cs.AI - 人工智能
cs.CC - 计算复杂度 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.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DM - 离散数学 cs.DS - 数据结构与算法 cs.GR - 计算机图形学 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.OC - 优化与控制 math.ST - 统计理论 physics.data-an - 数据分析、 统计和概率 q-bio.GN - 基因组学 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 Computational-Hermeneutic Approach for Conceptual Explicitation
• [cs.AI]A new approach to forecasting service parts demand by integrating user preferences into multi-objective optimization
• [cs.AI]Efficient predicate invention using shared “NeMuS”
• [cs.AI]Self-organized inductive reasoning with NeMuS
• [cs.AI]Towards Empathetic Planning
• [cs.CC]Running Time Analysis of the (1+1)-EA for Robust Linear Optimization
• [cs.CL]”My Way of Telling a Story”: Persona based Grounded Story Generation
• [cs.CL]A Hierarchical Attention Based Seq2seq Model for Chinese Lyrics Generation
• [cs.CL]A weakly supervised sequence tagging and grammar induction approach to semantic frame slot filling
• [cs.CL]Adversarial Training for Multilingual Acoustic Modeling
• [cs.CL]An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis
• [cs.CL]Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA
• [cs.CL]BERE: An accurate distantly supervised biomedical entity relation extraction network
• [cs.CL]Can neural networks understand monotonicity reasoning?
• [cs.CL]Context is Key: Grammatical Error Detection with Contextual Word Representations
• [cs.CL]Context-aware Embedding for Targeted Aspect-based Sentiment Analysis
• [cs.CL]Correlating Twitter Language with Community-Level Health Outcomes
• [cs.CL]Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing
• [cs.CL]Improving Background Based Conversation with Context-aware Knowledge Pre-selection
• [cs.CL]Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling
• [cs.CL]Making Fast Graph-based Algorithms with Graph Metric Embeddings
• [cs.CL]Manipulating the Difficulty of C-Tests
• [cs.CL]Multi-Hop Paragraph Retrieval for Open-Domain Question Answering
• [cs.CL]Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
• [cs.CL]Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B
• [cs.CL]Open Domain Event Extraction Using Neural Latent Variable Models
• [cs.CL]Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good
• [cs.CL]Practical User Feedback-driven Internal Search Using Online Learning to Rank
• [cs.CL]Principled Frameworks for Evaluating Ethics in NLP Systems
• [cs.CL]Recursive Style Breach Detection with Multifaceted Ensemble Learning
• [cs.CL]Robust Zero-Shot Cross-Domain Slot Filling with Example Values
• [cs.CL]Scalable Syntax-Aware Language Models Using Knowledge Distillation
• [cs.CL]Tagged Back-Translation
• [cs.CL]Theoretical Limitations of Self-Attention in Neural Sequence Models
• [cs.CL]Towards Integration of Statistical Hypothesis Tests into Deep Neural Networks
• [cs.CL]Using Automatically Extracted Minimum Spans to Disentangle Coreference Evaluation from Boundary Detection
• [cs.CR]A Secure Consensus Protocol for Sidechains
• [cs.CR]Physical Integrity Attack Detection of Surveillance Camera with Deep Learning Based Video Frame Interpolation
• [cs.CV]A Temporal Sequence Learning for Action Recognition and Prediction
• [cs.CV]Back-Projection based Fidelity Term for Ill-Posed Linear Inverse Problems
• [cs.CV]Beyond Product Quantization: Deep Progressive Quantization for Image Retrieval
• [cs.CV]Boosting Supervision with Self-Supervision for Few-shot Learning
• [cs.CV]Deep Recurrent Quantization for Generating Sequential Binary Codes
• [cs.CV]DeepMOT: A Differentiable Framework for Training Multiple Object Trackers
• [cs.CV]Defending Against Adversarial Attacks Using Random Forests
• [cs.CV]Delving into 3D Action Anticipation from Streaming Videos
• [cs.CV]Detecting Bias with Generative Counterfactual Face Attribute Augmentation
• [cs.CV]EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
• [cs.CV]Efficient Neural Network Approaches for Leather Defect Classification
• [cs.CV]EnlightenGAN: Deep Light Enhancement without Paired Supervision
• [cs.CV]Exemplar Guided Face Image Super-Resolution without Facial Landmarks
• [cs.CV]Fixing the train-test resolution discrepancy
• [cs.CV]Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction
• [cs.CV]Hallucinated Adversarial Learning for Robust Visual Tracking
• [cs.CV]Hierarchical Back Projection Network for Image Super-Resolution
• [cs.CV]IMP: Instance Mask Projection for High Accuracy Semantic Segmentation of Things
• [cs.CV]Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding
• [cs.CV]Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era
• [cs.CV]Improving temporal action proposal generation by using high performance computing
• [cs.CV]Learning Part Generation and Assembly for Structure-aware Shape Synthesis
• [cs.CV]MMDetection: Open MMLab Detection Toolbox and Benchmark
• [cs.CV]MV-C3D: A Spatial Correlated Multi-View 3D Convolutional Neural Networks
• [cs.CV]Machine-Assisted Map Editing
• [cs.CV]Mask Based Unsupervised Content Transfer
• [cs.CV]Mixture separability loss in a deep convolutional network for image classification
• [cs.CV]Multi-Scale Convolutions for Learning Context Aware Feature Representations
• [cs.CV]Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
• [cs.CV]NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising
• [cs.CV]Noisy-As-Clean: Learning Unsupervised Denoising from the Corrupted Image
• [cs.CV]On the Self-Similarity of Natural Stochastic Textures
• [cs.CV]On training deep networks for satellite image super-resolution
• [cs.CV]Panoptic Image Annotation with a Collaborative Assistant
• [cs.CV]ParNet: Position-aware Aggregated Relation Network for Image-Text matching
• [cs.CV]RECAL: Reuse of Established CNN classifer Apropos unsupervised Learning paradigm
• [cs.CV]REMAP: Multi-layer entropy-guided pooling of dense CNN features for image retrieval
• [cs.CV]Realistic Speech-Driven Facial Animation with GANs
• [cs.CV]STAR: A Structure and Texture Aware Retinex Model
• [cs.CV]Semi-Supervised Semantic Mapping through Label Propagation with Semantic Texture Meshes
• [cs.CV]Spatio-Temporal Fusion Networks for Action Recognition
• [cs.CV]Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images
• [cs.CV]Towards Real-Time Action Recognition on Mobile Devices Using Deep Models
• [cs.CV]Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks
• [cs.CV]VRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction
• [cs.CY]A multi-layered blockchain framework for smart mobility data-markets
• [cs.CY]AI Ethics — Too Principled to Fail?
