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.DM - 离散数学 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.OS - 操作系统 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 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.OC - 优化与控制 math.ST - 统计理论 physics.app-ph - 应用物理 quant-ph - 量子物理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cond-mat.dis-nn]Meta Distribution of SIR in Ultra-Dense Networks with Bipartite Euclidean Matchings
• [cs.AI]Multiplayer AlphaZero
• [cs.AI]Overcoming Catastrophic Interference in Online Reinforcement Learning with Dynamic Self-Organizing Maps
• [cs.CL]A Simple but Effective BERT Model for Dialog State Tracking on Resource-Limited Systems
• [cs.CL]An Efficient Model for Sentiment Analysis of Electronic Product Reviews in Vietnamese
• [cs.CL]An Empirical Study of Generation Order for Machine Translation
• [cs.CL]BPE-Dropout: Simple and Effective Subword Regularization
• [cs.CL]Big Bidirectional Insertion Representations for Documents
• [cs.CL]Contrastive Attention Mechanism for Abstractive Sentence Summarization
• [cs.CL]Cross-Domain Ambiguity Detection using Linear Transformation of Word Embedding Spaces
• [cs.CL]Findings of the Third Workshop on Neural Generation and Translation
• [cs.CL]Generating Questions for Knowledge Bases via Incorporating Diversified Contexts and Answer-Aware Loss
• [cs.CL]Incorporating Interlocutor-Aware Context into Response Generation on Multi-Party Chatbots
• [cs.CL]RAKA:Co-training of Relationships and Attributes for Cross-lingual Knowledge Alignment
• [cs.CL]Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control
• [cs.CL]Scalable Evaluation and Improvement of Document Set Expansion via Neural Positive-Unlabeled Learning
• [cs.CL]Sentence Embeddings for Russian NLU
• [cs.CL]Sketch-Fill-A-R: A Persona-Grounded Chit-Chat Generation Framework
• [cs.CL]Transformer-based Cascaded Multimodal Speech Translation
• [cs.CR]IPGuard: Protecting the Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary
• [cs.CR]MaskedNet: A Pathway for Secure Inference against Power Side-Channel Attacks
• [cs.CV]Adversarial Example in Remote Sensing Image Recognition
• [cs.CV]An α-Matte Boundary Defocus Model Based Cascaded Network for Multi-focus Image Fusion
• [cs.CV]Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images
• [cs.CV]Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation
• [cs.CV]Classification Calibration for Long-tail Instance Segmentation
• [cs.CV]Deep Learning Models for Digital Pathology
• [cs.CV]Detecting motorcycle helmet use with deep learning
• [cs.CV]Disentangling the Spatial Structure and Style in Conditional VAE
• [cs.CV]Distributed and Consistent Multi-Image Feature Matching via QuickMatch
• [cs.CV]ETNet: Error Transition Network for Arbitrary Style Transfer
• [cs.CV]Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets
• [cs.CV]Learning Rich Image Region Representation for Visual Question Answering
• [cs.CV]Literature Review: Human Segmentation with Static Camera
• [cs.CV]Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments
• [cs.CV]POIRot: A rotation invariant omni-directional pointnet
• [cs.CV]PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation
• [cs.CV]Region-based Convolution Neural Network Approach for Accurate Segmentation of Pelvic Radiograph
• [cs.CV]Resolution-independent meshes of super pixels
• [cs.CV]SID4VAM: A Benchmark Dataset with Synthetic Images for Visual Attention Modeling
• [cs.CV]STEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits
• [cs.CV]Semantic Object Accuracy for Generative Text-to-Image Synthesis
• [cs.CV]Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled Data
• [cs.CV]Style Mixer: Semantic-aware Multi-Style Transfer Network
• [cs.CV]The Six Fronts of the Generative Adversarial Networks
• [cs.CV]Use of a Capsule Network to Detect Fake Images and Videos
• [cs.CV]Weakly Supervised Prostate TMA Classification via Graph Convolutional Networks
• [cs.CV]Weighted Boxes Fusion: ensembling boxes for object detection models
• [cs.CY]Added Value of Intraoperative Data for Predicting Postoperative Complications: Development and Validation of a MySurgeryRisk Extension
• [cs.CY]Algorithmic decision-making in AVs: Understanding ethical and technical concerns for smart cities
• [cs.CY]Effects of Social Cues on Biosecurity Compliance in Livestock Facilities: Evidence from Experimental Simulations
• [cs.DC]Accounting for Information Freshness in Scheduling of Content Caching
• [cs.DC]Active Access: A Mechanism for High-Performance Distributed Data-Centric Computations
• [cs.DC]Decomposing Collectives for Exploiting Multi-lane Communication
• [cs.DC]Reproducing Scientific Experiment with Cloud DevOps
• [cs.DM]Estimating the Density of States of Boolean Satisfiability Problems on Classical and Quantum Computing Platforms
• [cs.IR]Towards a Model for Spoken Conversational Search
• [cs.IT]Adaptive Causal Network Coding with Feedback for Multipath Multi-hop Communications
• [cs.IT]Channel Estimation for Spatially/Temporally Correlated Massive MIMO Systems with One-Bit ADCs
• [cs.IT]Conjugate Phase Retrieval in Paley-Wiener Space
• [cs.IT]Multi-layer Interference Alignment and GDoF of the K-User Asymmetric Interference Channel
• [cs.IT]Noiseless Privacy
• [cs.IT]Resource Allocation Using Gradient Boosting Aided Deep Q-Network for IoT in C-RANs
• [cs.IT]Sign-Bit Shaping Using Polar Codes
• [cs.IT]Simultaneous Interference-Data Transmission for Secret Key Generation in Distributed IoT Sensor Networks
• [cs.IT]Support Recovery for Sparse Signals with Non-stationary Modulation
• [cs.IT]Throughput Maximization for Full Duplex Wireless Powered Communication Networks
• [cs.LG]A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models
