.org/abs/1910.14226v1

    • [cs.CV]Dynamic Regularizer with an Informative Prior
    Avinash Kori, Manik Sharma
    http://arxiv.org/abs/1910.14241v1

    • [cs.CV]Generalizing Energy-based Generative ConvNets from Particle Evolution Perspective
    Yang Wu, Pengxu Wei, Xu Cai, Guanbin Li, Liang Lin
    http://arxiv.org/abs/1910.14216v1

    • [cs.CV]Hidden State Guidance: Improving Image Captioning using An Image Conditioned Autoencoder
    Jialin Wu, Raymond J. Mooney
    http://arxiv.org/abs/1910.14208v1

    • [cs.CV]LiDAR-Flow: Dense Scene Flow Estimation from Sparse LiDAR and Stereo Images
    Ramy Battrawy, René Schuster, Oliver Wasenmüller, Qing Rao, Didier Stricker
    http://arxiv.org/abs/1910.14453v1

    • [cs.CV]Making an Invisibility Cloak: Real World Adversarial Attacks on Object Detectors
    Zuxuan Wu, Ser-Nam Lim, Larry Davis, Tom Goldstein
    http://arxiv.org/abs/1910.14667v1

    • [cs.CV]On the Interaction Between Deep Detectors and Siamese Trackers in Video Surveillance
    Madhu Kiran, Vivek Tiwari, Le Thanh Nguyen-Meidine, Eric Granger
    http://arxiv.org/abs/1910.14552v1

    • [cs.CV]Semantic Conditioned Dynamic Modulation for Temporal Sentence Grounding in Videos
    Yitian Yuan, Lin Ma, Jingwen Wang, Wei Liu, Wenwu Zhu
    http://arxiv.org/abs/1910.14303v1

    • [cs.CV]TAB-VCR: Tags and Attributes based VCR Baselines
    Jingxiang Lin, Unnat Jain, Alexander G. Schwing
    http://arxiv.org/abs/1910.14671v1

    • [cs.CV]Universal Adversarial Perturbations Against Person Re-Identification
    Wenjie Ding, Xing Wei, Xiaopeng Hong, Rongrong Ji, Yihong Gong
    http://arxiv.org/abs/1910.14184v1

    • [cs.CV]Very high resolution Airborne PolSAR Image Classification using Convolutional Neural Networks
    Minh-Tan Pham, Sébastien Lefèvre
    http://arxiv.org/abs/1910.14578v1

    • [cs.CV]Visual Appearance Based Person Retrieval in Unconstrained Environment Videos
    Hiren Galiyawala, Mehul S Raval, Shivansh Dave
    http://arxiv.org/abs/1910.14565v1

    • [cs.CV]Weakly Supervised Tracklet Person Re-Identification by Deep Feature-wise Mutual Learning
    Zhirui Chen, Jianheng Li, Wei-Shi Zheng
    http://arxiv.org/abs/1910.14333v1

    • [cs.CY]Blockchain and the Common Good Reimagined
    Joshua Ellul, Gordon Pace
    http://arxiv.org/abs/1910.14415v1

    • [cs.CY]Methodological Blind Spots in Machine Learning Fairness: Lessons from the Philosophy of Science and Computer Science
    Samuel Deng, Achille Varzi
    http://arxiv.org/abs/1910.14210v1

    • [cs.CY]Which Factors Impact Engagement on News Articles on Facebook?
    Marc Faddoul
    http://arxiv.org/abs/1910.14651v1

    • [cs.DC]A Self-Repairing Hardware Architecture for Safety-Critical Cyber-Physical-Systems
    Shawkat Khairullah, Carl Elks
    http://arxiv.org/abs/1910.14127v1

    • [cs.DC]Byzantine Lattice Agreement in Synchronous Systems
    Xiong Zheng, Vijay Garg
    http://arxiv.org/abs/1910.14141v1

    • [cs.DC]Decomposing Collectives for Exploiting Multi-lane Communication
    Jesper Larsson Träff
    http://arxiv.org/abs/1910.13373v2