• [cs.DB]Distributed Subtrajectory Clustering
• [cs.DC]Accelerating Concurrent Heap on GPUs
• [cs.DC]Near Optimal Coflow Scheduling in Networks
• [cs.DC]Self-Stabilizing Snapshot Objects for Asynchronous Fail-Prone Network Systems
• [cs.DC]Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems
• [cs.DM]A concise guide to existing and emerging vehicle routing problem variants
• [cs.DS]A New Family of Tractable Ising Models
• [cs.DS]Monotonically relaxing concurrent data-structure semantics for performance: An efficient 2D design framework
• [cs.GR]A Statistical View on Synthetic Aperture Imaging for Occlusion Removal
• [cs.IR]A Multi-Task Architecture on Relevance-based Neural Query Translation
• [cs.IR]A Strategy for Expert Recommendation From Open Data Available on the Lattes Platform
• [cs.IR]A formal approach for customization of schema.org based on SHACL
• [cs.IR]A/B Testing Measurement Framework for Recommendation Models Based on Expected Revenue
• [cs.IR]ConTrOn: Continuously Trained Ontology based on Technical Data Sheets and Wikidata
• [cs.IR]Relevance Feedback with Latent Variables in Riemann spaces
• [cs.IR]SEntNet: Source-aware Recurrent Entity Network for Dialogue Response Selection
• [cs.IT]An End-to-End Block Autoencoder For Physical Layer Based On Neural Networks
• [cs.IT]Constructions and necessities of some permutation polynomials
• [cs.IT]Covert Communication Over a Compound Channel
• [cs.IT]Density Evolution Analysis of Partially Information Coupled Turbo Codes on the Erasure Channel
• [cs.IT]Distributed Source Simulation With No Communication
• [cs.IT]Large Intelligent Surface/Antennas (LISA): Making Reflective Radios Smart
• [cs.IT]Lattice Coding for Downlink Multiuser Transmission
• [cs.IT]On the Performance of Low-Altitude UAV-Enabled Secure AF Relaying with Cooperative Jamming and SWIPT
• [cs.IT]Optimal Power Control for Over-the-Air Computation in Fading Channels
• [cs.IT]Performance Analysis of Blockchain Systems with Wireless Mobile Miners
• [cs.IT]Uplink Non-Orthogonal Multiple Access for UAV Communications
• [cs.LG]A Closer Look at Double Backpropagation
• [cs.LG]A General Interpretation of Deep Learning by Affine Transform and Region Dividing without Mutual Interference
• [cs.LG]A Provably Correct and Robust Algorithm for Convolutive Nonnegative Matrix Factorization
• [cs.LG]A Survey of Optimization Methods from a Machine Learning Perspective
• [cs.LG]ASAC: Active Sensing using Actor-Critic models
• [cs.LG]Active Generative Adversarial Network for Image Classification
• [cs.LG]Active Learning by Greedy Split and Label Exploration
• [cs.LG]Adversarial attacks on Copyright Detection Systems
• [cs.LG]Asymptotic Risk of Bezier Simplex Fitting
• [cs.LG]Attributed Graph Clustering: A Deep Attentional Embedding Approach
• [cs.LG]Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory
• [cs.LG]CheckNet: Secure Inference on Untrusted Devices
• [cs.LG]Conditional Computation for Continual Learning
• [cs.LG]Dataset shift quantification for credit card fraud detection
• [cs.LG]Dealing with the database variability problem in learning from medical data: an ensemble-based approach using convolutional neural networks and a case of study applied to automatic sleep scoring
• [cs.LG]Deep Learning of Preconditioners for Conjugate Gradient Solvers in Urban Water Related Problems
• [cs.LG]Deep Set Prediction Networks
• [cs.LG]Exact and Consistent Interpretation of Piecewise Linear Models Hidden behind APIs: A Closed Form Solution
• [cs.LG]Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias
• [cs.LG]Fixing Gaussian Mixture VAEs for Interpretable Text Generation
• [cs.LG]Generating Diverse and Informative Natural Language Fashion Feedback
• [cs.LG]Global optimization via inverse distance weighting
• [cs.LG]Hierarchical Soft Actor-Critic: Adversarial Exploration via Mutual Information Optimization
• [cs.LG]High-Performance Deep Learning via a Single Building Block
• [cs.LG]Improving Black-box Adversarial Attacks with a Transfer-based Prior
• [cs.LG]Injecting Prior Knowledge for Transfer Learning into Reinforcement Learning Algorithms using Logic Tensor Networks
• [cs.LG]Is the Policy Gradient a Gradient?
• [cs.LG]Joint Visual-Textual Embedding for Multimodal Style Search
• [cs.LG]LPaintB: Learning to Paint from Self-SupervisionLPaintB: Learning to Paint from Self-Supervision
• [cs.LG]Learning Interpretable Models Using an Oracle
• [cs.LG]Learning Restricted Boltzmann Machines with Arbitrary External Fields
• [cs.LG]Learning-Driven Exploration for Reinforcement Learning
• [cs.LG]LioNets: Local Interpretation of Neural Networks through Penultimate Layer Decoding
• [cs.LG]MixUp as Directional Adversarial Training
• [cs.LG]Model Compression by Entropy Penalized Reparameterization
• [cs.LG]MoËT: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees
• [cs.LG]Multi-Adversarial Variational Autoencoder Networks
• [cs.LG]Neural Theorem Provers Do Not Learn Rules Without Exploration
• [cs.LG]Normalizing flows for novelty detection in industrial time series data
• [cs.LG]One Epoch Is All You Need
• [cs.LG]Personalized Apprenticeship Learning from Heterogeneous Decision-Makers
• [cs.LG]Reconciling Utility and Membership Privacy via Knowledge Distillation
• [cs.LG]Recovering the parameters underlying the Lorenz-96 chaotic dynamics
• [cs.LG]Reinforcement Learning Driven Heuristic Optimization
• [cs.LG]Robust Federated Learning in a Heterogeneous Environment
• [cs.LG]Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks
• [cs.LG]Sample-Efficient Neural Architecture Search by Learning Action Space
• [cs.LG]Scrubbing Sensitive PHI Data from Medical Records made Easy by SpaCy — A Scalable Model Implementation Comparisons
• [cs.LG]Solution of Two-Player Zero-Sum Game by Successive Relaxation
• [cs.LG]Structured Pruning of Recurrent Neural Networks through Neuron Selection
• [cs.LG]The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks
• [cs.NE]Accelerating Neural ODEs with Spectral Elements
• [cs.NE]Rapid online learning and robust recall in a neuromorphic olfactory circuit
• [cs.NI]Supporting Web Archiving via Web Packaging
• [cs.RO]A Fast and Stable Omnidirectional Walking Engine for the Nao Humanoid Robot
• [cs.RO]Combining Safe Interval Path Planning and Constrained Path Following Control: Preliminary Results
• [cs.RO]DeepTemporalSeg: Temporally Consistent Semantic Segmentation of 3D LiDAR Scans
• [cs.RO]Designing, 3D Printing of a Quadruped Robot and Choice of Materials for Fabrication
• [cs.RO]Embracing Contact: Pushing Multiple Objects with Robot’s Forearm
• [cs.RO]Exploiting Physical Contacts for Robustness Improvement of a Dot-Painting Mission by a Micro Air Vehicle
• [cs.RO]Providentia — A Large Scale Sensing System for the Assistance of Autonomous Vehicles
• [cs.RO]Reinforcement Learning with Non-uniform State Representations for Adaptive Search
• [cs.RO]Robotic Navigation using Entropy-Based Exploration
• [cs.RO]Simple Swarm Foraging Algorithm Based on Gradient Computation
• [cs.RO]Trajectory Tracking for Quadrotors with Attitude Control on $\mathcal{S}^2 \times \mathcal{S}^1$
• [cs.RO]Understanding Natural Language Instructions for Fetching Daily Objects Using GAN-Based Multimodal Target-Source Classification
