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.DL - 数字图书馆 cs.DS - 数据结构与算法 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MM - 多媒体 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.PF - 计算性能 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 eess.SY - 系统和控制 math.CO - 组合数学 math.NA - 数值分析 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.data-an - 数据分析、 统计和概率 physics.med-ph - 医学物理学 physics.soc-ph - 物理学与社会 q-bio.PE - 人口与发展 q-fin.PM - 投资组合管理 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]Travel Time Estimation without Road Networks: An Urban Morphological Layout Representation Approach
• [cs.CL]A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context
• [cs.CL]ANETAC: Arabic Named Entity Transliteration and Classification Dataset
• [cs.CL]Applying a Pre-trained Language Model to Spanish Twitter Humor Prediction
• [cs.CL]BERT-DST: Scalable End-to-End Dialogue State Tracking with Bidirectional Encoder Representations from Transformer
• [cs.CL]Best Practices for Learning Domain-Specific Cross-Lingual Embeddings
• [cs.CL]Correct-and-Memorize: Learning to Translate from Interactive Revisions
• [cs.CL]Early Discovery of Emerging Entities in Microblogs
• [cs.CL]Evolutionary Algorithm for Sinhala to English Translation
• [cs.CL]Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation
• [cs.CL]Exploring difference in public perceptions on HPV vaccine between gender groups from Twitter using deep learning
• [cs.CL]Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures
• [cs.CL]Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training
• [cs.CL]Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control
• [cs.CL]Joint Lifelong Topic Model and Manifold Ranking for Document Summarization
• [cs.CL]Knowledge-aware Pronoun Coreference Resolution
• [cs.CL]Multiple Generative Models Ensemble for Knowledge-Driven Proactive Human-Computer Dialogue Agent
• [cs.CL]NIESR: Nuisance Invariant End-to-end Speech Recognition
• [cs.CL]Searching for Effective Neural Extractive Summarization: What Works and What’s Next
• [cs.CL]Short Text Conversation Based on Deep Neural Network and Analysis on Evaluation Measures
• [cs.CL]Towards Universal Dialogue Act Tagging for Task-Oriented Dialogues
• [cs.CL]Zero-Shot Open Entity Typing as Type-Compatible Grounding
• [cs.CR]Faking and Discriminating the Navigation Data of a Micro Aerial Vehicle Using Quantum Generative Adversarial Networks
• [cs.CR]FortuneTeller: Predicting Microarchitectural Attacks via Unsupervised Deep Learning
• [cs.CR]I Am Not What I Write: Privacy Preserving Text Representation Learning
• [cs.CR]QUOTIENT: Two-Party Secure Neural Network Training and Prediction
• [cs.CR]Smart Grid Cyber Attacks Detection using Supervised Learning and Heuristic Feature Selection
• [cs.CR]Uncovering Download Fraud Activities in Mobile App Markets
• [cs.CV]A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data
• [cs.CV]A Novel Teacher-Student Learning Framework For Occluded Person Re-Identification
• [cs.CV]A unified neural network for object detection, multiple object tracking and vehicle re-identification
• [cs.CV]AMD Severity Prediction And Explainability Using Image Registration And Deep Embedded Clustering
• [cs.CV]ASCNet: Adaptive-Scale Convolutional Neural Networks for Multi-Scale Feature Learning
• [cs.CV]Bilevel Integrative Optimization for Ill-posed Inverse Problems
• [cs.CV]Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning
• [cs.CV]Bootstrap Model Ensemble and Rank Loss for Engagement Intensity Regression
• [cs.CV]Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network
• [cs.CV]Data Distillation, Face-Related Tasks, Multi Task Learning, Semi-Supervised Learning
• [cs.CV]Deep Learning for Fine-Grained Image Analysis: A Survey
• [cs.CV]Dependency-aware Attention Control for Unconstrained Face Recognition with Image Sets
• [cs.CV]ELF: Embedded Localisation of Features in pre-trained CNN
• [cs.CV]Embodied Vision-and-Language Navigation with Dynamic Convolutional Filters
• [cs.CV]Facial Makeup Transfer Combining Illumination Transfer
• [cs.CV]Fast Universal Style Transfer for Artistic and Photorealistic Rendering
• [cs.CV]Learning Structural Graph Layouts and 3D Shapes for Long Span Bridges 3D Reconstruction
• [cs.CV]Linking Art through Human Poses
• [cs.CV]Multi-level Wavelet Convolutional Neural Networks
• [cs.CV]Multimodal Fusion with Deep Neural Networks for Audio-Video Emotion Recognition
• [cs.CV]Part-A^2 Net: 3D Part-Aware and Aggregation Neural Network for Object Detection from Point Cloud
• [cs.CV]Point-Voxel CNN for Efficient 3D Deep Learning
• [cs.CV]Revisiting Metric Learning for Few-Shot Image Classification
• [cs.CV]SAN: Scale-Aware Network for Semantic Segmentation of High-Resolution Aerial Images
• [cs.CV]Spacetime Graph Optimization for Video Object Segmentation
• [cs.CV]Tree-gated Deep Regressor Ensemble For Face Alignment In The Wild
• [cs.CV]Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired Images
• [cs.CV]Unsupervised Domain Alignment to Mitigate Low Level Dataset Biases
• [cs.CV]Unsupervised cycle-consistent deformation for shape matching
• [cs.CV]Variational Context: Exploiting Visual and Textual Context for Grounding Referring Expressions
• [cs.CV]Video Question Generation via Cross-Modal Self-Attention Networks Learning
• [cs.CY]A Conceptual Marketplace Model for IoT Generated Personal Data
• [cs.CY]Differential Privacy in the 2020 Decennial Census and the Implications for Available Data Products
• [cs.CY]Ensuring Responsible Outcomes from Technology
• [cs.DC]A Topological Perspective on Distributed Network Algorithms
• [cs.DC]Enabling Microsoft OneDrive Integration with HTCondor
• [cs.DC]Fair Byzantine Agreements for Blockchains
• [cs.DC]Graphyti: A Semi-External Memory Graph Library for FlashGraph
• [cs.DC]IoT Platforms for 5G Network and Practical Considerations: A Survey
• [cs.DC]Ostraka: Secure Blockchain Scaling by Node Sharding
• [cs.DC]Platypus: a Partially Synchronous Offchain Protocol for Blockchains
• [cs.DC]Qualitative Benchmarking of Deep Learning Hardware and Frameworks: Review and Tutorial
• [cs.DL]Publication modalities ‘article in press’ and ‘open access’ in relation to journal average citation
• [cs.DS]Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm
• [cs.DS]Contraction Clustering (RASTER): A Very Fast Big Data Algorithm for Sequential and Parallel Density-Based Clustering in Linear Time, Constant Memory, and a Single Pass
• [cs.DS]Towards Testing Monotonicity of Distributions Over General Posets
• [cs.IR]CobWeb: A Research Prototype for Exploring User Bias in Political Fact-Checking
