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.HC - 人机接口 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.NI - 网络和互联网体系结构 cs.PL - 编程语言 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 cs.SY - 系统与控制 econ.EM - 计量经济学 eess.AS - 语音处理 eess.SP - 信号处理 math.RA - 环与代数 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-bio.BM - 生物分子 q-bio.MN - 分子网络 q-bio.QM - 定量方法 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]A Short Survey On Memory Based Reinforcement Learning
    • [cs.AI]Improving interactive reinforcement learning: What makes a good teacher?
    • [cs.AI]Predicting human decisions with behavioral theories and machine learning
    • [cs.CL]Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translation
    • [cs.CL]Data Augmentation for BERT Fine-Tuning in Open-Domain Question Answering
    • [cs.CL]Distributed representation of multi-sense words: A loss-driven approach
    • [cs.CL]End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learning
    • [cs.CL]From News to Medical: Cross-domain Discourse Segmentation
    • [cs.CL]Improving Distantly-supervised Entity Typing with Compact Latent Space Clustering
    • [cs.CL]Improving Human Text Comprehension through Semi-Markov CRF-based Neural Section Title Generation
    • [cs.CL]No Adjective Ordering Mystery, and No Raven Paradox, Just an Ontological Mishap
    • [cs.CL]Pun Generation with Surprise
    • [cs.CL]Rare Words: A Major Problem for Contextualized Embeddings And How to Fix it by Attentive Mimicking
    • [cs.CL]Semantic query-by-example speech search using visual grounding
    • [cs.CL]Text segmentation on multilabel documents: A distant-supervised approach
    • [cs.CR]Differential Privacy for Eye-Tracking Data
    • [cs.CR]IoD-Crypt: A Lightweight Cryptographic Framework for Internet of Drones
    • [cs.CR]KeyForge: Mitigating Email Breaches with Forward-Forgeable Signatures
    • [cs.CR]Secure Consistency Verification for Untrusted Cloud Storage by Public Blockchains
    • [cs.CV]A Hybrid Traffic Speed Forecasting Approach Integrating Wavelet Transform and Motif-based Graph Convolutional Recurrent Neural Network
    • [cs.CV]A deep learning framework for quality assessment and restoration in video endoscopy
    • [cs.CV]Algorithms used for the Cell Segmentation Benchmark Competition at ISBI 2019 by RWTH-GE
    • [cs.CV]Biphasic Learning of GANs for High-Resolution Image-to-Image Translation
    • [cs.CV]Bounce and Learn: Modeling Scene Dynamics with Real-World Bounces
    • [cs.CV]Conditional Single-view Shape Generation for Multi-view Stereo Reconstruction
    • [cs.CV]ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging
    • [cs.CV]Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization
    • [cs.CV]Deep Comprehensive Correlation Mining for Image Clustering
    • [cs.CV]Detecting Anemia from Retinal Fundus Images
    • [cs.CV]Differentiable Iterative Surface Normal Estimation
    • [cs.CV]Direct Sparse Mapping
    • [cs.CV]Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing
    • [cs.CV]DuBox: No-Prior Box Objection Detection via Residual Dual Scale Detectors
    • [cs.CV]EXPERTNet Exigent Features Preservative Network for Facial Expression Recognition
    • [cs.CV]Explicit Spatial Encoding for Deep Local Descriptors
    • [cs.CV]GA-Net: Guided Aggregation Net for End-to-end Stereo Matching
    • [cs.CV]Geometric Image Correspondence Verification by Dense Pixel Matching
    • [cs.CV]Gyroscope-aided Relative Pose Estimation for Rolling Shutter Cameras
    • [cs.CV]HAKE: Human Activity Knowledge Engine
    • [cs.CV]Implicit Pairs for Boosting Unpaired Image-to-Image Translation
    • [cs.CV]Influence of Control Parameters and the Size of Biomedical Image Datasets on the Success of Adversarial Attacks
    • [cs.CV]Joint Discriminative and Generative Learning for Person Re-identification
    • [cs.CV]Learning Deformable Kernels for Image and Video Denoising
    • [cs.CV]Learning Discriminative Model Prediction for Tracking
    • [cs.CV]Learning Shape Templates with Structured Implicit Functions
    • [cs.CV]LiveSketch: Query Perturbations for Guided Sketch-based Visual Search
    • [cs.CV]Localizing Discriminative Visual Landmarks for Place Recognition
    • [cs.CV]Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes
    • [cs.CV]Lunar surface image restoration using U-net based deep neural networks
    • [cs.CV]Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation
    • [cs.CV]Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning
    • [cs.CV]PIV-Based 3D Fluid Flow Reconstruction Using Light Field Camera
    • [cs.CV]Patch redundancy in images: a statistical testing framework and some applications
    • [cs.CV]Pedestrian Detection in Thermal Images using Saliency Maps
    • [cs.CV]Processsing Simple Geometric Attributes with Autoencoders
    • [cs.CV]Recovery of Superquadrics from Range Images using Deep Learning: A Preliminary Study
    • [cs.CV]Recurrent Neural Network for (Un-)supervised Learning of Monocular VideoVisual Odometry and Depth
    • [cs.CV]Rethinking Classification and Localization in R-CNN
    • [cs.CV]Robust Visual Tracking Revisited: From Correlation Filter to Template Matching
    • [cs.CV]SIMCO: SIMilarity-based object COunting
    • [cs.CV]SR-GAN: Semantic Rectifying Generative Adversarial Network for Zero-shot Learning
    • [cs.CV]Saliency Prediction on Omnidirectional Images with Generative Adversarial Imitation Learning
    • [cs.CV]See the World through Network Cameras
    • [cs.CV]Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data
    • [cs.CV]Self-critical n-step Training for Image Captioning
    • [cs.CV]Semi-supervised Domain Adaptation via Minimax Entropy
    • [cs.CV]Shakeout: A New Approach to Regularized Deep Neural Network Training
    • [cs.CV]Synthesising 3D Facial Motion from “In-the-Wild” Speech
    • [cs.CV]Texture image analysis and texture classification methods - A review
    • [cs.CV]Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation
    • [cs.CV]Transformable Bottleneck Networks
    • [cs.CV]Universal Bounding Box Regression and Its Applications
    • [cs.CV]Unsupervised Synthesis of Anomalies in Videos: Transforming the Normal
    • [cs.CV]VORNet: Spatio-temporally Consistent Video Inpainting for Object Removal
    • [cs.CV]Visual-Inertial Mapping with Non-Linear Factor Recovery
    • [cs.CV]dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs
    • [cs.CY]Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms
    • [cs.CY]Challenges in Integrating Technology into Education
    • [cs.CY]Joint Seat Allocation 2018: An algorithmic perspective
    • [cs.DC]Cryptocurrency with Fully Asynchronous Communication based on Banks and Democracy
    • [cs.DC]Distributed Matrix Multiplication Using Speed Adaptive Coding
    • [cs.DC]Evaluation of the RIKEN Post-K Processor Simulator
    • [cs.DC]Management of mobile resources in Physical Internet logistic models
    • [cs.DC]Repeat-Authenticate Scheme for Multicasting of Blockchain Information in IoT Systems
    • [cs.DC]Single Machine Graph Analytics on Massive Datasets Using Intel Optane DC Persistent Memory
    • [cs.DC]White-Box Atomic Multicast (Extended Version)
    • [cs.HC]Learning to Engage with Interactive Systems: A field Study
    • [cs.IR]An Axiomatic Approach to Regularizing Neural Ranking Models
    • [cs.IR]BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
    • [cs.IR]Contextualized Word Representations for Document Re-Ranking
    • [cs.IR]Measuring the influence of mere exposure effect of TV commercial adverts on purchase behavior based on machine learning prediction models
    • [cs.IR]Personalized Context-aware Re-ranking for E-commerce Recommender Systems
    • [cs.IR]RelEmb: A relevance-based application embedding for Mobile App retrieval and categorization
    • [cs.IR]Topic Grouper: An Agglomerative Clustering Approach to Topic Modeling
    • [cs.IT]Asymptotic Outage Analysis of Spatially Correlated Rayleigh MIMO Channels
    • [cs.IT]Codes over an algebra over ring
    • [cs.IT]Coverage Analysis of 3-D Dense Cellular Networks with Realistic Propagation Conditions
    • [cs.IT]Deep CNN based Channel Estimation for mmWave Massive MIMO Systems
    • [cs.IT]Efficient Search and Elimination of Harmful Objects in Optimized QC SC-LDPC Codes
    • [cs.IT]Energy Efficient Node Deployment in Wireless Ad-hoc Sensor Networks
    • [cs.IT]Introducing Enumerative Sphere Shaping for Optical Communication Systems with Short Blocklengths
    • [cs.IT]Iterative Decoding of Trellis-Constrained Codes inspired by Amplitude Amplification (Preliminary Version)