• [cs.LG]Active Subspace of Neural Networks: Structural Analysis and Universal Attacks
• [cs.LG]Adversarial Fisher Vectors for Unsupervised Representation Learning
• [cs.LG]Bridging the ELBO and MMD
• [cs.LG]Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs
• [cs.LG]Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models
• [cs.LG]Constrained Reinforcement Learning Has Zero Duality Gap
• [cs.LG]Deep Learning Emulation of Multi-Angle Implementation of Atmospheric Correction (MAIAC)
• [cs.LG]Differentially Private Bayesian Linear Regression
• [cs.LG]Discriminant analysis based on projection onto generalized difference subspace
• [cs.LG]Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications
• [cs.LG]E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving
• [cs.LG]Entity Abstraction in Visual Model-Based Reinforcement Learning
• [cs.LG]FD-Net with Auxiliary Time Steps: Fast Prediction of PDEs using Hessian-Free Trust-Region Methods
• [cs.LG]Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation
• [cs.LG]GLIMPS: A Greedy Mixed Integer Approach for Super Robust Matched Subspace Detection
• [cs.LG]Gait Event Detection in Tibial Acceleration Profiles: a Structured Learning Approach
• [cs.LG]Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
• [cs.LG]Generalization of Reinforcement Learners with Working and Episodic Memory
• [cs.LG]Hyperbolic Graph Convolutional Neural Networks
• [cs.LG]Hyperbolic Graph Neural Networks
• [cs.LG]Hyperbolic Node Embedding for Signed Networks
• [cs.LG]Knowledge Tracing with Sequential Key-Value Memory Networks
• [cs.LG]LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks
• [cs.LG]Learning Transferable Graph Exploration
• [cs.LG]Learning from Label Proportions with Consistency Regularization
• [cs.LG]Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction
• [cs.LG]Measuring Similarity of Interactive Driving Behaviors Using Matrix Profile
• [cs.LG]Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians
• [cs.LG]Moving Towards Open Set Incremental Learning: Readily Discovering New Authors
• [cs.LG]Multitask Learning On Graph Neural Networks Applied To Molecular Property Predictions
• [cs.LG]Neural Similarity Learning
• [cs.LG]On Generalization Bounds of a Family of Recurrent Neural Networks
• [cs.LG]PRNet: Self-Supervised Learning for Partial-to-Partial Registration
• [cs.LG]Predicting Louisiana Public High School Dropout through Imbalanced Learning Techniques
• [cs.LG]Privacy Enhanced Multimodal Neural Representations for Emotion Recognition
• [cs.LG]ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
• [cs.LG]Real-time Bidding campaigns optimization using attribute selection
• [cs.LG]Recurrent Autoencoder with Skip Connections and Exogenous Variables for Traffic Forecasting
• [cs.LG]Scalable Deep Neural Networks via Low-Rank Matrix Factorization
• [cs.LG]Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation
• [cs.LG]Symbolic Graph Embedding using Frequent Pattern Mining
• [cs.LG]Towards Deep Physical Reservoir Computing Through Automatic Task Decomposition And Mapping
• [cs.LG]Weakly-Supervised Deep Learning for Domain Invariant Sentiment Classification
• [cs.LG]bLIMEy: Surrogate Prediction Explanations Beyond LIME
• [cs.NE]Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
• [cs.OS]Disaggregation and the Application
• [cs.RO]A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning
• [cs.RO]A Robust Pavement Mapping System Based on Normal-Constrained Stereo Visual Odometry
• [cs.RO]A data set of aerial imagery from robotics simulator for map-based localization systems benchmark
• [cs.RO]Autonomous UAV Landing System Based on Visual Navigation
• [cs.RO]Certified Adversarial Robustness for Deep Reinforcement Learning
• [cs.RO]Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation
• [cs.RO]Human Interface for Teleoperated Object Manipulation with a Soft Growing Robot
• [cs.RO]Human-centered Control of a Growing Soft Robot for Object Manipulation
• [cs.RO]Learning to Manipulate Deformable Objects without Demonstrations
• [cs.RO]Results from the Robocademy ITN: Autonomy, Disturbance Rejection and Perception for Advanced Marine Robotics
• [cs.RO]Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization
• [cs.RO]Toward Underground Localization: Lidar Inertial Odometry Enabled Aerial Robot Navigation
• [cs.SI]A Hierarchical Location Prediction Neural Network for Twitter User Geolocation
• [cs.SI]Efficient Approximation Algorithms for Adaptive Target Profit Maximization
• [cs.SI]Shifting Opinions in a Social Network Through Leader Selection
• [cs.SI]User’s Centrality Analysis for Home Location Estimation
• [econ.EM]Analyzing China’s Consumer Price Index Comparatively with that of United States
• [eess.AS]Dr.VOT : Measuring Positive and Negative Voice Onset Time in the Wild
• [eess.AS]Improving sequence-to-sequence speech recognition training with on-the-fly data augmentation
• [eess.AS]Transformer-Transducer: End-to-End Speech Recognition with Self-Attention
• [eess.AS]a novel cross-lingual voice cloning approach with a few text-free samples
• [eess.IV]Converged Deep Framework Assembling Principled Modules for CS-MRI
• [eess.IV]Deep Learning for Hyperspectral Image Classification: An Overview
• [eess.IV]Deep Multi-Magnification Networks for Multi-Class Breast Cancer Image Segmentation
• [eess.IV]On the Benefit of Adversarial Training for Monocular Depth Estimation
• [eess.IV]Sequential image processing methods for improving semantic video segmentation algorithms
• [eess.SP]Knowledge-Aided Deep Learning for Beamspace Channel Estimation in Millimeter-Wave Massive MIMO Systems
• [eess.SY]Deep Reinforcement Learning with Enhanced Safety for Autonomous Highway Driving