• [cs.IR]Global Aggregations of Local Explanations for Black Box models
• [cs.IR]Incorporating Query Term Independence Assumption for Efficient Retrieval and Ranking using Deep Neural Networks
• [cs.IR]Joint Neural Collaborative Filtering for Recommender Systems
• [cs.IR]NeuType: A Simple and Effective Neural Network Approach for Predicting Missing Entity Type Information in Knowledge Bases
• [cs.IR]Recommending Related Tables
• [cs.IR]Search-Based Serving Architecture of Embeddings-Based Recommendations
• [cs.IR]TEALS: Time-aware Text Embedding Approach to Leverage Subgraphs
• [cs.IT]Asymmetric LOCO Codes: Constrained Codes for Flash Memories
• [cs.IT]Capacity and Algorithms for a Cognitive Network with Primary-Secondary User Cooperation
• [cs.IT]Deep Learning based Wireless Resource Allocation with Application to Vehicular Networks
• [cs.IT]Early Detection for Optimal-Latency Communications in Multi-Hop Links
• [cs.IT]Enabling Ultra Reliable Wireless Communications for Factory Automation with Distributed MIMO
• [cs.IT]Error Probability Bounds for Gaussian Channels under Maximal and Average Power Constraints
• [cs.IT]Further results on some classes of permutation polynomials over finite fields
• [cs.IT]Fusion-Based Cooperative Support Identification for Compressive Networked Sensing
• [cs.IT]Graph Signal Processing — Part I: Graphs, Graph Spectra, and Spectral Clustering
• [cs.IT]Importance of Small Probability Events in Big Data: Information Measures, Applications, and Challenges
• [cs.IT]Intelligent Reflecting Surface Assisted Non-Orthogonal Multiple Access
• [cs.IT]Max-Min Rate of Cell-Free Massive MIMO Uplink with Optimal Uniform Quantization
• [cs.IT]Resource Allocation for Secure IRS-assisted Multiuser MISO Systems
• [cs.IT]Secure Network Coding in the Setting in Which a Non-Source Node May Generate Random Keys
• [cs.LG]A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning
• [cs.LG]A Human-Grounded Evaluation of SHAP for Alert Processing
• [cs.LG]A Multi-Stage Clustering Framework for Automotive Radar Data
• [cs.LG]Adversarial Fault Tolerant Training for Deep Neural Networks
• [cs.LG]AutoSlim: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates
• [cs.LG]Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks
• [cs.LG]Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models
• [cs.LG]Copula & Marginal Flows: Disentangling the Marginal from its Joint
• [cs.LG]Data Efficient Reinforcement Learning for Legged Robots
• [cs.LG]Deep Exponential-Family Auto-Encoders
• [cs.LG]Diachronic Embedding for Temporal Knowledge Graph Completion
• [cs.LG]Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
• [cs.LG]Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning
• [cs.LG]Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm
• [cs.LG]Fast and Provable ADMM for Learning with Generative Priors
• [cs.LG]Gaussian Processes for Analyzing Positioned Trajectories in Sports
• [cs.LG]General non-linear Bellman equations
• [cs.LG]Generalized Control Functions via Variational Decoupling
• [cs.LG]Generative Counterfactual Introspection for Explainable Deep Learning
• [cs.LG]Improving Detection of Credit Card Fraudulent Transactions using Generative Adversarial Networks
• [cs.LG]Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits
• [cs.LG]Intelligent Systems Design for Malware Classification Under Adversarial Conditions
• [cs.LG]Intrinsic Motivation Driven Intuitive Physics Learning using Deep Reinforcement Learning with Intrinsic Reward Normalization
• [cs.LG]Jointly Aligning and Predicting Continuous Emotion Annotations
• [cs.LG]Learning a Behavioral Repertoire from Demonstrations
• [cs.LG]Multivariate-Information Adversarial Ensemble for Scalable Joint Distribution Matching
• [cs.LG]On-Policy Robot Imitation Learning from a Converging Supervisor
• [cs.LG]Physics Informed Extreme Learning Machine (PIELM) — A rapid method for the numerical solution of partial differential equations
• [cs.LG]Playing Flappy Bird via Asynchronous Advantage Actor Critic Algorithm
• [cs.LG]Policy-Gradient Algorithms Have No Guarantees of Convergence in Continuous Action and State Multi-Agent Settings
• [cs.LG]Predicting Customer Call Intent by Analyzing Phone Call Transcripts based on CNN for Multi-Class Classification
• [cs.LG]Privacy-Preserving Classification with Secret Vector Machines
• [cs.LG]Quantifying Transparency of Machine Learning Systems through Analysis of Contributions
• [cs.LG]Quantitative $W_1$ Convergence of Langevin-Like Stochastic Processes with Non-Convex Potential State-Dependent Noise
• [cs.LG]Quantum-inspired canonical correlation analysis for exponentially large dimensional data
• [cs.LG]Regularizing linear inverse problems with convolutional neural networks
• [cs.LG]Resource-Efficient Computing in Wearable Systems
• [cs.LG]Resource-Efficient Wearable Computing for Real-Time Reconfigurable Machine Learning: A Cascading Binary Classification
• [cs.LG]Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning
• [cs.LG]ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning
• [cs.LG]The Price of Interpretability
• [cs.LG]Towards Debugging Deep Neural Networks by Generating Speech Utterances
• [cs.LG]Towards Robust, Locally Linear Deep Networks
• [cs.LG]TrackNet: A Deep Learning Network for Tracking High-speed and Tiny Objects in Sports Applications
• [cs.LG]Weakly-supervised Knowledge Graph Alignment with Adversarial Learning
• [cs.LG]What graph neural networks cannot learn: depth vs width
• [cs.MM]Informative Visual Storytelling with Cross-modal Rules
• [cs.NE]Adaptive Neuro-Surrogate-Based Optimisation Method for Wave Energy Converters Placement Optimisation
• [cs.NE]Takens-inspired neuromorphic processor: a downsizing tool for random recurrent neural networks via feature extraction
• [cs.NI]The Fog Development Kit: A Development Platform for SDN-based Edge-Fog Systems
• [cs.PF]Optimizing Xeon Phi for Interactive Data Analysis
• [cs.RO]A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms
• [cs.RO]Augmenting Knowledge through Statistical, Goal-oriented Human-Robot Dialog
• [cs.RO]Modeling and Simulation of the Quadrtor Delivery System
• [cs.RO]Segway DRIVE Benchmark: Place Recognition and SLAM Data Collected by A Fleet of Delivery Robots
• [cs.RO]System Architecture for Real-time Surface Inspection Using Multiple UAVs
• [cs.RO]Time Distance: A Novel Collision Prediction and Path Planning Method
• [cs.SD]Towards Explainable Music Emotion Recognition: The Route via Mid-level Features
• [cs.SE]MigrationMiner: An Automated Detection Tool of Third-Party Java Library Migration at the Method Level
