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.GR - 计算机图形学 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.PF - 计算性能 cs.PL - 编程语言 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 econ.GN - 一般经济学 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.OC - 优化与控制 math.ST - 统计理论 physics.soc-ph - 物理学与社会 q-fin.ST - 统计金融学 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]”Did You Hear That?” Learning to Play Video Games from Audio Cues
• [cs.AI]Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game Jass
• [cs.AI]Two-step Constructive Approaches for Dungeon Generation
• [cs.CL]A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots
• [cs.CL]Automated Curriculum Learning for Turn-level Spoken Language Understanding with Weak Supervision
• [cs.CL]Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology
• [cs.CL]DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain
• [cs.CL]Estimating Causal Effects of Tone in Online Debates
• [cs.CL]Federated Learning for Emoji Prediction in a Mobile Keyboard
• [cs.CL]Generating Summaries with Topic Templates and Structured Convolutional Decoders
• [cs.CL]HEAD-QA: A Healthcare Dataset for Complex Reasoning
• [cs.CL]Identifying Visible Actions in Lifestyle Vlogs
• [cs.CL]Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network
• [cs.CL]Journal Name Extraction from Japanese Scientific News Articles
• [cs.CL]Label-Agnostic Sequence Labeling by Copying Nearest Neighbors
• [cs.CL]Learning a Matching Model with Co-teaching for Multi-turn Response Selection in Retrieval-based Dialogue Systems
• [cs.CL]Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks
• [cs.CL]Modeling Sentiment Dependencies with Graph Convolutional Networks for Aspect-level Sentiment Classification
• [cs.CL]Parallel Scheduled Sampling
• [cs.CL]Psycholinguistics meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering
• [cs.CL]Reinforcement Learning of Minimalist Numeral Grammars
• [cs.CL]Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension
• [cs.CL]Self-Supervised Learning for Contextualized Extractive Summarization
• [cs.CL]Using Structured Representation and Data: A Hybrid Model for Negation and Sentiment in Customer Service Conversations
• [cs.CL]What Does BERT Look At? An Analysis of BERT’s Attention
• [cs.CL]What Kind of Language Is Hard to Language-Model?
• [cs.CL]Word-level Speech Recognition with a Dynamic Lexicon
• [cs.CR]New dynamic and verifiable multi-secret sharing schemes based on LFSR public key cryptosystem
• [cs.CV]3-D Surface Segmentation Meets Conditional Random Fields
• [cs.CV]BDNet: Bengali handwritten numeral digit recognition based on densely connected convolutional neural networks
• [cs.CV]Bag of Color Features For Color Constancy
• [cs.CV]Band Attention Convolutional Networks For Hyperspectral Image Classification
• [cs.CV]CVPR19 Tracking and Detection Challenge: How crowded can it get?
• [cs.CV]Challenges in Time-Stamp Aware Anomaly Detection in Traffic Videos
• [cs.CV]Clouds of Oriented Gradients for 3D Detection of Objects, Surfaces, and Indoor Scene Layouts
• [cs.CV]Cross-Modal Relationship Inference for Grounding Referring Expressions
• [cs.CV]E-LPIPS: Robust Perceptual Image Similarity via Random Transformation Ensembles
• [cs.CV]End-to-End CAD Model Retrieval and 9DoF Alignment in 3D Scans
• [cs.CV]FAMED-Net: A Fast and Accurate Multi-scale End-to-end Dehazing Network
• [cs.CV]FASTER Recurrent Networks for Video Classification
• [cs.CV]Few-Shot Point Cloud Region Annotation with Human in the Loop
• [cs.CV]Gated CRF Loss for Weakly Supervised Semantic Image Segmentation
• [cs.CV]Hybrid Function Sparse Representation towards Image Super Resolution
• [cs.CV]Joint Subspace Recovery and Enhanced Locality Driven Robust Flexible Discriminative Dictionary Learning
• [cs.CV]Large-scale Landmark Retrieval/Recognition under a Noisy and Diverse Dataset
• [cs.CV]Learning robust visual representations using data augmentation invariance
• [cs.CV]Mimic and Fool: A Task Agnostic Adversarial Attack
