astro-ph.IM - 仪器仪表和天体物理学方法
cond-mat.mes-hall - 尺度和物理纳米 cs.AI - 人工智能 cs.CG - 计算几何学 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.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.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.med-ph - 医学物理学 q-bio.MN - 分子网络 q-bio.NC - 神经元与认知 q-bio.QM - 定量方法 quant-ph - 量子物理 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 stat.OT - 其他统计学
• [astro-ph.IM]Development and Testing of an Engineering Model for an Asteroid Hopping Robot
• [cond-mat.mes-hall]Improvement in Retention Time of Capacitorless DRAM with Access Transistor
• [cs.AI]Detecting AI Trojans Using Meta Neural Analysis
• [cs.AI]Fast Task-Adaptation for Tasks Labeled Using Natural Language in Reinforcement Learning
• [cs.AI]Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancing Knowledge Graph Embedding
• [cs.AI]Model-based Reinforcement Learning for Predictions and Control for Limit Order Books
• [cs.AI]Toward a Computational Theory of Evidence-Based Reasoning for Instructable Cognitive Agents
• [cs.CG]On geodesic triangles with right angles in a dually flat space
• [cs.CL]Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Models
• [cs.CL]Assessing the Efficacy of Clinical Sentiment Analysis and Topic Extraction in Psychiatric Readmission Risk Prediction
• [cs.CL]BHAAV- A Text Corpus for Emotion Analysis from Hindi Stories
• [cs.CL]Do People Prefer “Natural” code?
• [cs.CL]Executing Instructions in Situated Collaborative Interactions
• [cs.CL]Is Multilingual BERT Fluent in Language Generation?
• [cs.CL]Knowledge Distillation from Internal Representations
• [cs.CL]Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations
• [cs.CL]Novel Applications of Factored Neural Machine Translation
• [cs.CL]The Daunting Task of Real-World Textual Style Transfer Auto-Evaluation
• [cs.CL]Towards De-identification of Legal Texts
• [cs.CL]Transformers: State-of-the-art Natural Language Processing
• [cs.CL]Word Embedding Visualization Via Dictionary Learning
• [cs.CR]Privacy-preserving and yet Robust Collaborative Filtering Recommender as a Service
• [cs.CV]3D Manhattan Room Layout Reconstruction from a Single 360 Image
• [cs.CV]A Semi-Supervised Maximum Margin Metric Learning Approach for Small Scale Person Re-identification
• [cs.CV]BIAS: Transparent reporting of biomedical image analysis challenges
• [cs.CV]Bias-Resilient Neural Network
• [cs.CV]Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusion
• [cs.CV]Detection and Identification of Objects and Humans in Thermal Images
• [cs.CV]ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations
• [cs.CV]Exploring Hate Speech Detection in Multimodal Publications
• [cs.CV]Fast Panoptic Segmentation Network
• [cs.CV]FisheyeDistanceNet: Self-Supervised Scale-Aware Distance Estimation using Monocular Fisheye Camera for Autonomous Driving
• [cs.CV]Gradient Information Guided Deraining with A Novel Network and Adversarial Training
• [cs.CV]Graph-based Spatial-temporal Feature Learning for Neuromorphic Vision Sensing
• [cs.CV]Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation
• [cs.CV]Learning deep forest with multi-scale Local Binary Pattern features for face anti-spoofing
• [cs.CV]Learning to Generalize One Sample at a Time with Self-Supervision
• [cs.CV]MIDV-2019: Challenges of the modern mobile-based document OCR
• [cs.CV]Meta-Transfer Learning through Hard Tasks
• [cs.CV]MixMatch Domain Adaptaion: Prize-winning solution for both tracks of VisDA 2019 challenge
• [cs.CV]Multiple Kernel Fisher Discriminant Metric Learning for Person Re-identification
• [cs.CV]NADS-Net: A Nimble Architecture for Driver and Seat Belt Detection via Convolutional Neural Networks
• [cs.CV]Next integrated result modelling for stopping the text field recognition process in a video using a result model with per-character alternatives
• [cs.CV]Patch Refinement — Localized 3D Object Detection
• [cs.CV]Person re-identification based on Res2Net network
• [cs.CV]Prose for a Painting
• [cs.CV]REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs
• [cs.CV]SNIDER: Single Noisy Image Denoising and Rectification for Improving License Plate Recognition
• [cs.CV]Semantic Understanding of Foggy Scenes with Purely Synthetic Data
• [cs.CV]Semantic-aware Image Deblurring
• [cs.CV]Skin Lesion Classification Using Ensembles of Multi-Resolution EfficientNets with Meta Data
• [cs.CV]Unaligned Image-to-Sequence Transformation with Loop Consistency
• [cs.CV]Vehicle Re-identification with Viewpoint-aware Metric Learning
• [cs.CV]View Confusion Feature Learning for Person Re-identification
• [cs.DC]Fog Computing as Privacy Enabler
• [cs.DC]Performance Impact of Memory Channels on Sparse and Irregular Algorithms
• [cs.DL]The role of mainstreamness and interdisciplinarity for the relevance of scientific papers
• [cs.DS]Span-core Decomposition for Temporal Networks: Algorithms and Applications
• [cs.IT]A Data Concealing Technique with Random Noise Disturbance and A Restoring Technique for the Concealed Data by Stochastic Process Estimation
• [cs.IT]A Survey on Deep-Learning based Techniques for Modeling and Estimation of MassiveMIMO Channels
• [cs.IT]Alternate Distributed Beamforming for Decode-and-Forward Multi-Relay Systems Using Buffers
• [cs.IT]Approaching the Finite Blocklength Capacity within 0.025dB by Short Polar Codes and CRC-Aided Hybrid Decoding
• [cs.IT]Counterexamples on the monotonicity of delay optimal strategies for energy harvesting transmitters
• [cs.IT]DNN-Aided Block Sparse Bayesian Learning for User Activity Detection and Channel Estimation in Grant-Free Non-Orthogonal Random Access
• [cs.IT]DNN-Aided Message Passing Based Block Sparse Bayesian Learning for Joint User Activity Detection and Channel Estimation
• [cs.IT]Entanglement-Enabled Communication
• [cs.IT]Evaluation of Error Probability of Classification Based on the Analysis of the Bayes Code
• [cs.IT]High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning
• [cs.IT]Overcoming DoF Limitation in Robust Beamforming: A Penalized Inequality-Constrained Approach
• [cs.IT]Secret key agreement from correlated data, with no prior information
• [cs.IT]Understanding the Performance of Bluetooth Mesh: Reliability, Delay and Scalability Analysis
• [cs.LG]A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks
• [cs.LG]Accelerating Federated Learning via Momentum Gradient Descent
• [cs.LG]Adversarial Learning of Deepfakes in Accounting
• [cs.LG]Algorithmic Probability-guided Supervised Machine Learning on Non-differentiable Spaces
• [cs.LG]An MDL-Based Classifier for Transactional Datasets with Application in Malware Detection
• [cs.LG]AutoML using Metadata Language Embeddings
• [cs.LG]Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs
• [cs.LG]Compatible features for Monotonic Policy Improvement
• [cs.LG]Continual Learning Using Bayesian Neural Networks
• [cs.LG]Ctrl-Z: Recovering from Instability in Reinforcement Learning
• [cs.LG]DEVDAN: Deep Evolving Denoising Autoencoder
• [cs.LG]Deep Latent Defence
• [cs.LG]Derivative-Free & Order-Robust Optimisation
• [cs.LG]Dissecting Deep Neural Networks
• [cs.LG]Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression
• [cs.LG]FedMD: Heterogenous Federated Learning via Model Distillation
• [cs.LG]How Well Do WGANs Estimate the Wasserstein Metric?