• [math.OC]Efficiently avoiding saddle points with zero order methods: No gradients required
• [math.OC]Feedback Linearization for Unknown Systems via Reinforcement Learning
• [math.OC]Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games
• [math.OC]Sinkhorn Divergences for Unbalanced Optimal Transport
• [math.ST]Arbitrary Rates of Convergence for Projected and Extrinsic Means
• [math.ST]Asymptotic Distributions of High-Dimensional Nonparametric Inference with Distance Correlation
• [math.ST]High dimensional regression for regenerative time-series: an application to road traffic modeling
• [math.ST]Jump Markov Chains and Rejection-Free Metropolis Algorithms
• [math.ST]Multi-level Thresholding Test for High Dimensional Covariance Matrices
• [math.ST]Optimal nonparametric multivariate change point detection and localization
• [math.ST]Penalized quasi likelihood estimation for variable selection
• [math.ST]Power analysis of knockoff filters for correlated designs
• [math.ST]Wasserstein information matrix
• [physics.app-ph]Comparing domain wall synapse with other Non Volatile Memory devices for on-chip learning in Analog Hardware Neural Network
• [quant-ph]Quantum Computing based Hybrid Solution Strategies for Large-scale Discrete-Continuous Optimization Problems
• [stat.AP]Reply to: Large-scale quantitative profiling of the Old English verse tradition
• [stat.ME]Joint Quantile Regression for Spatial Data
• [stat.ME]Minimum Detectable Effect Size Computations for Cluster-Level Regression Discontinuity: Quadratic Functional Form and Beyond
• [stat.ME]Outlier detection and influence diagnostics in network meta-analysis
• [stat.ME]Sine-skewed toroidal distributions and their application in protein bioinformatics
• [stat.ME]Spatial Spread Sampling Using Weakly Associated Vectors
• [stat.ME]Wasserstein $F$-tests and Confidence Bands for the Frèchet Regression of Density Response Curves
• [stat.ML]Bayesian Optimization with Unknown Search Space
• [stat.ML]Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support
• [stat.ML]Ensemble Quantile Classifier
• [stat.ML]Feature relevance quantification in explainable AI: A causality problem
• [stat.ML]Harnessing the power of Topological Data Analysis to detect change points in time series
• [stat.ML]How Much Can We See? A Note on Quantifying Explainability of Machine Learning Models
• [stat.ML]Improved Differentially Private Decentralized Source Separation for fMRI Data
• [stat.ML]Learning Sparse Distributions using Iterative Hard Thresholding
• [stat.ML]Minimal Variance Sampling in Stochastic Gradient Boosting
• [stat.ML]Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption
• [stat.ML]Model enhancement and personalization using weakly supervised learning for multi-modal mobile sensing
• [stat.ML]Neural Density Estimation and Likelihood-free Inference
• [stat.ML]Poisson-Randomized Gamma Dynamical Systems
• [stat.ML]Stein’s Lemma for the Reparameterization Trick with Exponential Family Mixtures
• [stat.ML]The Power of Graph Convolutional Networks to Distinguish Random Graph Models
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• [cond-mat.dis-nn]Meta Distribution of SIR in Ultra-Dense Networks with Bipartite Euclidean Matchings
Alexander P. Kartun-Giles, Konstantinos Koufos, Sunwoo Kim
http://arxiv.org/abs/1910.13216v1
• [cs.AI]Multiplayer AlphaZero
Nick Petosa, Tucker Balch
http://arxiv.org/abs/1910.13012v1
• [cs.AI]Overcoming Catastrophic Interference in Online Reinforcement Learning with Dynamic Self-Organizing Maps
Yat Long Lo, Sina Ghiassian
http://arxiv.org/abs/1910.13213v1
• [cs.CL]A Simple but Effective BERT Model for Dialog State Tracking on Resource-Limited Systems
Tuan Manh Lai, Quan Hung Tran, Trung Bui, Daisuke Kihara
http://arxiv.org/abs/1910.12995v1
• [cs.CL]An Efficient Model for Sentiment Analysis of Electronic Product Reviews in Vietnamese
Suong N. Hoang, Linh V. Nguyen, Tai Huynh, Vuong T. Pham
http://arxiv.org/abs/1910.13162v1
• [cs.CL]An Empirical Study of Generation Order for Machine Translation
William Chan, Mitchell Stern, Jamie Kiros, Jakob Uszkoreit
http://arxiv.org/abs/1910.13437v1
• [cs.CL]BPE-Dropout: Simple and Effective Subword Regularization
Ivan Provilkov, Dmitrii Emelianenko, Elena Voita
http://arxiv.org/abs/1910.13267v1
• [cs.CL]Big Bidirectional Insertion Representations for Documents
Lala Li, William Chan
http://arxiv.org/abs/1910.13034v1
• [cs.CL]Contrastive Attention Mechanism for Abstractive Sentence Summarization
Xiangyu Duan, Hoongfei Yu, Mingming Yin, Min Zhang, Weihua Luo, Yue Zhang
http://arxiv.org/abs/1910.13114v1
• [cs.CL]Cross-Domain Ambiguity Detection using Linear Transformation of Word Embedding Spaces
Vaibhav Jain, Sanskar Jain, Nishant Tanwar
http://arxiv.org/abs/1910.12956v1
• [cs.CL]Findings of the Third Workshop on Neural Generation and Translation
Hiroaki Hayashi, Yusuke Oda, Alexandra Birch, Ioannis Konstas, Andrew Finch, Minh-Thang Luong, Graham Neubig, Katsuhito Sudoh
http://arxiv.org/abs/1910.13299v1
• [cs.CL]Generating Questions for Knowledge Bases via Incorporating Diversified Contexts and Answer-Aware Loss
Cao Liu, Kang Liu, Shizhu He, Zaiqing Nie, Jun Zhao
http://arxiv.org/abs/1910.13108v1
• [cs.CL]Incorporating Interlocutor-Aware Context into Response Generation on Multi-Party Chatbots
Cao Liu, Kang Liu, Shizhu He, Zaiqing Nie, Jun Zhao
http://arxiv.org/abs/1910.13106v1
• [cs.CL]RAKA:Co-training of Relationships and Attributes for Cross-lingual Knowledge Alignment
Bo Chen, Jing Zhang, Xiaobin Tang, Hong Chen, Cuiping Li
http://arxiv.org/abs/1910.13105v1
• [cs.CL]Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control
Mo Yu, Shiyu Chang, Yang Zhang, Tommi S. Jaakkola
http://arxiv.org/abs/1910.13294v1
• [cs.CL]Scalable Evaluation and Improvement of Document Set Expansion via Neural Positive-Unlabeled Learning