• [cs.CV]NAS-FCOS: Fast Neural Architecture Search for Object Detection
• [cs.CV]Object-aware Aggregation with Bidirectional Temporal Graph for Video Captioning
• [cs.CV]On Stabilizing Generative Adversarial Training with Noise
• [cs.CV]On the Vector Space in Photoplethysmography Imaging
• [cs.CV]Online Object Representations with Contrastive Learning
• [cs.CV]PAN: Projective Adversarial Network for Medical Image Segmentation
• [cs.CV]Patch Transformer for Multi-tagging Whole Slide Histopathology Images
• [cs.CV]Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval
• [cs.CV]Recognizing License Plates in Real-Time
• [cs.CV]Rethinking Person Re-Identification with Confidence
• [cs.CV]Scale Invariant Fully Convolutional Network: Detecting Hands Efficiently
• [cs.CV]Semantic-guided Encoder Feature Learning for Blurry Boundary Delineation
• [cs.CV]Shapes and Context: In-the-Wild Image Synthesis & Manipulation
• [cs.CV]Simultaneously Learning Architectures and Features of Deep Neural Networks
• [cs.CV]Single Image Blind Deblurring Using Multi-Scale Latent Structure Prior
• [cs.CV]Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
• [cs.CV]SymNet: Symmetrical Filters in Convolutional Neural Networks
• [cs.CV]TW-SMNet: Deep Multitask Learning of Tele-Wide Stereo Matching
• [cs.CV]iProStruct2D: Identifying protein structural classes by deep learning via 2D representations
• [cs.CY]Creation of User Friendly Datasets: Insights from a Case Study concerning Explanations of Loan Denials
• [cs.DC]Anomaly Detection in High Performance Computers: A Vicinity Perspective
• [cs.DC]Membership-based Manoeuvre Negotiation in Autonomous and Safety-critical Vehicular Systems
• [cs.DC]Window Based BFT Blockchain Consensus
• [cs.DL]EXmatcher: Combining Features Based on Reference Strings and Segments to Enhance Citation Matching
• [cs.GR]Differentiable Surface Splatting for Point-based Geometry Processing
• [cs.HC]Human-Machine Collaboration for Fast Land Cover Mapping
• [cs.IR]Evaluation of Seed Set Selection Approaches and Active Learning Strategies in Predictive Coding
• [cs.IR]Modeling the Past and Future Contexts for Session-based Recommendation
• [cs.IR]The snippets taxonomy in web search engines
• [cs.IT]Artificial Noisy MIMO Systems under Correlated Scattering Rayleigh Fading — A Physical Layer Security Approach
• [cs.IT]Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface with Discrete Phase Shifts
• [cs.IT]Dual-Band Fading Multiple Access Relay Channels
• [cs.IT]Orthogonal Cocktail BPSK: Exceeding Shannon Capacity of QPSK Input
• [cs.IT]Rate-Splitting Unifying SDMA, OMA, NOMA, and Multicasting in MISO Broadcast Channel: A Simple Two-User Rate Analysis
• [cs.IT]Reinforcement Learning for Channel Coding: Learned Bit-Flipping Decoding
• [cs.IT]Stability and Metastability of Traffic Dynamics in Uplink Random Access Networks
• [cs.LG]A Taxonomy of Channel Pruning Signals in CNNs
• [cs.LG]A refined primal-dual analysis of the implicit bias
• [cs.LG]Adaptively Preconditioned Stochastic Gradient Langevin Dynamics
• [cs.LG]An Improved Analysis of Training Over-parameterized Deep Neural Networks
• [cs.LG]Analysis Of Momentum Methods
• [cs.LG]Associative Convolutional Layers
• [cs.LG]BasisConv: A method for compressed representation and learning in CNNs
• [cs.LG]Building High-Quality Auction Fraud Dataset
• [cs.LG]Causal Discovery with Reinforcement Learning
• [cs.LG]Communication and Memory Efficient Testing of Discrete Distributions
• [cs.LG]Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer
• [cs.LG]Coupled Variational Recurrent Collaborative Filtering
• [cs.LG]Data-Free Quantization through Weight Equalization and Bias Correction
• [cs.LG]DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks
• [cs.LG]Dynamical Anatomy of NARMA10 Benchmark Task
• [cs.LG]Efficient Kernel-based Subsequence Search for User Identification from Walking Activity
• [cs.LG]Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions
• [cs.LG]Evolutionary Trigger Set Generation for DNN Black-Box Watermarking