    • [cs.IT]Large Intelligent Surface-Based Index Modulation: A New Beyond MIMO Paradigm for 6G
    • [cs.IT]Mutual Information-Maximizing Quantized Belief Propagation Decoding of LDPC Codes
    • [cs.IT]Permutation codes over finite fields
    • [cs.IT]Power Allocation for Type-I ARQ Two-Hop Cooperative Networks for Ultra-Reliable Communication
    • [cs.IT]Spatially Coupled LDPC Codes with Non-uniform Coupling for Improved Decoding Speed
    • [cs.LG]A Discussion on Solving Partial Differential Equations using Neural Networks
    • [cs.LG]A Fast Dictionary Learning Method for Coupled Feature Space Learning
    • [cs.LG]A joint autoencoder for prediction and its application in GPS trajectory data
    • [cs.LG]An Empirical Investigation of Global and Local Normalization for Recurrent Neural Sequence Models Using a Continuous Relaxation to Beam Search
    • [cs.LG]Are Nearby Neighbors Relatives?: Diagnosing Deep Music Embedding Spaces
    • [cs.LG]Depth Separations in Neural Networks: What is Actually Being Separated?
    • [cs.LG]Disentangling Options with Hellinger Distance Regularizer
    • [cs.LG]Dot-to-Dot: Achieving Structured Robotic Manipulation through Hierarchical Reinforcement Learning
    • [cs.LG]Exact Rate-Distortion in Autoencoders via Echo Noise
    • [cs.LG]Exploiting Event Log Data-Attributes in RNN Based Prediction
    • [cs.LG]Exploring Representativeness and Informativeness for Active Learning
    • [cs.LG]Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
    • [cs.LG]Finding a latent k-simplex in O(k . nnz(data)) time via Subset Smoothing
    • [cs.LG]Graph-Based Method for Anomaly Detection in Functional Brain Network using Variational Autoencoder
    • [cs.LG]Graph-Embedded Multi-layer Kernel Extreme Learning Machine for One-class Classification or (Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification)
    • [cs.LG]GraphTSNE: A Visualization Technique for Graph-Structured Data
    • [cs.LG]Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice
    • [cs.LG]Information Theoretic Lower Bounds on Negative Log Likelihood
    • [cs.LG]LeanResNet: A Low-cost yet Effective Convolutional Residual Networks
    • [cs.LG]Learning Spatiotemporal Features of Ride-sourcing Services with Fusion Convolutional Network
    • [cs.LG]On the Performance of Differential Evolution for Hyperparameter Tuning
    • [cs.LG]Painting on Placement: Forecasting Routing Congestion using Conditional Generative Adversarial Nets
    • [cs.LG]Probabilistic Kernel Support Vector Machines
    • [cs.LG]Remaining Useful Life Estimation Using Functional Data Analysis
    • [cs.LG]Robust and Discriminative Labeling for Multi-label Active Learning Based on Maximum Correntropy Criterion
    • [cs.LG]Self-Paced Probabilistic Principal Component Analysis for Data with Outliers
    • [cs.LG]Should I Raise The Red Flag? A comprehensive survey of anomaly scoring methods toward mitigating false alarms
    • [cs.LG]Temporal Network Representation Learning
    • [cs.LG]The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent
    • [cs.LG]Tutorial: Safe and Reliable Machine Learning
    • [cs.LG]UR-FUNNY: A Multimodal Language Dataset for Understanding Humor
    • [cs.LG]Unsupervised Singing Voice Conversion
    • [cs.NE]A Hybrid Evolutionary Algorithm Framework for Optimising Power Take Off and Placements of Wave Energy Converters
    • [cs.NE]Efficient Feature Selection of Power Quality Events using Two Dimensional (2D) Particle Swarms
    • [cs.NE]Synthetic Neural Vision System Design for Motion Pattern Recognition in Dynamic Robot Scenes
    • [cs.NE]The Efficiency Threshold for the Offspring Population Size of the ($μ$, $λ$) EA
    • [cs.NI]A Personalized Preference Learning Framework for Caching in Mobile Networks
    • [cs.NI]How to Price Fresh Data
    • [cs.NI]When Tesla Meets Nash: Wireless Power Provision as a Public Good
    • [cs.PL]From Theory to Systems: A Grounded Approach to Programming Language Education
    • [cs.PL]Got: Git, but for Objects
    • [cs.PL]Specifying Concurrent Programs in Separation Logic: Morphisms and Simulations
    • [cs.RO]A Comparison of Policy Search in Joint Space and Cartesian Space for Refinement of Skills
    • [cs.RO]An LGMD Based Competitive Collision Avoidance Strategy for UAV
    • [cs.RO]Combining Physical Simulators and Object-Based Networks for Control
    • [cs.RO]Curious iLQR: Resolving Uncertainty in Model-based RL
    • [cs.RO]Learning Whole-Image Descriptors for Real-time Loop Detection andKidnap Recovery under Large Viewpoint Difference
    • [cs.RO]Learning to Generate Unambiguous Spatial Referring Expressions for Real-World Environments
    • [cs.RO]Learning to Guide: Guidance Law Based on Deep Meta-learning and Model Predictive Path Integral Control
    • [cs.RO]Learning to Navigate in Indoor Environments: from Memorizing to Reasoning
    • [cs.RO]On Model Adaptation for Sensorimotor Control of Robots
    • [cs.RO]Online Sampling in the Parameter Space of a Neural Network for GPU-accelerated Motion Planning of Autonomous Vehicles
    • [cs.RO]Quasi-static Analysis of Planar Sliding Using Friction Patches
    • [cs.RO]Real-time Model-based Image Color Correction for Underwater Robots
    • [cs.RO]Reinforcement Learning with Probabilistic Guarantees for Autonomous Driving
    • [cs.RO]Tightly Coupled 3D Lidar Inertial Odometry and Mapping
    • [cs.SI]Cyberbullying and Traditional Bullying in Greece: An Empirical Study
    • [cs.SI]Percolation Threshold for Competitive Influence in Random Networks
    • [cs.SI]What Makes Social Search Efficient
    • [cs.SY]Minimum Error Entropy Kalman Filter
    • [econ.EM]Estimation of Cross-Sectional Dependence in Large Panels
    • [econ.EM]Subgeometric ergodicity and $β$-mixing
    • [econ.EM]Subgeometrically ergodic autoregressions
    • [eess.AS]Low-Latency Speaker-Independent Continuous Speech Separation
    • [eess.AS]Singing voice synthesis based on convolutional neural networks
    • [eess.SP]Multi-Branch Tensor Network Structure for Tensor-Train Discriminant Analysis
    • [eess.SP]TDMR Detection System with Local Area Influence Probabilistic a Priori Detector
    • [math.RA]Wajsberg algebras arising from binary block codes
    • [math.ST]Asymptotic efficiency of M.L.E. using prior survey in multinomial distributions
    • [math.ST]Bootstrapping Covariance Operators of Functional Time Series
    • [math.ST]Independence Properties of the Truncated Multivariate Elliptical Distributions
    • [math.ST]On the construction of confidence intervals for ratios of expectations
    • [math.ST]Recursive density estimators based on Robbins-Monro’s scheme and using Bernstein polynomials
    • [math.ST]The Landscape of the Planted Clique Problem: Dense subgraphs and the Overlap Gap Property
    • [physics.comp-ph]Deep-learning PDEs with unlabeled data and hardwiring physics laws
    • [physics.soc-ph]The dynamic importance of nodes is poorly predicted by static topological features
    • [q-bio.BM]Detection of protein-ligand binding sites with 3D segmentation
    • [q-bio.MN]Disease gene prioritization using network topological analysis from a sequence based human functional linkage network
    • [q-bio.QM]Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
    • [quant-ph]Tensorization of the strong data processing inequality for quantum chi-square divergences
    • [stat.AP]A framework for streamlined statistical prediction using topic models
    • [stat.AP]Comparison of statistical post-processing methods for probabilistic NWP forecasts of solar radiation
    • [stat.AP]Estimation of group means in generalized linear mixed models
    • [stat.AP]Multiple imputation and selection of ordinal level 2 predictors in multilevel models. An analysis of the relationship between student ratings and teacher beliefs and practices
    • [stat.CO]Applications of Quantum Annealing in Statistics
    • [stat.ME]A Hitchhiker’s Guide to Statistical Comparisons of Reinforcement Learning Algorithms
    • [stat.ME]Analysis of overfitting in the regularized Cox model
    • [stat.ME]Interpretable hypothesis tests
    • [stat.ME]Proportional hazards model with partly interval censoring and its penalized likelihood estimation
    • [stat.ME]Validation of Association
    • [stat.ME]Variational Bayes for high-dimensional linear regression with sparse priors
    • [stat.ML]A Selective Overview of Deep Learning
    • [stat.ML]Copula-like Variational Inference
    • [stat.ML]Improved Precision and Recall Metric for Assessing Generative Models
    • [stat.ML]Maximum Correntropy Criterion with Variable Center