    • [cs.DC]Run-time Parameter Sensitivity Analysis Optimizations
    Eduardo Scartezini, Willian Barreiros Jr., Tahsin Kurc, Jun Kong, Alba C. M. A. Melo, Joel Saltz, George Teodoro
    http://arxiv.org/abs/1910.14548v1

    • [cs.DL]Towards a Predictive Patent Analytics and Evaluation Platform
    Nebula Alam, Khoi-Nguyen Tran, Sue Ann Chen, John Wagner, Josh Andres, Mukesh Mohania
    http://arxiv.org/abs/1910.14258v1

    • [cs.DS]Improved Local Computation Algorithm for Set Cover via Sparsification
    Christoph Grunau, Slobodan Mitrović, Ronitt Rubinfeld, Ali Vakilian
    http://arxiv.org/abs/1910.14154v1

    • [cs.FL]An Abstraction-Based Framework for Neural Network Verification
    Yizhak Yisrael Elboher, Justin Gottschlich, Guy Katz
    http://arxiv.org/abs/1910.14574v1

    • [cs.GR]LaplacianNet: Learning on 3D Meshes with Laplacian Encoding and Pooling
    Yi-Ling Qiao, Lin Gao, Jie Yang, Paul L. Rosin, Yu-Kun Lai, Xilin Chen
    http://arxiv.org/abs/1910.14063v1

    • [cs.IR]Graph Neural News Recommendation with Long-term and Short-term Interest Modeling
    Linmei Hu, Chen Li, Chuan Shi, Cheng Yang, Chao Shao
    http://arxiv.org/abs/1910.14025v1

    • [cs.IR]Multi-Stage Document Ranking with BERT
    Rodrigo Nogueira, Wei Yang, Kyunghyun Cho, Jimmy Lin
    http://arxiv.org/abs/1910.14424v1

    • [cs.IT]Age-Based Scheduling Policy for Federated Learning in Mobile Edge Networks
    Howard H. Yang, Ahmed Arafa, Tony Q. S. Quek, H. Vincent Poor
    http://arxiv.org/abs/1910.14648v1

    • [cs.IT]Anisotropic compressed sensing for non-Cartesian MRI acquisitions
    Philippe Ciuciu, Anna Kazeykina
    http://arxiv.org/abs/1910.14513v1

    • [cs.IT]Channel Capacity Optimization Using Reconfigurable Intelligent Surfaces in Indoor mmWave Environments
    Nemanja Stefan Perović, Marco Di Renzo, Mark F. Flanagan
    http://arxiv.org/abs/1910.14310v1

    • [cs.IT]Differentially low uniform permutations from known 4-uniform functions
    Marco Calderini
    http://arxiv.org/abs/1910.14337v1

    • [cs.IT]Hybrid Beamforming for Reconfigurable Intelligent Surface based Multi-user Communications: Achievable Rates with Limited Discrete Phase Shifts
    Boya Di, Hongliang Zhang, Lingyang Song, Yonghui Li, Zhu Han, H. Vincent Poor
    http://arxiv.org/abs/1910.14328v1

    • [cs.IT]Intelligent Reflecting Surface Aided Network: Power Control for Physical-Layer Broadcasting
    Huimei Han, Jun Zhao, Dusit Niyato, Marco Di Renzo, Quoc-Viet Pham
    http://arxiv.org/abs/1910.14383v1

    • [cs.IT]Joint Communication and Computation Optimization for Wireless Powered Mobile Edge Computing with D2D Offloading
    Dixiao Wu, Feng Wang, Xiaowen Cao, Jie Xu
    http://arxiv.org/abs/1910.14274v1

    • [cs.IT]MmWave Amplify-and-Forward MIMO Relay Networks with Hybrid Precoding/Combining Design
    Lisi Jiang, Hamid Jafarkhani
    http://arxiv.org/abs/1910.14182v1