• [cs.RO]Usability Squared: Principles for doing good systems research in robotics
• [cs.RO]ViTa-SLAM: A Bio-inspired Visuo-Tactile SLAM for Navigation while Interacting with Aliased Environments
• [cs.SD]Modeling Consonance and its Relationships with Temperament, Harmony, and Electronic Amplification
• [cs.SD]Modeling Music Modality with a Key-Class Invariant Pitch Chroma CNN
• [cs.SD]Multi-scale Embedded CNN for Music Tagging (MsE-CNN)
• [cs.SE]Machine Learning Software Engineering in Practice: An Industrial Case Study
• [cs.SI]Homogeneous Network Embedding for Massive Graphs via Personalized PageRank
• [cs.SI]Interactive health communication and the construction of the identity of the person with low vision in social media
• [cs.SI]Linear-time Hierarchical Community Detection
• [cs.SI]Media Environment, Dual Process and Polarization: A Computational Approach
• [cs.SI]Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling
• [econ.EM]Posterior Average Effects
• [eess.IV]4D X-Ray CT Reconstruction using Multi-Slice Fusion
• [eess.IV]A Fusion Adversarial Network for Underwater Image Enhancement
• [eess.IV]Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal
• [eess.IV]Particle Swarm Optimization for Great Enhancement in Semi-Supervised Retinal Vessel Segmentation with Generative Adversarial Networks
• [eess.IV]Single Image Super-resolution via Dense Blended Attention Generative Adversarial Network for Clinical Diagnosis
• [eess.IV]Speeding up VP9 Intra Encoder with Hierarchical Deep Learning Based Partition Prediction
• [eess.SP]Beam Entropy of 5G Cellular Millimetre Wave Channels
• [eess.SP]Deep Recurrent Adversarial Learning for Privacy-Preserving Smart Meter Data Release
• [math.OC]An efficient Lagrangian-based heuristic to solve a multi-objective sustainable supply chain problem
• [math.OC]Productivity equation and the m distributions of information processing in workflows
• [math.ST]Community Detection Based on the $L_\infty$ convergence of eigenvectors in DCBM
• [math.ST]Designing Test Information and Test Information in Design
• [math.ST]Minimax Density Estimation on Sobolev Spaces With Dominating Mixed Smoothness
• [math.ST]On the Locally Lipschitz Robustness of Bayesian Inverse Problems
• [physics.data-an]Detecting new signals under background mismodelling
• [q-bio.GN]Nested partitions from hierarchical clustering statistical validation
• [stat.AP]Bayesian Finite Population Modeling for Spatial Process Settings
• [stat.AP]Bayesian spatial extreme value analysis of maximum temperatures in County Dublin, Ireland
• [stat.AP]Identifying and characterizing extrapolation in multivariateresponse data
• [stat.AP]Linear regression with stationary errors : the R package slm
• [stat.AP]Parametric and non-parametric estimation of extreme earthquake event: the joint tail inference for mainshocks and aftershocks
• [stat.CO]A tunable multiresolution smoother for scattered data with application to particle filtering
• [stat.CO]lpdensity: Local Polynomial Density Estimation and Inference
• [stat.ME]Adaptive Variable Selection for Sequential Prediction in Multivariate Dynamic Models
• [stat.ME]An Optimal Test for the Additive Model with Discrete or Categorical Predictors
• [stat.ME]Depth-based Weighted Jackknife Empirical Likelihood for Non-smooth U-structure Equations
• [stat.ME]From Incomplete, Dynamic Data to Bayesian Networks
• [stat.ME]Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression
• [stat.ME]Linear Aggregation in Tree-based Estimators
• [stat.ME]Non parametric estimation of Joint entropy and Shannon mutual information, Asymptotic limits: Application to statistic tests
• [stat.ME]Probabilistic Diffusion MRI Fiber Tracking Using a Directed Acyclic Graph Auto-Regressive Model of Positive Definite Matrices
• [stat.ME]Sample Size Calculations for SMARTs
• [stat.ML]A Bayesian Solution to the M-Bias Problem
• [stat.ML]Automatic Relevance Determination Bayesian Neural Networks for Credit Card Default Modelling
• [stat.ML]Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
• [stat.ML]Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy
• [stat.ML]Metric on random dynamical systems with vector-valued reproducing kernel Hilbert spaces
• [stat.ML]Replacing the do-calculus with Bayes rule
• [stat.ML]Sampler for Composition Ratio by Markov Chain Monte Carlo
• [stat.ML]Smooth function approximation by deep neural networks with general activation functions
• [stat.ML]Stacked Capsule Autoencoders
• [stat.ML]The Price of Local Fairness in Multistage Selection
• [stat.ML]The True Sample Complexity of Identifying Good Arms
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• [cs.AI]A Computational-Hermeneutic Approach for Conceptual Explicitation
David Fuenmayor, Christoph Benzmüller
http://arxiv.org/abs/1906.06582v1
• [cs.AI]A new approach to forecasting service parts demand by integrating user preferences into multi-objective optimization
Wenli Ouyang
http://arxiv.org/abs/1906.06816v1
• [cs.AI]Efficient predicate invention using shared “NeMuS”
Edjard Mota, Jacob M. Howe, Ana Schramm, Artur d’Avila Garcez
http://arxiv.org/abs/1906.06455v1
• [cs.AI]Self-organized inductive reasoning with NeMuS
Leonardo Barreto, Edjard Mota
http://arxiv.org/abs/1906.06761v1
• [cs.AI]Towards Empathetic Planning
Maayan Shvo, Sheila A. McIlraith
http://arxiv.org/abs/1906.06436v1
• [cs.CC]Running Time Analysis of the (1+1)-EA for Robust Linear Optimization
Chao Bian, Chao Qian, Ke Tang
http://arxiv.org/abs/1906.06873v1
• [cs.CL]“My Way of Telling a Story”: Persona based Grounded Story Generation
Shrimai Prabhumoye, Khyathi Raghavi Chandu, Ruslan Salakhutdinov, Alan W Black
http://arxiv.org/abs/1906.06401v1
• [cs.CL]A Hierarchical Attention Based Seq2seq Model for Chinese Lyrics Generation
Haoshen Fan, Jie Wang, Bojin Zhuang, Shaojun Wang, Jing Xiao
http://arxiv.org/abs/1906.06481v1
• [cs.CL]A weakly supervised sequence tagging and grammar induction approach to semantic frame slot filling
Janneke van de Loo, Guy De Pauw, Walter Daelemans
http://arxiv.org/abs/1906.06493v1
• [cs.CL]Adversarial Training for Multilingual Acoustic Modeling
Ke Hu, Hasim Sak, Hank Liao
http://arxiv.org/abs/1906.07093v1
• [cs.CL]An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis
Ruidan He, Wee Sun Lee, Hwee Tou Ng, Daniel Dahlmeier
http://arxiv.org/abs/1906.06906v1
• [cs.CL]Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA
Yichen Jiang, Mohit Bansal
http://arxiv.org/abs/1906.07132v1
• [cs.CL]BERE: An accurate distantly supervised biomedical entity relation extraction network
Lixiang Hong, JinJian Lin, Jiang Tao, Jianyang Zeng
http://arxiv.org/abs/1906.06916v1
• [cs.CL]Can neural networks understand monotonicity reasoning?
Hitomi Yanaka, Koji Mineshima, Daisuke Bekki, Kentaro Inui, Satoshi Sekine, Lasha Abzianidze, Johan Bos
http://arxiv.org/abs/1906.06448v1
• [cs.CL]Context is Key: Grammatical Error Detection with Contextual Word Representations
Samuel Bell, Helen Yannakoudakis, Marek Rei
http://arxiv.org/abs/1906.06593v1
• [cs.CL]Context-aware Embedding for Targeted Aspect-based Sentiment Analysis
Bin Liang, Jiachen Du, Ruifeng Xu, Binyang Li, Hejiao Huang
http://arxiv.org/abs/1906.06945v1
• [cs.CL]Correlating Twitter Language with Community-Level Health Outcomes