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    • [cs.AI]A Short Survey On Memory Based Reinforcement Learning
    Dhruv Ramani
    http://arxiv.org/abs/1904.06736v1

    • [cs.AI]Improving interactive reinforcement learning: What makes a good teacher?
    Francisco Cruz, Sven Magg, Yukie Nagai, Stefan Wermter
    http://arxiv.org/abs/1904.06879v1

    • [cs.AI]Predicting human decisions with behavioral theories and machine learning
    Ori Plonsky, Reut Apel, Eyal Ert, Moshe Tennenholtz, David Bourgin, Joshua C. Peterson, Daniel Reichman, Thomas L. Griffiths, Stuart J. Russell, Evan C. Carter, James F. Cavanagh, Ido Erev
    http://arxiv.org/abs/1904.06866v1

    • [cs.CL]Attention-Passing Models for Robust and Data-Efficient End-to-End Speech Translation
    Matthias Sperber, Graham Neubig, Jan Niehues, Alex Waibel
    http://arxiv.org/abs/1904.07209v1

    • [cs.CL]Data Augmentation for BERT Fine-Tuning in Open-Domain Question Answering
    Wei Yang, Yuqing Xie, Luchen Tan, Kun Xiong, Ming Li, Jimmy Lin
    http://arxiv.org/abs/1904.06652v1

    • [cs.CL]Distributed representation of multi-sense words: A loss-driven approach
    Saurav Manchanda, George Karypis
    http://arxiv.org/abs/1904.06725v1

    • [cs.CL]End-to-end Text-to-speech for Low-resource Languages by Cross-Lingual Transfer Learning
    Tao Tu, Yuan-Jui Chen, Cheng-chieh Yeh, Hung-yi Lee
    http://arxiv.org/abs/1904.06508v1

    • [cs.CL]From News to Medical: Cross-domain Discourse Segmentation
    Elisa Ferracane, Titan Page, Junyi Jessy Li, Katrin Erk
    http://arxiv.org/abs/1904.06682v1

    • [cs.CL]Improving Distantly-supervised Entity Typing with Compact Latent Space Clustering
    Bo Chen, Xiaotao Gu, Yufeng Hu, Siliang Tang, Guoping Hu, Yueting Zhuang, Xiang Ren
    http://arxiv.org/abs/1904.06475v1

    • [cs.CL]Improving Human Text Comprehension through Semi-Markov CRF-based Neural Section Title Generation
    Sebastian Gehrmann, Steven Layne, Franck Dernoncourt
    http://arxiv.org/abs/1904.07142v1

    • [cs.CL]No Adjective Ordering Mystery, and No Raven Paradox, Just an Ontological Mishap
    Walid S. Saba
    http://arxiv.org/abs/1904.06779v1

    • [cs.CL]Pun Generation with Surprise
    He He, Nanyun Peng, Percy Liang
    http://arxiv.org/abs/1904.06828v1

    • [cs.CL]Rare Words: A Major Problem for Contextualized Embeddings And How to Fix it by Attentive Mimicking
    Timo Schick, Hinrich Schütze
    http://arxiv.org/abs/1904.06707v1

    • [cs.CL]Semantic query-by-example speech search using visual grounding
    Herman Kamper, Aristotelis Anastassiou, Karen Livescu
    http://arxiv.org/abs/1904.07078v1

    • [cs.CL]Text segmentation on multilabel documents: A distant-supervised approach
    Saurav Manchanda, George Karypis
    http://arxiv.org/abs/1904.06730v1

    • [cs.CR]Differential Privacy for Eye-Tracking Data
    Ao Liu, Lirong Xia, Andrew Duchowski, Reynold Bailey, Kenneth Holmqvist, Eakta Jain
    http://arxiv.org/abs/1904.06809v1

    • [cs.CR]IoD-Crypt: A Lightweight Cryptographic Framework for Internet of Drones
    Muslum Ozgur Ozmen, Rouzbeh Behnia, Attila A. Yavuz
    http://arxiv.org/abs/1904.06829v1

    • [cs.CR]KeyForge: Mitigating Email Breaches with Forward-Forgeable Signatures
    Michael Specter, Sunoo Park, Matthew Green
    http://arxiv.org/abs/1904.06425v1

    • [cs.CR]Secure Consistency Verification for Untrusted Cloud Storage by Public Blockchains
    Kai Li, Yuzhe, Tang, Beom Heyn, Kim, Jianliang Xu
    http://arxiv.org/abs/1904.06626v1

    • [cs.CV]A Hybrid Traffic Speed Forecasting Approach Integrating Wavelet Transform and Motif-based Graph Convolutional Recurrent Neural Network
    Na Zhang, Xuefeng Guan, Jun Cao, Xinglei Wang, Huayi Wu
    http://arxiv.org/abs/1904.06656v1

    • [cs.CV]A deep learning framework for quality assessment and restoration in video endoscopy
    Sharib Ali, Felix Zhou, Adam Bailey, Barbara Braden, James East, Xin Lu, Jens Rittscher
    http://arxiv.org/abs/1904.07073v1

    • [cs.CV]Algorithms used for the Cell Segmentation Benchmark Competition at ISBI 2019 by RWTH-GE
    Dennis Eschweiler, Johannes Stegmaier
    http://arxiv.org/abs/1904.06890v1

    • [cs.CV]Biphasic Learning of GANs for High-Resolution Image-to-Image Translation
    Jie Cao, Huaibo Huang, Yi Li, Jingtuo Liu, Ran He, Zhenan Sun
    http://arxiv.org/abs/1904.06624v1

    • [cs.CV]Bounce and Learn: Modeling Scene Dynamics with Real-World Bounces
    Senthil Purushwalkam, Abhinav Gupta, Danny M. Kaufman, Bryan Russell
    http://arxiv.org/abs/1904.06827v1

    • [cs.CV]Conditional Single-view Shape Generation for Multi-view Stereo Reconstruction
    Yi Wei, Shaohui Liu, Wang Zhao, Jiwen Lu, Jie Zhou
    http://arxiv.org/abs/1904.06699v1

    • [cs.CV]ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imaging
    Samarth Brahmbhatt, Cusuh Ham, Charles C. Kemp, James Hays
    http://arxiv.org/abs/1904.06830v1

    • [cs.CV]Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization
    Qilong Wang, Jiangtao Xie, Wangmeng Zuo, Lei Zhang, Peihua Li
    http://arxiv.org/abs/1904.06836v1

    • [cs.CV]Deep Comprehensive Correlation Mining for Image Clustering
    Jianlong Wu, Keyu Long, Fei Wang, Chen Qian, Cheng Li, Zhouchen Lin, Hongbin Zha
    http://arxiv.org/abs/1904.06925v1

    • [cs.CV]Detecting Anemia from Retinal Fundus Images
    Akinori Mitani, Yun Liu, Abigail Huang, Greg S. Corrado, Lily Peng, Dale R. Webster, Naama Hammel, Avinash V. Varadarajan
    http://arxiv.org/abs/1904.06435v1

    • [cs.CV]Differentiable Iterative Surface Normal Estimation
    Jan Eric Lenssen, Christian Osendorfer, Jonathan Masci
    http://arxiv.org/abs/1904.07172v1

    • [cs.CV]Direct Sparse Mapping
    Jon Zubizarreta, Iker Aguinaga, J. M. M. Montiel
    http://arxiv.org/abs/1904.06577v1