    • [cs.IT]Multi-resolution CSI Feedback with deep learning in Massive MIMO System
    Zhilin Lu, Jintao Wang, Jian Song
    http://arxiv.org/abs/1910.14322v1

    • [cs.IT]Rate Distortion Study for Time-Varying Autoregressive Gaussian Process
    Jia-Chyi Wu
    http://arxiv.org/abs/1910.14228v1

    • [cs.IT]Robust Beamforming Design for OTFS-NOMA
    Zhiguo Ding
    http://arxiv.org/abs/1910.14422v1

    • [cs.IT]Spatially Coupled Generalized LDPC Codes: Asymptotic Analysis and Finite Length Scaling
    David G. M. Mitchell, Pablo M. Olmos, Michael Lentmaier, Daniel J. Costello
    http://arxiv.org/abs/1910.14110v1

    • [cs.IT]Structured Channel Covariance Estimation from Limited Samples in Massive MIMO
    Mahdi Barzegar Khalilsarai, Tianyu Yang, Saeid Haghighatshoar, Giuseppe Caire
    http://arxiv.org/abs/1910.14467v1

    • [cs.LG]A Unified Framework for Data Poisoning Attack to Graph-based Semi-supervised Learning
    Xuanqing Liu, Si Si, Xiaojin Zhu, Yang Li, Cho-Jui Hsieh
    http://arxiv.org/abs/1910.14147v1

    • [cs.LG]BottleNet++: An End-to-End Approach for Feature Compression in Device-Edge Co-Inference Systems
    Jiawei Shao, Jun Zhang
    http://arxiv.org/abs/1910.14315v1

    • [cs.LG]Certifiable Robustness to Graph Perturbations
    Aleksandar Bojchevski, Stephan Günnemann
    http://arxiv.org/abs/1910.14356v1

    • [cs.LG]Continual Unsupervised Representation Learning
    Dushyant Rao, Francesco Visin, Andrei A. Rusu, Yee Whye Teh, Razvan Pascanu, Raia Hadsell
    http://arxiv.org/abs/1910.14481v1

    • [cs.LG]Deep Learning for 2D and 3D Rotatable Data: An Overview of Methods
    Luca Della Libera, Vladimir Golkov, Yue Zhu, Arman Mielke, Daniel Cremers
    http://arxiv.org/abs/1910.14594v1

    • [cs.LG]Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators
    Reinhard Heckel, Mahdi Soltanolkotabi
    http://arxiv.org/abs/1910.14634v1

    • [cs.LG]Energy-Inspired Models: Learning with Sampler-Induced Distributions
    Dieterich Lawson, George Tucker, Bo Dai, Rajesh Ranganath
    http://arxiv.org/abs/1910.14265v1

    • [cs.LG]Explainable Prediction of Adverse Outcomes Using Clinical Notes
    Justin R. Lovelace, Nathan C. Hurley, Adrian D. Haimovich, Bobak J. Mortazavi
    http://arxiv.org/abs/1910.14095v1

    • [cs.LG]Graph Structured Prediction Energy Networks
    Colin Graber, Alexander Schwing
    http://arxiv.org/abs/1910.14670v1

    • [cs.LG]Image-Conditioned Graph Generation for Road Network Extraction
    Davide Belli, Thomas Kipf
    http://arxiv.org/abs/1910.14388v1

    • [cs.LG]In-Place Zero-Space Memory Protection for CNN
    Hui Guan, Lin Ning, Zhen Lin, Xipeng Shen, Huiyang Zhou, Seung-Hwan Lim
    http://arxiv.org/abs/1910.14479v1

    • [cs.LG]Investigating Resistance of Deep Learning-based IDS against Adversaries using min-max Optimization
    Rana Abou Khamis, Omair Shafiq, Ashraf Matrawy
    http://arxiv.org/abs/1910.14107v1

    • [cs.LG]Iterative Hessian Sketch in Input Sparsity Time
    Graham Cormode, Charlie Dickens
    http://arxiv.org/abs/1910.14166v1

