cs.AI - 人工智能

    cs.AR - 硬件体系结构 cs.CL - 计算与语言 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.DS - 数据结构与算法 cs.GT - 计算机科学与博弈论 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 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.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.DS - 动力系统 math.PR - 概率 math.ST - 统计理论 q-bio.QM - 定量方法 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]Adversarial Inverse Reinforcement Learning for Decision Making in Autonomous Driving
    • [cs.AI]Attention Privileged Reinforcement Learning For Domain Transfer
    • [cs.AI]Multimedia Search and Temporal Reasoning
    • [cs.AI]The αμ Search Algorithm for the Game of Bridge
    • [cs.AI]Towards a computer-interpretable actionable formal model to encode data governance rules
    • [cs.AR]Stream Semantic Registers: A Lightweight RISC-V ISA Extension Achieving Full Compute Utilization in Single-Issue Cores
    • [cs.CL]A Hybrid Morpheme-Word Representation for Machine Translation of Morphologically Rich Languages
    • [cs.CL]Deep Poetry: A Chinese Classical Poetry Generation System
    • [cs.CL]Deep and Dense Sarcasm Detection
    • [cs.CL]End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures
    • [cs.CL]Error Analysis for Vietnamese Named Entity Recognition on Deep Neural Network Models
    • [cs.CL]Extended Answer and Uncertainty Aware Neural Question Generation
    • [cs.CL]Hunting for Troll Comments in News Community Forums
    • [cs.CL]Improving Document Classification with Multi-Sense Embeddings
    • [cs.CL]In Search of Credible News
    • [cs.CL]Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation
    • [cs.CL]Unsupervised Natural Question Answering with a Small Model
    • [cs.CV]A Boost Strategy to the Generative Error Based Video Anomaly Detection Algorithms
    • [cs.CV]A novel method for identifying the deep neural network model with the Serial Number
    • [cs.CV]AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
    • [cs.CV]Action Anticipation with RBF Kernelized Feature Mapping RNN
    • [cs.CV]Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data
    • [cs.CV]Constrained R-CNN: A general image manipulation detection model
    • [cs.CV]DebFace: De-biasing Face Recognition
    • [cs.CV]Defective Convolutional Layers Learn Robust CNNs
    • [cs.CV]Dense Fusion Classmate Network for Land Cover Classification
    • [cs.CV]Differentiating Features for Scene Segmentation Based on Dedicated Attention Mechanisms
    • [cs.CV]Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
    • [cs.CV]Dont Even Look Once: Synthesizing Features for Zero-Shot Detection
    • [cs.CV]Dual affine moment invariants
    • [cs.CV]Efficient Hardware Implementation of Incremental Learning and Inference on Chip
    • [cs.CV]Exploiting Human Social Cognition for the Detection of Fake and Fraudulent Faces via Memory Networks
    • [cs.CV]Finding Missing Children: Aging Deep Face Features
    • [cs.CV]FollowMeUp Sports: New Benchmark for 2D Human Keypoint Recognition
    • [cs.CV]General $E(2)$-Equivariant Steerable CNNs
    • [cs.CV]GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations
    • [cs.CV]IFQ-Net: Integrated Fixed-point Quantization Networks for Embedded Vision
    • [cs.CV]Improving the Robustness of Capsule Networks to Image Affine Transformations
    • [cs.CV]KISS: Keeping It Simple for Scene Text Recognition
    • [cs.CV]Learning Modulated Loss for Rotated Object Detection
    • [cs.CV]MarioNETte: Few-shot Face Reenactment Preserving Identity of Unseen Targets
    • [cs.CV]Mimic The Raw Domain: Accelerating Action Recognition in the Compressed Domain
    • [cs.CV]Modality To Modality Translation: An Adversarial Representation Learning and Graph Fusion Network for Multimodal Fusion
    • [cs.CV]Multiple Face Analyses through Adversarial Learning
    • [cs.CV]Neural Network Pruning with Residual-Connections and Limited-Data
    • [cs.CV]On the Impact of Object and Sub-component Level Segmentation Strategies for Supervised Anomaly Detection within X-ray Security Imagery
    • [cs.CV]Poison as a Cure: Detecting & Neutralizing Variable-Sized Backdoor Attacks in Deep Neural Networks
    • [cs.CV]Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach
    • [cs.CV]Rethinking deep active learning: Using unlabeled data at model training
    • [cs.CV]Segmentation Guided Attention Network for Crowd Counting via Curriculum Learning
    • [cs.CV]Simultaneous Mapping and Target Driven Navigation
    • [cs.CV]Simultaneous Region Localization and Hash Coding for Fine-grained Image Retrieval
    • [cs.CV]Single-Stage 6D Object Pose Estimation
    • [cs.CV]Solar Event Tracking with Deep Regression Networks: A Proof of Concept Evaluation
    • [cs.CV]Streetify: Using Street View Imagery And Deep Learning For Urban Streets Development
    • [cs.CV]Tell Me What They’re Holding: Weakly-supervised Object Detection with Transferable Knowledge from Human-object Interaction
    • [cs.CV]Towards a complete 3D morphable model of the human head
    • [cs.CV]TracKlinic: Diagnosis of Challenge Factors in Visual Tracking
    • [cs.CV]Two-Stream FCNs to Balance Content and Style for Style Transfer
    • [cs.CV]Vision-Language Navigation with Self-Supervised Auxiliary Reasoning Tasks
    • [cs.CV]Weakly-Supervised Video Moment Retrieval via Semantic Completion Network
    • [cs.CY]”The Human Body is a Black Box”: Supporting Clinical Decision-Making with Deep Learning
    • [cs.CY]A Methodology for Obtaining Objective Measurements of Population Obesogenic Behaviors in Relation to the Environment
    • [cs.CY]Exploring the added value of blockchain technology for the healthcare domain
    • [cs.CY]The AI Liability Puzzle and A Fund-Based Work-Around
    • [cs.CY]The gift of the gab: Are rental scammers skilled at the art of persuasion?
    • [cs.DC]Can 100 Machines Agree?
    • [cs.DC]Decentralization in Open Quorum Systems
    • [cs.DC]Evaluation of performance portability frameworks for the implementation of a particle-in-cell code
    • [cs.DC]On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning
    • [cs.DC]PES: Proactive Event Scheduling for Responsive and Energy-Efficient Mobile Web Computing
    • [cs.DC]The Design and Implementation of a Scalable DL Benchmarking Platform
    • [cs.DS]Consistent recovery threshold of hidden nearest neighbor graphs
    • [cs.DS]Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers
    • [cs.DS]Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
    • [cs.GT]All-Pay Bidding Games on Graphs
    • [cs.GT]Defending with Shared Resources on a Network
    • [cs.IT]Computation Offloading in the Untrusted MEC-aided Mobile Blockchain IoT System
    • [cs.IT]Cooperative Multiple-Access Channels with Distributed State Information
    • [cs.IT]Estimating Entropy of Distributions in Constant Space
    • [cs.IT]Hierarchical Distribution Matching: a Versatile Tool for Probabilistic Shaping
    • [cs.IT]Joint Unicast and Multi-group Multicast Transmission in Massive MIMO Systems
    • [cs.IT]Low Complexity Autoencoder based End-to-End Learning of Coded Communications Systems
    • [cs.IT]Low-Complexity Linear Equalization for OTFS Systems with Rectangular Waveforms
    • [cs.IT]New entanglement-assisted quantum MDS codes with length $n=\frac{q^2+1}5$
    • [cs.IT]On the Upper Bound of the Kullback-Leibler Divergence and Cross Entropy
    • [cs.IT]Optimal repairing schemes for Reed-Solomon codes with alphabet sizes linear in lengths under the rack-aware model
    • [cs.IT]Placement Optimization of Aerial Base Stations with Deep Reinforcement Learning
    • [cs.IT]Super-Nyquist Rateless Coding for Intersymbol Interference Channels
    • [cs.IT]Towards A Theory of Duality for Graph Signal Processing
    • [cs.IT]Two-Way Physical Layer Security Protocol for Gaussian Channels
    • [cs.LG]A Bias Trick for Centered Robust Principal Component Analysis
    • [cs.LG]A Multi-Task Gradient Descent Method for Multi-Label Learning
    • [cs.LG]A Study on various state of the art of the Art Face Recognition System using Deep Learning Techniques
    • [cs.LG]A model for predicting price polarity of real estate properties using information of real estate market websites
    • [cs.LG]ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
    • [cs.LG]Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning
    • [cs.LG]Adaptive Routing Between Capsules
    • [cs.LG]Adversarial Attacks on Grid Events Classification: An Adversarial Machine Learning Approach
    • [cs.LG]Attribute noise robust binary classification
    • [cs.LG]Basic Principles of Clustering Methods
    • [cs.LG]Benanza: Automatic $μ$Benchmark Generation to Compute “Lower-bound” Latency and Inform Optimizations of Deep Learning Models on GPUs