• [cs.LG]Improving Generalization in Meta Reinforcement Learning using Learned Objectives
• [cs.LG]Investigation on the generalization of the Sampled Policy Gradient algorithm
• [cs.LG]Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?
• [cs.LG]Learning Near-optimal Convex Combinations of Basis Models with Generalization Guarantees
• [cs.LG]Linking emotions to behaviors through deep transfer learning
• [cs.LG]Loss Surface Sightseeing by Multi-Point Optimization
• [cs.LG]MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions
• [cs.LG]Model-Based Reinforcement Learning Exploiting State-Action Equivalence
• [cs.LG]Multi-Modal Simultaneous Forecasting of Vehicle Position Sequences using Social Attention
• [cs.LG]Multiple-objective Reinforcement Learning for Inverse Design and Identification
• [cs.LG]Nearly Minimal Over-Parametrization of Shallow Neural Networks
• [cs.LG]On Dimension-free Tail Inequalities for Sums of Random Matrices and Applications
• [cs.LG]On the Possibility of Rewarding Structure Learning Agents: Mutual Information on Linguistic Random Sets
• [cs.LG]Policy Optimization Through Approximated Importance Sampling
• [cs.LG]Receding Horizon Curiosity
• [cs.LG]Sequential VAE-LSTM for Anomaly Detection on Time Series
• [cs.LG]SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations
• [cs.LG]Social Learning in Multi Agent Multi Armed Bandits
• [cs.LG]Supervised feature selection with orthogonal regression and feature weighting
• [cs.LG]Text-to-Image Synthesis Based on Machine Generated Captions
• [cs.LG]The fastest $\ell_{1,\infty}$ prox in the west
• [cs.NE]Deep neural network for pier scour prediction
• [cs.NE]Large Scale Global Optimization by Hybrid Evolutionary Computation
• [cs.NI]Explaining Deep Learning-Based Networked Systems
• [cs.NI]Hierarchical Deep Double Q-Routing
• [cs.RO]A Brain-Inspired Compact Cognitive Mapping System
• [cs.RO]Automated Multidisciplinary Design and Control of Hopping Robots for Exploration of Extreme Environments on the Moon and Mars
• [cs.RO]Autonomous Multirobot Technologies for Mars Mining Base Construction and Operation
• [cs.RO]Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models
• [cs.RO]Knowledge Induced Deep Q-Network for a Slide-to-Wall Object Grasping
• [cs.RO]Learned Critical Probabilistic Roadmaps for Robotic Motion Planning
• [cs.RO]Multi-Vehicle Interaction Scenarios Generation with Interpretable Traffic Primitives and Gaussian Process Regression
• [cs.RO]Multimodal representation models for prediction and control from partial information
• [cs.RO]Stochastic Triangular Mesh Mapping
• [cs.RO]Towards Learning to Detect and Predict Contact Events on Vision-based Tactile Sensors
• [cs.SI]A k-hop Collaborate Game Model: Adaptive Strategy to Maximize Total Revenue
• [cs.SI]Link Prediction Under Imperfect Detection: Collaborative Filtering for Ecological Networks
• [cs.SI]Rejection-Based Simulation of Non-Markovian Agents on Complex Networks
• [eess.AS]MelGAN-VC: Voice Conversion and Audio Style Transfer on arbitrarily long samples using Spectrograms
• [eess.IV]Cribriform pattern detection in prostate histopathological images using deep learning models
• [eess.IV]Deep Learning Accelerated Light Source Experiments
• [eess.IV]Did you miss it? Automatic lung nodule detection combined with gaze information improves radiologists’ screening performance
• [eess.IV]FastSurfer — A fast and accurate deep learning based neuroimaging pipeline
• [eess.IV]Large-scale Gastric Cancer Screening and Localization Using Multi-task Deep Neural Network
• [eess.IV]Wavelet Domain Style Transfer for an Effective Perception-distortion Tradeoff in Single Image Super-Resolution
• [math.NA]Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee
• [math.OC]Bregman Proximal Framework for Deep Linear Neural Networks
• [math.ST]Nonparametric principal subspace regression
• [math.ST]On adaptivity of wavelet thresholding estimators with negatively super-additive dependent noise
• [math.ST]On the feasibility of parsimonious variable selection for Hotelling’s $T^2$-test
• [math.ST]Penalized regression via the restricted bridge estimator
• [math.ST]Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm
• [math.ST]Variance reduction for Markov chains with application to MCMC
• [physics.med-ph]A cascaded dual-domain deep learning reconstruction method for sparsely spaced multidetector helical CT
• [q-bio.MN]BoolSi: a tool for distributed simulations and analysis of Boolean networks
• [q-bio.NC]Dynamic Brain Functional Networks Guided By Anatomical Knowledge
• [q-bio.QM]A Dual-Hormone Closed-Loop Delivery System for Type 1 Diabetes Using Deep Reinforcement Learning
• [quant-ph]Second-order coding rates for key distillation in quantum key distribution
• [stat.AP]On Post-Selection Inference in A/B Tests
• [stat.CO]Distilling importance sampling
• [stat.ME]A Bayesian Nonparametric Framework for Uncertainty Quantification in Simulation
• [stat.ME]A New Confidence Interval for Odds Ratio
• [stat.ME]Controlling Costs: Feature Selection on a Budget
• [stat.ME]Estimands and Inference in Cluster-Randomized Vaccine Trials
• [stat.ME]Forecast Aggregation via Peer Prediction
• [stat.ME]Percentile-Based Residuals for Model Assessment
• [stat.ME]Semi-parametric Bayes Regression with Network Valued Covariates
• [stat.ML]Active ordinal tuplewise querying for similarity learning
• [stat.ML]Deterministic Completion of Rectangular Matrices Using Ramanujan Bigraphs — II: Explicit Constructions and Phase Transitions
• [stat.ML]Estimating Density Models with Complex Truncation Boundaries