Arno Schneuwly, Ralf Grubenmann, Mark Cieliebak, Martin Jaggi
http://arxiv.org/abs/1906.06465v1
• [cs.CL]Coupling Retrieval and Meta-Learning for Context-Dependent Semantic Parsing
Daya Guo, Duyu Tang, Nan Duan, Ming Zhou, Jian Yin
http://arxiv.org/abs/1906.07108v1
• [cs.CL]Improving Background Based Conversation with Context-aware Knowledge Pre-selection
Yangjun Zhang, Pengjie Ren, Maarten de Rijke
http://arxiv.org/abs/1906.06685v1
• [cs.CL]Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling
Yifan Gao, Piji Li, Irwin King, Michael R. Lyu
http://arxiv.org/abs/1906.06893v1
• [cs.CL]Making Fast Graph-based Algorithms with Graph Metric Embeddings
Andrey Kutuzov, Mohammad Dorgham, Oleksiy Oliynyk, Chris Biemann, Alexander Panchenko
http://arxiv.org/abs/1906.07040v1
• [cs.CL]Manipulating the Difficulty of C-Tests
Ji-Ung Lee, Erik Schwan, Christian M. Meyer
http://arxiv.org/abs/1906.06905v1
• [cs.CL]Multi-Hop Paragraph Retrieval for Open-Domain Question Answering
Yair Feldman, Ran El-Yaniv
http://arxiv.org/abs/1906.06606v1
• [cs.CL]Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification
Zhi-Xiu Ye, Zhen-Hua Ling
http://arxiv.org/abs/1906.06678v1
• [cs.CL]Neural Decipherment via Minimum-Cost Flow: from Ugaritic to Linear B
Jiaming Luo, Yuan Cao, Regina Barzilay
http://arxiv.org/abs/1906.06718v1
• [cs.CL]Open Domain Event Extraction Using Neural Latent Variable Models
Xiao Liu, Heyan Huang, Yue Zhang
http://arxiv.org/abs/1906.06947v1
• [cs.CL]Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good
Xuewei Wang, Weiyan Shi, Richard Kim, Yoojung Oh, Sijia Yang, Jingwen Zhang, Zhou Yu
http://arxiv.org/abs/1906.06725v1
• [cs.CL]Practical User Feedback-driven Internal Search Using Online Learning to Rank
Rajhans Samdani, Pierre Rappolt, Ankit Goyal, Pratyus Patnaik
http://arxiv.org/abs/1906.06581v1
• [cs.CL]Principled Frameworks for Evaluating Ethics in NLP Systems
Shrimai Prabhumoye, Elijah Mayfield, Alan W Black
http://arxiv.org/abs/1906.06425v1
• [cs.CL]Recursive Style Breach Detection with Multifaceted Ensemble Learning
Daniel Kopev, Dimitrina Zlatkova, Kristiyan Mitov, Atanas Atanasov, Momchil Hardalov, Ivan Koychev, Preslav Nakov
http://arxiv.org/abs/1906.06917v1
• [cs.CL]Robust Zero-Shot Cross-Domain Slot Filling with Example Values
Darsh J Shah, Raghav Gupta, Amir A Fayazi, Dilek Hakkani-Tur
http://arxiv.org/abs/1906.06870v1
• [cs.CL]Scalable Syntax-Aware Language Models Using Knowledge Distillation
Adhiguna Kuncoro, Chris Dyer, Laura Rimell, Stephen Clark, Phil Blunsom
http://arxiv.org/abs/1906.06438v1
• [cs.CL]Tagged Back-Translation
Isaac Caswell, Ciprian Chelba, David Grangier
http://arxiv.org/abs/1906.06442v1
• [cs.CL]Theoretical Limitations of Self-Attention in Neural Sequence Models
Michael Hahn
http://arxiv.org/abs/1906.06755v1
• [cs.CL]Towards Integration of Statistical Hypothesis Tests into Deep Neural Networks
Ahmad Aghaebrahimian, Mark Cieliebak
http://arxiv.org/abs/1906.06550v1
• [cs.CL]Using Automatically Extracted Minimum Spans to Disentangle Coreference Evaluation from Boundary Detection
Nafise Sadat Moosavi, Leo Born, Massimo Poesio, Michael Strube
http://arxiv.org/abs/1906.06703v1
• [cs.CR]A Secure Consensus Protocol for Sidechains
Fangyu Gai, Cesar Grajales, Jianyu Niu, Chen Feng
http://arxiv.org/abs/1906.06490v1
• [cs.CR]Physical Integrity Attack Detection of Surveillance Camera with Deep Learning Based Video Frame Interpolation
Jonathan Pan
http://arxiv.org/abs/1906.06475v1
• [cs.CV]A Temporal Sequence Learning for Action Recognition and Prediction
Sangwoo Cho, Hassan Foroosh
http://arxiv.org/abs/1906.06813v1
• [cs.CV]Back-Projection based Fidelity Term for Ill-Posed Linear Inverse Problems
Tom Tirer, Raja Giryes
http://arxiv.org/abs/1906.06794v1
• [cs.CV]Beyond Product Quantization: Deep Progressive Quantization for Image Retrieval
Lianli Gao, Xiaosu Zhu, Jingkuan Song, Zhou Zhao, Heng Tao Shen
http://arxiv.org/abs/1906.06698v1
• [cs.CV]Boosting Supervision with Self-Supervision for Few-shot Learning
Jong-Chyi Su, Subhransu Maji, Bharath Hariharan
http://arxiv.org/abs/1906.07079v1
• [cs.CV]Deep Recurrent Quantization for Generating Sequential Binary Codes
Jingkuan Song, Xiaosu Zhu, Lianli Gao, Xin-Shun Xu, Wu Liu, Heng Tao Shen
http://arxiv.org/abs/1906.06699v1
• [cs.CV]DeepMOT: A Differentiable Framework for Training Multiple Object Trackers
Yihong Xu, Yutong Ban, Xavier Alameda-Pineda, Radu Horaud
http://arxiv.org/abs/1906.06618v1
• [cs.CV]Defending Against Adversarial Attacks Using Random Forests
Yifan Ding, Liqiang Wang, Huan Zhang, Jinfeng Yi, Deliang Fan, Boqing Gong
http://arxiv.org/abs/1906.06765v1
• [cs.CV]Delving into 3D Action Anticipation from Streaming Videos
Hongsong Wang, Jiashi Feng
http://arxiv.org/abs/1906.06521v1
• [cs.CV]Detecting Bias with Generative Counterfactual Face Attribute Augmentation
Emily Denton, Ben Hutchinson, Margaret Mitchell, Timnit Gebru
http://arxiv.org/abs/1906.06439v1
• [cs.CV]EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse
YoungJoon Yoo, Dongyoon Han, Sangdoo Yun
http://arxiv.org/abs/1906.06579v1
• [cs.CV]Efficient Neural Network Approaches for Leather Defect Classification
Sze-Teng Liong, Y. S. Gan, Kun-Hong Liu, Tran Quang Binh, Cong Tue Le, Chien An Wu, Cheng-Yan Yang, Yen-Chang Huang
http://arxiv.org/abs/1906.06446v1
• [cs.CV]EnlightenGAN: Deep Light Enhancement without Paired Supervision
Yifan Jiang, Xinyu Gong, Ding Liu, Yu Cheng, Chen Fang, Xiaohui Shen, Jianchao Yang, Pan Zhou, Zhangyang Wang
http://arxiv.org/abs/1906.06972v1
• [cs.CV]Exemplar Guided Face Image Super-Resolution without Facial Landmarks
Berk Dogan, Shuhang Gu, Radu Timofte
http://arxiv.org/abs/1906.07078v1
• [cs.CV]Fixing the train-test resolution discrepancy
Hugo Touvron, Andrea Vedaldi, Matthijs Douze, Hervé Jégou
http://arxiv.org/abs/1906.06423v1
• [cs.CV]Floors are Flat: Leveraging Semantics for Real-Time Surface Normal Prediction
Steven Hickson, Karthik Raveendran, Alireza Fathi, Kevin Murphy, Irfan Essa
http://arxiv.org/abs/1906.06792v1
• [cs.CV]Hallucinated Adversarial Learning for Robust Visual Tracking
Qiangqiang Wu, Zhihui Chen, Lin Cheng, Yan Yan, Bo Li, Hanzi Wang
http://arxiv.org/abs/1906.07008v1
• [cs.CV]Hierarchical Back Projection Network for Image Super-Resolution
Zhi-Song Liu, Li-Wen Wang, Chu-Tak Li, Wan-Chi Siu
http://arxiv.org/abs/1906.06874v1
• [cs.CV]IMP: Instance Mask Projection for High Accuracy Semantic Segmentation of Things
Cheng-Yang Fu, Tamara L. Berg, Alexander C. Berg
http://arxiv.org/abs/1906.06597v1
• [cs.CV]Image Captioning with Integrated Bottom-Up and Multi-level Residual Top-Down Attention for Game Scene Understanding
Jian Zheng, Sudha Krishnamurthy, Ruxin Chen, Min-Hung Chen, Zhenhao Ge, Xiaohua Li
http://arxiv.org/abs/1906.06632v1
• [cs.CV]Image-based 3D Object Reconstruction: State-of-the-Art and Trends in the Deep Learning Era
Xian-Feng Han, Hamid Laga, Mohammed Bennamoun
http://arxiv.org/abs/1906.06543v1
• [cs.CV]Improving temporal action proposal generation by using high performance computing
Tian Wang, Shiye Lei, Youyou Jiang, Zihang Deng, Xin Su, Hichem Snoussi, Chang Choi
http://arxiv.org/abs/1906.06496v1
• [cs.CV]Learning Part Generation and Assembly for Structure-aware Shape Synthesis
Jun Li, Chengjie Niu, Kai Xu