Alon Jacovi, Gang Niu, Yoav Goldberg, Masashi Sugiyama
http://arxiv.org/abs/1910.13339v1
• [cs.CL]Sentence Embeddings for Russian NLU
Dmitry Popov, Alexander Pugachev, Polina Svyatokum, Elizaveta Svitanko, Ekaterina Artemova
http://arxiv.org/abs/1910.13291v1
• [cs.CL]Sketch-Fill-A-R: A Persona-Grounded Chit-Chat Generation Framework
Michael Shum, Stephan Zheng, Wojciech Kryściński, Caiming Xiong, Richard Socher
http://arxiv.org/abs/1910.13008v1
• [cs.CL]Transformer-based Cascaded Multimodal Speech Translation
Zixiu Wu, Ozan Caglayan, Julia Ive, Josiah Wang, Lucia Specia
http://arxiv.org/abs/1910.13215v1
• [cs.CR]IPGuard: Protecting the Intellectual Property of Deep Neural Networks via Fingerprinting the Classification Boundary
Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong
http://arxiv.org/abs/1910.12903v1
• [cs.CR]MaskedNet: A Pathway for Secure Inference against Power Side-Channel Attacks
Anuj Dubey, Rosario Cammarota, Aydin Aysu
http://arxiv.org/abs/1910.13063v1
• [cs.CV]Adversarial Example in Remote Sensing Image Recognition
Li Chen, Guowei Zhu, Qi Li, Haifeng Li
http://arxiv.org/abs/1910.13222v1
• [cs.CV]An α-Matte Boundary Defocus Model Based Cascaded Network for Multi-focus Image Fusion
Haoyu Ma, Qingmin Liao, Juncheng Zhang, Shaojun Liu, Jing-Hao Xie
http://arxiv.org/abs/1910.13136v1
• [cs.CV]Best Practices for Convolutional Neural Networks Applied to Object Recognition in Images
Anderson de Andrade
http://arxiv.org/abs/1910.13029v1
• [cs.CV]Category Anchor-Guided Unsupervised Domain Adaptation for Semantic Segmentation
Qiming Zhang, Jing Zhang, Wei Liu, Dacheng Tao
http://arxiv.org/abs/1910.13049v1
• [cs.CV]Classification Calibration for Long-tail Instance Segmentation
Tao Wang, Yu Li, Bingyi Kang, Junnan Li, Jun Hao Liew, Sheng Tang, Steven Hoi, Jiashi Feng
http://arxiv.org/abs/1910.13081v1
• [cs.CV]Deep Learning Models for Digital Pathology
Aïcha BenTaieb, Ghassan Hamarneh
http://arxiv.org/abs/1910.12329v2
• [cs.CV]Detecting motorcycle helmet use with deep learning
Felix Wilhelm Siebert, Hanhe Lin
http://arxiv.org/abs/1910.13232v1
• [cs.CV]Disentangling the Spatial Structure and Style in Conditional VAE
Ziye Zhang, Li Sun, Zhilin Zheng, Qingli Li
http://arxiv.org/abs/1910.13062v1
• [cs.CV]Distributed and Consistent Multi-Image Feature Matching via QuickMatch
Zachary Serlin, Guang Yang, Brandon Sookraj, Calin Belta, Roberto Tron
http://arxiv.org/abs/1910.13317v1
• [cs.CV]ETNet: Error Transition Network for Arbitrary Style Transfer
Chunjin Song, Zhijie Wu, Yang Zhou, Minglun Gong, Hui Huang
http://arxiv.org/abs/1910.12056v2
• [cs.CV]Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets
Newton M. Kinyanjui, Timothy Odonga, Celia Cintas, Noel C. F. Codella, Rameswar Panda, Prasanna Sattigeri, Kush R. Varshney
http://arxiv.org/abs/1910.13268v1
• [cs.CV]Learning Rich Image Region Representation for Visual Question Answering
Bei Liu, Zhicheng Huang, Zhaoyang Zeng, Zheyu Chen, Jianlong Fu
http://arxiv.org/abs/1910.13077v1
• [cs.CV]Literature Review: Human Segmentation with Static Camera
Jiaxin Xu, Rui Wang, Vaibhav Rakheja
http://arxiv.org/abs/1910.12945v1
• [cs.CV]Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments
Martin Weiss, Simon Chamorro, Roger Girgis, Margaux Luck, Samira E. Kahou, Joseph P. Cohen, Derek Nowrouzezahrai, Doina Precup, Florian Golemo, Chris Pal
http://arxiv.org/abs/1910.13249v1
• [cs.CV]POIRot: A rotation invariant omni-directional pointnet
Liu Yang, Rudrasis Chakraborty, Stella X. Yu
http://arxiv.org/abs/1910.13050v1
• [cs.CV]PT-ResNet: Perspective Transformation-Based Residual Network for Semantic Road Image Segmentation
Rui Fan, Yuan Wang, Lei Qiao, Ruiwen Yao, Peng Han, Weidong Zhang, Ioannis Pitas, Ming Liu
http://arxiv.org/abs/1910.13055v1
• [cs.CV]Region-based Convolution Neural Network Approach for Accurate Segmentation of Pelvic Radiograph
Ata Jodeiri, Reza A. Zoroofi, Yuta Hiasa, Masaki Takao, Nobuhiko Sugano, Yoshinobu Sato, Yoshito Otake
http://arxiv.org/abs/1910.13231v1
• [cs.CV]Resolution-independent meshes of super pixels
Vitaliy Kurlin, Philip Smith
http://arxiv.org/abs/1910.13323v1
• [cs.CV]SID4VAM: A Benchmark Dataset with Synthetic Images for Visual Attention Modeling
David Berga, Xosé R. Fdez-Vidal, Xavier Otazu, Xosé M. Pardo
http://arxiv.org/abs/1910.13066v1
• [cs.CV]STEP: Spatial Temporal Graph Convolutional Networks for Emotion Perception from Gaits
Uttaran Bhattacharya, Trisha Mittal, Rohan Chandra, Tanmay Randhavane, Aniket Bera, Dinesh Manocha
http://arxiv.org/abs/1910.12906v1
• [cs.CV]Semantic Object Accuracy for Generative Text-to-Image Synthesis
Tobias Hinz, Stefan Heinrich, Stefan Wermter
http://arxiv.org/abs/1910.13321v1
• [cs.CV]Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled Data
Wanyu Lin, Zhaolin Gao, Baochun Li
http://arxiv.org/abs/1910.12976v1
• [cs.CV]Style Mixer: Semantic-aware Multi-Style Transfer Network
Zixuan Huang, Jinghuai Zhang, Jing Liao
http://arxiv.org/abs/1910.13093v1
• [cs.CV]The Six Fronts of the Generative Adversarial Networks
Alceu Bissoto, Eduardo Valle, Sandra Avila
http://arxiv.org/abs/1910.13076v1
• [cs.CV]Use of a Capsule Network to Detect Fake Images and Videos
Huy H. Nguyen, Junichi Yamagishi, Isao Echizen
http://arxiv.org/abs/1910.12467v2
• [cs.CV]Weakly Supervised Prostate TMA Classification via Graph Convolutional Networks
Jingwen Wang, Richard J. Chen, Ming Y. Lu, Alexander Baras, Faisal Mahmood
http://arxiv.org/abs/1910.13328v1
• [cs.CV]Weighted Boxes Fusion: ensembling boxes for object detection models
Roman Solovyev, Weimin Wang
http://arxiv.org/abs/1910.13302v1
• [cs.CY]Added Value of Intraoperative Data for Predicting Postoperative Complications: Development and Validation of a MySurgeryRisk Extension