• [cs.SI]Network Embedding: on Compression and Learning
• [eess.AS]The GDPR & Speech Data: Reflections of Legal and Technology Communities, First Steps towards a Common Understanding
• [eess.IV]Adaptive Weighting Depth-variant Deconvolution of Fluorescence Microscopy Images with Convolutional Neural Network
• [eess.IV]An Experimental-based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging
• [eess.IV]Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation
• [eess.IV]Dual Adversarial Learning with Attention Mechanism for Fine-grained Medical Image Synthesis
• [eess.IV]FC$^2$N: Fully Channel-Concatenated Network for Single Image Super-Resolution
• [eess.IV]Learning joint lesion and tissue segmentation from task-specific hetero-modal datasets
• [eess.IV]MRI Super-Resolution with Ensemble Learning and Complementary Priors
• [eess.IV]Perceptual representations of structural information in images: application to quality assessment of synthesized view in FTV scenario
• [eess.IV]Skin Lesion Analyser: An Efficient Seven-Way Multi-Class Skin Cancer Classification Using MobileNet
• [eess.SP]Vertex-Frequency Graph Signal Processing
• [eess.SY]A New Approach to Distributed Hypothesis Testing and Non-Bayesian Learning: Improved Learning Rate and Byzantine-Resilience
• [eess.SY]Smart Households Demand Response Management with Micro Grid
• [math.CO]One-step Majority-logic Decoding with Subspace Designs
• [math.CO]Placement Delivery Arrays from Combinations of Strong Edge Colorings
• [math.NA]Deep splitting method for parabolic PDEs
• [math.OC]ReLU Networks as Surrogate Models in Mixed-Integer Linear Programs
• [math.OC]Robust Guarantees for Perception-Based Control
• [math.PR]Distance from the Nucleus to a Uniformly Random Point in the Typical and the Crofton Cells of the Poisson-Voronoi Tessellation
• [math.PR]Posterior Convergence of $α$-Stable Sheets
• [math.PR]Volume Doubling Condition and a Local Poincaré Inequality on Unweighted Random Geometric Graphs
• [math.ST]Bayes factors with (overly) informative priors
• [math.ST]Convergence Analysis of a Collapsed Gibbs Sampler for Bayesian Vector Autoregressions
• [math.ST]Estimating location parameters in entangled single-sample distributions
• [math.ST]Improving Lasso for model selection and prediction
• [math.ST]On Inferences from Completed Data
• [math.ST]On the Glivenko-Cantelli theorem for the functional empirical process using associated sequences
• [math.ST]Testing Mixtures of Discrete Distributions
• [physics.comp-ph]IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery
• [physics.data-an]Precision annealing Monte Carlo methods for statistical data assimilation and machine learning
• [physics.med-ph]Non-Invasive MGMT Status Prediction in GBM Cancer Using Magnetic Resonance Images (MRI) Radiomics Features: Univariate and Multivariate Machine Learning Radiogenomics Analysis
• [physics.soc-ph]Characteristics of human mobility patterns revealed by high-frequency cell-phone position data
• [q-bio.PE]How many groups? A statistical methodology for data-driven partitioning of infectious disease incidence into age-groups
• [q-fin.PM]An intelligent financial portfolio trading strategy using deep Q-learning
• [stat.AP]Causal mechanism of extreme river discharges in the upper Danube basin network
• [stat.AP]Filaments of crime: Informing policing via thresholded ridge estimation
• [stat.AP]Investigating some attributes of periodicity in DNA sequences via semi-Markov modelling
• [stat.ME]A Versatile Estimation Procedure without Estimating the Nonignorable Missingness Mechanism
• [stat.ME]Bayesian Nonparametric Nonhomogeneous Poisson Process with Applications to USGS Earthquake Data
• [stat.ME]Learning a latent pattern of heterogeneity in the innovation rates of a time series of counts
• [stat.ME]Modeling Symmetric Positive Definite Matrices with An Application to Functional Brain Connectivity
• [stat.ME]The revisited knockoffs method for variable selection in L1-penalised regressions
• [stat.ML]Unbiased estimators for random design regression
• [stat.ML]XGBoostLSS — An extension of XGBoost to probabilistic forecasting
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• [cs.AI]Travel Time Estimation without Road Networks: An Urban Morphological Layout Representation Approach
Wuwei Lan, Yanyan Xu, Bin Zhao
http://arxiv.org/abs/1907.03381v1
• [cs.CL]A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context
Takuma Udagawa, Akiko Aizawa
http://arxiv.org/abs/1907.03399v1
• [cs.CL]ANETAC: Arabic Named Entity Transliteration and Classification Dataset
Mohamed Seghir Hadj Ameur, Farid Meziane, Ahmed Guessoum
http://arxiv.org/abs/1907.03110v1
• [cs.CL]Applying a Pre-trained Language Model to Spanish Twitter Humor Prediction
Bobak Farzin, Piotr Czapla, Jeremy Howard
http://arxiv.org/abs/1907.03187v1
• [cs.CL]BERT-DST: Scalable End-to-End Dialogue State Tracking with Bidirectional Encoder Representations from Transformer
Guan-Lin Chao, Ian Lane
http://arxiv.org/abs/1907.03040v1
• [cs.CL]Best Practices for Learning Domain-Specific Cross-Lingual Embeddings
Lena Shakurova, Beata Nyari, Chao Li, Mihai Rotaru
http://arxiv.org/abs/1907.03112v1
• [cs.CL]Correct-and-Memorize: Learning to Translate from Interactive Revisions
Rongxiang Weng, Hao Zhou, Shujian Huang, Lei Li, Yifan Xia, Jiajun Chen
http://arxiv.org/abs/1907.03468v1
• [cs.CL]Early Discovery of Emerging Entities in Microblogs
Satoshi Akasaki, Naoki Yoshinaga, Masashi Toyoda
http://arxiv.org/abs/1907.03513v1
• [cs.CL]Evolutionary Algorithm for Sinhala to English Translation
J. K. Joseph, W. M. T. Chathurika, A. Nugaliyadde, Y. Mallawarachchi
http://arxiv.org/abs/1907.03202v1
• [cs.CL]Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation
Aizhan Imankulova, Raj Dabre, Atsushi Fujita, Kenji Imamura
http://arxiv.org/abs/1907.03060v1
• [cs.CL]Exploring difference in public perceptions on HPV vaccine between gender groups from Twitter using deep learning
Jingcheng Du, Chongliang Luo, Qiang Wei, Yong Chen, Cui Tao
http://arxiv.org/abs/1907.03167v1
• [cs.CL]Graph based Neural Networks for Event Factuality Prediction using Syntactic and Semantic Structures
Amir Pouran Ben Veyseh, Thien Huu Nguyen, Dejing Dou
http://arxiv.org/abs/1907.03227v1
• [cs.CL]Improved low-resource Somali speech recognition by semi-supervised acoustic and language model training
Astik Biswas, Raghav Menon, Ewald van der Westhuizen, Thomas Niesler
http://arxiv.org/abs/1907.03064v1
• [cs.CL]Improving Cross-Domain Performance for Relation Extraction via Dependency Prediction and Information Flow Control