• [cs.LG]Exploration via Hindsight Goal Generation
• [cs.LG]Extracting Interpretable Concept-Based Decision Trees from CNNs
• [cs.LG]Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise
• [cs.LG]Fast and Accurate Least-Mean-Squares Solvers
• [cs.LG]Faster Algorithms for High-Dimensional Robust Covariance Estimation
• [cs.LG]Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning
• [cs.LG]Graph Convolutional Transformer: Learning the Graphical Structure of Electronic Health Records
• [cs.LG]Importance Resampling for Off-policy Prediction
• [cs.LG]Large Scale Structure of Neural Network Loss Landscapes
• [cs.LG]Learning Powerful Policies by Using Consistent Dynamics Model
• [cs.LG]Learning Selection Masks for Deep Neural Networks
• [cs.LG]Meta-Learning Neural Bloom Filters
• [cs.LG]Metrics for Learning in Topological Persistence
• [cs.LG]On Single Source Robustness in Deep Fusion Models
• [cs.LG]Optimizing Pipelined Computation and Communication for Latency-Constrained Edge Learning
• [cs.LG]Performance Analysis and Characterization of Training Deep Learning Models on NVIDIA TX2
• [cs.LG]Quantifying Intrinsic Uncertainty in Classification via Deep Dirichlet Mixture Networks
• [cs.LG]Representation Learning-Assisted Click-Through Rate Prediction
• [cs.LG]Scaling Laws for the Principled Design, Initialization and Preconditioning of ReLU Networks
• [cs.LG]Stochastic Neural Network with Kronecker Flow
• [cs.LG]Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective
• [cs.LG]Towards Amortized Ranking-Critical Training for Collaborative Filtering
• [cs.LG]Transfer Learning for Ultrasound Tongue Contour Extraction with Different Domains
• [cs.LG]Ultra Fast Medoid Identification via Correlated Sequential Halving
• [cs.LG]Variance-reduced $Q$-learning is minimax optimal
• [cs.LG]Wasserstein Reinforcement Learning
• [cs.LG]Weight Agnostic Neural Networks
• [cs.LG]WikiDataSets : Standardized sub-graphs from WikiData
• [cs.LG]k-Nearest Neighbor Optimization via Randomized Hyperstructure Convex Hull
• [cs.NE]Classification of EEG Signals using Genetic Programming for Feature Construction
• [cs.NE]Unsupervised Minimax: Adversarial Curiosity, Generative Adversarial Networks, and Predictability Minimization
• [cs.PF]ROOT I/O compression algorithms and their performance impact within Run 3
• [cs.PL]Write, Execute, Assess: Program Synthesis with a REPL
• [cs.RO]Automatic Multi-Sensor Extrinsic Calibration for Mobile Robots
• [cs.RO]Bilevel Optimization for Planning through Contact: A Semidirect Method
• [cs.RO]Design and integration of a parallel, soft robotic end-effector for extracorporeal ultrasound
• [cs.RO]Gait modeling and optimization for the perturbed Stokes regime
• [cs.RO]Visual-Inertial Odometry of Aerial Robots
• [cs.SI]Boosting Students’ Performance With The Aid Of Social Network Analysis
• [cs.SI]Control contribution identifies top driver nodes in complex networks
• [cs.SI]Corrected overlap weight and clustering coefficient
• [cs.SI]Examining Untempered Social Media: Analyzing Cascades of Polarized Conversations
• [cs.SI]Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks
• [cs.SI]Heterogeneous network approach to predict individuals’ mental health
• [cs.SI]Latent Channel Networks
• [cs.SI]Network-based Fake News Detection: A Pattern-driven Approach
• [cs.SI]StRE: Self Attentive Edit Quality Prediction in Wikipedia
• [econ.EM]Bias-Aware Inference in Fuzzy Regression Discontinuity Designs
• [econ.EM]The Regression Discontinuity Design
• [econ.GN]ProPublica’s COMPAS Data Revisited
• [eess.AS]Using generative modelling to produce varied intonation for speech synthesis
• [eess.IV]A Hybrid Approach Between Adversarial Generative Networks and Actor-Critic Policy Gradient for Low Rate High-Resolution Image Compression
• [eess.IV]A Novel Cost Function for Despeckling using Convolutional Neural Networks
• [eess.IV]Alzheimer’s Disease Brain MRI Classification: Challenges and Insights
• [eess.IV]Automatic brain tissue segmentation in fetal MRI using convolutional neural networks