Shounak Datta, Tyler J. Loftus, Matthew M. Ruppert, Chris Giordano, Lasith Adhikari, Ying-Chih Peng, Yuanfang Ren, Benjamin Shickel, Zheng Feng, Gloria Lipori, Gilbert R. Upchurch Jr., Xiaolin Li, Parisa Rashidi, Tezcan Ozrazgat-Baslanti, Azra Bihorac
http://arxiv.org/abs/1910.12895v1
• [cs.CY]Algorithmic decision-making in AVs: Understanding ethical and technical concerns for smart cities
Hazel Si Min Lim, Araz Taeihagh
http://arxiv.org/abs/1910.13122v1
• [cs.CY]Effects of Social Cues on Biosecurity Compliance in Livestock Facilities: Evidence from Experimental Simulations
Luke Trinity, Scott C. Merrill, Eric Clark, Christopher J. Koliba, Asim Zia, Gabriela Bucini, Julia M. Smith
http://arxiv.org/abs/1910.12978v1
• [cs.DC]Accounting for Information Freshness in Scheduling of Content Caching
Ghafour Ahani, Di Yuan
http://arxiv.org/abs/1910.13194v1
• [cs.DC]Active Access: A Mechanism for High-Performance Distributed Data-Centric Computations
Maciej Besta, Torsten Hoefler
http://arxiv.org/abs/1910.12897v1
• [cs.DC]Decomposing Collectives for Exploiting Multi-lane Communication
Jesper Larsson Träff
http://arxiv.org/abs/1910.13373v1
• [cs.DC]Reproducing Scientific Experiment with Cloud DevOps
Feng Zhao, Xingzhi Niu, Shao-Lun Huang, Lin Zhang
http://arxiv.org/abs/1910.13397v1
• [cs.DM]Estimating the Density of States of Boolean Satisfiability Problems on Classical and Quantum Computing Platforms
Tuhin Sahai, Anurag Mishra, Jose Miguel Pasini, Susmit Jha
http://arxiv.org/abs/1910.13088v1
• [cs.IR]Towards a Model for Spoken Conversational Search
Johanne R. Trippas, Damiano Spina, Paul Thomas, Mark Sanderson, Hideo Joho, Lawrence Cavedon
http://arxiv.org/abs/1910.13166v1
• [cs.IT]Adaptive Causal Network Coding with Feedback for Multipath Multi-hop Communications
Alejandro Cohen, Guillaume Thiran, Vered Bar Bracha, Muriel Médard
http://arxiv.org/abs/1910.13290v1
• [cs.IT]Channel Estimation for Spatially/Temporally Correlated Massive MIMO Systems with One-Bit ADCs
Hwanjin Kim, Junil Choi
http://arxiv.org/abs/1910.13243v1
• [cs.IT]Conjugate Phase Retrieval in Paley-Wiener Space
Chun-Kit Lai, Friedrich Littmann, Eric Weber
http://arxiv.org/abs/1910.12975v1
• [cs.IT]Multi-layer Interference Alignment and GDoF of the K-User Asymmetric Interference Channel
Jinyuan Chen
http://arxiv.org/abs/1910.12997v1
• [cs.IT]Noiseless Privacy
Farhad Farokhi
http://arxiv.org/abs/1910.13027v1
• [cs.IT]Resource Allocation Using Gradient Boosting Aided Deep Q-Network for IoT in C-RANs
Yifan Luo, Jiawei Yang, Wei Xu, Kezhi Wang, Marco Di Renzo
http://arxiv.org/abs/1910.13084v1
• [cs.IT]Sign-Bit Shaping Using Polar Codes
Onurcan İşcan, Ronald Böhnke, Wen Xu
http://arxiv.org/abs/1910.13240v1
• [cs.IT]Simultaneous Interference-Data Transmission for Secret Key Generation in Distributed IoT Sensor Networks
Najme Ebrahimi, Hun-seok Kim, D Blaauw
http://arxiv.org/abs/1910.13355v1
• [cs.IT]Support Recovery for Sparse Signals with Non-stationary Modulation
Youye Xie, Michael B. Wakin, Gongguo Tang
http://arxiv.org/abs/1910.13104v1
• [cs.IT]Throughput Maximization for Full Duplex Wireless Powered Communication Networks
Muhammad Shahid Iqbal, Yalcin Sadi, Sinem Coleri
http://arxiv.org/abs/1910.13242v1
• [cs.LG]A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models
Maksim Kuznetsov, Daniil Polykovskiy, Dmitry Vetrov, Alexander Zhebrak
http://arxiv.org/abs/1910.13148v1
• [cs.LG]Active Subspace of Neural Networks: Structural Analysis and Universal Attacks
Chunfeng Cui, Kaiqi Zhang, Talgat Daulbaev, Julia Gusak, Ivan Oseledets, Zheng Zhang
http://arxiv.org/abs/1910.13025v1
• [cs.LG]Adversarial Fisher Vectors for Unsupervised Representation Learning
Shuangfei Zhai, Walter Talbott, Carlos Guestrin, Joshua M. Susskind
http://arxiv.org/abs/1910.13101v1
• [cs.LG]Bridging the ELBO and MMD
Talip Ucar
http://arxiv.org/abs/1910.13181v1
• [cs.LG]Characterizing Distribution Equivalence for Cyclic and Acyclic Directed Graphs
AmirEmad Ghassami, Kun Zhang, Negar Kiyavash
http://arxiv.org/abs/1910.12993v1
• [cs.LG]Concept Saliency Maps to Visualize Relevant Features in Deep Generative Models
Lennart Brocki, Neo Christopher Chung
http://arxiv.org/abs/1910.13140v1
• [cs.LG]Constrained Reinforcement Learning Has Zero Duality Gap
Santiago Paternain, Luiz F. O. Chamon, Miguel Calvo-Fullana, Alejandro Ribeiro
http://arxiv.org/abs/1910.13393v1
• [cs.LG]Deep Learning Emulation of Multi-Angle Implementation of Atmospheric Correction (MAIAC)
Kate Duffy, Thomas Vandal, Weile Wang, Ramakrishna Nemani, Auroop R. Ganguly
http://arxiv.org/abs/1910.13408v1
• [cs.LG]Differentially Private Bayesian Linear Regression
Garrett Bernstein, Daniel Sheldon
http://arxiv.org/abs/1910.13153v1
• [cs.LG]Discriminant analysis based on projection onto generalized difference subspace
Kazuhiro Fukui, Naoya Sogi, Takumi Kobayashi, Jing-Hao Xue, Atsuto Maki
http://arxiv.org/abs/1910.13113v1
• [cs.LG]Distribution Density, Tails, and Outliers in Machine Learning: Metrics and Applications
Nicholas Carlini, Úlfar Erlingsson, Nicolas Papernot
http://arxiv.org/abs/1910.13427v1
• [cs.LG]E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving
Yue Wang, Ziyu Jiang, Xiaohan Chen, Pengfei Xu, Yang Zhao, Yingyan Lin, Zhangyang Wang
http://arxiv.org/abs/1910.13349v1
• [cs.LG]Entity Abstraction in Visual Model-Based Reinforcement Learning
Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine
http://arxiv.org/abs/1910.12827v2
• [cs.LG]FD-Net with Auxiliary Time Steps: Fast Prediction of PDEs using Hessian-Free Trust-Region Methods
Nur Sila Gulgec, Zheng Shi, Neil Deshmukh, Shamim Pakzad, Martin Takáč
http://arxiv.org/abs/1910.12680v2
• [cs.LG]Federated Learning over Wireless Networks: Convergence Analysis and Resource Allocation