Amir Pouran Ben Veyseh, Thien Huu Nguyen, Dejing Dou
http://arxiv.org/abs/1907.03230v1
• [cs.CL]Joint Lifelong Topic Model and Manifold Ranking for Document Summarization
Jianying Lin, Rui Liu, Quanye Jia
http://arxiv.org/abs/1907.03224v1
• [cs.CL]Knowledge-aware Pronoun Coreference Resolution
Hongming Zhang, Yan Song, Yangqiu Song, Dong Yu
http://arxiv.org/abs/1907.03663v1
• [cs.CL]Multiple Generative Models Ensemble for Knowledge-Driven Proactive Human-Computer Dialogue Agent
Zelin Dai, Weitang Liu, Hao Zhang, Minghao Zhu, Long Wang
http://arxiv.org/abs/1907.03590v1
• [cs.CL]NIESR: Nuisance Invariant End-to-end Speech Recognition
I-Hung Hsu, Ayush Jaiswal, Premkumar Natarajan
http://arxiv.org/abs/1907.03233v1
• [cs.CL]Searching for Effective Neural Extractive Summarization: What Works and What’s Next
Ming Zhong, Pengfei Liu, Danqing Wang, Xipeng Qiu, Xuanjing Huang
http://arxiv.org/abs/1907.03491v1
• [cs.CL]Short Text Conversation Based on Deep Neural Network and Analysis on Evaluation Measures
Hsiang-En Cherng, Chia-Hui Chang
http://arxiv.org/abs/1907.03070v1
• [cs.CL]Towards Universal Dialogue Act Tagging for Task-Oriented Dialogues
Shachi Paul, Rahul Goel, Dilek Hakkani-Tür
http://arxiv.org/abs/1907.03020v1
• [cs.CL]Zero-Shot Open Entity Typing as Type-Compatible Grounding
Ben Zhou, Daniel Khashabi, Chen-Tse Tsai, Dan Roth
http://arxiv.org/abs/1907.03228v1
• [cs.CR]Faking and Discriminating the Navigation Data of a Micro Aerial Vehicle Using Quantum Generative Adversarial Networks
Michel Barbeau, Joaquin Garcia-Alfaro
http://arxiv.org/abs/1907.03038v1
• [cs.CR]FortuneTeller: Predicting Microarchitectural Attacks via Unsupervised Deep Learning
Berk Gulmezoglu, Ahmad Moghimi, Thomas Eisenbarth, Berk Sunar
http://arxiv.org/abs/1907.03651v1
• [cs.CR]I Am Not What I Write: Privacy Preserving Text Representation Learning
Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu
http://arxiv.org/abs/1907.03189v1
• [cs.CR]QUOTIENT: Two-Party Secure Neural Network Training and Prediction
Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner, Adrià Gascón
http://arxiv.org/abs/1907.03372v1
• [cs.CR]Smart Grid Cyber Attacks Detection using Supervised Learning and Heuristic Feature Selection
Jacob Sakhnini, Hadis Karimipour, Ali Dehghantanha
http://arxiv.org/abs/1907.03313v1
• [cs.CR]Uncovering Download Fraud Activities in Mobile App Markets
Yingtong Dou, Weijian Li, Zhirong Liu, Zhenhua Dong, Jiebo Luo, Philip S. Yu
http://arxiv.org/abs/1907.03048v1
• [cs.CV]A Deep Learning Approach for Real-Time 3D Human Action Recognition from Skeletal Data
Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio A Velastin
http://arxiv.org/abs/1907.03520v1
• [cs.CV]A Novel Teacher-Student Learning Framework For Occluded Person Re-Identification
Jiaxuan Zhuo, Jianhuang Lai, Peijia Chen
http://arxiv.org/abs/1907.03253v1
• [cs.CV]A unified neural network for object detection, multiple object tracking and vehicle re-identification
Yuhao Xu, Jiakui Wang
http://arxiv.org/abs/1907.03465v1
• [cs.CV]AMD Severity Prediction And Explainability Using Image Registration And Deep Embedded Clustering
Dwarikanath Mahapatra
http://arxiv.org/abs/1907.03075v1
• [cs.CV]ASCNet: Adaptive-Scale Convolutional Neural Networks for Multi-Scale Feature Learning
Mo Zhang, Jie Zhao, Xiang Li, Li Zhang, Quanzheng Li
http://arxiv.org/abs/1907.03241v1
• [cs.CV]Bilevel Integrative Optimization for Ill-posed Inverse Problems
Risheng Liu, Long Ma, Xiaoming Yuan, Shangzhi Zeng, Jin Zhang
http://arxiv.org/abs/1907.03083v1
• [cs.CV]Blind Universal Bayesian Image Denoising with Gaussian Noise Level Learning
Majed El Helou, Sabine Susstrunk
http://arxiv.org/abs/1907.03029v1
• [cs.CV]Bootstrap Model Ensemble and Rank Loss for Engagement Intensity Regression
Kai Wang, Jianfei Yang, Da Guo, Kaipeng Zhang, Xiaojiang Peng, Yu Qiao
http://arxiv.org/abs/1907.03422v1
• [cs.CV]Correlation via synthesis: end-to-end nodule image generation and radiogenomic map learning based on generative adversarial network
Ziyue Xu, Xiaosong Wang, Hoo-Chang Shin, Dong Yang, Holger Roth, Fausto Milletari, Ling Zhang, Daguang Xu
http://arxiv.org/abs/1907.03728v1
• [cs.CV]Data Distillation, Face-Related Tasks, Multi Task Learning, Semi-Supervised Learning
Sepidehsadat Hosseini, Mohammad Amin Shabani, Nam Ik Cho
http://arxiv.org/abs/1907.03402v1
• [cs.CV]Deep Learning for Fine-Grained Image Analysis: A Survey
Xiu-Shen Wei, Jianxin Wu, Quan Cui
http://arxiv.org/abs/1907.03069v1
• [cs.CV]Dependency-aware Attention Control for Unconstrained Face Recognition with Image Sets
Xiaofeng Liu, B. V. K Vijaya Kumar, Chao Yang, Qingming Tang, Jane You
http://arxiv.org/abs/1907.03030v1
• [cs.CV]ELF: Embedded Localisation of Features in pre-trained CNN
Assia Benbihi, Matthieu Geist, Cédric Pradalier
http://arxiv.org/abs/1907.03261v1
• [cs.CV]Embodied Vision-and-Language Navigation with Dynamic Convolutional Filters
Federico Landi, Lorenzo Baraldi, Massimiliano Corsini, Rita Cucchiara
http://arxiv.org/abs/1907.02985v1
• [cs.CV]Facial Makeup Transfer Combining Illumination Transfer
Xin Jin, Rui Han, Ning Ning, Xiaodong Li, Xiaokun Zhang
http://arxiv.org/abs/1907.03398v1
• [cs.CV]Fast Universal Style Transfer for Artistic and Photorealistic Rendering
Jie An, Haoyi Xiong, Jiebo Luo, Jun Huan, Jinwen Ma
http://arxiv.org/abs/1907.03118v1
• [cs.CV]Learning Structural Graph Layouts and 3D Shapes for Long Span Bridges 3D Reconstruction
Fangqiao Hu, Jin Zhao, Yong Hunag, Hui Li
http://arxiv.org/abs/1907.03387v1
• [cs.CV]Linking Art through Human Poses
Tomas Jenicek, Ondřej Chum
http://arxiv.org/abs/1907.03537v1
• [cs.CV]Multi-level Wavelet Convolutional Neural Networks
Pengju Liu, Hongzhi Zhang, Wei Lian, Wangmeng Zuo
http://arxiv.org/abs/1907.03128v1
• [cs.CV]Multimodal Fusion with Deep Neural Networks for Audio-Video Emotion Recognition
Juan D. S. Ortega, Mohammed Senoussaoui, Eric Granger, Marco Pedersoli, Patrick Cardinal, Alessandro L. Koerich
http://arxiv.org/abs/1907.03196v1
• [cs.CV]Part-A^2 Net: 3D Part-Aware and Aggregation Neural Network for Object Detection from Point Cloud
Shaoshuai Shi, Zhe Wang, Xiaogang Wang, Hongsheng Li
http://arxiv.org/abs/1907.03670v1
• [cs.CV]Point-Voxel CNN for Efficient 3D Deep Learning
Zhijian Liu, Haotian Tang, Yujun Lin, Song Han
http://arxiv.org/abs/1907.03739v1
• [cs.CV]Revisiting Metric Learning for Few-Shot Image Classification
Xiaomeng Li, Lequan Yu, Chi-Wing Fu, Meng Fang, Pheng-Ann Heng
http://arxiv.org/abs/1907.03123v1
• [cs.CV]SAN: Scale-Aware Network for Semantic Segmentation of High-Resolution Aerial Images
Jingbo Lin, Weipeng Jing, Houbing Song
http://arxiv.org/abs/1907.03089v1