    • [cs.LG]Can You Really Backdoor Federated Learning?
    • [cs.LG]Carpe Diem, Seize the Samples Uncertain “At the Moment” for Adaptive Batch Selection
    • [cs.LG]Comments on the Du-Kakade-Wang-Yang Lower Bounds
    • [cs.LG]DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
    • [cs.LG]DLBricks: Composable Benchmark Generation toReduce Deep Learning Benchmarking Effort on CPUs
    • [cs.LG]Deep Detector Health Management under Adversarial Campaigns
    • [cs.LG]Deep Tile Coder: an Efficient Sparse Representation Learning Approach with applications in Reinforcement Learning
    • [cs.LG]Driver Identification Based on Vehicle Telematics Data using LSTM-Recurrent Neural Network
    • [cs.LG]Eigenvalue Normalized Recurrent Neural Networks for Short Term Memory
    • [cs.LG]Eliminating artefacts in Polarimetric Images using Deep Learning
    • [cs.LG]Energy Usage Reports: Environmental awareness as part of algorithmic accountability
    • [cs.LG]Fair Learning-to-Rank from Implicit Feedback
    • [cs.LG]Implicit Generative Modeling for Efficient Exploration
    • [cs.LG]Implicit Regularization of Normalization Methods
    • [cs.LG]Information-Theoretic Local Minima Characterization and Regularization
    • [cs.LG]Inter-layer Collision Networks
    • [cs.LG]Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned
    • [cs.LG]Learning Permutation Invariant Representations using Memory Networks
    • [cs.LG]Live Face De-Identification in Video
    • [cs.LG]MANGA: Method Agnostic Neural-policy Generalization and Adaptation
    • [cs.LG]Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
    • [cs.LG]Mixed-curvature Variational Autoencoders
    • [cs.LG]Modelling pressure-Hessian from local velocity gradients information in an incompressible turbulent flow field using deep neural networks
    • [cs.LG]Neural Forest Learning
    • [cs.LG]Online Learned Continual Compression with Stacked Quantization Module
    • [cs.LG]PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems
    • [cs.LG]Planning with Goal-Conditioned Policies
    • [cs.LG]Predicting overweight and obesity in later life from childhood data: A review of predictive modeling approaches
    • [cs.LG]Prestopping: How Does Early Stopping Help Generalization against Label Noise?
    • [cs.LG]Privacy Leakage Avoidance with Switching Ensembles
    • [cs.LG]Program synthesis performance constrained by non-linear spatial relations in Synthetic Visual Reasoning Test
    • [cs.LG]RWNE: A Scalable Random-Walk based Network Embedding Framework with Personalized Higher-order Proximity Preserved
    • [cs.LG]Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic
    • [cs.LG]Sequential Mode Estimation with Oracle Queries
    • [cs.LG]Survival and Neural Models for Private Equity Exit Prediction
    • [cs.LG]Temporal Knowledge Graph Embedding Model based on Additive Time Series Decomposition
    • [cs.LG]Thick-Net: Parallel Network Structure for Sequential Modeling
    • [cs.LG]Towards non-toxic landscapes: Automatic toxic comment detection using DNN
    • [cs.LG]Towards unstructured mortality prediction with free-text clinical notes
    • [cs.LG]Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling
    • [cs.LG]Variance Reduced Advantage Estimation with $δ$ Hindsight Credit Assignment
    • [cs.LG]WITCHcraft: Efficient PGD attacks with random step size
    • [cs.LG]vqSGD: Vector Quantized Stochastic Gradient Descent
    • [cs.MA]Cooperative Pathfinding based on high-scalability Multi-agent RRT*
    • [cs.NE]Deep Spiking Neural Networks for Large Vocabulary Automatic Speech Recognition
    • [cs.NE]ImmuNeCS: Neural Committee Search by an Artificial Immune System
    • [cs.NE]Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons
    • [cs.NI]Delay-Aware Wireless Network Coding in Adversarial Traffic
    • [cs.NI]The geopolitics behind the routes data travels: a case study of Iran
    • [cs.RO]A Deep Learning Approach for Robust Corridor Following
    • [cs.RO]Long-Term Personalization of an In-Home Socially Assistive Robot for Children With Autism Spectrum Disorders
    • [cs.RO]Nonlinear Model Predictive Control with Actuator Constraints for Multi-Rotor Aerial Vehicles
    • [cs.RO]Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Simulated Brush Model
    • [cs.RO]Task-Based Hybrid Shared Control for Training Through Forceful Interaction
    • [cs.RO]User-Driven Functional Movement Training with a Wearable Hand Robot after Stroke
    • [cs.SD]Alternating Between Spectral and Spatial Estimation for Speech Separation and Enhancement
    • [cs.SD]Improving Universal Sound Separation Using Sound Classification
    • [cs.SE]Commit2Vec: Learning Distributed Representations of Code Changes
    • [cs.SI]Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization
    • [cs.SI]Event detection in Colombian security Twitter news using fine-grained latent topic analysis
    • [cs.SI]Graph Learning for Spatiotemporal Signal with Long Short-Term Characterization
    • [eess.AS]Neural Network based End-to-End Query by Example Spoken Term Detection
    • [eess.IV]Automated fetal brain extraction from clinical Ultrasound volumes using 3D Convolutional Neural Networks
    • [eess.IV]CD2 : Combined Distances of Contrast Distributions for the Assessment of Perceptual Quality of Image Processing
    • [eess.IV]Convolutional Neural Network and decision support in medical imaging: case study of the recognition of blood cell subtypes
    • [eess.IV]Frequency Separation for Real-World Super-Resolution
    • [eess.IV]HighEr-Resolution Network for Image Demosaicing and Enhancing
    • [eess.IV]ISP4ML: Understanding the Role of Image Signal Processing in Efficient Deep Learning Vision Systems
    • [eess.IV]LNDb: A Lung Nodule Database on Computed Tomography
    • [eess.IV]Multi-Resolution 3D CNN for MRI Brain Tumor Segmentation and Survival Prediction
    • [eess.IV]Projection-to-Projection Translation for Hybrid X-ray and Magnetic Resonance Imaging
    • [eess.IV]Three-dimensional Generative Adversarial Nets for Unsupervised Metal Artifact Reduction
    • [eess.IV]Visualization approach to assess the robustness of neural networks for medical image classification
    • [eess.SP]AddNet: Deep Neural Networks Using FPGA-Optimized Multipliers
    • [eess.SP]Comparison of Deep learning models on time series forecasting : a case study of Dissolved Oxygen Prediction
    • [eess.SP]iGateLink: A Gateway Library for Linking IoT, Edge, Fog and Cloud Computing Environments
    • [math.DS]A topological dynamical system with two different positive sofic entropies
    • [math.PR]On critical points of Gaussian random fields under diffeomorphic transformations
    • [math.ST]Discussion contribution “Functional models for time-varying random objects’’ by Dubey and Müller (to appear in JRSS-B)
    • [math.ST]Estimation of dynamic networks for high-dimensional nonstationary time series
    • [math.ST]Improved clustering algorithms for the Bipartite Stochastic Block Model
    • [math.ST]Infinitesimal generators for two-dimensional Lévy process-driven hypothesis testing
    • [math.ST]Minimax rates of $\ell_p$-losses for high-dimensional linear regression models with additive measurement errors over $\ell_q$-balls
    • [math.ST]Sparse recovery via nonconvex regularized $M$-estimators over $\ell_q$-balls
    • [q-bio.QM]Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks
    • [stat.AP]A regularized hidden Markov model for analyzing the ‘hot shoe’ in football
    • [stat.AP]Anomaly and Novelty detection for robust semi-supervised learning
    • [stat.AP]Common Growth Patterns for Regional Social Networks: a Point Process Approach
    • [stat.AP]Large-Scale Spatiotemporal Density Smoothing with the Graph-fused Elastic Net: Application to Ride-sourcing Driver Productivity Analysis
    • [stat.AP]Principal Stratification for Advertising Experiments
    • [stat.ME]A Normal Approximation Method for Statistics in Knockouts
    • [stat.ME]Gradient-based Sparse Principal Component Analysis with Extensions to Online Learning
    • [stat.ME]Measuring spatiotemporal disease clustering with the tau statistic
    • [stat.ME]Optimal tests for elliptical symmetry: specified and unspecified location
    • [stat.ME]Uncertainty and Sensitivity Analyses Methods for Agent-Based Mathematical Models: An Introductory Review
    • [stat.ML]A Simple Heuristic for Bayesian Optimization with A Low Budget
    • [stat.ML]Deep Unsupervised Clustering with Clustered Generator Model
    • [stat.ML]Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders
    • [stat.ML]SimVAE: Simulator-Assisted Training forInterpretable Generative Models