http://arxiv.org/abs/1906.06693v1
• [cs.CV]MMDetection: Open MMLab Detection Toolbox and Benchmark
Kai Chen, Jiaqi Wang, Jiangmiao Pang, Yuhang Cao, Yu Xiong, Xiaoxiao Li, Shuyang Sun, Wansen Feng, Ziwei Liu, Jiarui Xu, Zheng Zhang, Dazhi Cheng, Chenchen Zhu, Tianheng Cheng, Qijie Zhao, Buyu Li, Xin Lu, Rui Zhu, Yue Wu, Jifeng Dai, Jingdong Wang, Jianping Shi, Wanli Ouyang, Chen Change Loy, Dahua Lin
http://arxiv.org/abs/1906.07155v1
• [cs.CV]MV-C3D: A Spatial Correlated Multi-View 3D Convolutional Neural Networks
Qi Xuan, Fuxian Li, Yi Liu, Yun Xiang
http://arxiv.org/abs/1906.06538v1
• [cs.CV]Machine-Assisted Map Editing
Favyen Bastani, Songtao He, Sofiane Abbar, Mohammad Alizadeh, Hari Balakrishnan, Sanjay Chawla, Sam Madden
http://arxiv.org/abs/1906.07138v1
• [cs.CV]Mask Based Unsupervised Content Transfer
Ron Mokady, Sagie Benaim, Lior Wolf, Amit Bermano
http://arxiv.org/abs/1906.06558v1
• [cs.CV]Mixture separability loss in a deep convolutional network for image classification
Trung Dung Do, Cheng-Bin Jin, Hakil Kim, Van Huan Nguyen
http://arxiv.org/abs/1906.06633v1
• [cs.CV]Multi-Scale Convolutions for Learning Context Aware Feature Representations
Nikolai Ufer, Kam To Lui, Katja Schwarz, Paul Warkentin, Björn Ommer
http://arxiv.org/abs/1906.06978v1
• [cs.CV]Multi-task Learning For Detecting and Segmenting Manipulated Facial Images and Videos
Huy H. Nguyen, Fuming Fang, Junichi Yamagishi, Isao Echizen
http://arxiv.org/abs/1906.06876v1
• [cs.CV]NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising
Yingkun Hou, Jun Xu, Mingxia Liu, Guanghai Liu, Li Liu, Fan Zhu, Ling Shao
http://arxiv.org/abs/1906.06834v1
• [cs.CV]Noisy-As-Clean: Learning Unsupervised Denoising from the Corrupted Image
Jun Xu, Yuan Huang, Li Liu, Fan Zhu, Xingsong Hou, Ling Shao
http://arxiv.org/abs/1906.06878v1
• [cs.CV]On the Self-Similarity of Natural Stochastic Textures
Samah Khawaled, Yehoshua Y. Zeevi
http://arxiv.org/abs/1906.06768v1
• [cs.CV]On training deep networks for satellite image super-resolution
Michal Kawulok, Szymon Piechaczek, Krzysztof Hrynczenko, Pawel Benecki, Daniel Kostrzewa, Jakub Nalepa
http://arxiv.org/abs/1906.06697v1
• [cs.CV]Panoptic Image Annotation with a Collaborative Assistant
Jasper R. R. Uijlings, Mykhaylo Andriluka, Vittorio Ferrari
http://arxiv.org/abs/1906.06798v1
• [cs.CV]ParNet: Position-aware Aggregated Relation Network for Image-Text matching
Yaxian Xia, Lun Huang, Wenmin Wang, Xiaoyong Wei, Wenmin Wang
http://arxiv.org/abs/1906.06892v1
• [cs.CV]RECAL: Reuse of Established CNN classifer Apropos unsupervised Learning paradigm
Jayasree Saha, Jayanta Mukhopadhyay
http://arxiv.org/abs/1906.06480v1
• [cs.CV]REMAP: Multi-layer entropy-guided pooling of dense CNN features for image retrieval
Syed Sameed Husain, Miroslaw Bober
http://arxiv.org/abs/1906.06626v1
• [cs.CV]Realistic Speech-Driven Facial Animation with GANs
Konstantinos Vougioukas, Stavros Petridis, Maja Pantic
http://arxiv.org/abs/1906.06337v1
• [cs.CV]STAR: A Structure and Texture Aware Retinex Model
Jun Xu, Mengyang Yu, Li Liu, Fan Zhu, Dongwei Ren, Yingkun Hou, Haoqian Wang, Ling Shao
http://arxiv.org/abs/1906.06690v1
• [cs.CV]Semi-Supervised Semantic Mapping through Label Propagation with Semantic Texture Meshes
Radu Alexandru Rosu, Jan Quenzel, Sven Behnke
http://arxiv.org/abs/1906.07029v1
• [cs.CV]Spatio-Temporal Fusion Networks for Action Recognition
Sangwoo Cho, Hassan Foroosh
http://arxiv.org/abs/1906.06822v1
• [cs.CV]Three-Dimensional Fourier Scattering Transform and Classification of Hyperspectral Images
Ilya Kavalerov, Weilin Li, Wojciech Czaja, Rama Chellappa
http://arxiv.org/abs/1906.06804v1
• [cs.CV]Towards Real-Time Action Recognition on Mobile Devices Using Deep Models
Chen-Lin Zhang, Xin-Xin Liu, Jianxin Wu
http://arxiv.org/abs/1906.07052v1
• [cs.CV]Uncovering Why Deep Neural Networks Lack Robustness: Representation Metrics that Link to Adversarial Attacks
Danilo Vasconcellos Vargas, Shashank Kotyan, Moe Matsuki
http://arxiv.org/abs/1906.06627v1
• [cs.CV]VRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction
Hongsong Wang, Jiashi Feng
http://arxiv.org/abs/1906.06514v1
• [cs.CY]A multi-layered blockchain framework for smart mobility data-markets
David Lopez, Bilal Farooq
http://arxiv.org/abs/1906.06435v1
• [cs.CY]AI Ethics — Too Principled to Fail?
Brent Mittelstadt
http://arxiv.org/abs/1906.06668v1
• [cs.DB]Distributed Subtrajectory Clustering
Panagiotis Tampakis, Nikos Pelekis, Christos Doulkeridis, Yannis Theodoridis
http://arxiv.org/abs/1906.06956v1
• [cs.DC]Accelerating Concurrent Heap on GPUs
Yanhao Chen, Fei Hua, Chaozhang Huang, Jeremy Bierema, Chi Zhang, Eddy Z. Zhang
http://arxiv.org/abs/1906.06504v1
• [cs.DC]Near Optimal Coflow Scheduling in Networks
Mosharaf Chowdhury, Samir Khuller, Manish Purohit, Sheng Yang, Jie You
http://arxiv.org/abs/1906.06851v1
• [cs.DC]Self-Stabilizing Snapshot Objects for Asynchronous Fail-Prone Network Systems
Chryssis Georgiou, Oskar Lundström, Elad Michael Schiller
http://arxiv.org/abs/1906.06420v1
• [cs.DC]Service Placement with Provable Guarantees in Heterogeneous Edge Computing Systems
Stephen Pasteris, Shiqiang Wang, Mark Herbster, Ting He
http://arxiv.org/abs/1906.07055v1
• [cs.DM]A concise guide to existing and emerging vehicle routing problem variants
Thibaut Vidal, Gilbert Laporte, Piotr Matl
http://arxiv.org/abs/1906.06750v1
• [cs.DS]A New Family of Tractable Ising Models
Valerii Likhosherstov, Yury Maximov, Michael Chertkov
http://arxiv.org/abs/1906.06431v1
• [cs.DS]Monotonically relaxing concurrent data-structure semantics for performance: An efficient 2D design framework
Adones Rukundo, Aras Atalar, Philippas Tsigas
http://arxiv.org/abs/1906.07105v1
• [cs.GR]A Statistical View on Synthetic Aperture Imaging for Occlusion Removal
Indrajit Kurmi, David C. Schedl, Oliver Bimber
http://arxiv.org/abs/1906.06600v1
• [cs.IR]A Multi-Task Architecture on Relevance-based Neural Query Translation
Sheikh Muhammad Sarwar, Hamed Bonab, James Allan
http://arxiv.org/abs/1906.06849v1
• [cs.IR]A Strategy for Expert Recommendation From Open Data Available on the Lattes Platform
Sérgio José de Sousa, Thiago Magela Rodrigues Dias, Adilson Luiz Pinto
http://arxiv.org/abs/1906.06437v1
• [cs.IR]A formal approach for customization of schema.org based on SHACL
Umutcan Şimşek, Kevin Angele, Elias Kärle, Oleksandra Panasiuk, Dieter Fensel
http://arxiv.org/abs/1906.06492v1
• [cs.IR]A/B Testing Measurement Framework for Recommendation Models Based on Expected Revenue
Meisam Hejazinia, Majid Hosseini, Bryant Sih
http://arxiv.org/abs/1906.06390v1
• [cs.IR]ConTrOn: Continuously Trained Ontology based on Technical Data Sheets and Wikidata
Kobkaew Opasjumruskit, Diana Peters, Sirko Schindler
http://arxiv.org/abs/1906.06752v1
• [cs.IR]Relevance Feedback with Latent Variables in Riemann spaces
Simone Santini
http://arxiv.org/abs/1906.06526v1
• [cs.IR]SEntNet: Source-aware Recurrent Entity Network for Dialogue Response Selection
Jiahuan Pei, Arent Stienstra, Julia Kiseleva, Maarten de Rijke
http://arxiv.org/abs/1906.06788v1
• [cs.IT]An End-to-End Block Autoencoder For Physical Layer Based On Neural Networks
Tianjie Mu, Xiaohui Chen, Li Chen, Huarui Yin, Weidong Wang
http://arxiv.org/abs/1906.06563v1