• [cs.CV]Spacetime Graph Optimization for Video Object Segmentation
Emanuela Haller, Adina Magda Florea, Marius Leordeanu
http://arxiv.org/abs/1907.03326v1
• [cs.CV]Tree-gated Deep Regressor Ensemble For Face Alignment In The Wild
Estephe Arnaud, Arnaud Dapogny, Kevin Bailly
http://arxiv.org/abs/1907.03248v1
• [cs.CV]Unified Attentional Generative Adversarial Network for Brain Tumor Segmentation From Multimodal Unpaired Images
Wenguang Yuan, Jia Wei, Jiabing Wang, Qianli Ma, Tolga Tasdizen
http://arxiv.org/abs/1907.03548v1
• [cs.CV]Unsupervised Domain Alignment to Mitigate Low Level Dataset Biases
Kirthi Shankar Sivamani
http://arxiv.org/abs/1907.03644v1
• [cs.CV]Unsupervised cycle-consistent deformation for shape matching
Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell, Mathieu Aubry
http://arxiv.org/abs/1907.03165v1
• [cs.CV]Variational Context: Exploiting Visual and Textual Context for Grounding Referring Expressions
Yulei Niu, Hanwang Zhang, Zhiwu Lu, Shih-Fu Chang
http://arxiv.org/abs/1907.03609v1
• [cs.CV]Video Question Generation via Cross-Modal Self-Attention Networks Learning
Yu-Siang Wang, Hung-Ting Su, Chen-Hsi Chang, Winston Hsu
http://arxiv.org/abs/1907.03049v1
• [cs.CY]A Conceptual Marketplace Model for IoT Generated Personal Data
Victor Molina, Marta Kersten-Oertel, Tristan Glatard
http://arxiv.org/abs/1907.03047v1
• [cs.CY]Differential Privacy in the 2020 Decennial Census and the Implications for Available Data Products
danah boyd
http://arxiv.org/abs/1907.03639v1
• [cs.CY]Ensuring Responsible Outcomes from Technology
Aaditeshwar Seth
http://arxiv.org/abs/1907.03263v1
• [cs.DC]A Topological Perspective on Distributed Network Algorithms
Armando Castañeda, Pierre Fraigniaud, Ami Paz, Sergio Rajsbaum, Matthieu Roy, Corentin Travers
http://arxiv.org/abs/1907.03565v1
• [cs.DC]Enabling Microsoft OneDrive Integration with HTCondor
Derek Weitzel
http://arxiv.org/abs/1907.03688v1
• [cs.DC]Fair Byzantine Agreements for Blockchains
Tzu-Wei Chao, Hao Chung, Po-Chun Kuo
http://arxiv.org/abs/1907.03437v1
• [cs.DC]Graphyti: A Semi-External Memory Graph Library for FlashGraph
Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal Burns
http://arxiv.org/abs/1907.03335v1
• [cs.DC]IoT Platforms for 5G Network and Practical Considerations: A Survey
Sejuti Banik, Irvin Steve Cardenas, Jong Hoon Kim
http://arxiv.org/abs/1907.03592v1
• [cs.DC]Ostraka: Secure Blockchain Scaling by Node Sharding
Alex Manuskin, Michael Mirkin, Ittay Eyal
http://arxiv.org/abs/1907.03331v1
• [cs.DC]Platypus: a Partially Synchronous Offchain Protocol for Blockchains
Alejandro Ranchal-Pedrosa, Vincent Gramoli
http://arxiv.org/abs/1907.03730v1
• [cs.DC]Qualitative Benchmarking of Deep Learning Hardware and Frameworks: Review and Tutorial
Wei Dai, Daniel Berleant
http://arxiv.org/abs/1907.03626v1
• [cs.DL]Publication modalities ‘article in press’ and ‘open access’ in relation to journal average citation
Sara M. González-Betancor, Pablo Dorta-González
http://arxiv.org/abs/1907.03518v1
• [cs.DS]Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm
Piotr Indyk, Sepideh Mahabadi, Shayan Oveis Gharan, Alireza Rezaei
http://arxiv.org/abs/1907.03197v1
• [cs.DS]Contraction Clustering (RASTER): A Very Fast Big Data Algorithm for Sequential and Parallel Density-Based Clustering in Linear Time, Constant Memory, and a Single Pass
Gregor Ulm, Simon Smith, Adrian Nilsson, Emil Gustavsson, Mats Jirstrand
http://arxiv.org/abs/1907.03620v1
• [cs.DS]Towards Testing Monotonicity of Distributions Over General Posets
Maryam Aliakbarpour, Themis Gouleakis, John Peebles, Ronitt Rubinfeld, Anak Yodpinyanee
http://arxiv.org/abs/1907.03182v1
• [cs.IR]CobWeb: A Research Prototype for Exploring User Bias in Political Fact-Checking
Anubrata Das, Kunjan Mehta, Matthew Lease
http://arxiv.org/abs/1907.03718v1
• [cs.IR]Global Aggregations of Local Explanations for Black Box models
Ilse van der Linden, Hinda Haned, Evangelos Kanoulas
http://arxiv.org/abs/1907.03039v1
• [cs.IR]Incorporating Query Term Independence Assumption for Efficient Retrieval and Ranking using Deep Neural Networks
Bhaskar Mitra, Corby Rosset, David Hawking, Nick Craswell, Fernando Diaz, Emine Yilmaz
http://arxiv.org/abs/1907.03693v1
• [cs.IR]Joint Neural Collaborative Filtering for Recommender Systems
Wanyu Chen, Fei Cai, Honghui Chen, Maarten de Rijke
http://arxiv.org/abs/1907.03459v1
• [cs.IR]NeuType: A Simple and Effective Neural Network Approach for Predicting Missing Entity Type Information in Knowledge Bases
Jon Arne Bø Hovda, Darío Garigliotti, Krisztian Balog
http://arxiv.org/abs/1907.03007v1
• [cs.IR]Recommending Related Tables
Shuo Zhang, Krisztian Balog
http://arxiv.org/abs/1907.03595v1
• [cs.IR]Search-Based Serving Architecture of Embeddings-Based Recommendations
Sonya Liberman, Shaked Bar, Raphael Vannerom, Danny Rosenstein, Ronny Lempel
http://arxiv.org/abs/1907.03336v1
• [cs.IR]TEALS: Time-aware Text Embedding Approach to Leverage Subgraphs
Saeid Hosseini, Saeed Najafi Pour, Ngai-Man Cheung, Mohammad Reza Kangavari, Xiaofang Zhou, Yuval Elovici
http://arxiv.org/abs/1907.03191v1
• [cs.IT]Asymmetric LOCO Codes: Constrained Codes for Flash Memories
Ahmed Hareedy, Robert Calderbank
http://arxiv.org/abs/1907.03707v1
• [cs.IT]Capacity and Algorithms for a Cognitive Network with Primary-Secondary User Cooperation
Athanasios Papadopoulos, Nestor D. Chatzidiamantis, Leonidas Georgiadis
http://arxiv.org/abs/1907.03444v1
• [cs.IT]Deep Learning based Wireless Resource Allocation with Application to Vehicular Networks
Le Liang, Hao Ye, Guanding Yu, Geoffrey Ye Li
http://arxiv.org/abs/1907.03289v1
• [cs.IT]Early Detection for Optimal-Latency Communications in Multi-Hop Links
Diego Barragán Guerrero, Minh Au, Ghyslain Gagnon, François Gagnon, Pascal Giard
http://arxiv.org/abs/1907.02576v2
• [cs.IT]Enabling Ultra Reliable Wireless Communications for Factory Automation with Distributed MIMO
Gianluca Casciano, Paolo Baracca, Stefano Buzzi
http://arxiv.org/abs/1907.03530v1
• [cs.IT]Error Probability Bounds for Gaussian Channels under Maximal and Average Power Constraints
Gonzalo Vazquez-Vilar
http://arxiv.org/abs/1907.03163v1
• [cs.IT]Further results on some classes of permutation polynomials over finite fields
Xiaogang Liu
http://arxiv.org/abs/1907.03386v1
• [cs.IT]Fusion-Based Cooperative Support Identification for Compressive Networked Sensing
Ming-Hsun Yang, Jwo-Yuh Wu, Tsang-Yi Wang, Robert G. Maunder, Rung-Hung Gau
http://arxiv.org/abs/1907.03071v1
• [cs.IT]Graph Signal Processing — Part I: Graphs, Graph Spectra, and Spectral Clustering