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

    • [cs.AI]Adversarial Inverse Reinforcement Learning for Decision Making in Autonomous Driving
    Pin Wang, Dapeng Liu, Jiayu Chen, Ching-Yao Chan
    http://arxiv.org/abs/1911.08044v1

    • [cs.AI]Attention Privileged Reinforcement Learning For Domain Transfer
    Sasha Salter, Dushyant Rao, Markus Wulfmeier, Raia Hadsell, Ingmar Posner
    http://arxiv.org/abs/1911.08363v1

    • [cs.AI]Multimedia Search and Temporal Reasoning
    Marcio Ferreira Moreno, Rodrigo Costa Mesquita Santos, Wallas Henrique Sousa dos Santos, Sandro Rama Fiorini, Reinaldo Mozart da Gama Silva
    http://arxiv.org/abs/1911.08225v1

    • [cs.AI]The αμ Search Algorithm for the Game of Bridge
    Tristan Cazenave, Véronique Ventos
    http://arxiv.org/abs/1911.07960v1

    • [cs.AI]Towards a computer-interpretable actionable formal model to encode data governance rules
    Rui Zhao, Malcolm Atkinson
    http://arxiv.org/abs/1911.08439v1

    • [cs.AR]Stream Semantic Registers: A Lightweight RISC-V ISA Extension Achieving Full Compute Utilization in Single-Issue Cores
    Fabian Schuiki, Florian Zaruba, Torsten Hoefler, Luca Benini
    http://arxiv.org/abs/1911.08356v1

    • [cs.CL]A Hybrid Morpheme-Word Representation for Machine Translation of Morphologically Rich Languages
    Minh-Thang Luong, Preslav Nakov, Min-Yen Kan
    http://arxiv.org/abs/1911.08117v1

    • [cs.CL]Deep Poetry: A Chinese Classical Poetry Generation System
    Yusen Liu, Dayiheng Liu, Jiancheng Lv
    http://arxiv.org/abs/1911.08212v1

    • [cs.CL]Deep and Dense Sarcasm Detection
    Devin Pelser, Hugh Murrell
    http://arxiv.org/abs/1911.07474v2

    • [cs.CL]End-to-end ASR: from Supervised to Semi-Supervised Learning with Modern Architectures
    Gabriel Synnaeve, Qiantong Xu, Jacob Kahn, Edouard Grave, Tatiana Likhomanenko, Vineel Pratap, Anuroop Sriram, Vitaliy Liptchinsky, Ronan Collobert
    http://arxiv.org/abs/1911.08460v1

    • [cs.CL]Error Analysis for Vietnamese Named Entity Recognition on Deep Neural Network Models
    Binh An Nguyen, Kiet Van Nguyen, Ngan Luu-Thuy Nguyen
    http://arxiv.org/abs/1911.07228v2

    • [cs.CL]Extended Answer and Uncertainty Aware Neural Question Generation
    Hongwei Zeng, Zhuo Zhi, Jun Liu, Bifan Wei
    http://arxiv.org/abs/1911.08112v1

    • [cs.CL]Hunting for Troll Comments in News Community Forums
    Todor Mihaylov, Preslav Nakov
    http://arxiv.org/abs/1911.08113v1

    • [cs.CL]Improving Document Classification with Multi-Sense Embeddings
    Vivek Gupta, Ankit Saw, Pegah Nokhiz, Harshit Gupta, Partha Talukdar
    http://arxiv.org/abs/1911.07918v1

    • [cs.CL]In Search of Credible News
    Momchil Hardalov, Ivan Koychev, Preslav Nakov
    http://arxiv.org/abs/1911.08125v1

    • [cs.CL]Retrospective and Prospective Mixture-of-Generators for Task-oriented Dialogue Response Generation
    Jiahuan Pei, Pengjie Ren, Christof Monz, Maarten de Rijke
    http://arxiv.org/abs/1911.08151v1

    • [cs.CL]Unsupervised Natural Question Answering with a Small Model
    Martin Andrews, Sam Witteveen
    http://arxiv.org/abs/1911.08340v1

    • [cs.CV]A Boost Strategy to the Generative Error Based Video Anomaly Detection Algorithms
    Zhiguo Wang, Yu-Jin Zhang
    http://arxiv.org/abs/1911.08402v1

    • [cs.CV]A novel method for identifying the deep neural network model with the Serial Number
    XiangRui Xu, YaQin Li, Cao Yuan
    http://arxiv.org/abs/1911.08053v1

    • [cs.CV]AIM 2019 Challenge on Real-World Image Super-Resolution: Methods and Results
    Andreas Lugmayr, Martin Danelljan, Radu Timofte, Manuel Fritsche, Shuhang Gu, Kuldeep Purohit, Praveen Kandula, Maitreya Suin, A N Rajagopalan, Nam Hyung Joon, Yu Seung Won, Guisik Kim, Dokyeong Kwon, Chih-Chung Hsu, Chia-Hsiang Lin, Yuanfei Huang, Xiaopeng Sun, Wen Lu, Jie Li, Xinbo Gao, Sefi Bell-Kligler
    http://arxiv.org/abs/1911.07783v2

    • [cs.CV]Action Anticipation with RBF Kernelized Feature Mapping RNN
    Yuge Shi, Basura Fernando, Richard Hartley
    http://arxiv.org/abs/1911.07806v2

    • [cs.CV]Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data
    David W. Romero, Mark Hoogendoorn
    http://arxiv.org/abs/1911.07849v1

    • [cs.CV]Constrained R-CNN: A general image manipulation detection model
    Huizhou Li, Chao Yang, Fangting Lin, Bin Jiang
    http://arxiv.org/abs/1911.08217v1

    • [cs.CV]DebFace: De-biasing Face Recognition
    Sixue Gong, Xiaoming Liu, Anil K. Jain
    http://arxiv.org/abs/1911.08080v1

    • [cs.CV]Defective Convolutional Layers Learn Robust CNNs
    Tiange Luo, Tianle Cai, Mengxiao Zhang, Siyu Chen, Di He, Liwei Wang
    http://arxiv.org/abs/1911.08432v1

    • [cs.CV]Dense Fusion Classmate Network for Land Cover Classification
    Chao Tian, Cong Li, Jianping Shi
    http://arxiv.org/abs/1911.08169v1

    • [cs.CV]Differentiating Features for Scene Segmentation Based on Dedicated Attention Mechanisms
    Zhiqiang Xiong, Zhicheng Wang, Zhaohui Yu, Xi Gu
    http://arxiv.org/abs/1911.08149v1

    • [cs.CV]Distance-IoU Loss: Faster and Better Learning for Bounding Box Regression
    Zhaohui Zheng, Ping Wang, Wei Liu, Jinze Li, Rongguang Ye, Dongwei Ren
    http://arxiv.org/abs/1911.08287v1