Canh Dinh, Nguyen H. Tran, Minh N. H. Nguyen, Choong Seon Hong, Wei Bao, Albert Zomaya, Vincent Gramoli
http://arxiv.org/abs/1910.13067v1
• [cs.LG]GLIMPS: A Greedy Mixed Integer Approach for Super Robust Matched Subspace Detection
Md Mahfuzur Rahman, Daniel Pimentel-Alarcon
http://arxiv.org/abs/1910.13089v1
• [cs.LG]Gait Event Detection in Tibial Acceleration Profiles: a Structured Learning Approach
Pieter Robberechts, Rud Derie, Pieter Van den Berghe, Joeri Gerlo, Dirk De Clercq, Veerle Segers, Jesse Davis
http://arxiv.org/abs/1910.13372v1
• [cs.LG]Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
http://arxiv.org/abs/1910.12911v1
• [cs.LG]Generalization of Reinforcement Learners with Working and Episodic Memory
Meire Fortunato, Melissa Tan, Ryan Faulkner, Steven Hansen, Adrià Puigdomènech Badia, Gavin Buttimore, Charlie Deck, Joel Z Leibo, Charles Blundell
http://arxiv.org/abs/1910.13406v1
• [cs.LG]Hyperbolic Graph Convolutional Neural Networks
Ines Chami, Rex Ying, Christopher Ré, Jure Leskovec
http://arxiv.org/abs/1910.12933v1
• [cs.LG]Hyperbolic Graph Neural Networks
Qi Liu, Maximilian Nickel, Douwe Kiela
http://arxiv.org/abs/1910.12892v1
• [cs.LG]Hyperbolic Node Embedding for Signed Networks
Wenzhuo Song, Shengsheng Wang
http://arxiv.org/abs/1910.13090v1
• [cs.LG]Knowledge Tracing with Sequential Key-Value Memory Networks
Ghodai Abdelrahman, Qing Wang
http://arxiv.org/abs/1910.13197v1
• [cs.LG]LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks
Jonathan Ephrath, Moshe Eliasof, Lars Ruthotto, Eldad Haber, Eran Treister
http://arxiv.org/abs/1910.13157v1
• [cs.LG]Learning Transferable Graph Exploration
Hanjun Dai, Yujia Li, Chenglong Wang, Rishabh Singh, Po-Sen Huang, Pushmeet Kohli
http://arxiv.org/abs/1910.12980v1
• [cs.LG]Learning from Label Proportions with Consistency Regularization
Kuen-Han Tsai, Hsuan-Tien Lin
http://arxiv.org/abs/1910.13188v1
• [cs.LG]Machine Learning-Based Analysis of Sperm Videos and Participant Data for Male Fertility Prediction
Steven A. Hicks, Jorunn M. Andersen, Oliwia Witczak, Vajira Thambawita, Påll Halvorsen, Hugo L. Hammer, Trine B. Haugen, Michael A. Riegler
http://arxiv.org/abs/1910.13327v1
• [cs.LG]Measuring Similarity of Interactive Driving Behaviors Using Matrix Profile
Qin Lin, Wenshuo Wang, Yihuan Zhang, John Dolan
http://arxiv.org/abs/1910.12969v1
• [cs.LG]Modelling heterogeneous distributions with an Uncountable Mixture of Asymmetric Laplacians
Axel Brando, Jose A. Rodríguez-Serrano, Jordi Vitrià, Alberto Rubio
http://arxiv.org/abs/1910.12288v2
• [cs.LG]Moving Towards Open Set Incremental Learning: Readily Discovering New Authors
Justin Leo, Jugal Kalita
http://arxiv.org/abs/1910.12944v1
• [cs.LG]Multitask Learning On Graph Neural Networks Applied To Molecular Property Predictions
Fabio Capela, Vincent Nouchi, Ruud Van Deursen, Igor V. Tetko, Guillaume Godin
http://arxiv.org/abs/1910.13124v1
• [cs.LG]Neural Similarity Learning
Weiyang Liu, Zhen Liu, James M. Rehg, Le Song
http://arxiv.org/abs/1910.13003v1
• [cs.LG]On Generalization Bounds of a Family of Recurrent Neural Networks
Minshuo Chen, Xingguo Li, Tuo Zhao
http://arxiv.org/abs/1910.12947v1
• [cs.LG]PRNet: Self-Supervised Learning for Partial-to-Partial Registration
Yue Wang, Justin M. Solomon
http://arxiv.org/abs/1910.12240v2
• [cs.LG]Predicting Louisiana Public High School Dropout through Imbalanced Learning Techniques
Marmar Orooji, Jianhua Chen
http://arxiv.org/abs/1910.13018v1
• [cs.LG]Privacy Enhanced Multimodal Neural Representations for Emotion Recognition
Mimansa Jaiswal, Emily Mower Provost
http://arxiv.org/abs/1910.13212v1
• [cs.LG]ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
Angus Dempster, François Petitjean, Geoffrey I. Webb
http://arxiv.org/abs/1910.13051v1
• [cs.LG]Real-time Bidding campaigns optimization using attribute selection
Luis Miralles, M. Atif Qureshi, Brian Mac Namee
http://arxiv.org/abs/1910.13292v1
• [cs.LG]Recurrent Autoencoder with Skip Connections and Exogenous Variables for Traffic Forecasting
Pedro Herruzo, Josep L. Larriba-Pey
http://arxiv.org/abs/1910.13295v1
• [cs.LG]Scalable Deep Neural Networks via Low-Rank Matrix Factorization
Atsushi Yaguchi, Taiji Suzuki, Shuhei Nitta, Yukinobu Sakata, Akiyuki Tanizawa
http://arxiv.org/abs/1910.13141v1
• [cs.LG]Scalable Inference for Nonparametric Hawkes Process Using Pólya-Gamma Augmentation
Feng Zhou, Zhidong Li, Xuhui Fan, Yang Wang, Arcot Sowmya, Fang Chen
http://arxiv.org/abs/1910.13052v1
• [cs.LG]Symbolic Graph Embedding using Frequent Pattern Mining
Blaz Škrlj, Jan Kralj, Nada Lavrač
http://arxiv.org/abs/1910.13314v1
• [cs.LG]Towards Deep Physical Reservoir Computing Through Automatic Task Decomposition And Mapping
Matthias Freiberger, Peter Bienstman, Joni Dambre
http://arxiv.org/abs/1910.13332v1
• [cs.LG]Weakly-Supervised Deep Learning for Domain Invariant Sentiment Classification
Pratik Kayal, Mayank Singh, Pawan Goyal
http://arxiv.org/abs/1910.13425v1
• [cs.LG]bLIMEy: Surrogate Prediction Explanations Beyond LIME
Kacper Sokol, Alexander Hepburn, Raul Santos-Rodriguez, Peter Flach
http://arxiv.org/abs/1910.13016v1
• [cs.NE]Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
C. Daniel Freeman, Luke Metz, David Ha
http://arxiv.org/abs/1910.13038v1
• [cs.OS]Disaggregation and the Application
Sebastian Angel, Mihir Nanavati, Siddhartha Sen
http://arxiv.org/abs/1910.13056v1
• [cs.RO]A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning
Somil Bansal, Andrea Bajcsy, Ellis Ratner, Anca D. Dragan, Claire J. Tomlin
http://arxiv.org/abs/1910.13369v1
• [cs.RO]A Robust Pavement Mapping System Based on Normal-Constrained Stereo Visual Odometry
Huaiyang Huang, Rui Fan, Yilong Zhu, Ming Liu, Ioannis Pitas
http://arxiv.org/abs/1910.13102v1