    • [cs.LG]Learning Disentangled Representations for Recommendation
    Jianxin Ma, Chang Zhou, Peng Cui, Hongxia Yang, Wenwu Zhu
    http://arxiv.org/abs/1910.14238v1

    • [cs.LG]Learning Fairness in Multi-Agent Systems
    Jiechuan Jiang, Zongqing Lu
    http://arxiv.org/abs/1910.14472v1

    • [cs.LG]Lsh-sampling Breaks the Computation Chicken-and-egg Loop in Adaptive Stochastic Gradient Estimation
    Beidi Chen, Yingchen Xu, Anshumali Shrivastava
    http://arxiv.org/abs/1910.14162v1

    • [cs.LG]Meta-Learning to Cluster
    Yibo Jiang, Nakul Verma
    http://arxiv.org/abs/1910.14134v1

    • [cs.LG]Multivariate Uncertainty in Deep Learning
    Rebecca L. Russell, Christopher Reale
    http://arxiv.org/abs/1910.14215v1

    • [cs.LG]NAT: Neural Architecture Transformer for Accurate and Compact Architectures
    Yong Guo, Yin Zheng, Mingkui Tan, Qi Chen, Jian Chen, Peilin Zhao, Junzhou Huang
    http://arxiv.org/abs/1910.14488v1

    • [cs.LG]Neural Assistant: Joint Action Prediction, Response Generation, and Latent Knowledge Reasoning
    Arvind Neelakantan, Semih Yavuz, Sharan Narang, Vishaal Prasad, Ben Goodrich, Daniel Duckworth, Chinnadhurai Sankar, Xifeng Yan
    http://arxiv.org/abs/1910.14613v1

    • [cs.LG]Neural networks trained with WiFi traces to predict airport passenger behavior
    Federico Orsini, Massimiliano Gastaldi, Luca Mantecchini, Riccardo Rossi
    http://arxiv.org/abs/1910.14026v1

    • [cs.LG]Object-oriented state editing for HRL
    Victor Bapst, Alvaro Sanchez-Gonzalez, Omar Shams, Kimberly Stachenfeld, Peter W. Battaglia, Satinder Singh, Jessica B. Hamrick
    http://arxiv.org/abs/1910.14361v1

    • [cs.LG]On the Convergence of Local Descent Methods in Federated Learning
    Farzin Haddadpour, Mehrdad Mahdavi
    http://arxiv.org/abs/1910.14425v1

    • [cs.LG]On the Regularization Properties of Structured Dropout
    Ambar Pal, Connor Lane, René Vidal, Benjamin D. Haeffele
    http://arxiv.org/abs/1910.14186v1

    • [cs.LG]Parameter Sharing Decoder Pair for Auto Composing
    Xu Zhao
    http://arxiv.org/abs/1910.14270v1

    • [cs.LG]Plan Arithmetic: Compositional Plan Vectors for Multi-Task Control
    Coline Devin, Daniel Geng, Pieter Abbeel, Trevor Darrell, Sergey Levine
    http://arxiv.org/abs/1910.14033v1

    • [cs.LG]Policy Continuation with Hindsight Inverse Dynamics
    Hao Sun, Zhizhong Li, Xiaotong Liu, Dahua Lin, Bolei Zhou
    http://arxiv.org/abs/1910.14055v1

    • [cs.LG]RLINK: Deep Reinforcement Learning for User Identity Linkage
    Xiaoxue Li, Yanan Cao, Yanmin Shang, Yangxi Li, Yanbing Liu, Jianlong Tan
    http://arxiv.org/abs/1910.14273v1

    • [cs.LG]Robust and Computationally-Efficient Anomaly Detection using Powers-of-Two Networks
    Usama Muneeb, Erdem Koyuncu, Yasaman Keshtkarjahromi, Hulya Seferoglu, Mehmet Fatih Erden, Ahmet Enis Cetin
    http://arxiv.org/abs/1910.14096v1