    • [cs.CV]Dont Even Look Once: Synthesizing Features for Zero-Shot Detection
    Pengkai Zhu, Hanxiao Wang, Venkatesh Saligrama
    http://arxiv.org/abs/1911.07933v1

    • [cs.CV]Dual affine moment invariants
    You Hao, Hanlin Mo, Qi Li, He Zhang, Hua Li
    http://arxiv.org/abs/1911.08233v1

    • [cs.CV]Efficient Hardware Implementation of Incremental Learning and Inference on Chip
    Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jezequel
    http://arxiv.org/abs/1911.07847v1

    • [cs.CV]Exploiting Human Social Cognition for the Detection of Fake and Fraudulent Faces via Memory Networks
    Tharindu Fernando, Clinton Fookes, Simon Denman, Sridha Sridharan
    http://arxiv.org/abs/1911.07844v1

    • [cs.CV]Finding Missing Children: Aging Deep Face Features
    Debayan Deb, Divyansh Aggarwal, Anil K. Jain
    http://arxiv.org/abs/1911.07538v2

    • [cs.CV]FollowMeUp Sports: New Benchmark for 2D Human Keypoint Recognition
    Ying Huang, Bin Sun, Haipeng Kan, Jiankai Zhuang, Zengchang Qin
    http://arxiv.org/abs/1911.08344v1

    • [cs.CV]General $E(2)$-Equivariant Steerable CNNs
    Maurice Weiler, Gabriele Cesa
    http://arxiv.org/abs/1911.08251v1

    • [cs.CV]GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations
    Xiang Gao, Wei Hu, Guo-Jun Qi
    http://arxiv.org/abs/1911.08142v1

    • [cs.CV]IFQ-Net: Integrated Fixed-point Quantization Networks for Embedded Vision
    Hongxing Gao, Wei Tao, Dongchao Wen, Tse-Wei Chen, Kinya Osa, Masami Kato
    http://arxiv.org/abs/1911.08076v1

    • [cs.CV]Improving the Robustness of Capsule Networks to Image Affine Transformations
    Jindong Gu, Volker Tresp
    http://arxiv.org/abs/1911.07968v1

    • [cs.CV]KISS: Keeping It Simple for Scene Text Recognition
    Christian Bartz, Joseph Bethge, Haojin Yang, Christoph Meinel
    http://arxiv.org/abs/1911.08400v1

    • [cs.CV]Learning Modulated Loss for Rotated Object Detection
    Wen Qian, Xue Yang, Silong Peng, Yue Guo, Chijun Yan
    http://arxiv.org/abs/1911.08299v1

    • [cs.CV]MarioNETte: Few-shot Face Reenactment Preserving Identity of Unseen Targets
    Sungjoo Ha, Martin Kersner, Beomsu Kim, Seokjun Seo, Dongyoung Kim
    http://arxiv.org/abs/1911.08139v1

    • [cs.CV]Mimic The Raw Domain: Accelerating Action Recognition in the Compressed Domain
    Barak Battash, Haim Barad, Hanlin Tang, Amit Bleiweiss
    http://arxiv.org/abs/1911.08206v1

    • [cs.CV]Modality To Modality Translation: An Adversarial Representation Learning and Graph Fusion Network for Multimodal Fusion
    Sijie Mai, Haifeng Hu, Songlong Xing
    http://arxiv.org/abs/1911.07848v1

    • [cs.CV]Multiple Face Analyses through Adversarial Learning
    Shangfei Wang, Shi Yin, Longfei Hao, Guang Liang
    http://arxiv.org/abs/1911.07846v1

    • [cs.CV]Neural Network Pruning with Residual-Connections and Limited-Data
    Jian-Hao Luo, Jianxin Wu
    http://arxiv.org/abs/1911.08114v1

    • [cs.CV]On the Impact of Object and Sub-component Level Segmentation Strategies for Supervised Anomaly Detection within X-ray Security Imagery
    Neelanjan Bhowmik, Yona Falinie A. Gaus, Samet Akcay, Jack W. Barker, Toby P. Breckon
    http://arxiv.org/abs/1911.08216v1

    • [cs.CV]Poison as a Cure: Detecting & Neutralizing Variable-Sized Backdoor Attacks in Deep Neural Networks
    Alvin Chan, Yew-Soon Ong
    http://arxiv.org/abs/1911.08040v1

    • [cs.CV]Reliability Does Matter: An End-to-End Weakly Supervised Semantic Segmentation Approach
    Bingfeng Zhang, Jimin Xiao, Yunchao Wei, Mingjie Sun, Kaizhu Huang
    http://arxiv.org/abs/1911.08039v1

    • [cs.CV]Rethinking deep active learning: Using unlabeled data at model training
    Oriane Siméoni, Mateusz Budnik, Yannis Avrithis, Guillaume Gravier
    http://arxiv.org/abs/1911.08177v1

    • [cs.CV]Segmentation Guided Attention Network for Crowd Counting via Curriculum Learning
    Qian Wang, Toby P. Breckon
    http://arxiv.org/abs/1911.07990v1

    • [cs.CV]Simultaneous Mapping and Target Driven Navigation
    Georgios Georgakis, Yimeng Li, Jana Kosecka
    http://arxiv.org/abs/1911.07980v1

    • [cs.CV]Simultaneous Region Localization and Hash Coding for Fine-grained Image Retrieval
    Haien Zeng, Hanjiang Lai, Jian Yin
    http://arxiv.org/abs/1911.08028v1

    • [cs.CV]Single-Stage 6D Object Pose Estimation
    Yinlin Hu, Pascal Fua, Wei Wang, Mathieu Salzmann
    http://arxiv.org/abs/1911.08324v1

    • [cs.CV]Solar Event Tracking with Deep Regression Networks: A Proof of Concept Evaluation
    Toqi Tahamid Sarker, Juan M. Banda
    http://arxiv.org/abs/1911.08350v1

    • [cs.CV]Streetify: Using Street View Imagery And Deep Learning For Urban Streets Development
    Fahad Alhasoun, Marta Gonzalez
    http://arxiv.org/abs/1911.08007v1

    • [cs.CV]Tell Me What They’re Holding: Weakly-supervised Object Detection with Transferable Knowledge from Human-object Interaction
    Daesik Kim, Gyujeong Lee, Jisoo Jeong, Nojun Kwak
    http://arxiv.org/abs/1911.08141v1

    • [cs.CV]Towards a complete 3D morphable model of the human head
    Stylianos Ploumpis, Evangelos Ververas, Eimear O’ Sullivan, Stylianos Moschoglou, Haoyang Wang, Nick Pears, William A. P. Smith, Baris Gecer, Stefanos Zafeiriou
    http://arxiv.org/abs/1911.08008v1

    • [cs.CV]TracKlinic: Diagnosis of Challenge Factors in Visual Tracking
    Heng Fan, Fan Yang, Peng Chu, Lin Yuan, Haibin Ling
    http://arxiv.org/abs/1911.07959v1

    • [cs.CV]Two-Stream FCNs to Balance Content and Style for Style Transfer
    Duc Minh Vo, Akihiro Sugimoto
    http://arxiv.org/abs/1911.08079v1

    • [cs.CV]Vision-Language Navigation with Self-Supervised Auxiliary Reasoning Tasks
    Fengda Zhu, Yi Zhu, Xiaojun Chang, Xiaodan Liang
    http://arxiv.org/abs/1911.07883v1

    • [cs.CV]Weakly-Supervised Video Moment Retrieval via Semantic Completion Network
    Zhijie Lin, Zhou Zhao, Zhu Zhang, Qi Wang, Huasheng Liu
    http://arxiv.org/abs/1911.08199v1

    • [cs.CY]“The Human Body is a Black Box”: Supporting Clinical Decision-Making with Deep Learning
    Mark Sendak, Madeleine Elish, Michael Gao, Joseph Futoma, William Ratliff, Marshall Nichols, Armando Bedoya, Suresh Balu, Cara O’Brien
    http://arxiv.org/abs/1911.08089v1