• [stat.ML]Estimating regression errors without ground truth values
• [stat.ML]Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization
• [stat.ML]Learning with minibatch Wasserstein : asymptotic and gradient properties
• [stat.ML]Optimal Training of Fair Predictive Models
• [stat.ML]Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks
• [stat.ML]Practical Posterior Error Bounds from Variational Objectives
• [stat.ML]Private Protocols for U-Statistics in the Local Model and Beyond
• [stat.ML]Probabilistic sequential matrix factorization
• [stat.ML]Spatio-Temporal Alignments: Optimal transport through space and time
• [stat.ML]The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure
• [stat.OT]Computing the Expected Value of Sample Information Efficiently: Expertise and Skills Required for Four Model-Based Methods
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• [astro-ph.IM]Development and Testing of an Engineering Model for an Asteroid Hopping Robot
Greg Wilburn, Himangshu Kalita, Jekan Thangavelautham
http://arxiv.org/abs/1910.03831v1
• [cond-mat.mes-hall]Improvement in Retention Time of Capacitorless DRAM with Access Transistor
Md. Hasan Raza Ansari, Jawar Singh Member
http://arxiv.org/abs/1910.03907v1
• [cs.AI]Detecting AI Trojans Using Meta Neural Analysis
Xiaojun Xu, Qi Wang, Huichen Li, Nikita Borisov, Carl A. Gunter, Bo Li
http://arxiv.org/abs/1910.03137v2
• [cs.AI]Fast Task-Adaptation for Tasks Labeled Using Natural Language in Reinforcement Learning
Matthias Hutsebaut-Buysse, Kevin Mets, Steven Latré
http://arxiv.org/abs/1910.04040v1
• [cs.AI]Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancing Knowledge Graph Embedding
Wenqiang Liu, Hongyun Cai, Xu Cheng, Sifa Xie, Yipeng Yu, Hanyu Zhang
http://arxiv.org/abs/1910.03891v1
• [cs.AI]Model-based Reinforcement Learning for Predictions and Control for Limit Order Books
Haoran Wei, Yuanbo Wang, Lidia Mangu, Keith Decker
http://arxiv.org/abs/1910.03743v1
• [cs.AI]Toward a Computational Theory of Evidence-Based Reasoning for Instructable Cognitive Agents
Gheorghe Tecuci, Dorin Marcu, Mihai Boicu, Steven Meckl, Chirag Uttamsingh
http://arxiv.org/abs/1910.03990v1
• [cs.CG]On geodesic triangles with right angles in a dually flat space
Frank Nielsen
http://arxiv.org/abs/1910.03935v1
• [cs.CL]Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Models
Qingyang Wu, Yichi Zhang, Yu Li, Zhou Yu
http://arxiv.org/abs/1910.03756v1
• [cs.CL]Assessing the Efficacy of Clinical Sentiment Analysis and Topic Extraction in Psychiatric Readmission Risk Prediction
Elena Alvarez-Mellado, Eben Holderness, Nicholas Miller, Fyonn Dhang, Philip Cawkwell, Kirsten Bolton, James Pustejovsky, Mei-Hua Hall
http://arxiv.org/abs/1910.04006v1
• [cs.CL]BHAAV- A Text Corpus for Emotion Analysis from Hindi Stories
Yaman Kumar, Debanjan Mahata, Sagar Aggarwal, Anmol Chugh, Rajat Maheshwari, Rajiv Ratn Shah
http://arxiv.org/abs/1910.04073v1
• [cs.CL]Do People Prefer “Natural” code?
Casey Casalnuovo, Kevin Lee, Hulin Wang, Prem Devanbu, Emily Morgan
http://arxiv.org/abs/1910.03704v1
• [cs.CL]Executing Instructions in Situated Collaborative Interactions
Alane Suhr, Claudia Yan, Jacob Schluger, Stanley Yu, Hadi Khader, Marwa Mouallem, Iris Zhang, Yoav Artzi
http://arxiv.org/abs/1910.03655v1
• [cs.CL]Is Multilingual BERT Fluent in Language Generation?
Samuel Rönnqvist, Jenna Kanerva, Tapio Salakoski, Filip Ginter
http://arxiv.org/abs/1910.03806v1
• [cs.CL]Knowledge Distillation from Internal Representations
Gustavo Aguilar, Yuan Ling, Yu Zhang, Benjamin Yao, Xing Fan, Edward Guo
http://arxiv.org/abs/1910.03723v1
• [cs.CL]Make Up Your Mind! Adversarial Generation of Inconsistent Natural Language Explanations
Oana-Maria Camburu, Brendan Shillingford, Pasquale Minervini, Thomas Lukasiewicz, Phil Blunsom
http://arxiv.org/abs/1910.03065v2
• [cs.CL]Novel Applications of Factored Neural Machine Translation
Patrick Wilken, Evgeny Matusov
http://arxiv.org/abs/1910.03912v1
• [cs.CL]The Daunting Task of Real-World Textual Style Transfer Auto-Evaluation
Richard Yuanzhe Pang
http://arxiv.org/abs/1910.03747v1
• [cs.CL]Towards De-identification of Legal Texts
Diego Garat, Dina Wonsever
http://arxiv.org/abs/1910.03739v1
• [cs.CL]Transformers: State-of-the-art Natural Language Processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Jamie Brew
http://arxiv.org/abs/1910.03771v1
• [cs.CL]Word Embedding Visualization Via Dictionary Learning
Juexiao Zhang, Yubei Chen, Brian Cheung, Bruno A Olshausen
http://arxiv.org/abs/1910.03833v1
• [cs.CR]Privacy-preserving and yet Robust Collaborative Filtering Recommender as a Service
Qiang Tang
http://arxiv.org/abs/1910.03846v1
• [cs.CV]3D Manhattan Room Layout Reconstruction from a Single 360 Image
Chuhang Zou, Jheng-Wei Su, Chi-Han Peng, Alex Colburn, Qi Shan, Peter Wonka, Hung-Kuo Chu, Derek Hoiem
http://arxiv.org/abs/1910.04099v1
• [cs.CV]A Semi-Supervised Maximum Margin Metric Learning Approach for Small Scale Person Re-identification
T M Feroz Ali, Subhasis Chaudhuri
http://arxiv.org/abs/1910.03905v1
• [cs.CV]BIAS: Transparent reporting of biomedical image analysis challenges
Lena Maier-Hein, Annika Reinke, Michal Kozubek, Anne L. Martel, Tal Arbel, Matthias Eisenmann, Allan Hanbuary, Pierre Jannin, Henning Müller, Sinan Onogur, Julio Saez-Rodriguez, Bram van Ginneken, Annette Kopp-Schneider, Bennett Landman
http://arxiv.org/abs/1910.04071v1
• [cs.CV]Bias-Resilient Neural Network
Ehsan Adeli, Qingyu Zhao, Adolf Pfefferbaum, Edith V. Sullivan, Li Fei-Fei, Juan Carlos Niebles, Kilian M. Pohl