• [cs.IT]Constructions and necessities of some permutation polynomials
Xiaogang Liu
http://arxiv.org/abs/1906.06453v1
• [cs.IT]Covert Communication Over a Compound Channel
Sadaf Salehkalaibar, Mohammad Hossein Yassaee, Vincent Y. F. Tan
http://arxiv.org/abs/1906.06675v1
• [cs.IT]Density Evolution Analysis of Partially Information Coupled Turbo Codes on the Erasure Channel
Min Qiu, Xiaowei Wu, Yixuan Xie, Jinhong Yuan
http://arxiv.org/abs/1906.06649v1
• [cs.IT]Distributed Source Simulation With No Communication
Tomer Berg, Ofer Shayevitz, Young-Han Kim, Lele Wang
http://arxiv.org/abs/1906.06970v1
• [cs.IT]Large Intelligent Surface/Antennas (LISA): Making Reflective Radios Smart
Ying-Chang Liang, Ruizhe Long, Qianqian Zhang, Jie Chen, Hei Victor Cheng, Huayan Guo
http://arxiv.org/abs/1906.06578v1
• [cs.IT]Lattice Coding for Downlink Multiuser Transmission
Min Qiu
http://arxiv.org/abs/1906.06651v1
• [cs.IT]On the Performance of Low-Altitude UAV-Enabled Secure AF Relaying with Cooperative Jamming and SWIPT
Milad Tatar Mamaghani, Yi Hong
http://arxiv.org/abs/1906.06867v1
• [cs.IT]Optimal Power Control for Over-the-Air Computation in Fading Channels
Xiaowen Cao, Guangxu Zhu, Jie Xu, Kaibin Huang
http://arxiv.org/abs/1906.06858v1
• [cs.IT]Performance Analysis of Blockchain Systems with Wireless Mobile Miners
Gilsoo Lee, Jihong Park, Walid Saad, Mehdi Bennis
http://arxiv.org/abs/1906.06759v1
• [cs.IT]Uplink Non-Orthogonal Multiple Access for UAV Communications
Xidong Mu, Yuanwei Liu, Li Guo, Jiaru Lin
http://arxiv.org/abs/1906.06523v1
• [cs.LG]A Closer Look at Double Backpropagation
Christian Etmann
http://arxiv.org/abs/1906.06637v1
• [cs.LG]A General Interpretation of Deep Learning by Affine Transform and Region Dividing without Mutual Interference
Changcun Huang
http://arxiv.org/abs/1906.06706v1
• [cs.LG]A Provably Correct and Robust Algorithm for Convolutive Nonnegative Matrix Factorization
Anthony Degleris, Nicolas Gillis
http://arxiv.org/abs/1906.06899v1
• [cs.LG]A Survey of Optimization Methods from a Machine Learning Perspective
Shiliang Sun, Zehui Cao, Han Zhu, Jing Zhao
http://arxiv.org/abs/1906.06821v1
• [cs.LG]ASAC: Active Sensing using Actor-Critic models
Jinsung Yoon, James Jordon, Mihaela van der Schaar
http://arxiv.org/abs/1906.06796v1
• [cs.LG]Active Generative Adversarial Network for Image Classification
Quan Kong, Bin Tong, Martin Klinkigt, Yuki Watanabe, Naoto Akira, Tomokazu Murakami
http://arxiv.org/abs/1906.07133v1
• [cs.LG]Active Learning by Greedy Split and Label Exploration
Alyssa Herbst, Bert Huang
http://arxiv.org/abs/1906.07046v1
• [cs.LG]Adversarial attacks on Copyright Detection Systems
Parsa Saadatpanah, Ali Shafahi, Tom Goldstein
http://arxiv.org/abs/1906.07153v1
• [cs.LG]Asymptotic Risk of Bezier Simplex Fitting
Akinori Tanaka, Akiyoshi Sannai, Ken Kobayashi, Naoki Hamada
http://arxiv.org/abs/1906.06924v1
• [cs.LG]Attributed Graph Clustering: A Deep Attentional Embedding Approach
Chun Wang, Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Chengqi Zhang
http://arxiv.org/abs/1906.06532v1
• [cs.LG]Characterizing the Exact Behaviors of Temporal Difference Learning Algorithms Using Markov Jump Linear System Theory
Bin Hu, Usman Ahmed Syed
http://arxiv.org/abs/1906.06781v1
• [cs.LG]CheckNet: Secure Inference on Untrusted Devices
Marcus Comiter, Surat Teerapittayanon, H. T. Kung
http://arxiv.org/abs/1906.07148v1
• [cs.LG]Conditional Computation for Continual Learning
Min Lin, Jie Fu, Yoshua Bengio
http://arxiv.org/abs/1906.06635v1
• [cs.LG]Dataset shift quantification for credit card fraud detection
Yvan Lucas, Pierre-Edouard Portier, Léa Laporte, Sylvie Calabretto, Liyun He-Guelton, Frederic Oblé, Michael Granitzer
http://arxiv.org/abs/1906.06977v1
• [cs.LG]Dealing with the database variability problem in learning from medical data: an ensemble-based approach using convolutional neural networks and a case of study applied to automatic sleep scoring
Diego Alvarez-Estevez, Isaac Fernández-Varela
http://arxiv.org/abs/1906.06666v1
• [cs.LG]Deep Learning of Preconditioners for Conjugate Gradient Solvers in Urban Water Related Problems
Johannes Sappl, Laurent Seiler, Matthias Harders, Wolfgang Rauch
http://arxiv.org/abs/1906.06925v1
• [cs.LG]Deep Set Prediction Networks
Yan Zhang, Jonathon Hare, Adam Prügel-Bennett
http://arxiv.org/abs/1906.06565v1
• [cs.LG]Exact and Consistent Interpretation of Piecewise Linear Models Hidden behind APIs: A Closed Form Solution
Zicun Cong, Lingyang Chu, Lanjun Wang, Xia Hu, Jian Pei
http://arxiv.org/abs/1906.06857v1
• [cs.LG]Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias
Stéphane d’Ascoli, Levent Sagun, Joan Bruna, Giulio Biroli
http://arxiv.org/abs/1906.06766v1
• [cs.LG]Fixing Gaussian Mixture VAEs for Interpretable Text Generation
Wenxian Shi, Hao Zhou, Ning Miao, Shenjian Zhao, Lei Li
http://arxiv.org/abs/1906.06719v1
• [cs.LG]Generating Diverse and Informative Natural Language Fashion Feedback
Gil Sadeh, Lior Fritz, Gabi Shalev, Eduard Oks
http://arxiv.org/abs/1906.06619v1
• [cs.LG]Global optimization via inverse distance weighting
Alberto Bemporad
http://arxiv.org/abs/1906.06498v1
• [cs.LG]Hierarchical Soft Actor-Critic: Adversarial Exploration via Mutual Information Optimization
Ari Azarafrooz, John Brock
http://arxiv.org/abs/1906.07122v1
• [cs.LG]High-Performance Deep Learning via a Single Building Block
Evangelos Georganas, Kunal Banerjee, Dhiraj Kalamkar, Sasikanth Avancha, Anand Venkat, Michael Anderson, Greg Henry, Hans Pabst, Alexander Heinecke
http://arxiv.org/abs/1906.06440v1
• [cs.LG]Improving Black-box Adversarial Attacks with a Transfer-based Prior
Shuyu Cheng, Yinpeng Dong, Tianyu Pang, Hang Su, Jun Zhu
http://arxiv.org/abs/1906.06919v1
• [cs.LG]Injecting Prior Knowledge for Transfer Learning into Reinforcement Learning Algorithms using Logic Tensor Networks
Samy Badreddine, Michael Spranger
http://arxiv.org/abs/1906.06576v1
• [cs.LG]Is the Policy Gradient a Gradient?
Chris Nota, Philip S. Thomas
http://arxiv.org/abs/1906.07073v1
• [cs.LG]Joint Visual-Textual Embedding for Multimodal Style Search
Gil Sadeh, Lior Fritz, Gabi Shalev, Eduard Oks
http://arxiv.org/abs/1906.06620v1
• [cs.LG]LPaintB: Learning to Paint from Self-SupervisionLPaintB: Learning to Paint from Self-Supervision
Biao Jia, Jonathan Brandt, Radomir Mech, Byungmoon Kim, Dinesh Manocha
http://arxiv.org/abs/1906.06841v1
• [cs.LG]Learning Interpretable Models Using an Oracle
Abhishek Ghose, Balaraman Ravindran
http://arxiv.org/abs/1906.06852v1
• [cs.LG]Learning Restricted Boltzmann Machines with Arbitrary External Fields
Surbhi Goel
http://arxiv.org/abs/1906.06595v1
• [cs.LG]Learning-Driven Exploration for Reinforcement Learning
Muhammad Usama, Dong Eui Chang
http://arxiv.org/abs/1906.06890v1
• [cs.LG]LioNets: Local Interpretation of Neural Networks through Penultimate Layer Decoding
Ioannis Mollas, Nikolaos Bassiliades, Grigorios Tsoumakas
http://arxiv.org/abs/1906.06566v1
• [cs.LG]MixUp as Directional Adversarial Training
Guillaume P. Archambault, Yongyi Mao, Hongyu Guo, Richong Zhang
http://arxiv.org/abs/1906.06875v1
• [cs.LG]Model Compression by Entropy Penalized Reparameterization
Deniz Oktay, Johannes Ballé, Saurabh Singh, Abhinav Shrivastava
http://arxiv.org/abs/1906.06624v1