    • [cs.CY]A Methodology for Obtaining Objective Measurements of Population Obesogenic Behaviors in Relation to the Environment
    Christos Diou, Ioannis Sarafis, Vasileios Papapanagiotou, Ioannis Ioakimidis, Anastasios Delopoulos
    http://arxiv.org/abs/1911.08315v1

    • [cs.CY]Exploring the added value of blockchain technology for the healthcare domain
    Bas R. J. Bolmer, Monique Taverne, Marco Scherer
    http://arxiv.org/abs/1911.08277v1

    • [cs.CY]The AI Liability Puzzle and A Fund-Based Work-Around
    Olivia J. Erdélyi, Gábor Erdélyi
    http://arxiv.org/abs/1911.08005v1

    • [cs.CY]The gift of the gab: Are rental scammers skilled at the art of persuasion?
    Sophie Van Der Zee, Richard Clayton, Ross Anderson
    http://arxiv.org/abs/1911.08253v1

    • [cs.DC]Can 100 Machines Agree?
    Rachid Guerraoui, Jad Hamza, Dragos-Adrian Seredinschi, Marko Vukolic
    http://arxiv.org/abs/1911.07966v1

    • [cs.DC]Decentralization in Open Quorum Systems
    Andrea Bracciali, Davide Grossi, Ronald de Haan
    http://arxiv.org/abs/1911.08182v1

    • [cs.DC]Evaluation of performance portability frameworks for the implementation of a particle-in-cell code
    Victor Artigues, Katharina Kormann, Markus Rampp, Klaus Reuter
    http://arxiv.org/abs/1911.08394v1

    • [cs.DC]On the Discrepancy between the Theoretical Analysis and Practical Implementations of Compressed Communication for Distributed Deep Learning
    Aritra Dutta, El Houcine Bergou, Ahmed M. Abdelmoniem, Chen-Yu Ho, Atal Narayan Sahu, Marco Canini, Panos Kalnis
    http://arxiv.org/abs/1911.08250v1

    • [cs.DC]PES: Proactive Event Scheduling for Responsive and Energy-Efficient Mobile Web Computing
    Yu Feng, Yuhao Zhu
    http://arxiv.org/abs/1911.07787v1

    • [cs.DC]The Design and Implementation of a Scalable DL Benchmarking Platform
    Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-mei Hwu
    http://arxiv.org/abs/1911.08031v1

    • [cs.DS]Consistent recovery threshold of hidden nearest neighbor graphs
    Jian Ding, Yihong Wu, Jiaming Xu, Dana Yang
    http://arxiv.org/abs/1911.08004v1

    • [cs.DS]Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers
    Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
    http://arxiv.org/abs/1911.08015v1

    • [cs.DS]Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering
    Ilias Diakonikolas, Sushrut Karmalkar, Daniel Kane, Eric Price, Alistair Stewart
    http://arxiv.org/abs/1911.08085v1

    • [cs.GT]All-Pay Bidding Games on Graphs
    Guy Avni, Rasmus Ibsen-Jensen, Josef Tkadlec
    http://arxiv.org/abs/1911.08360v1

    • [cs.GT]Defending with Shared Resources on a Network
    Minming Li, Long Tran-Thanh, Xiaowei Wu
    http://arxiv.org/abs/1911.08196v1

    • [cs.IT]Computation Offloading in the Untrusted MEC-aided Mobile Blockchain IoT System
    Yiping Zuo, Shi Jin, Shengli Zhang
    http://arxiv.org/abs/1911.08255v1

    • [cs.IT]Cooperative Multiple-Access Channels with Distributed State Information
    Lorenzo Miretti, Mari Kobayashi, David Gesbert, Paul de Kerret
    http://arxiv.org/abs/1911.07899v1

    • [cs.IT]Estimating Entropy of Distributions in Constant Space
    Jayadev Acharya, Sourbh Bhadane, Piotr Indyk, Ziteng Sun
    http://arxiv.org/abs/1911.07976v1

    • [cs.IT]Hierarchical Distribution Matching: a Versatile Tool for Probabilistic Shaping
    Stella Civelli, Marco Secondini
    http://arxiv.org/abs/1911.08243v1

    • [cs.IT]Joint Unicast and Multi-group Multicast Transmission in Massive MIMO Systems
    Meysam Sadeghi, Emil Björnson, Erik G. Larsson, Chau Yuen, Thomas L. Marzetta
    http://arxiv.org/abs/1911.08165v1

    • [cs.IT]Low Complexity Autoencoder based End-to-End Learning of Coded Communications Systems
    Nuwanthika Rajapaksha, Nandana Rajatheva, Matti Latva-aho
    http://arxiv.org/abs/1911.08009v1

    • [cs.IT]Low-Complexity Linear Equalization for OTFS Systems with Rectangular Waveforms
    Wenjun Xu, Tingting Zou, Hui Gao, Zhisong Bie, Zhiyong Feng, Zhiguo Ding
    http://arxiv.org/abs/1911.08133v1

    • [cs.IT]New entanglement-assisted quantum MDS codes with length $n=\frac{q^2+1}5$
    Shixin Zhu, Wan Jiang, Xiaojing Chen
    http://arxiv.org/abs/1911.08416v1

    • [cs.IT]On the Upper Bound of the Kullback-Leibler Divergence and Cross Entropy
    Min Chen, Mateu Sbert
    http://arxiv.org/abs/1911.08334v1

    • [cs.IT]Optimal repairing schemes for Reed-Solomon codes with alphabet sizes linear in lengths under the rack-aware model
    Lingfei Jin, Gaojun Luo, Chaoping Xing
    http://arxiv.org/abs/1911.08016v1

    • [cs.IT]Placement Optimization of Aerial Base Stations with Deep Reinforcement Learning
    Jin Qiu, Jiangbin Lyu, Liqun Fu
    http://arxiv.org/abs/1911.08111v1

    • [cs.IT]Super-Nyquist Rateless Coding for Intersymbol Interference Channels
    Uri Erez, Gregory W. Wornell
    http://arxiv.org/abs/1911.08034v1

    • [cs.IT]Towards A Theory of Duality for Graph Signal Processing
    B Subbareddy, S Sai Ashish, Aditya Siripuram
    http://arxiv.org/abs/1911.08135v1

    • [cs.IT]Two-Way Physical Layer Security Protocol for Gaussian Channels
    Masahito Hayashi, Angeles Vazquez-Castro
    http://arxiv.org/abs/1911.08150v1

    • [cs.LG]A Bias Trick for Centered Robust Principal Component Analysis
    Baokun He, Guihong Wan, Haim Schweitzer
    http://arxiv.org/abs/1911.08024v1

    • [cs.LG]A Multi-Task Gradient Descent Method for Multi-Label Learning
    Lu Bai, Yew-Soon Ong, Tiantian He, Abhishek Gupta
    http://arxiv.org/abs/1911.07693v2

    • [cs.LG]A Study on various state of the art of the Art Face Recognition System using Deep Learning Techniques
    Sukhada Chokkadi, Sannidhan M S, Sudeepa K B, Abhir Bhandary
    http://arxiv.org/abs/1911.08426v1

    • [cs.LG]A model for predicting price polarity of real estate properties using information of real estate market websites
    Vladimir Vargas-Calderón, Jorge E. Camargo
    http://arxiv.org/abs/1911.08382v1

    • [cs.LG]ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
    Ekagra Ranjan, Soumya Sanyal, Partha Pratim Talukdar
    http://arxiv.org/abs/1911.07979v1

    • [cs.LG]Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning
    Yingru Liu, Xuewen Yang, Dongliang Xie, Xin Wang, Li Shen, Haozhi Huang, Niranjan Balasubramanian
    http://arxiv.org/abs/1911.08065v1

    • [cs.LG]Adaptive Routing Between Capsules
    Qiang Ren, Shaohua Shang, Lianghua He
    http://arxiv.org/abs/1911.08119v1

    • [cs.LG]Adversarial Attacks on Grid Events Classification: An Adversarial Machine Learning Approach
    Iman Niazazari, Hanif Livani
    http://arxiv.org/abs/1911.08011v1

    • [cs.LG]Attribute noise robust binary classification
    Aditya Petety, Sandhya Tripathi, N Hemachandra
    http://arxiv.org/abs/1911.07875v1