    • [cs.CV]Distributed Deep Learning Model for Intelligent Video Surveillance Systems with Edge Computing
    Jianguo Chen, Kenli Li, Qingying Deng, Keqin Li, Philip S. Yu
    http://arxiv.org/abs/1904.06400v1

    • [cs.CV]DuBox: No-Prior Box Objection Detection via Residual Dual Scale Detectors
    Shuai Chen, Jinpeng Li, Chuanqi Yao, Wenbo Hou, Shuo Qin, Wenyao Jin, Tang Xu
    http://arxiv.org/abs/1904.06883v1

    • [cs.CV]EXPERTNet Exigent Features Preservative Network for Facial Expression Recognition
    Monu Verma, Jaspreet Kaur Bhui, Santosh Vipparthi, Girdhari Singh
    http://arxiv.org/abs/1904.06658v1

    • [cs.CV]Explicit Spatial Encoding for Deep Local Descriptors
    Arun Mukundan, Giorgos Tolias, Ondrej Chum
    http://arxiv.org/abs/1904.07190v1

    • [cs.CV]GA-Net: Guided Aggregation Net for End-to-end Stereo Matching
    Feihu Zhang, Victor Prisacariu, Ruigang Yang, Philip H. S. Torr
    http://arxiv.org/abs/1904.06587v1

    • [cs.CV]Geometric Image Correspondence Verification by Dense Pixel Matching
    Zakaria Laskar, Iaroslav Melekhov, Hamed R. Tavakoli, Juha Ylioinas, Juho Kannala
    http://arxiv.org/abs/1904.06882v1

    • [cs.CV]Gyroscope-aided Relative Pose Estimation for Rolling Shutter Cameras
    Chang-Ryeol Lee, Ju Hong Yoon, Min-Gyu Park, Kuk-Jin Yoon
    http://arxiv.org/abs/1904.06770v1

    • [cs.CV]HAKE: Human Activity Knowledge Engine
    Yong-Lu Li, Liang Xu, Xijie Huang, Xinpeng Liu, Ze Ma, Mingyang Chen, Shiyi Wang, Hao-Shu Fang, Cewu Lu
    http://arxiv.org/abs/1904.06539v1

    • [cs.CV]Implicit Pairs for Boosting Unpaired Image-to-Image Translation
    Yiftach Ginger, Dov Danon, Hadar Averbuch-Elor, Daniel Cohen-Or
    http://arxiv.org/abs/1904.06913v1

    • [cs.CV]Influence of Control Parameters and the Size of Biomedical Image Datasets on the Success of Adversarial Attacks
    Vassili Kovalev, Dmitry Voynov
    http://arxiv.org/abs/1904.06964v1

    • [cs.CV]Joint Discriminative and Generative Learning for Person Re-identification
    Zhedong Zheng, Xiaodong Yang, Zhiding Yu, Liang Zheng, Yi Yang, Jan Kautz
    http://arxiv.org/abs/1904.07223v1

    • [cs.CV]Learning Deformable Kernels for Image and Video Denoising
    Xiangyu Xu, Muchen Li, Wenxiu Sun
    http://arxiv.org/abs/1904.06903v1

    • [cs.CV]Learning Discriminative Model Prediction for Tracking
    Goutam Bhat, Martin Danelljan, Luc Van Gool, Radu Timofte
    http://arxiv.org/abs/1904.07220v1

    • [cs.CV]Learning Shape Templates with Structured Implicit Functions
    Kyle Genova, Forrester Cole, Daniel Vlasic, Aaron Sarna, William T. Freeman, Thomas Funkhouser
    http://arxiv.org/abs/1904.06447v1

    • [cs.CV]LiveSketch: Query Perturbations for Guided Sketch-based Visual Search
    John Collomosse, Tu Bui, Hailin Jin
    http://arxiv.org/abs/1904.06611v1

    • [cs.CV]Localizing Discriminative Visual Landmarks for Place Recognition
    Zhe Xin, Yinghao Cai, Tao Lu, Xiaoxia Xing, Shaojun Cai, Jixiang Zhang, Yiping Yang, Yanqing Wang
    http://arxiv.org/abs/1904.06635v1

    • [cs.CV]Look More Than Once: An Accurate Detector for Text of Arbitrary Shapes
    Chengquan Zhang, Borong Liang, Zuming Huang, Mengyi En, Junyu Han, Errui Ding, Xinghao Ding
    http://arxiv.org/abs/1904.06535v1

    • [cs.CV]Lunar surface image restoration using U-net based deep neural networks
    Hiya Roy, Subhajit Chaudhury, Toshihiko Yamasaki, Danielle DeLatte, Makiko Ohtake, Tatsuaki Hashimoto
    http://arxiv.org/abs/1904.06683v1

    • [cs.CV]Multi-Channel Attention Selection GAN with Cascaded Semantic Guidance for Cross-View Image Translation
    Hao Tang, Dan Xu, Nicu Sebe, Yanzhi Wang, Jason J. Corso, Yan Yan
    http://arxiv.org/abs/1904.06807v1

    • [cs.CV]Multi-Similarity Loss with General Pair Weighting for Deep Metric Learning
    Xun Wang, Xintong Han, Weiling Huang, Dengke Dong, Matthew R. Scott
    http://arxiv.org/abs/1904.06627v1

    • [cs.CV]PIV-Based 3D Fluid Flow Reconstruction Using Light Field Camera
    Zhong Li, Jinwei Ye, Yu Ji, Hao Sheng, Jingyi Yu
    http://arxiv.org/abs/1904.06841v1

    • [cs.CV]Patch redundancy in images: a statistical testing framework and some applications
    De Bortoli Valentin, Desolneux Agnès, Galerne Bruno, Leclaire Arthur
    http://arxiv.org/abs/1904.06428v1

    • [cs.CV]Pedestrian Detection in Thermal Images using Saliency Maps
    Debasmita Ghose, Shasvat Mukeshkumar Desai, Sneha Bhattacharya, Deep Chakraborty, Madalina Fiterau, Tauhidur Rahman
    http://arxiv.org/abs/1904.06859v1

    • [cs.CV]Processsing Simple Geometric Attributes with Autoencoders
    Alasdair Newson, Andrés Almansa, Yann Gousseau, Saïd Ladjal
    http://arxiv.org/abs/1904.07099v1

    • [cs.CV]Recovery of Superquadrics from Range Images using Deep Learning: A Preliminary Study
    Tim Oblak, Klemen Grm, Aleš Jaklič, Peter Peer, Vitomir Štruc, Franc Solina
    http://arxiv.org/abs/1904.06585v1

    • [cs.CV]Recurrent Neural Network for (Un-)supervised Learning of Monocular VideoVisual Odometry and Depth
    Rui Wang, Stephen M. Pizer, Jan-Michael Frahm
    http://arxiv.org/abs/1904.07087v1

    • [cs.CV]Rethinking Classification and Localization in R-CNN
    Yue Wu, Yinpeng Chen, Lu Yuan, Zicheng Liu, Lijuan Wang, Hongzhi Li, Yun Fu
    http://arxiv.org/abs/1904.06493v1

    • [cs.CV]Robust Visual Tracking Revisited: From Correlation Filter to Template Matching
    Fanghui Liu, Chen Gong, Xiaolin Huang, Tao Zhou, Jie Yang, Dacheng Tao
    http://arxiv.org/abs/1904.06842v1

    • [cs.CV]SIMCO: SIMilarity-based object COunting
    Marco Godi, Christian Joppi, Andrea Giachetti, Marco Cristani
    http://arxiv.org/abs/1904.07092v1

    • [cs.CV]SR-GAN: Semantic Rectifying Generative Adversarial Network for Zero-shot Learning
    Zihan Ye, Fan lyu, Linyan Li, Qiming Fu, Jinchang Ren, Fuyuan Hu
    http://arxiv.org/abs/1904.06996v1

    • [cs.CV]Saliency Prediction on Omnidirectional Images with Generative Adversarial Imitation Learning
    Mai Xu, Li Yang, Xiaoming Tao, Yiping Duan, Zulin Wang
    http://arxiv.org/abs/1904.07080v1

    • [cs.CV]See the World through Network Cameras
    Yung-Hsiang Lu, George K. Thiruvathukal, Ahmed S. Kaseb, Kent Gauen, Damini Rijhwani, Ryan Dailey, Deeptanshu Malik, Yutong Huang, Sarah Aghajanzadeh, Minghao Guo
    http://arxiv.org/abs/1904.06775v1