    • [cs.LG]Sample Complexity of Learning Mixtures of Sparse Linear Regressions
    Akshay Krishnamurthy, Arya Mazumdar, Andrew McGregor, Soumyabrata Pal
    http://arxiv.org/abs/1910.14106v1

    • [cs.LG]Sobolev Independence Criterion
    Youssef Mroueh, Tom Sercu, Mattia Rigotti, Inkit Padhi, Cicero Dos Santos
    http://arxiv.org/abs/1910.14212v1

    • [cs.LG]Solving NMF with smoothness and sparsity constraints using PALM
    Raimon Fabregat, Nelly Pustelnik, Paulo Gonçalves, Pierre Borgnat
    http://arxiv.org/abs/1910.14576v1

    • [cs.LG]Transport Model for Feature Extraction
    Wojciech Czaja, Dong Dong, Pierre-Emmanuel Jabin, Franck Olivier Ndjakou Njeunje
    http://arxiv.org/abs/1910.14543v1

    • [cs.LG]Understanding Isomorphism Bias in Graph Data Sets
    Sergei Ivanov, Sergei Sviridov, Evgeny Burnaev
    http://arxiv.org/abs/1910.12091v2

    • [cs.LG]Unsupervised Star Galaxy Classification with Cascade Variational Auto-Encoder
    Hao Sun, Jiadong Guo, Edward J. Kim, Robert J. Brunner
    http://arxiv.org/abs/1910.14056v1

    • [cs.LG]VASE: Variational Assorted Surprise Exploration for Reinforcement Learning
    Haitao Xu, Brendan McCane, Lech Szymanski
    http://arxiv.org/abs/1910.14351v1

    • [cs.LG]What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers
    Ananth Balashankar, Alyssa Lees, Chris Welty, Lakshminarayanan Subramanian
    http://arxiv.org/abs/1910.14120v1

    • [cs.LO]Belief revision and 3-valued logics: Characterization of 19,683 belief change operators
    Nerio Borges, Ramón Pino Pérez
    http://arxiv.org/abs/1910.14138v1

    • [cs.NE]An Automatic Design Framework of Swarm Pattern Formation based on Multi-objective Genetic Programming
    Zhun Fan, Zhaojun Wang, Xiaomin Zhu, Bingliang Hu
    http://arxiv.org/abs/1910.14627v1

    • [cs.NE]Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
    C. Daniel Freeman, Luke Metz, David Ha
    http://arxiv.org/abs/1910.13038v2

    • [cs.NE]Sharp Bounds for Genetic Drift in EDAs
    Benjamin Doerr, Weijie Zheng
    http://arxiv.org/abs/1910.14389v1

    • [cs.RO]CALC2.0: Combining Appearance, Semantic and Geometric Information for Robust and Efficient Visual Loop Closure
    Nathaniel Merrill, Guoquan Huang
    http://arxiv.org/abs/1910.14103v1

    • [cs.RO]Crop Height and Plot Estimation from Unmanned Aerial Vehicles using 3D LiDAR
    Harnaik Dhami, Kevin Yu, Tianshu Xu, Qian Zhu, Kshitiz Dhakal, James Friel, Song Li, Pratap Tokekar
    http://arxiv.org/abs/1910.14031v1

    • [cs.RO]Duckiefloat: a Collision-Tolerant Resource-Constrained Blimp for Long-Term Autonomy in Subterranean Environments
    Yi-Wei Huang, Chen-Lung Lu, Kuan-Lin Chen, Po-Sheng Ser, Jui-Te Huang, Yu-Chia Shen, Pin-Wei Chen, Po-Kai Chang, Sheng-Cheng Lee, Hsueh-Cheng Wang
    http://arxiv.org/abs/1910.14275v1

    • [cs.RO]Dynamic Cloth Manipulation with Deep Reinforcement Learning
    Rishabh Jangir, Guillem Alenya, Carme Torras
    http://arxiv.org/abs/1910.14475v1