http://arxiv.org/abs/1910.03676v1
• [cs.CV]Deep Convolutional Neural Network for Multi-modal Image Restoration and Fusion
Xin Deng, Pier Luigi Dragotti
http://arxiv.org/abs/1910.04066v1
• [cs.CV]Detection and Identification of Objects and Humans in Thermal Images
Manish Bhattarai, Manel Martínez-Ramón
http://arxiv.org/abs/1910.03617v1
• [cs.CV]ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations
Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree Kalpathy-Cramer, Ramesh Raskar
http://arxiv.org/abs/1910.03731v1
• [cs.CV]Exploring Hate Speech Detection in Multimodal Publications
Raul Gomez, Jaume Gibert, Lluis Gomez, Dimosthenis Karatzas
http://arxiv.org/abs/1910.03814v1
• [cs.CV]Fast Panoptic Segmentation Network
Daan de Geus, Panagiotis Meletis, Gijs Dubbelman
http://arxiv.org/abs/1910.03892v1
• [cs.CV]FisheyeDistanceNet: Self-Supervised Scale-Aware Distance Estimation using Monocular Fisheye Camera for Autonomous Driving
Varun Ravi Kumar, Sandesh Athni Hiremath, Stefan Milz, Christian Witt, Clement Pinnard, Senthil Yogamani, Patrick Mader
http://arxiv.org/abs/1910.04076v1
• [cs.CV]Gradient Information Guided Deraining with A Novel Network and Adversarial Training
Yinglong Wang, Haokui Zhang, Yu Liu, Qinfeng Shi, Bing Zeng
http://arxiv.org/abs/1910.03839v1
• [cs.CV]Graph-based Spatial-temporal Feature Learning for Neuromorphic Vision Sensing
Yin Bi, Aaron Chadha, Alhabib Abbas, Eirina Bourtsoulatze, Yiannis Andreopoulos
http://arxiv.org/abs/1910.03579v1
• [cs.CV]Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation
Zhijie Fang, Antonio M. López
http://arxiv.org/abs/1910.03858v1
• [cs.CV]Learning deep forest with multi-scale Local Binary Pattern features for face anti-spoofing
Rizhao Cai, Changsheng Chen
http://arxiv.org/abs/1910.03850v1
• [cs.CV]Learning to Generalize One Sample at a Time with Self-Supervision
Antonio D’Innocente, Silvia Bucci, Tatiana Tommasi, Barbara Caputo
http://arxiv.org/abs/1910.03915v1
• [cs.CV]MIDV-2019: Challenges of the modern mobile-based document OCR
Konstantin Bulatov, Daniil Matalov, Vladimir V. Arlazarov
http://arxiv.org/abs/1910.04009v1
• [cs.CV]Meta-Transfer Learning through Hard Tasks
Qianru Sun, Yaoyao Liu, Zhaozheng Chen, Tat-Seng Chua, Bernt Schiele
http://arxiv.org/abs/1910.03648v1
• [cs.CV]MixMatch Domain Adaptaion: Prize-winning solution for both tracks of VisDA 2019 challenge
Danila Rukhovich, Danil Galeev
http://arxiv.org/abs/1910.03903v1
• [cs.CV]Multiple Kernel Fisher Discriminant Metric Learning for Person Re-identification
T M Feroz Ali, Kalpesh K Patel, Rajbabu Velmurugan, Subhasis Chaudhuri
http://arxiv.org/abs/1910.03923v1
• [cs.CV]NADS-Net: A Nimble Architecture for Driver and Seat Belt Detection via Convolutional Neural Networks
Sehyun Chun, Nima Hamidi Ghalehjegh, Joseph B. Choi, Chris W. Schwarz, John G. Gaspar, Daniel V. McGehee, Stephen S. Baek
http://arxiv.org/abs/1910.03695v1
• [cs.CV]Next integrated result modelling for stopping the text field recognition process in a video using a result model with per-character alternatives
Konstantin Bulatov, Boris Savelyev, Vladimir V. Arlazarov
http://arxiv.org/abs/1910.04107v1
• [cs.CV]Patch Refinement — Localized 3D Object Detection
Johannes Lehner, Andreas Mitterecker, Thomas Adler, Markus Hofmarcher, Bernhard Nessler, Sepp Hochreiter
http://arxiv.org/abs/1910.04093v1
• [cs.CV]Person re-identification based on Res2Net network
Zongjing Cao, Hyo Jong Lee
http://arxiv.org/abs/1910.04061v1
• [cs.CV]Prose for a Painting
Prerna Kashyap, Samrat Phatale, Iddo Drori
http://arxiv.org/abs/1910.03634v1
• [cs.CV]REFUGE Challenge: A Unified Framework for Evaluating Automated Methods for Glaucoma Assessment from Fundus Photographs
José Ignacio Orlando, Huazhu Fu, João Barbossa Breda, Karel van Keer, Deepti R. Bathula, Andrés Diaz-Pinto, Ruogu Fang, Pheng-Ann Heng, Jeyoung Kim, JoonHo Lee, Joonseok Lee, Xiaoxiao Li, Peng Liu, Shuai Lu, Balamurali Murugesan, Valery Naranjo, Sai Samarth R. Phaye, Sharath M. Shankaranarayana, Apoorva Sikka, Jaemin Son, Anton van den Hengel, Shujun Wang, Junyan Wu, Zifeng Wu, Guanghui Xu, Yongli Xu, Pengshuai Yin, Fei Li, Xiulan Zhang, Yanwu Xu, Xiulan Zhang, Hrvoje Bogunović
http://arxiv.org/abs/1910.03667v1
• [cs.CV]SNIDER: Single Noisy Image Denoising and Rectification for Improving License Plate Recognition
Younkwan Lee, Juhyun Lee, Hoyeon Ahn, Moongu Jeon
http://arxiv.org/abs/1910.03876v1
• [cs.CV]Semantic Understanding of Foggy Scenes with Purely Synthetic Data
Martin Hahner, Dengxin Dai, Christos Sakaridis, Jan-Nico Zaech, Luc Van Gool
http://arxiv.org/abs/1910.03997v1
• [cs.CV]Semantic-aware Image Deblurring
Fuhai Chen, Rongrong Ji, Chengpeng Dai, Xiaoshuai Sun, Chia-Wen Lin, Jiayi Ji, Baochang Zhang, Feiyue Huang, Liujuan Cao
http://arxiv.org/abs/1910.03853v1
• [cs.CV]Skin Lesion Classification Using Ensembles of Multi-Resolution EfficientNets with Meta Data
Nils Gessert, Maximilian Nielsen, Mohsin Shaikh, René Werner, Alexander Schlaefer
http://arxiv.org/abs/1910.03910v1
• [cs.CV]Unaligned Image-to-Sequence Transformation with Loop Consistency
Siyang Wang, Justin Lazarow, Kwonjoon Lee, Zhuowen Tu
http://arxiv.org/abs/1910.04149v1
• [cs.CV]Vehicle Re-identification with Viewpoint-aware Metric Learning
Ruihang Chu, Yifan Sun, Yadong Li, Zheng Liu, Chi Zhang, Yichen Wei
http://arxiv.org/abs/1910.04104v1
• [cs.CV]View Confusion Feature Learning for Person Re-identification
Fangyi Liu, Lei Zhang
http://arxiv.org/abs/1910.03849v1
• [cs.DC]Fog Computing as Privacy Enabler
Frank Pallas, Philip Raschke, David Bermbach
http://arxiv.org/abs/1910.04032v1