    • [cs.CV]Segmenting Potentially Cancerous Areas in Prostate Biopsies using Semi-Automatically Annotated Data
    Nikolay Burlutskiy, Nicolas Pinchaud, Feng Gu, Daniel Hägg, Mats Andersson, Lars Björk, Kristian Eurén, Cristina Svensson, Lena Kajland Wilén, Martin Hedlund
    http://arxiv.org/abs/1904.06969v1

    • [cs.CV]Self-critical n-step Training for Image Captioning
    Junlong Gao, Shiqi Wang, Shanshe Wang, Siwei Ma, Wen Gao
    http://arxiv.org/abs/1904.06861v1

    • [cs.CV]Semi-supervised Domain Adaptation via Minimax Entropy
    Kuniaki Saito, Donghyun Kim, Stan Sclaroff, Trevor Darrell, Kate Saenko
    http://arxiv.org/abs/1904.06487v1

    • [cs.CV]Shakeout: A New Approach to Regularized Deep Neural Network Training
    Guoliang Kang, Jun Li, Dacheng Tao
    http://arxiv.org/abs/1904.06593v1

    • [cs.CV]Synthesising 3D Facial Motion from “In-the-Wild” Speech
    Panagiotis Tzirakis, Athanasios Papaioannou, Alexander Lattas, Michail Tarasiou, Björn Schuller, Stefanos Zafeiriou
    http://arxiv.org/abs/1904.07002v1

    • [cs.CV]Texture image analysis and texture classification methods - A review
    Laleh Armi, Shervan Fekri-Ershad
    http://arxiv.org/abs/1904.06554v1

    • [cs.CV]Towards Self-similarity Consistency and Feature Discrimination for Unsupervised Domain Adaptation
    Chao Chen, Zhihang Fu, Zhihong Chen, Zhaowei Cheng, Xinyu Jin, Xian-Sheng Hua
    http://arxiv.org/abs/1904.06490v1

    • [cs.CV]Transformable Bottleneck Networks
    Kyle Olszewski, Sergey Tulyakov, Oliver Woodford, Hao Li, Linjie Luo
    http://arxiv.org/abs/1904.06458v1

    • [cs.CV]Universal Bounding Box Regression and Its Applications
    Seungkwan Lee, Suha Kwak, Minsu Cho
    http://arxiv.org/abs/1904.06805v1

    • [cs.CV]Unsupervised Synthesis of Anomalies in Videos: Transforming the Normal
    Abhishek Joshi, Vinay P. Namboodiri
    http://arxiv.org/abs/1904.06633v1

    • [cs.CV]VORNet: Spatio-temporally Consistent Video Inpainting for Object Removal
    Ya-Liang Chang, Zhe Yu Liu, Winston Hsu
    http://arxiv.org/abs/1904.06726v1

    • [cs.CV]Visual-Inertial Mapping with Non-Linear Factor Recovery
    Vladyslav Usenko, Nikolaus Demmel, David Schubert, Jörg Stückler, Daniel Cremers
    http://arxiv.org/abs/1904.06504v1

    • [cs.CV]dipIQ: Blind Image Quality Assessment by Learning-to-Rank Discriminable Image Pairs
    Kede Ma, Wentao Liu, Tongliang Liu, Zhou Wang, Dacheng Tao
    http://arxiv.org/abs/1904.06505v1

    • [cs.CY]Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms
    Snehalkumar, S. Gaikwad, Durim Morina, Adam Ginzberg, Catherine Mullings, Shirish Goyal, Dilrukshi Gamage, Christopher Diemert, Mathias Burton, Sharon Zhou, Mark Whiting, Karolina Ziulkoski, Alipta Ballav, Aaron Gilbee, Senadhipathige S. Niranga, Vibhor Sehgal, Jasmine Lin, Leonardy Kristianto, Angela Richmond-Fuller, Jeff Regino, Nalin Chhibber, Dinesh Majeti, Sachin Sharma, Kamila Mananova, Dinesh Dhakal, William Dai, Victoria Purynova, Samarth Sandeep, Varshine Chandrakanthan, Tejas Sarma, Sekandar Matin, Ahmed Nasser, Rohit Nistala, Alexander Stolzoff, Kristy Milland, Vinayak Mathur, Rajan Vaish, Michael S. Bernstein
    http://arxiv.org/abs/1904.06722v1

    • [cs.CY]Challenges in Integrating Technology into Education
    Oguzhan Atabek
    http://arxiv.org/abs/1904.06518v1

    • [cs.CY]Joint Seat Allocation 2018: An algorithmic perspective
    S. Baswana, P. P. Chakrabarti, Yashodan Kanoria, U. Patange, Sharat Chandran
    http://arxiv.org/abs/1904.06698v1

    • [cs.DC]Cryptocurrency with Fully Asynchronous Communication based on Banks and Democracy
    Asa Dan
    http://arxiv.org/abs/1904.06522v1

    • [cs.DC]Distributed Matrix Multiplication Using Speed Adaptive Coding
    Krishna Narra, Zhifeng Lin, Mehrdad Kiamari, Salman Avestimehr, Murali Annavaram
    http://arxiv.org/abs/1904.07098v1

    • [cs.DC]Evaluation of the RIKEN Post-K Processor Simulator
    Yuetsu Kodama, Tetsuya Odajima, Akira Asato, Mitsuhisa Sato
    http://arxiv.org/abs/1904.06451v1

    • [cs.DC]Management of mobile resources in Physical Internet logistic models
    Jean-Yves Colin, Moustafa Nakechbandi, Hervé Mathieu
    http://arxiv.org/abs/1904.07024v1

    • [cs.DC]Repeat-Authenticate Scheme for Multicasting of Blockchain Information in IoT Systems
    Pietro Danzi, Anders E. Kalør, Čedomir Stefanović, Petar Popovski
    http://arxiv.org/abs/1904.07069v1

    • [cs.DC]Single Machine Graph Analytics on Massive Datasets Using Intel Optane DC Persistent Memory
    Gurbinder Gill, Roshan Dathathri, Loc Hoang, Ramesh Peri, Keshav Pingali
    http://arxiv.org/abs/1904.07162v1

    • [cs.DC]White-Box Atomic Multicast (Extended Version)
    Alexey Gotsman, Anatole Lefort, Gregory Chockler
    http://arxiv.org/abs/1904.07171v1

    • [cs.HC]Learning to Engage with Interactive Systems: A field Study
    Lingheng Meng, Daiwei Lin, Adam Francey, Rob Gorbet, Philip Beesley, Dana Kulić
    http://arxiv.org/abs/1904.06764v1

    • [cs.IR]An Axiomatic Approach to Regularizing Neural Ranking Models
    Corby Rosset, Bhaskar Mitra, Chenyan Xiong, Nick Craswell, Xia Song, Saurabh Tiwary
    http://arxiv.org/abs/1904.06808v1

    • [cs.IR]BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
    Fei Sun, Jun Liu, Jian Wu, Changhua Pei, Xiao Lin, Wenwu Ou, Peng Jiang
    http://arxiv.org/abs/1904.06690v1

    • [cs.IR]Contextualized Word Representations for Document Re-Ranking
    Sean MacAvaney, Andrew Yates, Arman Cohan, Nazli Goharian
    http://arxiv.org/abs/1904.07094v1

    • [cs.IR]Measuring the influence of mere exposure effect of TV commercial adverts on purchase behavior based on machine learning prediction models
    Elisa Claire Alemán Carreón, Hirofumi Nonaka, Asahi Hentona, Hirochika Yamashiro
    http://arxiv.org/abs/1904.06862v1

    • [cs.IR]Personalized Context-aware Re-ranking for E-commerce Recommender Systems
    Changhua Pei, Yi Zhang, Yongfeng Zhang, Fei Sun, Xiao Lin, Hanxiao Sun, Jian Wu, Peng Jiang, Wenwu Ou, Dan Pei
    http://arxiv.org/abs/1904.06813v1

    • [cs.IR]RelEmb: A relevance-based application embedding for Mobile App retrieval and categorization
    Ahsaas Bajaj, Shubham Krishna, Mukund Rungta, Hemant Tiwari, Vanraj Vala
    http://arxiv.org/abs/1904.06672v1