Ljubisa Stankovic, Danilo Mandic, Milos Dakovic, Milos Brajovic, Bruno Scalzo, Tony Constantinides
http://arxiv.org/abs/1907.03467v1
• [cs.IT]Importance of Small Probability Events in Big Data: Information Measures, Applications, and Challenges
Rui She, Shanyun Liu, Shuo Wan, Ke Xiong, Pingyi Fan
http://arxiv.org/abs/1907.02652v2
• [cs.IT]Intelligent Reflecting Surface Assisted Non-Orthogonal Multiple Access
Gang Yang, Xinyue Xu, Ying-Chang Liang
http://arxiv.org/abs/1907.03133v1
• [cs.IT]Max-Min Rate of Cell-Free Massive MIMO Uplink with Optimal Uniform Quantization
Manijeh Bashar, Kanapathippillai Cumanan, Alister G. Burr, Hien Quoc Ngo, Merouane Debbah, Pei Xiao
http://arxiv.org/abs/1907.03262v1
• [cs.IT]Resource Allocation for Secure IRS-assisted Multiuser MISO Systems
Dongfang Xu, Xianghao Yu, Yan Sun, Derrick Wing Kwan Ng, Robert Schober
http://arxiv.org/abs/1907.03085v1
• [cs.IT]Secure Network Coding in the Setting in Which a Non-Source Node May Generate Random Keys
Debaditya Chaudhuri, Michael Langberg, Michelle Effros
http://arxiv.org/abs/1907.03522v1
• [cs.LG]A Communication-Efficient Multi-Agent Actor-Critic Algorithm for Distributed Reinforcement Learning
Yixuan Lin, Kaiqing Zhang, Zhuoran Yang, Zhaoran Wang, Tamer Başar, Romeil Sandhu, Ji Liu
http://arxiv.org/abs/1907.03053v1
• [cs.LG]A Human-Grounded Evaluation of SHAP for Alert Processing
Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy
http://arxiv.org/abs/1907.03324v1
• [cs.LG]A Multi-Stage Clustering Framework for Automotive Radar Data
Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick
http://arxiv.org/abs/1907.03511v1
• [cs.LG]Adversarial Fault Tolerant Training for Deep Neural Networks
Vasisht Duddu, D. Vijay Rao, Valentina E. Balas
http://arxiv.org/abs/1907.03103v1
• [cs.LG]AutoSlim: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates
Ning Liu, Xiaolong Ma, Zhiyuan Xu, Yanzhi Wang, Jian Tang, Jieping Ye
http://arxiv.org/abs/1907.03141v1
• [cs.LG]Blending-target Domain Adaptation by Adversarial Meta-Adaptation Networks
Ziliang Chen, Jingyu Zhuang, Xiaodan Liang, Liang Lin
http://arxiv.org/abs/1907.03389v1
• [cs.LG]Case-Based Reasoning for Assisting Domain Experts in Processing Fraud Alerts of Black-Box Machine Learning Models
Hilde J. P. Weerts, Werner van Ipenburg, Mykola Pechenizkiy
http://arxiv.org/abs/1907.03334v1
• [cs.LG]Copula & Marginal Flows: Disentangling the Marginal from its Joint
Magnus Wiese, Robert Knobloch, Ralf Korn
http://arxiv.org/abs/1907.03361v1
• [cs.LG]Data Efficient Reinforcement Learning for Legged Robots
Yuxiang Yang, Ken Caluwaerts, Atil Iscen, Tingnan Zhang, Jie Tan, Vikas Sindhwani
http://arxiv.org/abs/1907.03613v1
• [cs.LG]Deep Exponential-Family Auto-Encoders
Bahareh Tolooshams, Andrew H. Song, Simona Temereanca, Demba Ba
http://arxiv.org/abs/1907.03211v1
• [cs.LG]Diachronic Embedding for Temporal Knowledge Graph Completion
Rishab Goel, Seyed Mehran Kazemi, Marcus Brubaker, Pascal Poupart
http://arxiv.org/abs/1907.03143v1
• [cs.LG]Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale
Atılım Güneş Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip Torr, Victor Lee, Kyle Cranmer, Prabhat, Frank Wood
http://arxiv.org/abs/1907.03382v1
• [cs.LG]Expressive power of tensor-network factorizations for probabilistic modeling, with applications from hidden Markov models to quantum machine learning
Ivan Glasser, Ryan Sweke, Nicola Pancotti, Jens Eisert, J. Ignacio Cirac
http://arxiv.org/abs/1907.03741v1
• [cs.LG]Fast ES-RNN: A GPU Implementation of the ES-RNN Algorithm
Andrew Redd, Kaung Khin, Aldo Marini
http://arxiv.org/abs/1907.03329v1
• [cs.LG]Fast and Provable ADMM for Learning with Generative Priors
Fabian Latorre Gómez, Armin Eftekhari, Volkan Cevher
http://arxiv.org/abs/1907.03343v1
• [cs.LG]Gaussian Processes for Analyzing Positioned Trajectories in Sports
Yuxin Zhao, Feng Yin, Fredrik Gunnarsson, Fredrik Hultkrantz
http://arxiv.org/abs/1907.03043v1
• [cs.LG]General non-linear Bellman equations
Hado van Hasselt, John Quan, Matteo Hessel, Zhongwen Xu, Diana Borsa, Andre Barreto
http://arxiv.org/abs/1907.03687v1
• [cs.LG]Generalized Control Functions via Variational Decoupling
Aahlad Manas Puli, Rajesh Ranganath
http://arxiv.org/abs/1907.03451v1
• [cs.LG]Generative Counterfactual Introspection for Explainable Deep Learning
Shusen Liu, Bhavya Kailkhura, Donald Loveland, Yong Han
http://arxiv.org/abs/1907.03077v1
• [cs.LG]Improving Detection of Credit Card Fraudulent Transactions using Generative Adversarial Networks
Hung Ba
http://arxiv.org/abs/1907.03355v1
• [cs.LG]Individual Regret in Cooperative Nonstochastic Multi-Armed Bandits
Yogev Bar-On, Yishay Mansour
http://arxiv.org/abs/1907.03346v1
• [cs.LG]Intelligent Systems Design for Malware Classification Under Adversarial Conditions
Sean M. Devine, Nathaniel D. Bastian
http://arxiv.org/abs/1907.03149v1
• [cs.LG]Intrinsic Motivation Driven Intuitive Physics Learning using Deep Reinforcement Learning with Intrinsic Reward Normalization
JaeWon Choi, Sung-eui Yoon
http://arxiv.org/abs/1907.03116v1
• [cs.LG]Jointly Aligning and Predicting Continuous Emotion Annotations
Soheil Khorram, Melvin G McInnis, Emily Mower Provost
http://arxiv.org/abs/1907.03050v1
• [cs.LG]Learning a Behavioral Repertoire from Demonstrations
Niels Justesen, Miguel Gonzalez Duque, Daniel Cabarcas Jaramillo, Jean-Baptiste Mouret, Sebastian Risi
http://arxiv.org/abs/1907.03046v1
• [cs.LG]Multivariate-Information Adversarial Ensemble for Scalable Joint Distribution Matching
Ziliang Chen, Zhanfu Yang, Xiaoxi Wang, Xiaodan Liang, Xiaopeng Yan, Guanbin Li, Liang Lin
http://arxiv.org/abs/1907.03426v1
• [cs.LG]On-Policy Robot Imitation Learning from a Converging Supervisor
Ashwin Balakrishna, Brijen Thananjeyan, Jonathan Lee, Arsh Zahed, Felix Li, Joseph E. Gonzalez, Ken Goldberg
http://arxiv.org/abs/1907.03423v1
• [cs.LG]Physics Informed Extreme Learning Machine (PIELM) — A rapid method for the numerical solution of partial differential equations
Vikas Dwivedi, Balaji Srinivasan
http://arxiv.org/abs/1907.03507v1
• [cs.LG]Playing Flappy Bird via Asynchronous Advantage Actor Critic Algorithm
Elit Cenk Alp, Mehmet Serdar Guzel
http://arxiv.org/abs/1907.03098v1
• [cs.LG]Policy-Gradient Algorithms Have No Guarantees of Convergence in Continuous Action and State Multi-Agent Settings
Eric Mazumdar, Lillian J. Ratliff, Michael I. Jordan, S. Shankar Sastry
http://arxiv.org/abs/1907.03712v1
• [cs.LG]Predicting Customer Call Intent by Analyzing Phone Call Transcripts based on CNN for Multi-Class Classification
Junmei Zhong, William Li
http://arxiv.org/abs/1907.03715v1
• [cs.LG]Privacy-Preserving Classification with Secret Vector Machines