    • [cs.RO]Interactive Gibson: A Benchmark for Interactive Navigation in Cluttered Environments
    Fei Xia, William B. Shen, Chengshu Li, Priya Kasimbeg, Micael Tchapmi, Alexander Toshev, Roberto Martín-Martín, Silvio Savarese
    http://arxiv.org/abs/1910.14442v1

    • [cs.RO]S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenes
    Yuzhe Qin, Rui Chen, Hao Zhu, Meng Song, Jing Xu, Hao Su
    http://arxiv.org/abs/1910.14218v1

    • [cs.RO]Team NCTU: Toward AI-Driving for Autonomous Surface Vehicles — From Duckietown to RobotX
    Yi-Wei Huang, Tzu-Kuan Chuang, Ni-Ching Lin, Yu-Chieh Hsiao, Pin-Wei Chen, Ching-Tang Hung, Shih-Hsing Liu, Hsiao-Sheng Chen, Ya-Hsiu Hsieh, Ching-Tang Hung, Yen-Hsiang Huang, Yu-Xuan Chen, Kuan-Lin Chen, Ya-Jou Lan, Chao-Chun Hsu, Chun-Yi Lin, Jhih-Ying Li, Jui-Te Huang, Yu-Jen Menn, Sin-Kiat Lim, Kim-Boon Lua, Chia-Hung Dylan Tsai, Chi-Fang Chen, Hsueh-Cheng Wang
    http://arxiv.org/abs/1910.14540v1

    • [cs.RO]Towards vision-based robotic skins: a data-driven, multi-camera tactile sensor
    Camill Trueeb, Carmelo Sferrazza, Raffaello D’Andrea
    http://arxiv.org/abs/1910.14526v1

    • [cs.SE]Selecting Reliable Blockchain Peers via Hybrid Blockchain Reliability Prediction
    Peilin Zheng, Zibin Zheng, Liang Chen
    http://arxiv.org/abs/1910.14614v1

    • [cs.SI]Semi-supervisedly Co-embedding Attributed Networks
    Zaiqiao Meng, Shangsong Liang, Jinyuan Fang, Teng Xiao
    http://arxiv.org/abs/1910.14491v1

    • [eess.AS]End-to-end Microphone Permutation and Number Invariant Multi-channel Speech Separation
    Yi Luo, Zhuo Chen, Nima Mesgarani, Takuya Yoshioka
    http://arxiv.org/abs/1910.14104v1

    • [eess.IV]Conditional Denoising of Remote Sensing Imagery Using Cycle-Consistent Deep Generative Models
    Michael Zotov, Jevgenij Gamper
    http://arxiv.org/abs/1910.14567v1

    • [eess.IV]Flash X-ray diffraction imaging in 3D: a proposed analysis pipeline
    Jing Liu, Stefan Engblom, Carl Nettelblad
    http://arxiv.org/abs/1910.14029v1

    • [eess.IV]Image-Guided Depth Upsampling via Hessian and TV Priors
    Alireza Ahrabian, Joao F. C. Mota, Andrew M. Wallace
    http://arxiv.org/abs/1910.14377v1

    • [eess.IV]Multi-defect microscopy image restoration under limited data conditions
    Anastasia Razdaibiedina, Jeevaa Velayutham, Miti Modi
    http://arxiv.org/abs/1910.14207v1

    • [eess.IV]On the Proof of Fixed-Point Convergence for Plug-and-Play ADMM
    Ruturaj G. Gavaskar, Kunal N. Chaudhury
    http://arxiv.org/abs/1910.14325v1

    • [eess.SP]Geometric Sequence Decomposition with $k$-simplexes Transform
    Woong-Hee Lee, Jong-Ho Lee, Ki Won Sung
    http://arxiv.org/abs/1910.14412v1

    • [eess.SY]Recurrent averaging inequalities, opinion formation and distributed algorithms
    Anton V. Proskurnikov, Giuseppe Calafiore, Ming Cao
    http://arxiv.org/abs/1910.14465v1