    • [cs.IR]Topic Grouper: An Agglomerative Clustering Approach to Topic Modeling
    Daniel Pfeifer, Jochen L. Leidner
    http://arxiv.org/abs/1904.06483v1

    • [cs.IT]Asymptotic Outage Analysis of Spatially Correlated Rayleigh MIMO Channels
    Zheng Shi, Huan Zhang, Guanghua Yang, Shaodan Ma
    http://arxiv.org/abs/1904.06872v1

    • [cs.IT]Codes over an algebra over ring
    Irwansyah, Djoko Suprijanto
    http://arxiv.org/abs/1904.06811v1

    • [cs.IT]Coverage Analysis of 3-D Dense Cellular Networks with Realistic Propagation Conditions
    Aritra Chatterjee, Suvra Sekhar Das
    http://arxiv.org/abs/1904.06946v1

    • [cs.IT]Deep CNN based Channel Estimation for mmWave Massive MIMO Systems
    Peihao Dong, Hua Zhang, Geoffrey Ye Li, Navid NaderiAlizadeh, Ivan Simoes Gaspar
    http://arxiv.org/abs/1904.06761v1

    • [cs.IT]Efficient Search and Elimination of Harmful Objects in Optimized QC SC-LDPC Codes
    Massimo Battaglioni, Franco Chiaraluce, Marco Baldi, David Mitchell
    http://arxiv.org/abs/1904.07158v1

    • [cs.IT]Energy Efficient Node Deployment in Wireless Ad-hoc Sensor Networks
    Jun Guo, Saeed Karimi-Bidhendi, Hamid Jafarkhani
    http://arxiv.org/abs/1904.06380v1

    • [cs.IT]Introducing Enumerative Sphere Shaping for Optical Communication Systems with Short Blocklengths
    Abdelkerim Amari, Sebastiaan Goossens, Yunus Can Gultekin, Olga Vassilieva, Inwoong Kim, Tadashi Ikeuchi, Chigo Okonkwo, Frans M. J. Willems, Alex Alvarado
    http://arxiv.org/abs/1904.06601v1

    • [cs.IT]Iterative Decoding of Trellis-Constrained Codes inspired by Amplitude Amplification (Preliminary Version)
    Christian Franck
    http://arxiv.org/abs/1904.06473v1

    • [cs.IT]Large Intelligent Surface-Based Index Modulation: A New Beyond MIMO Paradigm for 6G
    Ertugrul Basar
    http://arxiv.org/abs/1904.06704v1

    • [cs.IT]Mutual Information-Maximizing Quantized Belief Propagation Decoding of LDPC Codes
    Xuan He, Kui Cai, Zhen Mei
    http://arxiv.org/abs/1904.06666v1

    • [cs.IT]Permutation codes over finite fields
    Irwansyah, Intan Muchtadi-Alamsyah, Aleams Barra
    http://arxiv.org/abs/1904.06820v1

    • [cs.IT]Power Allocation for Type-I ARQ Two-Hop Cooperative Networks for Ultra-Reliable Communication
    Endrit Dosti, Themistoklis Charalambous, Risto Wichman
    http://arxiv.org/abs/1904.06708v1

    • [cs.IT]Spatially Coupled LDPC Codes with Non-uniform Coupling for Improved Decoding Speed
    Laurent Schmalen, Vahid Aref
    http://arxiv.org/abs/1904.07026v1

    • [cs.LG]A Discussion on Solving Partial Differential Equations using Neural Networks
    Tim Dockhorn
    http://arxiv.org/abs/1904.07200v1

    • [cs.LG]A Fast Dictionary Learning Method for Coupled Feature Space Learning
    F. G. Veshki, S. A. Vorobyov
    http://arxiv.org/abs/1904.06968v1

    • [cs.LG]A joint autoencoder for prediction and its application in GPS trajectory data
    Baogui Xin, Wei Peng
    http://arxiv.org/abs/1904.06513v1

    • [cs.LG]An Empirical Investigation of Global and Local Normalization for Recurrent Neural Sequence Models Using a Continuous Relaxation to Beam Search
    Kartik Goyal, Chris Dyer, Taylor Berg-Kirkpatrick
    http://arxiv.org/abs/1904.06834v1

    • [cs.LG]Are Nearby Neighbors Relatives?: Diagnosing Deep Music Embedding Spaces
    Jaehun Kim, Julián Urbano, Cynthia C. S. Liem, Alan Hanjalic
    http://arxiv.org/abs/1904.07154v1

    • [cs.LG]Depth Separations in Neural Networks: What is Actually Being Separated?
    Itay Safran, Ronen Eldan, Ohad Shamir
    http://arxiv.org/abs/1904.06984v1

    • [cs.LG]Disentangling Options with Hellinger Distance Regularizer
    Minsung Hyun, Junyoung Choi, Nojun Kwak
    http://arxiv.org/abs/1904.06887v1

    • [cs.LG]Dot-to-Dot: Achieving Structured Robotic Manipulation through Hierarchical Reinforcement Learning
    Benjamin Beyret, Ali Shafti, A. Aldo Faisal
    http://arxiv.org/abs/1904.06703v1

    • [cs.LG]Exact Rate-Distortion in Autoencoders via Echo Noise
    Rob Brekelmans, Daniel Moyer, Aram Galstyan, Greg Ver Steeg
    http://arxiv.org/abs/1904.07199v1

    • [cs.LG]Exploiting Event Log Data-Attributes in RNN Based Prediction
    Markku Hinkka, Teemu Lehto, Keijo Heljanko
    http://arxiv.org/abs/1904.06895v1

    • [cs.LG]Exploring Representativeness and Informativeness for Active Learning
    Bo Du, Zengmao Wang, Lefei Zhang, Liangpei Zhang, Wei Liu, Jialie Shen, Dacheng Tao
    http://arxiv.org/abs/1904.06685v1

    • [cs.LG]Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
    Daniel S. Brown, Wonjoon Goo, Prabhat Nagarajan, Scott Niekum
    http://arxiv.org/abs/1904.06387v1

    • [cs.LG]Finding a latent k-simplex in O(k . nnz(data)) time via Subset Smoothing
    Chiranjib Bhattacharyya, Ravindran Kannan
    http://arxiv.org/abs/1904.06738v1

    • [cs.LG]Graph-Based Method for Anomaly Detection in Functional Brain Network using Variational Autoencoder
    Jalal Mirakhorli, Mojgan Mirakhorli
    http://arxiv.org/abs/1904.07163v1

    • [cs.LG]Graph-Embedded Multi-layer Kernel Extreme Learning Machine for One-class Classification or (Graph-Embedded Multi-layer Kernel Ridge Regression for One-class Classification)
    Chandan Gautam, Aruna Tiwari, M. Tanveer
    http://arxiv.org/abs/1904.06491v1

    • [cs.LG]GraphTSNE: A Visualization Technique for Graph-Structured Data
    Yao Yang Leow, Thomas Laurent, Xavier Bresson
    http://arxiv.org/abs/1904.06915v1

    • [cs.LG]Human-Guided Learning of Column Networks: Augmenting Deep Learning with Advice
    Mayukh Das, Yang Yu, Devendra Singh Dhami, Gautam Kunapuli, Sriraam Natarajan
    http://arxiv.org/abs/1904.06950v1

    • [cs.LG]Information Theoretic Lower Bounds on Negative Log Likelihood
    Luis A. Lastras
    http://arxiv.org/abs/1904.06395v1

    • [cs.LG]LeanResNet: A Low-cost yet Effective Convolutional Residual Networks
    Jonathan Ephrath, Lars Ruthotto, Eldad Haber, Eran Treister
    http://arxiv.org/abs/1904.06952v1

    • [cs.LG]Learning Spatiotemporal Features of Ride-sourcing Services with Fusion Convolutional Network
    Dapeng Zhang, Feng Xiao, Lu Li, Gang Kou
    http://arxiv.org/abs/1904.06823v1

    • [cs.LG]On the Performance of Differential Evolution for Hyperparameter Tuning
    Mischa Schmidt, Shahd Safarani, Julia Gastinger, Tobias Jacobs, Sebastien Nicolas, Anett Schülke
    http://arxiv.org/abs/1904.06960v1

    • [cs.LG]Painting on Placement: Forecasting Routing Congestion using Conditional Generative Adversarial Nets
    Cunxi Yu, Zhiru Zhang
    http://arxiv.org/abs/1904.07077v1