Valentin Hartmann, Konark Modi, Josep M. Pujol, Robert West
http://arxiv.org/abs/1907.03373v1
• [cs.LG]Quantifying Transparency of Machine Learning Systems through Analysis of Contributions
Iain Barclay, Alun Preece, Ian Taylor, Dinesh Verma
http://arxiv.org/abs/1907.03483v1
• [cs.LG]Quantitative $W_1$ Convergence of Langevin-Like Stochastic Processes with Non-Convex Potential State-Dependent Noise
Xiang Cheng, Peter L. Bartlett, Michael I. Jordan
http://arxiv.org/abs/1907.03215v1
• [cs.LG]Quantum-inspired canonical correlation analysis for exponentially large dimensional data
Naoko Koide-Majima, Kei Majima
http://arxiv.org/abs/1907.03236v1
• [cs.LG]Regularizing linear inverse problems with convolutional neural networks
Reinhard Heckel
http://arxiv.org/abs/1907.03100v1
• [cs.LG]Resource-Efficient Computing in Wearable Systems
Mahdi Pedram, Mahsan Rofouei, Francesco Fraternali, Zhila Esna Ashari, Hassan Ghasemzadeh
http://arxiv.org/abs/1907.03247v1
• [cs.LG]Resource-Efficient Wearable Computing for Real-Time Reconfigurable Machine Learning: A Cascading Binary Classification
Mahdi Pedram, Seyed Ali Rokni, Marjan Nourollahi, Houman Homayoun, Hassan Ghasemzadeh
http://arxiv.org/abs/1907.03250v1
• [cs.LG]Self-supervised Learning of Distance Functions for Goal-Conditioned Reinforcement Learning
Srinivas Venkattaramanujam, Eric Crawford, Thang Doan, Doina Precup
http://arxiv.org/abs/1907.02998v1
• [cs.LG]ShrinkML: End-to-End ASR Model Compression Using Reinforcement Learning
Łukasz Dudziak, Mohamed S. Abdelfattah, Ravichander Vipperla, Stefanos Laskaridis, Nicholas D. Lane
http://arxiv.org/abs/1907.03540v1
• [cs.LG]The Price of Interpretability
Dimitris Bertsimas, Arthur Delarue, Patrick Jaillet, Sebastien Martin
http://arxiv.org/abs/1907.03419v1
• [cs.LG]Towards Debugging Deep Neural Networks by Generating Speech Utterances
Bilal Soomro, Anssi Kanervisto, Trung Ngo Trong, Ville Hautamäki
http://arxiv.org/abs/1907.03164v1
• [cs.LG]Towards Robust, Locally Linear Deep Networks
Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola
http://arxiv.org/abs/1907.03207v1
• [cs.LG]TrackNet: A Deep Learning Network for Tracking High-speed and Tiny Objects in Sports Applications
Yu-Chuan Huang, I-No Liao, Ching-Hsuan Chen, Tsì-Uí İk, Wen-Chih Peng
http://arxiv.org/abs/1907.03698v1
• [cs.LG]Weakly-supervised Knowledge Graph Alignment with Adversarial Learning
Meng Qu, Jian Tang, Yoshua Bengio
http://arxiv.org/abs/1907.03179v1
• [cs.LG]What graph neural networks cannot learn: depth vs width
Andreas Loukas
http://arxiv.org/abs/1907.03199v1
• [cs.MM]Informative Visual Storytelling with Cross-modal Rules
Jiacheng Li, Haizhou Shi, Siliang Tang, Fei Wu, Yueting Zhuang
http://arxiv.org/abs/1907.03240v1
• [cs.NE]Adaptive Neuro-Surrogate-Based Optimisation Method for Wave Energy Converters Placement Optimisation
Mehdi, Neshat, Ehsan, Abbasnejad, Qinfeng, Shi, Bradley, Alexander, Markus, Wagner
http://arxiv.org/abs/1907.03076v1
• [cs.NE]Takens-inspired neuromorphic processor: a downsizing tool for random recurrent neural networks via feature extraction
Bicky A. Marquez, Jose Suarez-Vargas, Bhavin J. Shastri
http://arxiv.org/abs/1907.03122v1
• [cs.NI]The Fog Development Kit: A Development Platform for SDN-based Edge-Fog Systems
Colton Powell, Christopher Desiniotis, Behnam Dezfouli
http://arxiv.org/abs/1907.03081v1
• [cs.PF]Optimizing Xeon Phi for Interactive Data Analysis
Chansup Byun, Jeremy Kepner, William Arcand, David Bestor, William Bergeron, Matthew Hubbell, Vijay Gadepally, Michael Houle, Michael Jones, Anne Klein, Lauren Milechin, Peter Michaleas, Julie Mullen, Andrew Prout, Antonio Rosa, Siddharth Samsi, Charles Yee, Albert Reuther
http://arxiv.org/abs/1907.03195v1
• [cs.RO]A Review of Robot Learning for Manipulation: Challenges, Representations, and Algorithms
Oliver Kroemer, Scott Niekum, George Konidaris
http://arxiv.org/abs/1907.03146v1
• [cs.RO]Augmenting Knowledge through Statistical, Goal-oriented Human-Robot Dialog
Saeid Amiri, Sujay Bajracharya, Cihangir Goktolga, Jesse Thomason, Shiqi Zhang
http://arxiv.org/abs/1907.03390v1
• [cs.RO]Modeling and Simulation of the Quadrtor Delivery System
A. M. El-Edkawy, M. A. El-Dosuky
http://arxiv.org/abs/1907.03716v1
• [cs.RO]Segway DRIVE Benchmark: Place Recognition and SLAM Data Collected by A Fleet of Delivery Robots
Jianzhu Huai, Yusen Qin, Fumin Pang, Zichong Chen
http://arxiv.org/abs/1907.03424v1
• [cs.RO]System Architecture for Real-time Surface Inspection Using Multiple UAVs
Van Truong Hoang, Manh Duong Phung, Tran Hiep Dinh, Quang P. Ha
http://arxiv.org/abs/1907.03305v1
• [cs.RO]Time Distance: A Novel Collision Prediction and Path Planning Method
Ali Analooee, Shahram Azadi, Reza Kazemi
http://arxiv.org/abs/1907.03244v1
• [cs.SD]Towards Explainable Music Emotion Recognition: The Route via Mid-level Features
Shreyan Chowdhury, Andreu Vall, Verena Haunschmid, Gerhard Widmer
http://arxiv.org/abs/1907.03572v1
• [cs.SE]MigrationMiner: An Automated Detection Tool of Third-Party Java Library Migration at the Method Level
Hussein Alrubaye
http://arxiv.org/abs/1907.02997v1
• [cs.SI]Network Embedding: on Compression and Learning
Esra Akbas, Mehmet Aktas
http://arxiv.org/abs/1907.02811v2
• [eess.AS]The GDPR & Speech Data: Reflections of Legal and Technology Communities, First Steps towards a Common Understanding
Andreas Nautsch, Catherine Jasserand, Els Kindt, Massimiliano Todisco, Isabel Trancoso, Nicholas Evans
http://arxiv.org/abs/1907.03458v1
• [eess.IV]Adaptive Weighting Depth-variant Deconvolution of Fluorescence Microscopy Images with Convolutional Neural Network
Da He, De Cai, Jiasheng Zhou, Jiajia Luo, Sung-Liang Chen
http://arxiv.org/abs/1907.03217v1
• [eess.IV]An Experimental-based Review of Image Enhancement and Image Restoration Methods for Underwater Imaging
Yan Wang, Wei Song, Giancarlo Fortino, Lizhe Qi, Wenqiang Zhang, Antonio Liotta
http://arxiv.org/abs/1907.03246v1
• [eess.IV]Assessing Reliability and Challenges of Uncertainty Estimations for Medical Image Segmentation
Alain Jungo, Mauricio Reyes
http://arxiv.org/abs/1907.03338v1
• [eess.IV]Dual Adversarial Learning with Attention Mechanism for Fine-grained Medical Image Synthesis
Dong Nie, Lei Xiang, Qian Wang, Dinggang Shen
http://arxiv.org/abs/1907.03297v1
• [eess.IV]FC$^2$N: Fully Channel-Concatenated Network for Single Image Super-Resolution
Xiaole Zhao, Ying Liao, Ye Li, Tao Zhang, Xueming Zou
http://arxiv.org/abs/1907.03221v1
• [eess.IV]Learning joint lesion and tissue segmentation from task-specific hetero-modal datasets
Reuben Dorent, Wenqi Li, Jinendra Ekanayake, Sebastien Ourselin, Tom Vercauteren