    • [math.NA]Spectral properties of kernel matrices in the flat limit
    Simon Barthelmé, Konstantin Usevich
    http://arxiv.org/abs/1910.14067v1

    • [math.OC]A Decentralized Proximal Point-type Method for Saddle Point Problems
    Weijie Liu, Aryan Mokhtari, Asuman Ozdaglar, Sarath Pattathil, Zebang Shen, Nenggan Zheng
    http://arxiv.org/abs/1910.14380v1

    • [math.OC]Mixing of Stochastic Accelerated Gradient Descent
    Peiyuan Zhang, Hadi Daneshmand, Thomas Hofmann
    http://arxiv.org/abs/1910.14616v1

    • [math.PR]Phase Transitions for Detecting Latent Geometry in Random Graphs
    Matthew Brennan, Guy Bresler, Dheeraj Nagaraj
    http://arxiv.org/abs/1910.14167v1

    • [math.ST]Multiplicative noise in Bayesian inverse problems: Well-posedness and consistency of MAP estimators
    Matthew M. Dunlop
    http://arxiv.org/abs/1910.14632v1

    • [math.ST]Rate of convergence for geometric inference based on the empirical Christoffel function
    Mai Trang Vu, François Bachoc, Edouard Pauwels
    http://arxiv.org/abs/1910.14458v1

    • [physics.acc-ph]Machine learning for design optimization of storage ring nonlinear dynamics
    Faya Wang, Minghao Song, Auralee Edelen, Xiaobiao Huang
    http://arxiv.org/abs/1910.14220v1

    • [physics.comp-ph]Connecting exciton diffusion with surface roughness via deep learning
    Liyao Lyu, Zhiwen Zhang, Jingrun Chen
    http://arxiv.org/abs/1910.14209v1

    • [physics.comp-ph]Evaluation of Surrogate Models for Multi-fin Flapping Propulsion Systems
    Kamal Viswanath, Alisha Sharma, Saketh Gabbita, Jason Geder, Ravi Ramamurti, Marius Pruessner
    http://arxiv.org/abs/1910.14194v1

    • [physics.med-ph]The importance of evaluating the complete automated knowledge-based planning pipeline
    Aaron Babier, Rafid Mahmood, Andrea L. McNiven, Adam Diamant, Timothy C. Y. Chan
    http://arxiv.org/abs/1910.14257v1

    • [q-bio.GN]Assessment of Multiple-Biomarker Classifiers: fundamental principles and a proposed strategy
    Waleed A. Yousef
    http://arxiv.org/abs/1910.14502v1

    • [q-bio.QM]Precision disease networks (PDN)
    J. Cabrera, D. Amaratunga, W. Kostis, J Kostis
    http://arxiv.org/abs/1910.14460v1

    • [stat.AP]Accounting for Location Measurement Error in Atomic Resolution Images of Crystalline Materials
    Matthew J. Miller, Matthew J. Cabral, Elizabeth C. Dickey, James M. LeBeau, Brian J. Reich
    http://arxiv.org/abs/1910.14195v1

    • [stat.AP]Change Point Detection for Nonparametric Regression under Strongly Mixing Process
    Q. Yang, Y. Li, Y. Zhang
    http://arxiv.org/abs/1910.14330v1

    • [stat.AP]EnergyStar++: Towards more accurate and explanatory building energy benchmarking
    Pandarasamy Arjunan, Kameshwar Poolla, Clayton Miller
    http://arxiv.org/abs/1910.14563v1

    • [stat.AP]Horvitz-Thompson-like estimation with distance-based detection probabilities for circular plot sampling of forests
    Kasper Kansanen, Petteri Packalen, Matti Maltamo, Lauri Mehtätalo
    http://arxiv.org/abs/1910.14647v1

    • [stat.CO]“multiColl”: An R package to detect multicollinearity
    Román Salmerón, Catalina García, José García
    http://arxiv.org/abs/1910.14590v1