• [cs.LG]MoËT: Interpretable and Verifiable Reinforcement Learning via Mixture of Expert Trees
Marko Vasic, Andrija Petrovic, Kaiyuan Wang, Mladen Nikolic, Rishabh Singh, Sarfraz Khurshid
http://arxiv.org/abs/1906.06717v1
• [cs.LG]Multi-Adversarial Variational Autoencoder Networks
Abdullah-Al-Zubaer Imran, Demetri Terzopoulos
http://arxiv.org/abs/1906.06430v1
• [cs.LG]Neural Theorem Provers Do Not Learn Rules Without Exploration
Michiel de Jong, Fei Sha
http://arxiv.org/abs/1906.06805v1
• [cs.LG]Normalizing flows for novelty detection in industrial time series data
Maximilian Schmidt, Marko Simic
http://arxiv.org/abs/1906.06904v1
• [cs.LG]One Epoch Is All You Need
Aran Komatsuzaki
http://arxiv.org/abs/1906.06669v1
• [cs.LG]Personalized Apprenticeship Learning from Heterogeneous Decision-Makers
Rohan Paleja, Andrew Silva, Matthew Gombolay
http://arxiv.org/abs/1906.06397v1
• [cs.LG]Reconciling Utility and Membership Privacy via Knowledge Distillation
Virat Shejwalkar, Amir Houmansadr
http://arxiv.org/abs/1906.06589v1
• [cs.LG]Recovering the parameters underlying the Lorenz-96 chaotic dynamics
Soukayna Mouatadid, Pierre Gentine, Wei Yu, Steve Easterbrook
http://arxiv.org/abs/1906.06786v1
• [cs.LG]Reinforcement Learning Driven Heuristic Optimization
Qingpeng Cai, Will Hang, Azalia Mirhoseini, George Tucker, Jingtao Wang, Wei Wei
http://arxiv.org/abs/1906.06639v1
• [cs.LG]Robust Federated Learning in a Heterogeneous Environment
Avishek Ghosh, Justin Hong, Dong Yin, Kannan Ramchandran
http://arxiv.org/abs/1906.06629v1
• [cs.LG]Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks
Felipe A. Mejia, Paul Gamble, Zigfried Hampel-Arias, Michael Lomnitz, Nina Lopatina, Lucas Tindall, Maria Alejandra Barrios
http://arxiv.org/abs/1906.06449v1
• [cs.LG]Sample-Efficient Neural Architecture Search by Learning Action Space
Linnan Wang, Saining Xie, Teng Li, Rodrigo Fonseca, Yuandong Tian
http://arxiv.org/abs/1906.06832v1
• [cs.LG]Scrubbing Sensitive PHI Data from Medical Records made Easy by SpaCy — A Scalable Model Implementation Comparisons
Rashmi Jain, Dinah Samuel Anand, Vijayalakshmi Janakiraman
http://arxiv.org/abs/1906.06968v1
• [cs.LG]Solution of Two-Player Zero-Sum Game by Successive Relaxation
Raghuram Bharadwaj Diddigi, Chandramouli Kamanchi, Shalabh Bhatnagar
http://arxiv.org/abs/1906.06659v1
• [cs.LG]Structured Pruning of Recurrent Neural Networks through Neuron Selection
Liangjiang Wen, Xueyang Zhang, Haoli Bai, Zenglin Xu
http://arxiv.org/abs/1906.06847v1
• [cs.LG]The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks
Felix Assion, Peter Schlicht, Florens Greßner, Wiebke Günther, Fabian Hüger, Nico Schmidt, Umair Rasheed
http://arxiv.org/abs/1906.07077v1
• [cs.NE]Accelerating Neural ODEs with Spectral Elements
Alessio Quaglino, Marco Gallieri, Jonathan Masci, Jan Koutník
http://arxiv.org/abs/1906.07038v1
• [cs.NE]Rapid online learning and robust recall in a neuromorphic olfactory circuit
Nabil Imam, Thomas A. Cleland
http://arxiv.org/abs/1906.07067v1
• [cs.NI]Supporting Web Archiving via Web Packaging
Sawood Alam, Michele C. Weigle, Michael L. Nelson, Martin Klein, Herbert Van de Sompel
http://arxiv.org/abs/1906.07104v1
• [cs.RO]A Fast and Stable Omnidirectional Walking Engine for the Nao Humanoid Robot
Mohammadreza Kasaei, Nuno Lau, Artur Pereira
http://arxiv.org/abs/1906.06932v1
• [cs.RO]Combining Safe Interval Path Planning and Constrained Path Following Control: Preliminary Results
Konstantin Yakovlev, Anton Andreychuk, Juliya Belinskaya, Dmitry Makarov
http://arxiv.org/abs/1906.06911v1
• [cs.RO]DeepTemporalSeg: Temporally Consistent Semantic Segmentation of 3D LiDAR Scans
Ayush Dewan, Wolfram Burgard
http://arxiv.org/abs/1906.06962v1
• [cs.RO]Designing, 3D Printing of a Quadruped Robot and Choice of Materials for Fabrication
Akash Maity, Koustav Roy, Dhrubajyoti Gupta
http://arxiv.org/abs/1906.06502v1
• [cs.RO]Embracing Contact: Pushing Multiple Objects with Robot’s Forearm
Akansel Cosgun, Luke Ditria, Shayne D’Lima, Tom Drummond
http://arxiv.org/abs/1906.06866v1
• [cs.RO]Exploiting Physical Contacts for Robustness Improvement of a Dot-Painting Mission by a Micro Air Vehicle
Thomas Chaffre, Kevin Tudal, Sylvain Bertrand, Lionel Prevost
http://arxiv.org/abs/1906.06515v1
• [cs.RO]Providentia — A Large Scale Sensing System for the Assistance of Autonomous Vehicles
Annkathrin Krämmer, Christoph Schöller, Dhiraj Gulati, Alois Knoll
http://arxiv.org/abs/1906.06789v1
• [cs.RO]Reinforcement Learning with Non-uniform State Representations for Adaptive Search
Sandeep Manjanna, Herke van Hoof, Gregory Dudek
http://arxiv.org/abs/1906.06588v1
• [cs.RO]Robotic Navigation using Entropy-Based Exploration
Muhammad Usama, Dong Eui Chang
http://arxiv.org/abs/1906.06969v1
• [cs.RO]Simple Swarm Foraging Algorithm Based on Gradient Computation
Simon O. Obute, Mehmet R. Dogar, Jordan H. Boyle
http://arxiv.org/abs/1906.07030v1
• [cs.RO]Trajectory Tracking for Quadrotors with Attitude Control on $\mathcal{S}^2 \times \mathcal{S}^1$
Dave Kooijman, Angela P. Schoellig, Duarte J. Antunes
http://arxiv.org/abs/1906.06926v1
• [cs.RO]Understanding Natural Language Instructions for Fetching Daily Objects Using GAN-Based Multimodal Target-Source Classification
Aly Magassouba, Komei Sugiura, Anh Trinh Quoc, Hisashi Kawai
http://arxiv.org/abs/1906.06830v1
• [cs.RO]Usability Squared: Principles for doing good systems research in robotics
Soham Sankaran, Ross A. Knepper
http://arxiv.org/abs/1906.06775v1
• [cs.RO]ViTa-SLAM: A Bio-inspired Visuo-Tactile SLAM for Navigation while Interacting with Aliased Environments
Oliver Struckmeier, Kshitij Tiwari, Mohammed Salman, Martin J. Pearson, Ville Kyrki
http://arxiv.org/abs/1906.06422v1
• [cs.SD]Modeling Consonance and its Relationships with Temperament, Harmony, and Electronic Amplification
Luciano da Fontoura Costa
http://arxiv.org/abs/1906.06559v1
• [cs.SD]Modeling Music Modality with a Key-Class Invariant Pitch Chroma CNN
Anders Elowsson, Anders Friberg
http://arxiv.org/abs/1906.07145v1
• [cs.SD]Multi-scale Embedded CNN for Music Tagging (MsE-CNN)
Nima Hamidi, Mohsen Vahidzadeh, Stephen Baek
http://arxiv.org/abs/1906.06746v1
• [cs.SE]Machine Learning Software Engineering in Practice: An Industrial Case Study
Md Saidur Rahman, Emilio Rivera, Foutse Khomh, Yann-Gaël Guéhéneuc, Bernd Lehnert
http://arxiv.org/abs/1906.07154v1
• [cs.SI]Homogeneous Network Embedding for Massive Graphs via Personalized PageRank
Renchi Yang, Jieming Shi, Xiaokui Xiao, Sourav S. Bhowmick, Yin Yang
http://arxiv.org/abs/1906.06826v1
• [cs.SI]Interactive health communication and the construction of the identity of the person with low vision in social media
Gustavo Caran, Ronaldo Araujo, Crispulo Travieso-Rodriguez
http://arxiv.org/abs/1906.06545v1
• [cs.SI]Linear-time Hierarchical Community Detection
Ryan A. Rossi, Nesreen K. Ahmed, Eunyee Koh, Sungchul Kim
http://arxiv.org/abs/1906.06432v1
• [cs.SI]Media Environment, Dual Process and Polarization: A Computational Approach
In-Ho Yi
http://arxiv.org/abs/1906.06531v1
• [cs.SI]Supracentrality Analysis of Temporal Networks with Directed Interlayer Coupling
Dane Taylor, Mason A. Porter, Peter J. Mucha
http://arxiv.org/abs/1906.06366v1
• [econ.EM]Posterior Average Effects