http://arxiv.org/abs/1907.03327v1
• [eess.IV]MRI Super-Resolution with Ensemble Learning and Complementary Priors
Qing Lyu, Hongming Shan, Ge Wang
http://arxiv.org/abs/1907.03063v1
• [eess.IV]Perceptual representations of structural information in images: application to quality assessment of synthesized view in FTV scenario
Ling suiyi, Li Jing, Le Callet Patrick, Wang Junle
http://arxiv.org/abs/1907.03448v1
• [eess.IV]Skin Lesion Analyser: An Efficient Seven-Way Multi-Class Skin Cancer Classification Using MobileNet
Saket S. Chaturvedi, Kajol Gupta, Prakash. S. Prasad
http://arxiv.org/abs/1907.03220v1
• [eess.SP]Vertex-Frequency Graph Signal Processing
Ljubisa Stankovic, Danilo P. Mandic, Milos Dakovic, Bruno Scalzo, Milos Brajovic, Ervin Sejdic, Anthony G. Constantinides
http://arxiv.org/abs/1907.03471v1
• [eess.SY]A New Approach to Distributed Hypothesis Testing and Non-Bayesian Learning: Improved Learning Rate and Byzantine-Resilience
Aritra Mitra, John A. Richards, Shreyas Sundaram
http://arxiv.org/abs/1907.03588v1
• [eess.SY]Smart Households Demand Response Management with Micro Grid
Hossein Mohammadi Rouzbahani, Abolfazl Rahimnezhad, Hadis Karimipour
http://arxiv.org/abs/1907.03641v1
• [math.CO]One-step Majority-logic Decoding with Subspace Designs
Alfred Wassermann
http://arxiv.org/abs/1907.03344v1
• [math.CO]Placement Delivery Arrays from Combinations of Strong Edge Colorings
Jerod Michel, Qi Wang
http://arxiv.org/abs/1907.03177v1
• [math.NA]Deep splitting method for parabolic PDEs
Christian Beck, Sebastian Becker, Patrick Cheridito, Arnulf Jentzen, Ariel Neufeld
http://arxiv.org/abs/1907.03452v1
• [math.OC]ReLU Networks as Surrogate Models in Mixed-Integer Linear Programs
Bjarne Grimstad, Henrik Andersson
http://arxiv.org/abs/1907.03140v1
• [math.OC]Robust Guarantees for Perception-Based Control
Sarah Dean, Nikolai Matni, Benjamin Recht, Vickie Ye
http://arxiv.org/abs/1907.03680v1
• [math.PR]Distance from the Nucleus to a Uniformly Random Point in the Typical and the Crofton Cells of the Poisson-Voronoi Tessellation
Praful D. Mankar, Priyabrata Parida, Harpreet S. Dhillon, Martin Haenggi
http://arxiv.org/abs/1907.03635v1
• [math.PR]Posterior Convergence of $α$-Stable Sheets
Neil K. Chada, Sari. Lasanen, Lassi. Roininen
http://arxiv.org/abs/1907.03086v1
• [math.PR]Volume Doubling Condition and a Local Poincaré Inequality on Unweighted Random Geometric Graphs
Franziska Göbel, Gilles Blanchard
http://arxiv.org/abs/1907.03192v1
• [math.ST]Bayes factors with (overly) informative priors
Richard A Lockhart
http://arxiv.org/abs/1907.02473v2
• [math.ST]Convergence Analysis of a Collapsed Gibbs Sampler for Bayesian Vector Autoregressions
Karl Oskar Ekvall, Galin L. Jones
http://arxiv.org/abs/1907.03170v1
• [math.ST]Estimating location parameters in entangled single-sample distributions
Ankit Pensia, Varun Jog, Po-Ling Loh
http://arxiv.org/abs/1907.03087v1
• [math.ST]Improving Lasso for model selection and prediction
Piotr Pokarowski, Wojciech Rejchel, Agnieszka Soltys, Michal Frej, Jan Mielniczuk
http://arxiv.org/abs/1907.03025v1
• [math.ST]On Inferences from Completed Data
Jamie Haddock, Denali Molitor, Deanna Needell, Sneha Sambandam, Joy Song, Simon Sun
http://arxiv.org/abs/1907.03028v1
• [math.ST]On the Glivenko-Cantelli theorem for the functional empirical process using associated sequences
Harouna Sangare, Gane Samb Lo
http://arxiv.org/abs/1907.03625v1
• [math.ST]Testing Mixtures of Discrete Distributions
Maryam Aliakbarpour, Ravi Kumar, Ronitt Rubinfeld
http://arxiv.org/abs/1907.03190v1
• [physics.comp-ph]IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery
Dipendra Jha, Logan Ward, Zijiang Yang, Christopher Wolverton, Ian Foster, Wei-keng Liao, Alok Choudhary, Ankit Agrawal
http://arxiv.org/abs/1907.03222v1
• [physics.data-an]Precision annealing Monte Carlo methods for statistical data assimilation and machine learning
Zheng Fang, Adrian S. Wong, Kangbo Hao, Alexander J. A. Ty, Henry D. I. Abarbanel
http://arxiv.org/abs/1907.03137v1
• [physics.med-ph]Non-Invasive MGMT Status Prediction in GBM Cancer Using Magnetic Resonance Images (MRI) Radiomics Features: Univariate and Multivariate Machine Learning Radiogenomics Analysis
Ghasem Hajianfar, Isaac Shiri, Hassan Maleki, Niki Oveisi, Abbass Haghparast, Hamid Abdollahi, Mehrdad Oveisi
http://arxiv.org/abs/1907.03495v1
• [physics.soc-ph]Characteristics of human mobility patterns revealed by high-frequency cell-phone position data
Chen Zhao, An Zeng, Chi Ho Yeung
http://arxiv.org/abs/1907.03604v1
• [q-bio.PE]How many groups? A statistical methodology for data-driven partitioning of infectious disease incidence into age-groups
Rami Yaari, Amit Huppert, Itai Dattner
http://arxiv.org/abs/1907.03441v1
• [q-fin.PM]An intelligent financial portfolio trading strategy using deep Q-learning
Hyungjun Park, Min Kyu Sim, Dong Gu Choi
http://arxiv.org/abs/1907.03665v1
• [stat.AP]Causal mechanism of extreme river discharges in the upper Danube basin network
Linda Mhalla, Valérie Chavez-Demoulin, Debbie J. Dupuis
http://arxiv.org/abs/1907.03555v1
• [stat.AP]Filaments of crime: Informing policing via thresholded ridge estimation
Ben Moews, Jaime R. Argueta Jr., Antonia Gieschen
http://arxiv.org/abs/1907.03206v1
• [stat.AP]Investigating some attributes of periodicity in DNA sequences via semi-Markov modelling
Pavlos Kolias, Alexandra Papadopoulou
http://arxiv.org/abs/1907.03119v1
• [stat.ME]A Versatile Estimation Procedure without Estimating the Nonignorable Missingness Mechanism
Jiwei Zhao, Yanyuan Ma
http://arxiv.org/abs/1907.03682v1
• [stat.ME]Bayesian Nonparametric Nonhomogeneous Poisson Process with Applications to USGS Earthquake Data
Junxian Geng, Wei Shi, Guanyu Hu
http://arxiv.org/abs/1907.03186v1
• [stat.ME]Learning a latent pattern of heterogeneity in the innovation rates of a time series of counts
Helton Graziadei, Hedibert F. Lopes, Paulo C. Marques F
http://arxiv.org/abs/1907.03155v1
• [stat.ME]Modeling Symmetric Positive Definite Matrices with An Application to Functional Brain Connectivity
Zhenhua Lin, Dehan Kong, Qiang Sun
http://arxiv.org/abs/1907.03385v1
• [stat.ME]The revisited knockoffs method for variable selection in L1-penalised regressions
Anne Gégout-Petit, Aurélie Gueudin-Muller, Clémence Karmann
http://arxiv.org/abs/1907.03153v1
• [stat.ML]Unbiased estimators for random design regression
Michał Dereziński, Manfred K. Warmuth, Daniel Hsu
http://arxiv.org/abs/1907.03411v1
• [stat.ML]XGBoostLSS — An extension of XGBoost to probabilistic forecasting
Alexander März
http://arxiv.org/abs/1907.03178v1