    • [cs.LG]Basic Principles of Clustering Methods
    Alexander Jung, Ivan Baranov
    http://arxiv.org/abs/1911.07891v1

    • [cs.LG]Benanza: Automatic $μ$Benchmark Generation to Compute “Lower-bound” Latency and Inform Optimizations of Deep Learning Models on GPUs
    Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-mei Hwu
    http://arxiv.org/abs/1911.06922v2

    • [cs.LG]Can You Really Backdoor Federated Learning?
    Ziteng Sun, Peter Kairouz, Ananda Theertha Suresh, H. Brendan McMahan
    http://arxiv.org/abs/1911.07963v1

    • [cs.LG]Carpe Diem, Seize the Samples Uncertain “At the Moment” for Adaptive Batch Selection
    Hwanjun Song, Minseok Kim, Sundong Kim, Jae-Gil Lee
    http://arxiv.org/abs/1911.08050v1

    • [cs.LG]Comments on the Du-Kakade-Wang-Yang Lower Bounds
    Benjamin Van Roy, Shi Dong
    http://arxiv.org/abs/1911.07910v1

    • [cs.LG]DARB: A Density-Aware Regular-Block Pruning for Deep Neural Networks
    Ao Ren, Tao Zhang, Yuhao Wang, Sheng Lin, Peiyan Dong, Yen-kuang Chen, Yuan Xie, Yanzhi Wang
    http://arxiv.org/abs/1911.08020v1

    • [cs.LG]DLBricks: Composable Benchmark Generation toReduce Deep Learning Benchmarking Effort on CPUs
    Cheng Li, Abdul Dakkak, Jinjun Xiong, Wen-mei Hwu
    http://arxiv.org/abs/1911.07967v1

    • [cs.LG]Deep Detector Health Management under Adversarial Campaigns
    Javier Echauz, Keith Kenemer, Sarfaraz Hussein, Jay Dhaliwal, Saurabh Shintre, Slawomir Grzonkowski, Andrew Gardner
    http://arxiv.org/abs/1911.08090v1

    • [cs.LG]Deep Tile Coder: an Efficient Sparse Representation Learning Approach with applications in Reinforcement Learning
    Yangchen Pan
    http://arxiv.org/abs/1911.08068v1

    • [cs.LG]Driver Identification Based on Vehicle Telematics Data using LSTM-Recurrent Neural Network
    Abenezer Girma, Xuyang Yan, Abdollah Homaifar
    http://arxiv.org/abs/1911.08030v1

    • [cs.LG]Eigenvalue Normalized Recurrent Neural Networks for Short Term Memory
    Kyle Helfrich, Qiang Ye
    http://arxiv.org/abs/1911.07964v1

    • [cs.LG]Eliminating artefacts in Polarimetric Images using Deep Learning
    Dhruv Paranjpye, Ashish Mahabal, A. N. Ramaprakash, Gina Panopoulou, Kieran Cleary, Anthony Readhead, Dmitry Blinov, Kostas Tassis
    http://arxiv.org/abs/1911.08327v1

    • [cs.LG]Energy Usage Reports: Environmental awareness as part of algorithmic accountability
    Kadan Lottick, Silvia Susai, Sorelle A. Friedler, Jonathan P. Wilson
    http://arxiv.org/abs/1911.08354v1

    • [cs.LG]Fair Learning-to-Rank from Implicit Feedback
    Himank Yadav, Zhengxiao Du, Thorsten Joachims
    http://arxiv.org/abs/1911.08054v1

    • [cs.LG]Implicit Generative Modeling for Efficient Exploration
    Neale Ratzlaff, Qinxun Bai, Li Fuxin, Wei Xu
    http://arxiv.org/abs/1911.08017v1

    • [cs.LG]Implicit Regularization of Normalization Methods
    Xiaoxia Wu, Edgar Dobriban, Tongzheng Ren, Shanshan Wu, Zhiyuan Li, Suriya Gunasekar, Rachel Ward, Qiang Liu
    http://arxiv.org/abs/1911.07956v1

    • [cs.LG]Information-Theoretic Local Minima Characterization and Regularization
    Zhiwei Jia, Hao Su
    http://arxiv.org/abs/1911.08192v1

    • [cs.LG]Inter-layer Collision Networks
    Junyi An, Fengshan Liu, Furao Shen, Jian Zhao
    http://arxiv.org/abs/1911.08252v1

    • [cs.LG]Knowledge Graph Entity Alignment with Graph Convolutional Networks: Lessons Learned
    Max Berrendorf, Evgeniy Faerman, Valentyn Melnychuk, Volker Tresp, Thomas Seidl
    http://arxiv.org/abs/1911.08342v1

    • [cs.LG]Learning Permutation Invariant Representations using Memory Networks
    Shivam Kalra, Mohammed Adnan, Graham Taylor, Hamid Tizhoosh
    http://arxiv.org/abs/1911.07984v1

    • [cs.LG]Live Face De-Identification in Video
    Oran Gafni, Lior Wolf, Yaniv Taigman
    http://arxiv.org/abs/1911.08348v1

    • [cs.LG]MANGA: Method Agnostic Neural-policy Generalization and Adaptation
    Homanga Bharadhwaj, Shoichiro Yamaguchi, Shin-ichi Maeda
    http://arxiv.org/abs/1911.08444v1

    • [cs.LG]Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
    Julian Schrittwieser, Ioannis Antonoglou, Thomas Hubert, Karen Simonyan, Laurent Sifre, Simon Schmitt, Arthur Guez, Edward Lockhart, Demis Hassabis, Thore Graepel, Timothy Lillicrap, David Silver
    http://arxiv.org/abs/1911.08265v1

    • [cs.LG]Mixed-curvature Variational Autoencoders
    Ondrej Skopek, Octavian-Eugen Ganea, Gary Bécigneul
    http://arxiv.org/abs/1911.08411v1

    • [cs.LG]Modelling pressure-Hessian from local velocity gradients information in an incompressible turbulent flow field using deep neural networks
    Nishant Parashar, Sawan S. Sinha, Balaji Srinivasan
    http://arxiv.org/abs/1911.08056v1

    • [cs.LG]Neural Forest Learning
    Yun-Hao Cao, Jianxin Wu
    http://arxiv.org/abs/1911.07845v1

    • [cs.LG]Online Learned Continual Compression with Stacked Quantization Module
    Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau
    http://arxiv.org/abs/1911.08019v1

    • [cs.LG]PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems
    Azin Ghazimatin, Oana Balalau, Rishiraj Saha Roy, Gerhard Weikum
    http://arxiv.org/abs/1911.08378v1

    • [cs.LG]Planning with Goal-Conditioned Policies
    Soroush Nasiriany, Vitchyr H. Pong, Steven Lin, Sergey Levine
    http://arxiv.org/abs/1911.08453v1

    • [cs.LG]Predicting overweight and obesity in later life from childhood data: A review of predictive modeling approaches
    Ilkka Rautiainen, Sami Äyrämö
    http://arxiv.org/abs/1911.08361v1

    • [cs.LG]Prestopping: How Does Early Stopping Help Generalization against Label Noise?
    Hwanjun Song, Minseok Kim, Dongmin Park, Jae-Gil Lee
    http://arxiv.org/abs/1911.08059v1

    • [cs.LG]Privacy Leakage Avoidance with Switching Ensembles
    Rauf Izmailov, Peter Lin, Chris Mesterharm, Samyadeep Basu
    http://arxiv.org/abs/1911.07921v1

    • [cs.LG]Program synthesis performance constrained by non-linear spatial relations in Synthetic Visual Reasoning Test
    Lu Yihe, Scott C. Lowe, Penelope A. Lewis, Mark C. W. van Rossum
    http://arxiv.org/abs/1911.07721v2

    • [cs.LG]RWNE: A Scalable Random-Walk based Network Embedding Framework with Personalized Higher-order Proximity Preserved
    Yu He, Jianxin Li, Yangqiu Song, Xinmiao Zhang, Fanzhang Peng, Hao Peng
    http://arxiv.org/abs/1911.07874v1

    • [cs.LG]Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic
    Zhen Xiang, David J. Miller, George Kesidis
    http://arxiv.org/abs/1911.07970v1