Stéphane Bonhomme, Martin Weidner
http://arxiv.org/abs/1906.06360v1
• [eess.IV]4D X-Ray CT Reconstruction using Multi-Slice Fusion
Soumendu Majee, Thilo Balke, Craig A. J. Kemp, Gregery T. Buzzard, Charles A. Bouman
http://arxiv.org/abs/1906.06601v1
• [eess.IV]A Fusion Adversarial Network for Underwater Image Enhancement
Jingjing Li, Hanyu Li
http://arxiv.org/abs/1906.06819v1
• [eess.IV]Differentiated Backprojection Domain Deep Learning for Conebeam Artifact Removal
Yoseob Han, Junyoung Kim, Jong Chul Ye
http://arxiv.org/abs/1906.06854v1
• [eess.IV]Particle Swarm Optimization for Great Enhancement in Semi-Supervised Retinal Vessel Segmentation with Generative Adversarial Networks
Qiang Huo
http://arxiv.org/abs/1906.07084v1
• [eess.IV]Single Image Super-resolution via Dense Blended Attention Generative Adversarial Network for Clinical Diagnosis
Kewen Liu, Yuan Ma, Hongxia Xiong, Zejun Yan, Zhijun Zhou, Chaoyang Liu, Panpan Fang, Xiaojun Li, Yalei Chen
http://arxiv.org/abs/1906.06575v1
• [eess.IV]Speeding up VP9 Intra Encoder with Hierarchical Deep Learning Based Partition Prediction
Somdyuti Paul, Andrey Norkin, Alan C. Bovik
http://arxiv.org/abs/1906.06476v1
• [eess.SP]Beam Entropy of 5G Cellular Millimetre Wave Channels
Krishan Kumar Tiwari, Eckhard Grass, John S. Thompson, Rolf Kraemer
http://arxiv.org/abs/1906.07012v1
• [eess.SP]Deep Recurrent Adversarial Learning for Privacy-Preserving Smart Meter Data Release
Mohammadhadi Shateri, Francisco Messina, Pablo Piantanida, Fabrice Labeau
http://arxiv.org/abs/1906.06427v1
• [math.OC]An efficient Lagrangian-based heuristic to solve a multi-objective sustainable supply chain problem
Camila P. S. Tautenhain, Ana Paula Barbosa-Povoa, Bruna Mota, Mariá C. V. Nascimento
http://arxiv.org/abs/1906.06375v1
• [math.OC]Productivity equation and the m distributions of information processing in workflows
Charles Roberto Telles
http://arxiv.org/abs/1906.06997v1
• [math.ST]Community Detection Based on the $L_\infty$ convergence of eigenvectors in DCBM
Yan Liu, Zhiqiang Hou, Zhigang Yao, Zhidong Bai, Jiang Hu, Shurong Zheng
http://arxiv.org/abs/1906.06713v1
• [math.ST]Designing Test Information and Test Information in Design
David E. Jones, Xiao-Li Meng
http://arxiv.org/abs/1906.06749v1
• [math.ST]Minimax Density Estimation on Sobolev Spaces With Dominating Mixed Smoothness
Galatia Cleanthous, Athanasios G. Georgiadis, Emilio Porcu
http://arxiv.org/abs/1906.06835v1
• [math.ST]On the Locally Lipschitz Robustness of Bayesian Inverse Problems
Björn Sprungk
http://arxiv.org/abs/1906.07120v1
• [physics.data-an]Detecting new signals under background mismodelling
Sara Algeri
http://arxiv.org/abs/1906.06615v1
• [q-bio.GN]Nested partitions from hierarchical clustering statistical validation
Christian Bongiorno, Salvatore Miccichè, Rosario N. Mantegna
http://arxiv.org/abs/1906.06908v1
• [stat.AP]Bayesian Finite Population Modeling for Spatial Process Settings
Alec M. Chan-Golston, Sudipto Banerjee, Mark S. Handcock
http://arxiv.org/abs/1906.06714v1
• [stat.AP]Bayesian spatial extreme value analysis of maximum temperatures in County Dublin, Ireland
John O’Sullivan, Conor Sweeney, Andrew C. Parnell
http://arxiv.org/abs/1906.06744v1
• [stat.AP]Identifying and characterizing extrapolation in multivariateresponse data
Meridith L Bartley, Ephraim M Hanks, Erin M Schliep, Patricia A Soranno, Tyler Wagner
http://arxiv.org/abs/1906.07036v1
• [stat.AP]Linear regression with stationary errors : the R package slm
Emmanuel Caron, Jérôme Dedecker, Michel Bertrand
http://arxiv.org/abs/1906.06583v1
• [stat.AP]Parametric and non-parametric estimation of extreme earthquake event: the joint tail inference for mainshocks and aftershocks
Juan-Juan Cai, Phyllis Wan, Gamze Ozel
http://arxiv.org/abs/1906.06882v1
• [stat.CO]A tunable multiresolution smoother for scattered data with application to particle filtering
Gregor A. Robinson, Ian G. Grooms
http://arxiv.org/abs/1906.06722v1
• [stat.CO]lpdensity: Local Polynomial Density Estimation and Inference
Matias D. Cattaneo, Michael Jansson, Xinwei Ma
http://arxiv.org/abs/1906.06529v1
• [stat.ME]Adaptive Variable Selection for Sequential Prediction in Multivariate Dynamic Models
Isaac Lavine, Michael Lindon, Mike West
http://arxiv.org/abs/1906.06580v1
• [stat.ME]An Optimal Test for the Additive Model with Discrete or Categorical Predictors
Abhijit Mandal
http://arxiv.org/abs/1906.06828v1
• [stat.ME]Depth-based Weighted Jackknife Empirical Likelihood for Non-smooth U-structure Equations
Yongli Sang, Xin Dang, Yichuan Zhao
http://arxiv.org/abs/1906.06742v1
• [stat.ME]From Incomplete, Dynamic Data to Bayesian Networks
Marco Scutari
http://arxiv.org/abs/1906.06513v1
• [stat.ME]Hierarchical Total Variations and Doubly Penalized ANOVA Modeling for Multivariate Nonparametric Regression
Ting Yang, Zhiqiang Tan
http://arxiv.org/abs/1906.06729v1
• [stat.ME]Linear Aggregation in Tree-based Estimators
Sören R. Künzel, Theo F. Saarinen, Edward W. Liu, Jasjeet S. Sekhon
http://arxiv.org/abs/1906.06463v1
• [stat.ME]Non parametric estimation of Joint entropy and Shannon mutual information, Asymptotic limits: Application to statistic tests
Amadou Diadie Ba, Gane Samb Lo
http://arxiv.org/abs/1906.06484v1
• [stat.ME]Probabilistic Diffusion MRI Fiber Tracking Using a Directed Acyclic Graph Auto-Regressive Model of Positive Definite Matrices
Zhou Lan, Brian J Reich
http://arxiv.org/abs/1906.06459v1
• [stat.ME]Sample Size Calculations for SMARTs
Eric J. Rose, Eric B. Laber, Marie Davidian, Anastasios A. Tsiatis, Ying-Qi Zhao, Michael R. Kosorok
http://arxiv.org/abs/1906.06646v1
• [stat.ML]A Bayesian Solution to the M-Bias Problem
David Rohde
http://arxiv.org/abs/1906.07136v1
• [stat.ML]Automatic Relevance Determination Bayesian Neural Networks for Credit Card Default Modelling
Rendani Mbuvha, Illyes Boulkaibet, Tshilidzi Marwala
http://arxiv.org/abs/1906.06382v1
• [stat.ML]Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities
Wei Qian, Yuqian Zhang, Yudong Chen
http://arxiv.org/abs/1906.06776v1
• [stat.ML]Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy
Alex Lamb, Vikas Verma, Juho Kannala, Yoshua Bengio
http://arxiv.org/abs/1906.06784v1
• [stat.ML]Metric on random dynamical systems with vector-valued reproducing kernel Hilbert spaces
Isao Ishikawa, Akinori Tanaka, Masahiro Ikeda, Yoshinobu Kawahara
http://arxiv.org/abs/1906.06957v1
• [stat.ML]Replacing the do-calculus with Bayes rule
Finnian Lattimore, David Rohde
http://arxiv.org/abs/1906.07125v1
• [stat.ML]Sampler for Composition Ratio by Markov Chain Monte Carlo
Yachiko Obara, Tetsuro Morimura, Hiroki Yanagisawa
http://arxiv.org/abs/1906.06663v1
• [stat.ML]Smooth function approximation by deep neural networks with general activation functions
Ilsang Ohn, Yongdai Kim
http://arxiv.org/abs/1906.06903v1
• [stat.ML]Stacked Capsule Autoencoders
Adam R. Kosiorek, Sara Sabour, Yee Whye Teh, Geoffrey E. Hinton
http://arxiv.org/abs/1906.06818v1
• [stat.ML]The Price of Local Fairness in Multistage Selection
Vitalii Emelianov, George Arvanitakis, Nicolas Gast, Krishna Gummadi, Patrick Loiseau
http://arxiv.org/abs/1906.06613v1
• [stat.ML]The True Sample Complexity of Identifying Good Arms
Julian Katz-Samuels, Kevin Jamieson
http://arxiv.org/abs/1906.06594v1