• [cs.RO]A data set of aerial imagery from robotics simulator for map-based localization systems benchmark
Rokas Jurevičius, Virginijus Marcinkevičius
http://arxiv.org/abs/1910.12968v1
• [cs.RO]Autonomous UAV Landing System Based on Visual Navigation
Zhixin Wu, Peng Han, Ruiwen Yao, Lei Qiao, Weidong Zhang, Tielong Shen, Min Sun, Yilong Zhu, Ming Liu, Rui Fan
http://arxiv.org/abs/1910.13174v1
• [cs.RO]Certified Adversarial Robustness for Deep Reinforcement Learning
Björn Lütjens, Michael Everett, Jonathan P. How
http://arxiv.org/abs/1910.12908v1
• [cs.RO]Dynamics Learning with Cascaded Variational Inference for Multi-Step Manipulation
Kuan Fang, Yuke Zhu, Animesh Garg, Silvio Savarese, Li Fei-Fei
http://arxiv.org/abs/1910.13395v1
• [cs.RO]Human Interface for Teleoperated Object Manipulation with a Soft Growing Robot
Fabio Stroppa, Ming Luo, Kyle Yoshida, Margaret M. Coad, Laura H. Blumenschein, Allison M. Okamura
http://arxiv.org/abs/1910.12998v1
• [cs.RO]Human-centered Control of a Growing Soft Robot for Object Manipulation
Fabio Stroppa, Ming Luo, Giada Gerboni, Margaret M. Coad, Julie M. Walker, Allison M. Okamura
http://arxiv.org/abs/1910.13000v1
• [cs.RO]Learning to Manipulate Deformable Objects without Demonstrations
Yilin Wu, Wilson Yan, Thanard Kurutach, Lerrel Pinto, Pieter Abbeel
http://arxiv.org/abs/1910.13439v1
• [cs.RO]Results from the Robocademy ITN: Autonomy, Disturbance Rejection and Perception for Advanced Marine Robotics
Matias Valdenegro-Toro, Mariela De Lucas Alvarez, Mariia Dmitrieva, Bilal Wehbe, Georgios Salavasidis, Shahab Heshmati-Alamdari, Juan F. Fuentes-Pérez, Veronika Yordanova, Klemen Istenič, Thomas Guerneve
http://arxiv.org/abs/1910.13144v1
• [cs.RO]Robust Model-free Reinforcement Learning with Multi-objective Bayesian Optimization
Matteo Turchetta, Andreas Krause, Sebastian Trimpe
http://arxiv.org/abs/1910.13399v1
• [cs.RO]Toward Underground Localization: Lidar Inertial Odometry Enabled Aerial Robot Navigation
Jiun Fatt Chow, Basaran Bahadir Kocer, John Henawy, Gerald Seet, Zhengguo Li, Wei Yun Yau, Mahardhika Pratama
http://arxiv.org/abs/1910.13085v1
• [cs.SI]A Hierarchical Location Prediction Neural Network for Twitter User Geolocation
Binxuan Huang, Kathleen M. Carley
http://arxiv.org/abs/1910.12941v1
• [cs.SI]Efficient Approximation Algorithms for Adaptive Target Profit Maximization
Keke Huang, Jing Tang, Xiaokui Xiao, Aixin Sun, Andrew Lim
http://arxiv.org/abs/1910.13073v1
• [cs.SI]Shifting Opinions in a Social Network Through Leader Selection
Yuhao Yi, Timothy Castiglia, Stacy Patterson
http://arxiv.org/abs/1910.13009v1
• [cs.SI]User’s Centrality Analysis for Home Location Estimation
Shiori Hironaka, Mitsuo Yoshida, Kyoji Umemura
http://arxiv.org/abs/1910.13195v1
• [econ.EM]Analyzing China’s Consumer Price Index Comparatively with that of United States
Zhenzhong Wang, Yundong Tu, Song Xi Chen
http://arxiv.org/abs/1910.13301v1
• [eess.AS]Dr.VOT : Measuring Positive and Negative Voice Onset Time in the Wild
Yosi Shrem, Matthew Goldrick, Joseph Keshet
http://arxiv.org/abs/1910.13255v1
• [eess.AS]Improving sequence-to-sequence speech recognition training with on-the-fly data augmentation
Thai-Son Nguyen, Sebastian Stueker, Jan Niehues, Alex Waibel
http://arxiv.org/abs/1910.13296v1
• [eess.AS]Transformer-Transducer: End-to-End Speech Recognition with Self-Attention
Ching-Feng Yeh, Jay Mahadeokar, Kaustubh Kalgaonkar, Yongqiang Wang, Duc Le, Mahaveer Jain, Kjell Schubert, Christian Fuegen, Michael L. Seltzer
http://arxiv.org/abs/1910.12977v1
• [eess.AS]a novel cross-lingual voice cloning approach with a few text-free samples
Xinyong Zhou, Hao Che, Xiaorui Wang, Lei Xie
http://arxiv.org/abs/1910.13276v1
• [eess.IV]Converged Deep Framework Assembling Principled Modules for CS-MRI
Risheng Liu, Yuxi Zhang, Shichao Cheng, Zhongxuan Luo, Xin Fan
http://arxiv.org/abs/1910.13046v1
• [eess.IV]Deep Learning for Hyperspectral Image Classification: An Overview
Shutao Li, Weiwei Song, Leyuan Fang, Yushi Chen, Pedram Ghamisi, Jón Atli Benediktsson
http://arxiv.org/abs/1910.12861v1
• [eess.IV]Deep Multi-Magnification Networks for Multi-Class Breast Cancer Image Segmentation
David Joon Ho, Dig V. K. Yarlagadda, Timothy M. D’Alfonso, Matthew G. Hanna, Anne Grabenstetter, Peter Ntiamoah, Edi Brogi, Lee K. Tan, Thomas J. Fuchs
http://arxiv.org/abs/1910.13042v1
• [eess.IV]On the Benefit of Adversarial Training for Monocular Depth Estimation
Rick Groenendijk, Sezer Karaoglu, Theo Gevers, Thomas Mensink
http://arxiv.org/abs/1910.13340v1
• [eess.IV]Sequential image processing methods for improving semantic video segmentation algorithms
Beril Sirmacek, Nicolò Botteghi, Santiago Sanchez Escalonilla Plaza
http://arxiv.org/abs/1910.13348v1
• [eess.SP]Knowledge-Aided Deep Learning for Beamspace Channel Estimation in Millimeter-Wave Massive MIMO Systems
Xiuhong Wei, Chen Hu, Linglong Dai
http://arxiv.org/abs/1910.12455v1
• [eess.SY]Deep Reinforcement Learning with Enhanced Safety for Autonomous Highway Driving
Ali Baheri, Subramanya Nageshrao, H. Eric Tseng, Ilya Kolmanovsky, Anouck Girard, Dimitar Filev
http://arxiv.org/abs/1910.12905v1
• [math.OC]Efficiently avoiding saddle points with zero order methods: No gradients required
Lampros Flokas, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Georgios Piliouras
http://arxiv.org/abs/1910.13021v1
• [math.OC]Feedback Linearization for Unknown Systems via Reinforcement Learning
Tyler Westenbroek, David Fridovich-Keil, Eric Mazumdar, Shreyas Arora, Valmik Prabhu, S. Shankar Sastry, Claire J. Tomlin
http://arxiv.org/abs/1910.13272v1
• [math.OC]Poincaré Recurrence, Cycles and Spurious Equilibria in Gradient-Descent-Ascent for Non-Convex Non-Concave Zero-Sum Games
Lampros Flokas, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Georgios Piliouras