    • [cs.LG]Sequential Mode Estimation with Oracle Queries
    Dhruti Shah, Tuhinangshu Choudhury, Nikhil Karamchandani, Aditya Gopalan
    http://arxiv.org/abs/1911.08197v1

    • [cs.LG]Survival and Neural Models for Private Equity Exit Prediction
    Giuseppe C. Calafiore, Marisa H. Morales, Vittorio Tiozzo, Giulia Fracastoro, Serge Marquie
    http://arxiv.org/abs/1911.08201v1

    • [cs.LG]Temporal Knowledge Graph Embedding Model based on Additive Time Series Decomposition
    Chengjin Xu, Mojtaba Nayyeri, Fouad Alkhoury, Jens Lehmann, Hamed Shariat Yazdi
    http://arxiv.org/abs/1911.07893v1

    • [cs.LG]Thick-Net: Parallel Network Structure for Sequential Modeling
    Yu-Xuan Li, Jin-Yuan Liu, Liang Li, Xiang Guan
    http://arxiv.org/abs/1911.08074v1

    • [cs.LG]Towards non-toxic landscapes: Automatic toxic comment detection using DNN
    Ashwin Geet D’Sa, Irina Illina, Dominique Fohr
    http://arxiv.org/abs/1911.08395v1

    • [cs.LG]Towards unstructured mortality prediction with free-text clinical notes
    Mohammad Hashir, Rapinder Sawhney
    http://arxiv.org/abs/1911.08437v1

    • [cs.LG]Unsupervised Domain Adaptation via Structured Prediction Based Selective Pseudo-Labeling
    Qian Wang, Toby P. Breckon
    http://arxiv.org/abs/1911.07982v1

    • [cs.LG]Variance Reduced Advantage Estimation with $δ$ Hindsight Credit Assignment
    Kenny Young
    http://arxiv.org/abs/1911.08362v1

    • [cs.LG]WITCHcraft: Efficient PGD attacks with random step size
    Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi
    http://arxiv.org/abs/1911.07989v1

    • [cs.LG]vqSGD: Vector Quantized Stochastic Gradient Descent
    Venkata Gandikota, Raj Kumar Maity, Arya Mazumdar
    http://arxiv.org/abs/1911.07971v1

    • [cs.MA]Cooperative Pathfinding based on high-scalability Multi-agent RRT*
    Jinmingwu Jiang, Kaigui Wu
    http://arxiv.org/abs/1911.07840v1

    • [cs.NE]Deep Spiking Neural Networks for Large Vocabulary Automatic Speech Recognition
    Jibin Wu, Emre Yilmaz, Malu Zhang, Haizhou Li, Kay Chen Tan
    http://arxiv.org/abs/1911.08373v1

    • [cs.NE]ImmuNeCS: Neural Committee Search by an Artificial Immune System
    Luc Frachon, Wei Pang, George M. Coghill
    http://arxiv.org/abs/1911.07729v2

    • [cs.NE]Unsupervised AER Object Recognition Based on Multiscale Spatio-Temporal Features and Spiking Neurons
    Qianhui Liu, Gang Pan, Haibo Ruan, Dong Xing, Qi Xu, Huajin Tang
    http://arxiv.org/abs/1911.08261v1

    • [cs.NI]Delay-Aware Wireless Network Coding in Adversarial Traffic
    Yu-Pin Hsu
    http://arxiv.org/abs/1911.08078v1

    • [cs.NI]The geopolitics behind the routes data travels: a case study of Iran
    Loqman Salamatian, Frederick Douzet, Kevin Limonier, Kavé Salamatian
    http://arxiv.org/abs/1911.07723v2

    • [cs.RO]A Deep Learning Approach for Robust Corridor Following
    Vishnu Sashank Dorbala, A. H. Abdul Hafez, C. V. Jawahar
    http://arxiv.org/abs/1911.07896v1

    • [cs.RO]Long-Term Personalization of an In-Home Socially Assistive Robot for Children With Autism Spectrum Disorders
    Caitlyn Clabaugh, Kartik Mahajan, Shomik Jain, Roxanna Pakkar, David Becerra, Zhonghao Shi, Eric Deng, Rhianna Lee, Gisele Ragusa, Maja Matarić
    http://arxiv.org/abs/1911.07992v1

    • [cs.RO]Nonlinear Model Predictive Control with Actuator Constraints for Multi-Rotor Aerial Vehicles
    Davide Bicego, Jacopo Mazzetto, Ruggero Carli, Marcello Farina, Antonio Franchi
    http://arxiv.org/abs/1911.08183v1

    • [cs.RO]Robot Calligraphy using Pseudospectral Optimal Control in Conjunction with a Simulated Brush Model
    Sen Wang, Jiaqi Chen, Xuanliang Deng, Seth Hutchinson, Frank Dellaert
    http://arxiv.org/abs/1911.08002v1

    • [cs.RO]Task-Based Hybrid Shared Control for Training Through Forceful Interaction
    Kathleen Fitzsimons, Aleksandra Kalinowska, Julius P. A. Dewald, Todd Murphey
    http://arxiv.org/abs/1911.07983v1

    • [cs.RO]User-Driven Functional Movement Training with a Wearable Hand Robot after Stroke
    Sangwoo Park, Michaela Fraser, Lynne M. Weber, Cassie Meeker, Lauri Bishop, Daniel Geller, Joel Stein, Matei Ciocarlie
    http://arxiv.org/abs/1911.08003v1

    • [cs.SD]Alternating Between Spectral and Spatial Estimation for Speech Separation and Enhancement
    Zhong-Qiu Wang, Scott Wisdom, Kevin Wilson, John R. Hershey
    http://arxiv.org/abs/1911.07953v1

    • [cs.SD]Improving Universal Sound Separation Using Sound Classification
    Efthymios Tzinis, Scott Wisdom, John R. Hershey, Aren Jansen, Daniel P. W. Ellis
    http://arxiv.org/abs/1911.07951v1

    • [cs.SE]Commit2Vec: Learning Distributed Representations of Code Changes
    Rocìo Cabrera Lozoya, Arnaud Baumann, Antonino Sabetta, Michele Bezzi
    http://arxiv.org/abs/1911.07605v2

    • [cs.SI]Adaptive Greedy versus Non-adaptive Greedy for Influence Maximization
    Wei Chen, Binghui Peng, Grant Schoenebeck, Biaoshuai Tao
    http://arxiv.org/abs/1911.08164v1

    • [cs.SI]Event detection in Colombian security Twitter news using fine-grained latent topic analysis
    Vladimir Vargas-Calderón, Nicolás Parra-A., Jorge E. Camargo, Herbert Vinck-Posada
    http://arxiv.org/abs/1911.08370v1

    • [cs.SI]Graph Learning for Spatiotemporal Signal with Long Short-Term Characterization
    Yueliang Liu, Wenbin Guo, Kangyong You, Lei Zhao, Tao Peng, Wenbo Wang
    http://arxiv.org/abs/1911.08018v1

    • [eess.AS]Neural Network based End-to-End Query by Example Spoken Term Detection
    Dhananjay Ram, Lesly Miculicich, Hervé Bourlard
    http://arxiv.org/abs/1911.08332v1

    • [eess.IV]Automated fetal brain extraction from clinical Ultrasound volumes using 3D Convolutional Neural Networks
    Felipe Moser, Ruobing Huang, Aris T. Papageorghiou, Bartlomiej W. Papiez, Ana I. L. Namburete
    http://arxiv.org/abs/1911.07566v2

    • [eess.IV]CD2 : Combined Distances of Contrast Distributions for the Assessment of Perceptual Quality of Image Processing
    Sascha Xu, Jan Bauer, Benjamin Axmann
    http://arxiv.org/abs/1911.07995v1

    • [eess.IV]Convolutional Neural Network and decision support in medical imaging: case study of the recognition of blood cell subtypes
    Daouda Diouf, Djibril Seck, Mountaga Diop, Abdoulye Ba
    http://arxiv.org/abs/1911.08010v1