    • [cs.LG]Probabilistic Kernel Support Vector Machines
    Yongxin Chen, Tryphon T. Georgiou, Allen R. Tannenbaum
    http://arxiv.org/abs/1904.06762v1

    • [cs.LG]Remaining Useful Life Estimation Using Functional Data Analysis
    Qiyao Wang, Shuai Zheng, Ahmed Farahat, Susumu Serita, Chetan Gupta
    http://arxiv.org/abs/1904.06442v1

    • [cs.LG]Robust and Discriminative Labeling for Multi-label Active Learning Based on Maximum Correntropy Criterion
    Bo Du, Zengmao Wang, Lefei Zhang, Liangpei Zhang, Dacheng Tao
    http://arxiv.org/abs/1904.06689v1

    • [cs.LG]Self-Paced Probabilistic Principal Component Analysis for Data with Outliers
    Bowen Zhao, Xi Xiao, Wanpeng Zhang, Bin Zhang, Shutao Xia
    http://arxiv.org/abs/1904.06546v1

    • [cs.LG]Should I Raise The Red Flag? A comprehensive survey of anomaly scoring methods toward mitigating false alarms
    Zahra Zohrevand, Uwe Glässer
    http://arxiv.org/abs/1904.06646v1

    • [cs.LG]Temporal Network Representation Learning
    John Boaz Lee, Giang Nguyen, Ryan A. Rossi, Nesreen K. Ahmed, Eunyee Koh, Sungchul Kim
    http://arxiv.org/abs/1904.06449v1

    • [cs.LG]The Impact of Neural Network Overparameterization on Gradient Confusion and Stochastic Gradient Descent
    Karthik A. Sankararaman, Soham De, Zheng Xu, W. Ronny Huang, Tom Goldstein
    http://arxiv.org/abs/1904.06963v1

    • [cs.LG]Tutorial: Safe and Reliable Machine Learning
    Suchi Saria, Adarsh Subbaswamy
    http://arxiv.org/abs/1904.07204v1

    • [cs.LG]UR-FUNNY: A Multimodal Language Dataset for Understanding Humor
    Md Kamrul Hasan, Wasifur Rahman, Amir Zadeh, Jianyuan Zhong, Md Iftekhar Tanveer, Louis-Philippe Morency, Mohammed, Hoque
    http://arxiv.org/abs/1904.06618v1

    • [cs.LG]Unsupervised Singing Voice Conversion
    Eliya Nachmani, Lior Wolf
    http://arxiv.org/abs/1904.06590v1

    • [cs.NE]A Hybrid Evolutionary Algorithm Framework for Optimising Power Take Off and Placements of Wave Energy Converters
    Mehdi Neshat, Bradley Alexander, Nataliia Sergiienko, Markus Wagner
    http://arxiv.org/abs/1904.07043v1

    • [cs.NE]Efficient Feature Selection of Power Quality Events using Two Dimensional (2D) Particle Swarms
    Faizal Hafiz, Akshya Swain, Chirag Naik, Nitish Patel
    http://arxiv.org/abs/1904.06972v1

    • [cs.NE]Synthetic Neural Vision System Design for Motion Pattern Recognition in Dynamic Robot Scenes
    Qinbing Fu, Cheng Hu, Pengcheng Liu, Shigang Yue
    http://arxiv.org/abs/1904.07180v1

    • [cs.NE]The Efficiency Threshold for the Offspring Population Size of the ($μ$, $λ$) EA
    Denis Antipov, Benjamin Doerr, Quentin Yang
    http://arxiv.org/abs/1904.06981v1

    • [cs.NI]A Personalized Preference Learning Framework for Caching in Mobile Networks
    Adeel Malik, Joongheon Kim, Won-Yong Shin
    http://arxiv.org/abs/1904.06744v1

    • [cs.NI]How to Price Fresh Data
    Meng Zhang, Ahmed Arafa, Jianwei Huang, H. Vincent Poor
    http://arxiv.org/abs/1904.06899v1

    • [cs.NI]When Tesla Meets Nash: Wireless Power Provision as a Public Good
    Meng Zhang, Jianwei Huang, Rui Zhang
    http://arxiv.org/abs/1904.06907v1

    • [cs.PL]From Theory to Systems: A Grounded Approach to Programming Language Education
    Will Crichton
    http://arxiv.org/abs/1904.06750v1

    • [cs.PL]Got: Git, but for Objects
    Rohan Achar, Cristina V. Lopes
    http://arxiv.org/abs/1904.06584v1

    • [cs.PL]Specifying Concurrent Programs in Separation Logic: Morphisms and Simulations
    Aleksandar Nanevski, Anindya Banerjee, Germán Andrés Delbianco, Ignacio Fábregas
    http://arxiv.org/abs/1904.07136v1

    • [cs.RO]A Comparison of Policy Search in Joint Space and Cartesian Space for Refinement of Skills
    Alexander Fabisch
    http://arxiv.org/abs/1904.06765v1

    • [cs.RO]An LGMD Based Competitive Collision Avoidance Strategy for UAV
    Jiannan Zhao, Xingzao Ma, Qinbing Fu, Cheng Hu, Shigang Yue
    http://arxiv.org/abs/1904.07206v1

    • [cs.RO]Combining Physical Simulators and Object-Based Networks for Control
    Anurag Ajay, Maria Bauza, Jiajun Wu, Nima Fazeli, Joshua B. Tenenbaum, Alberto Rodriguez, Leslie P. Kaelbling
    http://arxiv.org/abs/1904.06580v1

    • [cs.RO]Curious iLQR: Resolving Uncertainty in Model-based RL
    Sarah Bechtle, Akshara Rai, Yixin Lin, Ludovic Righetti, Franziska Meier
    http://arxiv.org/abs/1904.06786v1

    • [cs.RO]Learning Whole-Image Descriptors for Real-time Loop Detection andKidnap Recovery under Large Viewpoint Difference
    Manohar Kuse, Shaojie Shen
    http://arxiv.org/abs/1904.06962v1

    • [cs.RO]Learning to Generate Unambiguous Spatial Referring Expressions for Real-World Environments
    Fethiye Irmak Doğan, Sinan Kalkan, Iolanda Leite
    http://arxiv.org/abs/1904.07165v1

    • [cs.RO]Learning to Guide: Guidance Law Based on Deep Meta-learning and Model Predictive Path Integral Control
    Chen Liang, Weihong Wang, Zhenghua Liu, Chao Lai, Benchun Zhou
    http://arxiv.org/abs/1904.06892v1

    • [cs.RO]Learning to Navigate in Indoor Environments: from Memorizing to Reasoning
    Liulong Ma, Yanjie Liu, Jiao Chen, Dong Jin
    http://arxiv.org/abs/1904.06933v1

    • [cs.RO]On Model Adaptation for Sensorimotor Control of Robots
    David Navarro-Alarcon, Andrea Cherubini, Xiang Li
    http://arxiv.org/abs/1904.06524v1

    • [cs.RO]Online Sampling in the Parameter Space of a Neural Network for GPU-accelerated Motion Planning of Autonomous Vehicles
    Mogens Graf Plessen
    http://arxiv.org/abs/1904.06680v1

    • [cs.RO]Quasi-static Analysis of Planar Sliding Using Friction Patches
    M. Mahdi Ghazaei Ardakani, Joao Bimbo, Domenico Prattichizzo
    http://arxiv.org/abs/1904.06677v1

    • [cs.RO]Real-time Model-based Image Color Correction for Underwater Robots
    Monika Roznere, Alberto Quattrini Li
    http://arxiv.org/abs/1904.06437v1

    • [cs.RO]Reinforcement Learning with Probabilistic Guarantees for Autonomous Driving
    Maxime Bouton, Jesper Karlsson, Alireza Nakhaei, Kikuo Fujimura, Mykel J. Kochenderfer, Jana Tumova
    http://arxiv.org/abs/1904.07189v1

    • [cs.RO]Tightly Coupled 3D Lidar Inertial Odometry and Mapping
    Haoyang Ye, Yuying Chen, Ming Liu
    http://arxiv.org/abs/1904.06993v1

    • [cs.SI]Cyberbullying and Traditional Bullying in Greece: An Empirical Study
    Maria Papatsimouli, John Skordas, Lazaros Lazaridis, Eleni Michailidi, Vaggelis Saprikis, George F. Fragulis
    http://arxiv.org/abs/1904.07188v1

