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
·····································
• [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