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