• [eess.IV]BowNet: Dilated Convolution Neural Network for Ultrasound Tongue Contour Extraction
• [eess.IV]Deep learning analysis of cardiac CT angiography for detection of coronary arteries with functionally significant stenosis
• [eess.IV]DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution
• [eess.IV]Generative adversarial network for segmentation of motion affected neonatal brain MRI
• [eess.IV]Multiscale Nakagami parametric imaging for improved liver tumor localization
• [eess.IV]`Project & Excite’ Modules for Segmentation of Volumetric Medical Scans
• [eess.SP]Adaptive Neural Signal Detection for Massive MIMO
• [eess.SP]Beam Learning — Using Machine Learning for Finding Beam Directions
• [eess.SP]Transport Triggered Array Processor for Vision Applications
• [eess.SY]Sequential Source Coding for Stochastic Systems Subject to Finite Rate Constraints
• [math.CO]Schur ring and Codes for $S$-subgroups over $\Z_{2}^{n}$
• [math.OC]Hybrid Nonlinear Observers for Inertial Navigation Using Landmark Measurements
• [math.ST]Convergence of Dümbgen’s Algorithm for Estimation of Tail Inflation
• [math.ST]Detection and estimation of parameters in high dimensional multiple change point regression models via $\ell_1/\ell_0$ regularization and discrete optimization
• [math.ST]Mean estimation and regression under heavy-tailed distributions—a survey
• [math.ST]Monte Carlo and Quasi-Monte Carlo Density Estimation via Conditioning
• [math.ST]Selection consistency of Lasso-based procedures for misspecified high-dimensional binary model and random regressors
• [physics.soc-ph]Achieving competitive advantage in academia through early career coauthorship with top scientists
• [physics.soc-ph]Analysis of the susceptible-infected-susceptible epidemic dynamics in networks via the non-backtracking matrix
• [physics.soc-ph]Intertemporal Community Detection in Bikeshare Networks
• [q-fin.ST]Likelihood Evaluation of Jump-Diffusion Models Using Deterministic Nonlinear Filters
• [quant-ph]Quantum Random Numbers generated by the Cloud Superconducting Quantum Computer
• [stat.AP]Assessing the effects of exposure to sulfuric acid aerosol on respiratory function in adults
• [stat.AP]Causal Inference in Higher Education: Building Better Curriculums
• [stat.AP]Characterization and valuation of uncertainty of calibrated parameters in stochastic decision models
• [stat.AP]Regional economic convergence and spatial quantile regression
• [stat.AP]Statistical Species Identification
• [stat.AP]Technical Preprint: Rationale and Design of a Planned Observational Study to Evaluate the Impact of Hydrocodone Rescheduling on Opioid Prescribing After Surgery
• [stat.CO]Likelihood-free approximate Gibbs sampling
• [stat.ME]Adaptative significance levels in linear regression models with known variance
• [stat.ME]An approximate Bayesian approach to regression estimation with many auxiliary variables
• [stat.ML]Approximate Variational Inference Based on a Finite Sample of Gaussian Latent Variables
• [stat.ML]Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance
• [stat.ML]Efficient structure learning with automatic sparsity selection for causal graph processes
• [stat.ML]Maximum Mean Discrepancy Gradient Flow
• [stat.ML]Principled Training of Neural Networks with Direct Feedback Alignment
• [stat.ML]Probabilistic Forecasting with Temporal Convolutional Neural Network
• [stat.ML]SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation
• [stat.ML]Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
·····································
• [cs.AI]“Did You Hear That?” Learning to Play Video Games from Audio Cues
Raluca D. Gaina, Matthew Stephenson
http://arxiv.org/abs/1906.04027v2
• [cs.AI]Survey of Artificial Intelligence for Card Games and Its Application to the Swiss Game Jass
Joel Niklaus, Michele Alberti, Vinaychandran Pondenkandath, Rolf Ingold, Marcus Liwicki
http://arxiv.org/abs/1906.04439v1
• [cs.AI]Two-step Constructive Approaches for Dungeon Generation