http://arxiv.org/abs/1910.13010v1
• [math.OC]Sinkhorn Divergences for Unbalanced Optimal Transport
Thibault Séjourné, Jean Feydy, François-Xavier Vialard, Alain Trouvé, Gabriel Peyré
http://arxiv.org/abs/1910.12958v1
• [math.ST]Arbitrary Rates of Convergence for Projected and Extrinsic Means
Christof Schötz
http://arxiv.org/abs/1910.11223v2
• [math.ST]Asymptotic Distributions of High-Dimensional Nonparametric Inference with Distance Correlation
Lan Gao, Jinchi Lv, Qiman Shao
http://arxiv.org/abs/1910.12970v1
• [math.ST]High dimensional regression for regenerative time-series: an application to road traffic modeling
Mohammed Bouchouia, François Portier
http://arxiv.org/abs/1910.11095v2
• [math.ST]Jump Markov Chains and Rejection-Free Metropolis Algorithms
J. S. Rosenthal, A. Dote, K. Dabiri, T. Hirotaka, A. Sheikholeslami
http://arxiv.org/abs/1910.13316v1
• [math.ST]Multi-level Thresholding Test for High Dimensional Covariance Matrices
Song Xi Chen, Bin Guo, Yumou Qiu
http://arxiv.org/abs/1910.13074v1
• [math.ST]Optimal nonparametric multivariate change point detection and localization
Oscar Hernan Madrid Padilla, Yi Yu, Daren Wang, Alessandro Rinaldo
http://arxiv.org/abs/1910.13289v1
• [math.ST]Penalized quasi likelihood estimation for variable selection
Yoshiki Kinoshita, Nakahiro Yoshida
http://arxiv.org/abs/1910.12871v1
• [math.ST]Power analysis of knockoff filters for correlated designs
Jingbo Liu, Philippe Rigollet
http://arxiv.org/abs/1910.12428v2
• [math.ST]Wasserstein information matrix
Wuchen Li, Jiaxi Zhao
http://arxiv.org/abs/1910.11248v2
• [physics.app-ph]Comparing domain wall synapse with other Non Volatile Memory devices for on-chip learning in Analog Hardware Neural Network
Divya Kaushik, Utkarsh Singh, Upasana Sahu, Indu Sreedevi, Debanjan Bhowmik
http://arxiv.org/abs/1910.12919v1
• [quant-ph]Quantum Computing based Hybrid Solution Strategies for Large-scale Discrete-Continuous Optimization Problems
Akshay Ajagekar, Travis Humble, Fengqi You
http://arxiv.org/abs/1910.13045v1
• [stat.AP]Reply to: Large-scale quantitative profiling of the Old English verse tradition
Petr Plecháč, Andrew Cooper, Benjamin Nagy, Artjoms Šela
http://arxiv.org/abs/1910.12927v1
• [stat.ME]Joint Quantile Regression for Spatial Data
Xu Chen, Surya T. Tokdar
http://arxiv.org/abs/1910.13119v1
• [stat.ME]Minimum Detectable Effect Size Computations for Cluster-Level Regression Discontinuity: Quadratic Functional Form and Beyond
Metin Bulus
http://arxiv.org/abs/1910.12925v1
• [stat.ME]Outlier detection and influence diagnostics in network meta-analysis
Hisashi Noma, Masahiko Gosho, Ryota Ishii, Koji Oba, Toshi A. Furukawa
http://arxiv.org/abs/1910.13080v1
• [stat.ME]Sine-skewed toroidal distributions and their application in protein bioinformatics
Jose Ameijeiras-Alonso, Christophe Ley
http://arxiv.org/abs/1910.13293v1
• [stat.ME]Spatial Spread Sampling Using Weakly Associated Vectors
Raphaël Jauslin, Yves Tillé
http://arxiv.org/abs/1910.13152v1
• [stat.ME]Wasserstein $F$-tests and Confidence Bands for the Frèchet Regression of Density Response Curves
Alexander Petersen, Xi Liu, Afshin A. Divani
http://arxiv.org/abs/1910.13418v1
• [stat.ML]Bayesian Optimization with Unknown Search Space
Huong Ha, Santu Rana, Sunil Gupta, Thanh Nguyen, Hung Tran-The, Svetha Venkatesh
http://arxiv.org/abs/1910.13092v1
• [stat.ML]Divide, Conquer, and Combine: a New Inference Strategy for Probabilistic Programs with Stochastic Support
Yuan Zhou, Hongseok Yang, Yee Whye Teh, Tom Rainforth
http://arxiv.org/abs/1910.13324v1
• [stat.ML]Ensemble Quantile Classifier
Yuanhao Lai, Ian McLeod
http://arxiv.org/abs/1910.12960v1
• [stat.ML]Feature relevance quantification in explainable AI: A causality problem
Dominik Janzing, Lenon Minorics, Patrick Blöbaum
http://arxiv.org/abs/1910.13413v1
• [stat.ML]Harnessing the power of Topological Data Analysis to detect change points in time series
Umar Islambekov, Monisha Yuvaraj, Yulia R. Gel
http://arxiv.org/abs/1910.12939v1
• [stat.ML]How Much Can We See? A Note on Quantifying Explainability of Machine Learning Models
Gero Szepannek
http://arxiv.org/abs/1910.13376v1
• [stat.ML]Improved Differentially Private Decentralized Source Separation for fMRI Data
Hafiz Imtiaz, Jafar Mohammadi, Rogers Silva, Bradley Baker, Sergey M. Plis, Anand D. Sarwate, Vince Calhoun
http://arxiv.org/abs/1910.12913v1
• [stat.ML]Learning Sparse Distributions using Iterative Hard Thresholding
Jacky Y. Zhang, Rajiv Khanna, Anastasios Kyrillidis, Oluwasanmi Koyejo
http://arxiv.org/abs/1910.13389v1
• [stat.ML]Minimal Variance Sampling in Stochastic Gradient Boosting
Bulat Ibragimov, Gleb Gusev
http://arxiv.org/abs/1910.13204v1
• [stat.ML]Missing Not at Random in Matrix Completion: The Effectiveness of Estimating Missingness Probabilities Under a Low Nuclear Norm Assumption
Wei Ma, George H. Chen
http://arxiv.org/abs/1910.12774v2
• [stat.ML]Model enhancement and personalization using weakly supervised learning for multi-modal mobile sensing
Diyan Teng, Rashmi Kulkarni, Justin McGloin
http://arxiv.org/abs/1910.13401v1
• [stat.ML]Neural Density Estimation and Likelihood-free Inference
George Papamakarios
http://arxiv.org/abs/1910.13233v1
• [stat.ML]Poisson-Randomized Gamma Dynamical Systems
Aaron Schein, Scott W. Linderman, Mingyuan Zhou, David M. Blei, Hanna Wallach
http://arxiv.org/abs/1910.12991v1
• [stat.ML]Stein’s Lemma for the Reparameterization Trick with Exponential Family Mixtures
Wu Lin, Mohammad Emtiyaz Khan, Mark Schmidt
http://arxiv.org/abs/1910.13398v1
• [stat.ML]The Power of Graph Convolutional Networks to Distinguish Random Graph Models
Abram Magner, Mayank Baranwal, Alfred O. Hero III
http://arxiv.org/abs/1910.12954v1
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