    • [cs.SI]Percolation Threshold for Competitive Influence in Random Networks
    Yu-Hsien Peng, Ping-En Lu, Cheng-Shang Chang, Duan-Shin Lee
    http://arxiv.org/abs/1904.05754v2

    • [cs.SI]What Makes Social Search Efficient
    Amr Elsisy, Buster O. Holzbauer, Boleslaw K. Szymanski, Miao Qi, Alex Pentland
    http://arxiv.org/abs/1904.06551v1

    • [cs.SY]Minimum Error Entropy Kalman Filter
    Badong Chen, Lujuan Dang, Yuantao Gu, Nanning Zheng, Jose C. Prıncipe
    http://arxiv.org/abs/1904.06617v1

    • [econ.EM]Estimation of Cross-Sectional Dependence in Large Panels
    Jiti Gao, Guangming Pan, Yanrong Yang, Bo Zhang
    http://arxiv.org/abs/1904.06843v1

    • [econ.EM]Subgeometric ergodicity and $β$-mixing
    Mika Meitz, Pentti Saikkonen
    http://arxiv.org/abs/1904.07103v1

    • [econ.EM]Subgeometrically ergodic autoregressions
    Mika Meitz, Pentti Saikkonen
    http://arxiv.org/abs/1904.07089v1

    • [eess.AS]Low-Latency Speaker-Independent Continuous Speech Separation
    Takuya Yoshioka, Zhuo Chen, Changliang Liu, Xiong Xiao, Hakan Erdogan, Dimitrios Dimitriadis
    http://arxiv.org/abs/1904.06478v1

    • [eess.AS]Singing voice synthesis based on convolutional neural networks
    Kazuhiro Nakamura, Kei Hashimoto, Keiichiro Oura, Yoshihiko Nankaku, Keiichi Tokuda
    http://arxiv.org/abs/1904.06868v1

    • [eess.SP]Multi-Branch Tensor Network Structure for Tensor-Train Discriminant Analysis
    Seyyid Emre Sofuoglu, Selin Aviyente
    http://arxiv.org/abs/1904.06788v1

    • [eess.SP]TDMR Detection System with Local Area Influence Probabilistic a Priori Detector
    Jinlu Shen, Xueliang Sun, Krishnamoorthy Sivakumar, Benjamin J. Belzer, Kheong Sann Chan, Ashish James
    http://arxiv.org/abs/1904.06599v1

    • [math.RA]Wajsberg algebras arising from binary block codes
    Cristina Flaut, Radu Vasile
    http://arxiv.org/abs/1904.07169v1

    • [math.ST]Asymptotic efficiency of M.L.E. using prior survey in multinomial distributions
    Yo Sheena
    http://arxiv.org/abs/1904.06826v1

    • [math.ST]Bootstrapping Covariance Operators of Functional Time Series
    Olimjon Sh. Sharipov, Martin Wendler
    http://arxiv.org/abs/1904.06721v1

    • [math.ST]Independence Properties of the Truncated Multivariate Elliptical Distributions
    Michael Levine, Donald Richards, Jianxi Su
    http://arxiv.org/abs/1904.06412v1

    • [math.ST]On the construction of confidence intervals for ratios of expectations
    Alexis Derumigny, Lucas Girard, Yannick Guyonvarch
    http://arxiv.org/abs/1904.07111v1

    • [math.ST]Recursive density estimators based on Robbins-Monro’s scheme and using Bernstein polynomials
    Yousri SLAOUI, Asma JMAEI
    http://arxiv.org/abs/1904.06675v1

    • [math.ST]The Landscape of the Planted Clique Problem: Dense subgraphs and the Overlap Gap Property
    David Gamarnik, Ilias Zadik
    http://arxiv.org/abs/1904.07174v1

    • [physics.comp-ph]Deep-learning PDEs with unlabeled data and hardwiring physics laws
    S. Mohammad H. Hashemi, Demetri Psaltis
    http://arxiv.org/abs/1904.06578v1

    • [physics.soc-ph]The dynamic importance of nodes is poorly predicted by static topological features
    Casper van Elteren, Rick Quax
    http://arxiv.org/abs/1904.06654v1

    • [q-bio.BM]Detection of protein-ligand binding sites with 3D segmentation
    Marta M. Stepniewska-Dziubinska, Piotr Zielenkiewicz, Pawel Siedlecki
    http://arxiv.org/abs/1904.06517v1

    • [q-bio.MN]Disease gene prioritization using network topological analysis from a sequence based human functional linkage network
    Ali Jalilvand, Behzad Akbari, Fatemeh Zare Mirakabad, Foad Ghaderi
    http://arxiv.org/abs/1904.06973v1

    • [q-bio.QM]Deep neural networks can predict mortality from 12-lead electrocardiogram voltage data
    Sushravya Raghunath, Alvaro E. Ulloa Cerna, Linyuan Jing, David P. vanMaanen, Joshua Stough, Dustin N. Hartzel, Joseph B. Leader, H. Lester Kirchner, Christopher W. Good, Aalpen A. Patel, Brian P. Delisle, Amro Alsaid, Dominik Beer, Christopher M. Haggerty, Brandon K. Fornwalt
    http://arxiv.org/abs/1904.07032v1

    • [quant-ph]Tensorization of the strong data processing inequality for quantum chi-square divergences
    Yu Cao, Jianfeng Lu
    http://arxiv.org/abs/1904.06562v1

    • [stat.AP]A framework for streamlined statistical prediction using topic models
    Vanessa Glenny, Jonathan Tuke, Nigel Bean, Lewis Mitchell
    http://arxiv.org/abs/1904.06941v1

    • [stat.AP]Comparison of statistical post-processing methods for probabilistic NWP forecasts of solar radiation
    Kilian Bakker, Kirien Whan, Wouter Knap, Maurice Schmeits
    http://arxiv.org/abs/1904.07192v1

    • [stat.AP]Estimation of group means in generalized linear mixed models
    Jiexin Duan, Michael Levine, Junxiang Luo, Yongming Qu
    http://arxiv.org/abs/1904.06384v1

    • [stat.AP]Multiple imputation and selection of ordinal level 2 predictors in multilevel models. An analysis of the relationship between student ratings and teacher beliefs and practices
    Leonardo Grilli, Maria Francesca Marino, Omar Paccagnella, Carla Rampichini
    http://arxiv.org/abs/1904.05062v2

    • [stat.CO]Applications of Quantum Annealing in Statistics
    Robert C. Foster, Brian Weaver, James Gattiker
    http://arxiv.org/abs/1904.06819v1

    • [stat.ME]A Hitchhiker’s Guide to Statistical Comparisons of Reinforcement Learning Algorithms
    Cédric Colas, Olivier Sigaud, Pierre-Yves Oudeyer
    http://arxiv.org/abs/1904.06979v1

    • [stat.ME]Analysis of overfitting in the regularized Cox model
    M Sheikh, ACC Coolen
    http://arxiv.org/abs/1904.06632v1

    • [stat.ME]Interpretable hypothesis tests
    Victor Coscrato, Luís Gustavo Esteves, Rafael Izbicki, Rafael Bassi Stern
    http://arxiv.org/abs/1904.06605v1

    • [stat.ME]Proportional hazards model with partly interval censoring and its penalized likelihood estimation
    Jun Ma, Dominique-Laurent Couturier, Stephane Heritier, Ian Marschner
    http://arxiv.org/abs/1904.06789v1

    • [stat.ME]Validation of Association
    Ćmiel Bogdan, Ledwina Teresa
    http://arxiv.org/abs/1904.06519v1

    • [stat.ME]Variational Bayes for high-dimensional linear regression with sparse priors
    Kolyan Ray, Botond Szabo
    http://arxiv.org/abs/1904.07150v1

    • [stat.ML]A Selective Overview of Deep Learning
    Jianqing Fan, Cong Ma, Yiqiao Zhong
    http://arxiv.org/abs/1904.05526v2

    • [stat.ML]Copula-like Variational Inference
    Marcel Hirt, Petros Dellaportas, Alain Durmus
    http://arxiv.org/abs/1904.07153v1

    • [stat.ML]Improved Precision and Recall Metric for Assessing Generative Models
    Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, Timo Aila
    http://arxiv.org/abs/1904.06991v1

    • [stat.ML]Maximum Correntropy Criterion with Variable Center
    Badong Chen, Xin Wang, Yingsong Li, Jose C. Principe
    http://arxiv.org/abs/1904.06501v1