    • [stat.CO]Bayesian nonstationary Gaussian process modeling: the BayesNSGP package for R
    Mark D. Risser, Daniel Turek
    http://arxiv.org/abs/1910.14101v1

    • [stat.CO]Combined parameter and state inference with automatically calibrated ABC
    Anthony Ebert, Pierre Pudlo, Kerrie Mengersen, Paul Wu
    http://arxiv.org/abs/1910.14227v1

    • [stat.CO]Evaluation of Granger causality measures for constructing networks from multivariate time series
    Elsa Siggiridou, Christos Koutlis, Alkiviadis Tsimpiris, Dimitris Kugiumtzis
    http://arxiv.org/abs/1910.14290v1

    • [stat.CO]Parameter elimination in particle Gibbs sampling
    Anna Wigren, Riccardo Sven Risuleo, Lawrence Murray, Fredrik Lindsten
    http://arxiv.org/abs/1910.14145v1

    • [stat.ME]A Semiparametric Approach to Model-based Sensitivity Analysis in Observational Studies
    Bo Zhang, Eric J. Tchetgen Tchetgen
    http://arxiv.org/abs/1910.14130v1

    • [stat.ME]Connecting population-level AUC and latent scale-invariant $R^2$ via Semiparametric Gaussian Copula and rank correlations
    Debangan Dey, Vadim Zipunnikov
    http://arxiv.org/abs/1910.14233v1

    • [stat.ME]New weighted $L^2$-type tests for the inverse Gaussian distribution
    J. S. Allison, S. Betsch, B. Ebner, I. J. H. Visagie
    http://arxiv.org/abs/1910.14119v1

    • [stat.ME]Order Determination for Spiked Models
    Yicheng Zeng, Lixing Zhu
    http://arxiv.org/abs/1910.14498v1

    • [stat.ME]Probabilistic Detection and Estimation of Conic Sections from Noisy Data
    Subharup Guha, Sujit K. Ghosh
    http://arxiv.org/abs/1910.14078v1

    • [stat.ML]A study of data and label shift in the LIME framework
    Amir Hossein Akhavan Rahnama, Henrik Boström
    http://arxiv.org/abs/1910.14421v1

    • [stat.ML]Enhancing Certifiable Robustness via a Deep Model Ensemble
    Huan Zhang, Minhao Cheng, Cho-Jui Hsieh
    http://arxiv.org/abs/1910.14655v1

    • [stat.ML]Heteroscedastic Calibration of Uncertainty Estimators in Deep Learning
    Bindya Venkatesh, Jayaraman J. Thiagarajan
    http://arxiv.org/abs/1910.14179v1

    • [stat.ML]Investigating Under and Overfitting in Wasserstein Generative Adversarial Networks
    Ben Adlam, Charles Weill, Amol Kapoor
    http://arxiv.org/abs/1910.14137v1

    • [stat.ML]Kernel-Guided Training of Implicit Generative Models with Stability Guarantees
    Arash Mehrjou, Wittawat Jitkrittum, Krikamol Muandet, Bernhard Schölkopf
    http://arxiv.org/abs/1910.14428v1

    • [stat.ML]Learn-By-Calibrating: Using Calibration as a Training Objective
    Jayaraman J. Thiagarajan, Bindya Venkatesh, Deepta Rajan
    http://arxiv.org/abs/1910.14175v1

    • [stat.ML]Recovering Bandits
    Ciara Pike-Burke, Steffen Grünewälder
    http://arxiv.org/abs/1910.14354v1

    • [stat.ML]SPARQ-SGD: Event-Triggered and Compressed Communication in Decentralized Stochastic Optimization
    Navjot Singh, Deepesh Data, Jemin George, Suhas Diggavi
    http://arxiv.org/abs/1910.14280v1

    • [stat.ML]Unsupervised inference approach to facial attractiveness
    Miguel Ibáñez-Berganza, Gian Luca Lancia, Ambra Amico, Bernardo Monechi, Vittorio Loreto
    http://arxiv.org/abs/1910.14072v1