• [cs.DC]Performance Impact of Memory Channels on Sparse and Irregular Algorithms
Oded Green, James Fox, Jeffrey Young, Jun Shirako, David Bader
http://arxiv.org/abs/1910.03679v1
• [cs.DL]The role of mainstreamness and interdisciplinarity for the relevance of scientific papers
Stefan Thurner, Wenyuan Liu, Peter Klimek, Siew Ann Cheong
http://arxiv.org/abs/1910.03628v1
• [cs.DS]Span-core Decomposition for Temporal Networks: Algorithms and Applications
Edoardo Galimberti, Martino Ciaperoni, Alain Barrat, Francesco Bonchi, Ciro Cattuto, Francesco Gullo
http://arxiv.org/abs/1910.03645v1
• [cs.IT]A Data Concealing Technique with Random Noise Disturbance and A Restoring Technique for the Concealed Data by Stochastic Process Estimation
Tomohiro Fujii, Masao Hirokawa
http://arxiv.org/abs/1910.03214v1
• [cs.IT]A Survey on Deep-Learning based Techniques for Modeling and Estimation of MassiveMIMO Channels
Makan Zamanipour
http://arxiv.org/abs/1910.03390v1
• [cs.IT]Alternate Distributed Beamforming for Decode-and-Forward Multi-Relay Systems Using Buffers
Jiayu Zhou, Deli Qiao
http://arxiv.org/abs/1910.03954v1
• [cs.IT]Approaching the Finite Blocklength Capacity within 0.025dB by Short Polar Codes and CRC-Aided Hybrid Decoding
Jinnan Piao, Kai Niu, Jincheng Dai, Chao Dong
http://arxiv.org/abs/1910.03254v1
• [cs.IT]Counterexamples on the monotonicity of delay optimal strategies for energy harvesting transmitters
Borna Sayedana, Aditya Mahajan
http://arxiv.org/abs/1910.03556v1
• [cs.IT]DNN-Aided Block Sparse Bayesian Learning for User Activity Detection and Channel Estimation in Grant-Free Non-Orthogonal Random Access
Zhaoji Zhang, Ying Li, Chongwen Huang, Qinghua Guo, Chau Yuen, Yong Liang Guan
http://arxiv.org/abs/1910.02953v1
• [cs.IT]DNN-Aided Message Passing Based Block Sparse Bayesian Learning for Joint User Activity Detection and Channel Estimation
Zhaoji Zhang, Ying Li, Chongwen Huang, Qinghua Guo, Chau Yuen, Yong Liang Guan
http://arxiv.org/abs/1910.04154v1
• [cs.IT]Entanglement-Enabled Communication
Janis Nötzel
http://arxiv.org/abs/1910.03796v1
• [cs.IT]Evaluation of Error Probability of Classification Based on the Analysis of the Bayes Code
Shota Saito, Toshiyasu Matsushima
http://arxiv.org/abs/1910.03257v1
• [cs.IT]High-Dimensional Stochastic Gradient Quantization for Communication-Efficient Edge Learning
Yuqing Du, Sheng Yang, Kaibin Huang
http://arxiv.org/abs/1910.03865v1
• [cs.IT]Overcoming DoF Limitation in Robust Beamforming: A Penalized Inequality-Constrained Approach
Wenqiang Pu, Jinjun Xiao, Tao Zhang, Zhi-Quan Luo
http://arxiv.org/abs/1910.03365v1
• [cs.IT]Secret key agreement from correlated data, with no prior information
Marius Zimand
http://arxiv.org/abs/1910.03757v1
• [cs.IT]Understanding the Performance of Bluetooth Mesh: Reliability, Delay and Scalability Analysis
Raúl Rondón, Aamir Mahmood, Simone Grimaldi, Mikael Gidlund
http://arxiv.org/abs/1910.03345v1
• [cs.LG]A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks
Takanori Maehara, Hoang NT
http://arxiv.org/abs/1910.03802v1
• [cs.LG]Accelerating Federated Learning via Momentum Gradient Descent
Wei Liu, Li Chen, Yunfei Chen, Wenyi Zhang
http://arxiv.org/abs/1910.03197v2
• [cs.LG]Adversarial Learning of Deepfakes in Accounting
Marco Schreyer, Timur Sattarov, Bernd Reimer, Damian Borth
http://arxiv.org/abs/1910.03810v1
• [cs.LG]Algorithmic Probability-guided Supervised Machine Learning on Non-differentiable Spaces
Santiago Hernández-Orozco, Hector Zenil, Jürgen Riedel, Adam Uccello, Narsis A. Kiani, Jesper Tegnér
http://arxiv.org/abs/1910.02758v2
• [cs.LG]An MDL-Based Classifier for Transactional Datasets with Application in Malware Detection
Behzad Asadi, Vijay Varadharajan
http://arxiv.org/abs/1910.03751v1
• [cs.LG]AutoML using Metadata Language Embeddings
Iddo Drori, Lu Liu, Yi Nian, Sharath C. Koorathota, Jie S. Li, Antonio Khalil Moretti, Juliana Freire, Madeleine Udell
http://arxiv.org/abs/1910.03698v1
• [cs.LG]Beyond Vector Spaces: Compact Data Representationas Differentiable Weighted Graphs
Denis Mazur, Vage Egiazarian, Stanislav Morozov, Artem Babenko
http://arxiv.org/abs/1910.03524v2
• [cs.LG]Compatible features for Monotonic Policy Improvement
Marcin B. Tomczak, Enrique Munoz de Cote, Sergio Valcarcel Macua, Peter Vrancx
http://arxiv.org/abs/1910.03880v1
• [cs.LG]Continual Learning Using Bayesian Neural Networks
HongLin Li, Payam Barnaghi, Shirin Enshaeifar, Frieder Ganz
http://arxiv.org/abs/1910.04112v1
• [cs.LG]Ctrl-Z: Recovering from Instability in Reinforcement Learning
Vibhavari Dasagi, Jake Bruce, Thierry Peynot, Jürgen Leitner
http://arxiv.org/abs/1910.03732v1
• [cs.LG]DEVDAN: Deep Evolving Denoising Autoencoder
Andri Ashfahani, Mahardhika Pratama, Edwin Lughofer, Yew Soon Ong
http://arxiv.org/abs/1910.04062v1
• [cs.LG]Deep Latent Defence
Giulio Zizzo, Chris Hankin, Sergio Maffeis, Kevin Jones
http://arxiv.org/abs/1910.03916v1
• [cs.LG]Derivative-Free & Order-Robust Optimisation
Victor Gabillon, Rasul Tutunov, Michal Valko, Haitham Bou Ammar
http://arxiv.org/abs/1910.04034v1
• [cs.LG]Dissecting Deep Neural Networks
Haakon Robinson, Adil Rasheed, Omer San
http://arxiv.org/abs/1910.03879v1
• [cs.LG]Electric Load and Power Forecasting Using Ensemble Gaussian Process Regression
Tong Ma, Renke Huang, David Barajas-Solano, Ramakrishna Tipireddy, Alexandre M. Tartakovsky
http://arxiv.org/abs/1910.03783v1
• [cs.LG]FedMD: Heterogenous Federated Learning via Model Distillation
Daliang Li, Junpu Wang
http://arxiv.org/abs/1910.03581v1
• [cs.LG]How Well Do WGANs Estimate the Wasserstein Metric?