Michael Cerny Green, Ahmed Khalifa, Athoug Alsoughayer, Divyesh Surana, Antonios Liapis, Julian Togelius
http://arxiv.org/abs/1906.04660v1
• [cs.CL]A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots
Xueliang Zhao, Chongyang Tao, Wei Wu, Can Xu, Dongyan Zhao, Rui Yan
http://arxiv.org/abs/1906.04362v1
• [cs.CL]Automated Curriculum Learning for Turn-level Spoken Language Understanding with Weak Supervision
Hao Lang, Wen Wang
http://arxiv.org/abs/1906.04291v1
• [cs.CL]Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology
Ran Zmigrod, Sebastian J. Mielke, Hanna Wallach, Ryan Cotterell
http://arxiv.org/abs/1906.04571v1
• [cs.CL]DoubleTransfer at MEDIQA 2019: Multi-Source Transfer Learning for Natural Language Understanding in the Medical Domain
Yichong Xu, Xiaodong Liu, Chunyuan Li, Hoifung Poon, Jianfeng Gao
http://arxiv.org/abs/1906.04382v1
• [cs.CL]Estimating Causal Effects of Tone in Online Debates
Dhanya Sridhar, Lise Getoor
http://arxiv.org/abs/1906.04177v1
• [cs.CL]Federated Learning for Emoji Prediction in a Mobile Keyboard
Swaroop Ramaswamy, Rajiv Mathews, Kanishka Rao, Françoise Beaufays
http://arxiv.org/abs/1906.04329v1
• [cs.CL]Generating Summaries with Topic Templates and Structured Convolutional Decoders
Laura Perez-Beltrachini, Yang Liu, Mirella Lapata
http://arxiv.org/abs/1906.04687v1
• [cs.CL]HEAD-QA: A Healthcare Dataset for Complex Reasoning
David Vilares, Carlos Gómez-Rodríguez
http://arxiv.org/abs/1906.04701v1
• [cs.CL]Identifying Visible Actions in Lifestyle Vlogs
Oana Ignat, Laura Burdick, Jia Deng, Rada Mihalcea
http://arxiv.org/abs/1906.04236v1
• [cs.CL]Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network
Sunil Kumar Sahu, Fenia Christopoulou, Makoto Miwa, Sophia Ananiadou
http://arxiv.org/abs/1906.04684v1
• [cs.CL]Journal Name Extraction from Japanese Scientific News Articles
Masato Kikuchi, Mitsuo Yoshida, Kyoji Umemura
http://arxiv.org/abs/1906.04655v1
• [cs.CL]Label-Agnostic Sequence Labeling by Copying Nearest Neighbors
Sam Wiseman, Karl Stratos
http://arxiv.org/abs/1906.04225v1
• [cs.CL]Learning a Matching Model with Co-teaching for Multi-turn Response Selection in Retrieval-based Dialogue Systems
Jiazhan Feng, Chongyang Tao, Wei Wu, Yansong Feng, Dongyan Zhao, Rui Yan
http://arxiv.org/abs/1906.04413v1
• [cs.CL]Lightweight and Efficient Neural Natural Language Processing with Quaternion Networks
Yi Tay, Aston Zhang, Luu Anh Tuan, Jinfeng Rao, Shuai Zhang, Shuohang Wang, Jie Fu, Siu Cheung Hui
http://arxiv.org/abs/1906.04393v1
• [cs.CL]Modeling Sentiment Dependencies with Graph Convolutional Networks for Aspect-level Sentiment Classification
Pinlong Zhaoa, Linlin Houb, Ou Wua
http://arxiv.org/abs/1906.04501v1
• [cs.CL]Parallel Scheduled Sampling
Daniel Duckworth, Arvind Neelakantan, Ben Goodrich, Lukasz Kaiser, Samy Bengio
http://arxiv.org/abs/1906.04331v1
• [cs.CL]Psycholinguistics meets Continual Learning: Measuring Catastrophic Forgetting in Visual Question Answering
Claudio Greco, Barbara Plank, Raquel Fernández, Raffaella Bernardi
http://arxiv.org/abs/1906.04229v1
• [cs.CL]Reinforcement Learning of Minimalist Numeral Grammars
Peter beim Graben, Ronald Römer, Werner Meyer, Markus Huber, Matthias Wolff
http://arxiv.org/abs/1906.04447v1
• [cs.CL]Retrieve, Read, Rerank: Towards End-to-End Multi-Document Reading Comprehension
Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li
http://arxiv.org/abs/1906.04618v1
• [cs.CL]Self-Supervised Learning for Contextualized Extractive Summarization
Hong Wang, Xin Wang, Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Shiyu Chang, William Yang Wang
http://arxiv.org/abs/1906.04466v1
• [cs.CL]Using Structured Representation and Data: A Hybrid Model for Negation and Sentiment in Customer Service Conversations
Amita Misra, Mansurul Bhuiyan, Jalal Mahmud, Saurabh Tripathy
http://arxiv.org/abs/1906.04706v1
• [cs.CL]What Does BERT Look At? An Analysis of BERT’s Attention
Kevin Clark, Urvashi Khandelwal, Omer Levy, Christopher D. Manning
http://arxiv.org/abs/1906.04341v1
• [cs.CL]What Kind of Language Is Hard to Language-Model?