    • [eess.IV]Frequency Separation for Real-World Super-Resolution
    Manuel Fritsche, Shuhang Gu, Radu Timofte
    http://arxiv.org/abs/1911.07850v1

    • [eess.IV]HighEr-Resolution Network for Image Demosaicing and Enhancing
    Kangfu Mei, Juncheng Li, Jiajie Zhang, Haoyu Wu, Jie Li, Rui Huang
    http://arxiv.org/abs/1911.08098v1

    • [eess.IV]ISP4ML: Understanding the Role of Image Signal Processing in Efficient Deep Learning Vision Systems
    Patrick Hansen, Alexey Vilkin, Yury Khrustalev, David Hanwell, Matthew Mattina, Paul N. Whatmough
    http://arxiv.org/abs/1911.07954v1

    • [eess.IV]LNDb: A Lung Nodule Database on Computed Tomography
    João Pedrosa, Guilherme Aresta, Carlos Ferreira, Márcio Rodrigues, Patrícia Leitão, André Silva Carvalho, João Rebelo, Eduardo Negrão, Isabel Ramos, António Cunha, Aurélio Campilho
    http://arxiv.org/abs/1911.08434v1

    • [eess.IV]Multi-Resolution 3D CNN for MRI Brain Tumor Segmentation and Survival Prediction
    Mehdi Amian, Mohammadreza Soltaninejad
    http://arxiv.org/abs/1911.08388v1

    • [eess.IV]Projection-to-Projection Translation for Hybrid X-ray and Magnetic Resonance Imaging
    Bernhard Stimpel, Christopher Syben, Tobias Würfl, Katharina Breininger, Philipp Hoelter, Arnd Dörfler, Andreas Maier
    http://arxiv.org/abs/1911.08163v1

    • [eess.IV]Three-dimensional Generative Adversarial Nets for Unsupervised Metal Artifact Reduction
    Megumi Nakao, Keiho Imanishi, Nobuhiro Ueda, Yuichiro Imai, Tadaaki Kirita, Tetsuya Matsuda
    http://arxiv.org/abs/1911.08105v1

    • [eess.IV]Visualization approach to assess the robustness of neural networks for medical image classification
    Elina Thibeau Sutre, Olivier Colliot, Didier Dormont, Ninon Burgos
    http://arxiv.org/abs/1911.08264v1

    • [eess.SP]AddNet: Deep Neural Networks Using FPGA-Optimized Multipliers
    Julian Faraone, Martin Kumm, Martin Hardieck, Peter Zipf, Xueyuan Liu, David Boland, Philip H. W. Leong
    http://arxiv.org/abs/1911.08097v1

    • [eess.SP]Comparison of Deep learning models on time series forecasting : a case study of Dissolved Oxygen Prediction
    Hongqian Qin
    http://arxiv.org/abs/1911.08414v1

    • [eess.SP]iGateLink: A Gateway Library for Linking IoT, Edge, Fog and Cloud Computing Environments
    Riccardo Mancini, Shreshth Tuli, Tommaso Cucinotta, Rajkumar Buyya
    http://arxiv.org/abs/1911.08413v1

    • [math.DS]A topological dynamical system with two different positive sofic entropies
    Dylan Airey, Lewis Bowen, Frank Lin
    http://arxiv.org/abs/1911.08272v1

    • [math.PR]On critical points of Gaussian random fields under diffeomorphic transformations
    Dan Cheng, Armin Schwartzman
    http://arxiv.org/abs/1911.08100v1

    • [math.ST]Discussion contribution “Functional models for time-varying random objects’’ by Dubey and Müller (to appear in JRSS-B)
    Wicher Bergsma
    http://arxiv.org/abs/1911.08468v1

    • [math.ST]Estimation of dynamic networks for high-dimensional nonstationary time series
    Mengyu Xu, Xiaohui Chen, Weibiao Wu
    http://arxiv.org/abs/1911.06385v2

    • [math.ST]Improved clustering algorithms for the Bipartite Stochastic Block Model
    Mohamed Ndaoud, Suzanne Sigalla, Alexandre B. Tsybakov
    http://arxiv.org/abs/1911.07987v1

    • [math.ST]Infinitesimal generators for two-dimensional Lévy process-driven hypothesis testing
    Michael Roberts, Indranil SenGupta
    http://arxiv.org/abs/1911.08412v1

    • [math.ST]Minimax rates of $\ell_p$-losses for high-dimensional linear regression models with additive measurement errors over $\ell_q$-balls
    Xin Li, Dongya Wu
    http://arxiv.org/abs/1911.08063v1

    • [math.ST]Sparse recovery via nonconvex regularized $M$-estimators over $\ell_q$-balls
    Xin Li, Dongya Wu, Chong Li, Jinhua Wang, Jen-Chih Yao
    http://arxiv.org/abs/1911.08061v1

    • [q-bio.QM]Estimation of Orientation and Camera Parameters from Cryo-Electron Microscopy Images with Variational Autoencoders and Generative Adversarial Networks
    Nina Miolane, Frédéric Poitevin, Yee-Ting Li, Susan Holmes
    http://arxiv.org/abs/1911.08121v1

    • [stat.AP]A regularized hidden Markov model for analyzing the ‘hot shoe’ in football
    Marius Ötting, Andreas Groll
    http://arxiv.org/abs/1911.08138v1

    • [stat.AP]Anomaly and Novelty detection for robust semi-supervised learning
    Andrea Cappozzo, Francesca Greselin, Thomas Brendan Murphy
    http://arxiv.org/abs/1911.08381v1

    • [stat.AP]Common Growth Patterns for Regional Social Networks: a Point Process Approach
    Tiandong Wang, Sidney I. Resnick
    http://arxiv.org/abs/1911.07902v1

    • [stat.AP]Large-Scale Spatiotemporal Density Smoothing with the Graph-fused Elastic Net: Application to Ride-sourcing Driver Productivity Analysis
    Mauricio Tec, Natalia Zuniga-Garcia, Randy B. Machemehl, James G. Scott
    http://arxiv.org/abs/1911.08106v1

    • [stat.AP]Principal Stratification for Advertising Experiments
    Ron Berman, Elea McDonnell Feit
    http://arxiv.org/abs/1911.08438v1

    • [stat.ME]A Normal Approximation Method for Statistics in Knockouts
    Yutong Nie, Chenhe Zhang
    http://arxiv.org/abs/1911.08103v1

    • [stat.ME]Gradient-based Sparse Principal Component Analysis with Extensions to Online Learning
    Yixuan Qiu, Jing Lei, Kathryn Roeder
    http://arxiv.org/abs/1911.08048v1

    • [stat.ME]Measuring spatiotemporal disease clustering with the tau statistic
    Timothy M. Pollington, Michael J. Tildesley, T. Déirdre Hollingsworth, Lloyd A. C. Chapman
    http://arxiv.org/abs/1911.08022v1

    • [stat.ME]Optimal tests for elliptical symmetry: specified and unspecified location
    Sladana Babic, Laetitia Gelbgras, Marc Hallin, Christophe Ley
    http://arxiv.org/abs/1911.08171v1

    • [stat.ME]Uncertainty and Sensitivity Analyses Methods for Agent-Based Mathematical Models: An Introductory Review
    Sara Hamis, Stanislav Stratiev, Gibin G Powathil
    http://arxiv.org/abs/1911.08429v1

    • [stat.ML]A Simple Heuristic for Bayesian Optimization with A Low Budget
    Masahiro Nomura, Kenshi Abe
    http://arxiv.org/abs/1911.07790v2

    • [stat.ML]Deep Unsupervised Clustering with Clustered Generator Model
    Dandan Zhu, Tian Han, Linqi Zhou, Xiaokang Yang, Ying Nian Wu
    http://arxiv.org/abs/1911.08459v1

    • [stat.ML]Learning Weighted Submanifolds with Variational Autoencoders and Riemannian Variational Autoencoders
    Nina Miolane, Susan Holmes
    http://arxiv.org/abs/1911.08147v1

    • [stat.ML]SimVAE: Simulator-Assisted Training forInterpretable Generative Models
    Akash Srivastava, Jessie Rosenberg, Dan Gutfreund, David D. Cox
    http://arxiv.org/abs/1911.08051v1