Anton Mallasto, Guido Montúfar, Augusto Gerolin
http://arxiv.org/abs/1910.03875v1
• [cs.LG]Improving Generalization in Meta Reinforcement Learning using Learned Objectives
Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber
http://arxiv.org/abs/1910.04098v1
• [cs.LG]Investigation on the generalization of the Sampled Policy Gradient algorithm
Nil Stolt Ansó
http://arxiv.org/abs/1910.03728v1
• [cs.LG]Is a Good Representation Sufficient for Sample Efficient Reinforcement Learning?
Simon S. Du, Sham M. Kakade, Ruosong Wang, Lin F. Yang
http://arxiv.org/abs/1910.03016v2
• [cs.LG]Learning Near-optimal Convex Combinations of Basis Models with Generalization Guarantees
Tan Nguyen, Nan Ye, Peter L. Bartlett
http://arxiv.org/abs/1910.03742v1
• [cs.LG]Linking emotions to behaviors through deep transfer learning
Haoqi Li, Brian Baucom, Panayiotis Georgiou
http://arxiv.org/abs/1910.03641v1
• [cs.LG]Loss Surface Sightseeing by Multi-Point Optimization
Ivan Skorokhodov, Mikhail Burtsev
http://arxiv.org/abs/1910.03867v1
• [cs.LG]MVFST-RL: An Asynchronous RL Framework for Congestion Control with Delayed Actions
Viswanath Sivakumar, Tim Rocktäschel, Alexander H. Miller, Heinrich Küttler, Nantas Nardelli, Mike Rabbat, Joelle Pineau, Sebastian Riedel
http://arxiv.org/abs/1910.04054v1
• [cs.LG]Model-Based Reinforcement Learning Exploiting State-Action Equivalence
Mahsa Asadi, Mohammad Sadegh Talebi, Hippolyte Bourel, Odalric-Ambrym Maillard
http://arxiv.org/abs/1910.04077v1
• [cs.LG]Multi-Modal Simultaneous Forecasting of Vehicle Position Sequences using Social Attention
Jean Mercat, Thomas Gilles, Nicole El Zoghby, Guillaume Sandou, Dominique Beauvois, Guillermo Pita Gil
http://arxiv.org/abs/1910.03650v1
• [cs.LG]Multiple-objective Reinforcement Learning for Inverse Design and Identification
Haoran Wei, Mariefel Olarte, Garrett B. Goh
http://arxiv.org/abs/1910.03741v1
• [cs.LG]Nearly Minimal Over-Parametrization of Shallow Neural Networks
Armin Eftekhari, ChaeHwan Song, Volkan Cevher
http://arxiv.org/abs/1910.03948v1
• [cs.LG]On Dimension-free Tail Inequalities for Sums of Random Matrices and Applications
Chao Zhang, Min-Hsiu Hsieh, Dacheng Tao
http://arxiv.org/abs/1910.03718v1
• [cs.LG]On the Possibility of Rewarding Structure Learning Agents: Mutual Information on Linguistic Random Sets
Ignacio Arroyo-Fernández, Mauricio Carrasco-Ruíz, J. Anibal Arias-Aguilar
http://arxiv.org/abs/1910.04023v1
• [cs.LG]Policy Optimization Through Approximated Importance Sampling
Marcin B. Tomczak, Dongho Kim, Peter Vrancx, Kee-Eung Kim
http://arxiv.org/abs/1910.03857v1
• [cs.LG]Receding Horizon Curiosity
Matthias Schultheis, Boris Belousov, Hany Abdulsamad, Jan Peters
http://arxiv.org/abs/1910.03620v1
• [cs.LG]Sequential VAE-LSTM for Anomaly Detection on Time Series
Run-Qing Chen, Guang-Hui Shi, Wan-Lei Zhao, Chang-Hui Liang
http://arxiv.org/abs/1910.03818v1
• [cs.LG]SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations
Ali Dabouei, Sobhan Soleymani, Fariborz Taherkhani, Jeremy Dawson, Nasser M. Nasrabadi
http://arxiv.org/abs/1910.03624v1
• [cs.LG]Social Learning in Multi Agent Multi Armed Bandits
Abishek Sankararaman, Ayalvadi Ganesh, Sanjay Shakkottai
http://arxiv.org/abs/1910.02100v2
• [cs.LG]Supervised feature selection with orthogonal regression and feature weighting
Xia Wu, Xueyuan Xu, Jianhong Liu, Hailing Wang, Bin Hu, Feiping Nie
http://arxiv.org/abs/1910.03787v1
• [cs.LG]Text-to-Image Synthesis Based on Machine Generated Captions
Marco Menardi, Alex Falcon, Saida S. Mohamed, Lorenzo Seidenari, Giuseppe Serra, Alberto Del Bimbo, Carlo Tasso
http://arxiv.org/abs/1910.04056v1
• [cs.LG]The fastest $\ell_{1,\infty}$ prox in the west
Benjamín Béjar, Ivan Dokmanić, René Vidal
http://arxiv.org/abs/1910.03749v1
• [cs.NE]Deep neural network for pier scour prediction
Mahesh Pal
http://arxiv.org/abs/1910.03804v1
• [cs.NE]Large Scale Global Optimization by Hybrid Evolutionary Computation
Gutha Jaya Krishna, Vadlamani Ravi
http://arxiv.org/abs/1910.03799v1
• [cs.NI]Explaining Deep Learning-Based Networked Systems
Zili Meng, Minhu Wang, Mingwei Xu, Hongzi Mao, Jiasong Bai, Hongxin Hu
http://arxiv.org/abs/1910.03835v1
• [cs.NI]Hierarchical Deep Double Q-Routing
Ramy E. Ali, Bilgehan Erman, Ejder Baştuğ, Bruce Cilli
http://arxiv.org/abs/1910.04041v1
• [cs.RO]A Brain-Inspired Compact Cognitive Mapping System
Taiping Zeng, Bailu Si
http://arxiv.org/abs/1910.03913v1
• [cs.RO]Automated Multidisciplinary Design and Control of Hopping Robots for Exploration of Extreme Environments on the Moon and Mars
Himangshu Kalita, Jekan Thangavelautham
http://arxiv.org/abs/1910.03827v1
• [cs.RO]Autonomous Multirobot Technologies for Mars Mining Base Construction and Operation
Jekan Thangavelautham, Aman Chandra, Erik Jensen
http://arxiv.org/abs/1910.03829v1
• [cs.RO]Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models
Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Siegel, Nicolas Heess, Martin Riedmiller
http://arxiv.org/abs/1910.04142v1
• [cs.RO]Knowledge Induced Deep Q-Network for a Slide-to-Wall Object Grasping
Hengyue Liang, Xibai Lou, Changhyun Choi
http://arxiv.org/abs/1910.03781v1
• [cs.RO]Learned Critical Probabilistic Roadmaps for Robotic Motion Planning
Brian Ichter, Edward Schmerling, Tsang-Wei Edward Lee, Aleksandra Faust
http://arxiv.org/abs/1910.03701v1
• [cs.RO]Multi-Vehicle Interaction Scenarios Generation with Interpretable Traffic Primitives and Gaussian Process Regression
Weiyang Zhang, Wenshuo Wang, Ding Zhao
http://arxiv.org/abs/1910.03633v1
• [cs.RO]Multimodal representation models for prediction and control from partial information
Martina Zambelli, Antoine Cully, Yiannis Demiris
http://arxiv.org/abs/1910.03854v1
• [cs.RO]Stochastic Triangular Mesh Mapping
Clint D. Lombard, Corné E. van Daalen
http://arxiv.org/abs/1910.03644v1
• [cs.RO]Towards Learning to Detect and Predict Contact Events on Vision-based Tactile Sensors
Yazhan Zhang, Weihao Yuan, Zicheng Kan, Michael Yu Wang
http://arxiv.org/abs/1910.03973v1
• [cs.SI]A k-hop Collaborate Game Model: Adaptive Strategy to Maximize Total Revenue
Jianxiong Guo, Weili Wu
http://arxiv.org/abs/1910.04125v1
• [cs.SI]Link Prediction Under Imperfect Detection: Collaborative Filtering for Ecological Networks
Xiao Fu, Eugene Seo, Justin Clarke, Rebecca A. Hutchinson
http://arxiv.org/abs/1910.03659v1
• [cs.SI]Rejection-Based Simulation of Non-Markovian Agents on Complex Networks
Gerrit Großmann, Luca Bortolussi, Verena Wolf
http://arxiv.org/abs/1910.03964v1
• [eess.AS]MelGAN-VC: Voice Conversion and Audio Style Transfer on arbitrarily long samples using Spectrograms
Marco Pasini
http://arxiv.org/abs/1910.03713v1
• [eess.IV]Cribriform pattern detection in prostate histopathological images using deep learning models
Malay Singh, Emarene Mationg Kalaw, Wang Jie, Mundher Al-Shabi, Chin Fong Wong, Danilo Medina Giron, Kian-Tai Chong, Maxine Tan, Zeng Zeng, Hwee Kuan Lee
http://arxiv.org/abs/1910.04030v1
• [eess.IV]Deep Learning Accelerated Light Source Experiments
Zhengchun Liu, Tekin Bicer, Rajkumar Kettimuthu, Ian Foster
http://arxiv.org/abs/1910.04081v1
• [eess.IV]Did you miss it? Automatic lung nodule detection combined with gaze information improves radiologists’ screening performance
Guilherme Aresta, Carlos Ferreira, João Pedrosa, Teresa Araújo, João Rebelo, Eduardo Negrão, Margarida Morgado, Filipe Alves, António Cunha, Isabel Ramos, Aurélio Campilho
http://arxiv.org/abs/1910.03986v1
• [eess.IV]FastSurfer — A fast and accurate deep learning based neuroimaging pipeline
Leonie Henschel, Sailesh Conjeti, Santiago Estrada, Kersten Diers, Bruce Fischl, Martin Reuter
http://arxiv.org/abs/1910.03866v1
• [eess.IV]Large-scale Gastric Cancer Screening and Localization Using Multi-task Deep Neural Network
Hong Yu, Xiaofan Zhang, Lingjun Song, Liren Jiang, Xiaodi Huang, Wen Chen, Chenbin Zhang, Jiahui Li, Jiji Yang, Zhiqiang Hu, Qi Duan, Wanyuan Chen, Xianglei He, Jinshuang Fan, Weihai Jiang, Li Zhang, Chengmin Qiu, Minmin Gu, Weiwei Sun, Yangqiong Zhang, Guangyin Peng, Weiwei Shen, Guohui Fu
http://arxiv.org/abs/1910.03729v1
• [eess.IV]Wavelet Domain Style Transfer for an Effective Perception-distortion Tradeoff in Single Image Super-Resolution
Xin Deng, Ren Yang, Mai Xu, Pier Luigi Dragotti
http://arxiv.org/abs/1910.04074v1
• [math.NA]Implicit Neural Solver for Time-dependent Linear PDEs with Convergence Guarantee
Suprosanna Shit, Abinav Ravi Venkatakrishnan, Ivan Ezhov, Jana Lipkova, Marie Piraud, Bjoern Menze
http://arxiv.org/abs/1910.03452v2
• [math.OC]Bregman Proximal Framework for Deep Linear Neural Networks
Mahesh Chandra Mukkamala, Felix Westerkamp, Emanuel Laude, Daniel Cremers, Peter Ochs
http://arxiv.org/abs/1910.03638v1
• [math.ST]Nonparametric principal subspace regression
Mark Koudstaal, Dengdeng Yu, Dehan Kong, Fang Yao
http://arxiv.org/abs/1910.02866v3
• [math.ST]On adaptivity of wavelet thresholding estimators with negatively super-additive dependent noise
Yuncai Yu, Xinsheng Liu, Ling Liu, Weisi Liu
http://arxiv.org/abs/1910.03911v1
• [math.ST]On the feasibility of parsimonious variable selection for Hotelling’s $T^2$-test
Michael D. Perlman
http://arxiv.org/abs/1910.03669v1
• [math.ST]Penalized regression via the restricted bridge estimator
Bahadır Yüzbaşı, Mohammad Arashi, Fikri Akdeniz
http://arxiv.org/abs/1910.03660v1
• [math.ST]Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm
Matteo Barigozzi, Matteo Luciani
http://arxiv.org/abs/1910.03821v1
• [math.ST]Variance reduction for Markov chains with application to MCMC
D. Belomestny, L. Iosipoi, E. Moulines, A. Naumov, S. Samsonov
http://arxiv.org/abs/1910.03643v1
• [physics.med-ph]A cascaded dual-domain deep learning reconstruction method for sparsely spaced multidetector helical CT
Ao Zheng, Hewei Gao, Li Zhang, Yuxiang Xing
http://arxiv.org/abs/1910.03746v1
• [q-bio.MN]BoolSi: a tool for distributed simulations and analysis of Boolean networks
Vladyslav Oles, Anton Kukushkin
http://arxiv.org/abs/1910.03736v1
• [q-bio.NC]Dynamic Brain Functional Networks Guided By Anatomical Knowledge
Suprateek Kundu, Jin Ming, Jennifer Stevens
http://arxiv.org/abs/1910.03577v1
• [q-bio.QM]A Dual-Hormone Closed-Loop Delivery System for Type 1 Diabetes Using Deep Reinforcement Learning
Taiyu Zhu, Kezhi Li, Pantelis Georgiou
http://arxiv.org/abs/1910.04059v1
• [quant-ph]Second-order coding rates for key distillation in quantum key distribution
Mark M. Wilde, Sumeet Khatri, Eneet Kaur, Saikat Guha
http://arxiv.org/abs/1910.03883v1
• [stat.AP]On Post-Selection Inference in A/B Tests
Alex Deng, Yicheng Li, Jiannan Lu
http://arxiv.org/abs/1910.03788v1
• [stat.CO]Distilling importance sampling
Dennis Prangle
http://arxiv.org/abs/1910.03632v1
• [stat.ME]A Bayesian Nonparametric Framework for Uncertainty Quantification in Simulation
Wei Xie, Cheng Li, Yuefeng Wu, Pu Zhang
http://arxiv.org/abs/1910.03766v1
• [stat.ME]A New Confidence Interval for Odds Ratio
Wojciech Zieliński
http://arxiv.org/abs/1910.03832v1
• [stat.ME]Controlling Costs: Feature Selection on a Budget
Guo Yu, Daniela Witten, Jacob Bien
http://arxiv.org/abs/1910.03627v1
• [stat.ME]Estimands and Inference in Cluster-Randomized Vaccine Trials
Kayla W. Kilpatrick, Michael G. Hudgens, M. Elizabeth Halloran
http://arxiv.org/abs/1910.03675v1
• [stat.ME]Forecast Aggregation via Peer Prediction
Juntao Wang, Yang Liu, Yiling Chen
http://arxiv.org/abs/1910.03779v1
• [stat.ME]Percentile-Based Residuals for Model Assessment
Sophie Bérubé, Abhirup Datta, Qingfeng Li, Chenguang Wang, Thomas A. Louis
http://arxiv.org/abs/1910.03709v1
• [stat.ME]Semi-parametric Bayes Regression with Network Valued Covariates
Xin Ma, Suprateek Kundu, Jennifer Stevens
http://arxiv.org/abs/1910.03772v1
• [stat.ML]Active ordinal tuplewise querying for similarity learning
Gregory Canal, Stefano Fenu, Christopher Rozell
http://arxiv.org/abs/1910.04115v1
• [stat.ML]Deterministic Completion of Rectangular Matrices Using Ramanujan Bigraphs — II: Explicit Constructions and Phase Transitions
Shantanu Prasad Burnwal, Mathukumalli Vidyasagar, Kaneenika Sinha
http://arxiv.org/abs/1910.03937v1
• [stat.ML]Estimating Density Models with Complex Truncation Boundaries
Song Liu, Takafumi Kanamori
http://arxiv.org/abs/1910.03834v1
• [stat.ML]Estimating regression errors without ground truth values
Henri Tiittanen, Emilia Oikarinen, Andreas Henelius, Kai Puolamäki
http://arxiv.org/abs/1910.04069v1
• [stat.ML]Kernels over Sets of Finite Sets using RKHS Embeddings, with Application to Bayesian (Combinatorial) Optimization
Poompol Buathong, David Ginsbourger, Tipaluck Krityakierne
http://arxiv.org/abs/1910.04086v1
• [stat.ML]Learning with minibatch Wasserstein : asymptotic and gradient properties
Kilian Fatras, Younes Zine, Rémi Flamary, Rémi Gribonval, Nicolas Courty
http://arxiv.org/abs/1910.04091v1
• [stat.ML]Optimal Training of Fair Predictive Models
Razieh Nabi, Daniel Malinsky, Ilya Shpitser
http://arxiv.org/abs/1910.04109v1
• [stat.ML]Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks
Julius von Kügelgen, Paul K Rubenstein, Bernhard Schölkopf, Adrian Weller
http://arxiv.org/abs/1910.03962v1
• [stat.ML]Practical Posterior Error Bounds from Variational Objectives
Jonathan H. Huggins, Mikołaj Kasprzak, Trevor Campbell, Tamara Broderick
http://arxiv.org/abs/1910.04102v1
• [stat.ML]Private Protocols for U-Statistics in the Local Model and Beyond
James Bell, Aurélien Bellet, Adrià Gascón, Tejas Kulkarni
http://arxiv.org/abs/1910.03861v1
• [stat.ML]Probabilistic sequential matrix factorization
Ömer Deniz Akyildiz, Theodoros Damoulas, Mark F. J. Steel
http://arxiv.org/abs/1910.03906v1
• [stat.ML]Spatio-Temporal Alignments: Optimal transport through space and time
Hicham Janati, Marco Cuturi, Alexandre Gramfort
http://arxiv.org/abs/1910.03860v1
• [stat.ML]The Area of the Convex Hull of Sampled Curves: a Robust Functional Statistical Depth Measure
Guillaume Staerman, Pavlo Mozharovskyi, Stephan Clémençon
http://arxiv.org/abs/1910.04085v1
• [stat.OT]Computing the Expected Value of Sample Information Efficiently: Expertise and Skills Required for Four Model-Based Methods
Natalia R. Kunst, Edward Wilson, Fernando Alarid-Escudero, Gianluca Baio, Alan Brennan, Michael Fairley, David Glynn, Jeremy D. Goldhaber-Fiebert, Chris Jackson, Hawre Jalal, Nicolas A. Menzies, Mark Strong, Howard Thom, Anna Heath
http://arxiv.org/abs/1910.03368v1