Sebastian J. Mielke, Ryan Cotterell, Kyle Gorman, Brian Roark, Jason Eisner
http://arxiv.org/abs/1906.04726v1
• [cs.CL]Word-level Speech Recognition with a Dynamic Lexicon
Ronan Collobert, Awni Hannun, Gabriel Synnaeve
http://arxiv.org/abs/1906.04323v1
• [cs.CR]New dynamic and verifiable multi-secret sharing schemes based on LFSR public key cryptosystem
Jing Yang, Fang-Wei Fu
http://arxiv.org/abs/1906.04611v1
• [cs.CV]3-D Surface Segmentation Meets Conditional Random Fields
Leixin Zhou, Zisha Zhong, Abhay Shah, Xiaodong Wu
http://arxiv.org/abs/1906.04714v1
• [cs.CV]BDNet: Bengali handwritten numeral digit recognition based on densely connected convolutional neural networks
A. Sufian, Anirudha Ghosh, Avijit Naskar, Farhana Sultana
http://arxiv.org/abs/1906.03786v2
• [cs.CV]Bag of Color Features For Color Constancy
Firas Laakom, Nikolaos Passalis, Jenni Raitoharju, Jarno Nikkanen, Anastasios Tefas, Alexandros Iosifidis, Moncef Gabbouj
http://arxiv.org/abs/1906.04445v1
• [cs.CV]Band Attention Convolutional Networks For Hyperspectral Image Classification
Hongwei Dong, Lamei Zhang, Bin Zou
http://arxiv.org/abs/1906.04379v1
• [cs.CV]CVPR19 Tracking and Detection Challenge: How crowded can it get?
Patrick Dendorfer, Hamid Rezatofighi, Anton Milan, Javen Shi, Daniel Cremers, Ian Reid, Stefan Roth, Konrad Schindler, Laura Leal-Taixe
http://arxiv.org/abs/1906.04567v1
• [cs.CV]Challenges in Time-Stamp Aware Anomaly Detection in Traffic Videos
Kuldeep Marotirao Biradar, Ayushi Gupta, Murari Mandal, Santosh Kumar Vipparthi
http://arxiv.org/abs/1906.04574v1
• [cs.CV]Clouds of Oriented Gradients for 3D Detection of Objects, Surfaces, and Indoor Scene Layouts
Zhile Ren, Erik B. Sudderth
http://arxiv.org/abs/1906.04725v1
• [cs.CV]Cross-Modal Relationship Inference for Grounding Referring Expressions
Sibei Yang, Guanbin Li, Yizhou Yu
http://arxiv.org/abs/1906.04464v1
• [cs.CV]E-LPIPS: Robust Perceptual Image Similarity via Random Transformation Ensembles
Markus Kettunen, Erik Härkönen, Jaakko Lehtinen
http://arxiv.org/abs/1906.03973v2
• [cs.CV]End-to-End CAD Model Retrieval and 9DoF Alignment in 3D Scans
Armen Avetisyan, Angela Dai, Matthias Nießner
http://arxiv.org/abs/1906.04201v1
• [cs.CV]FAMED-Net: A Fast and Accurate Multi-scale End-to-end Dehazing Network
Jing Zhang, Dacheng Tao
http://arxiv.org/abs/1906.04334v1
• [cs.CV]FASTER Recurrent Networks for Video Classification
Linchao Zhu, Laura Sevilla-Lara, Du Tran, Matt Feiszli, Yi Yang, Heng Wang
http://arxiv.org/abs/1906.04226v1
• [cs.CV]Few-Shot Point Cloud Region Annotation with Human in the Loop
Siddhant Jain, Sowmya Munukutla, David Held
http://arxiv.org/abs/1906.04409v1
• [cs.CV]Gated CRF Loss for Weakly Supervised Semantic Image Segmentation
Anton Obukhov, Stamatios Georgoulis, Dengxin Dai, Luc Van Gool
http://arxiv.org/abs/1906.04651v1
• [cs.CV]Hybrid Function Sparse Representation towards Image Super Resolution
Junyi Bian, Baojun Lin, Ke Zhang
http://arxiv.org/abs/1906.04363v1
• [cs.CV]Joint Subspace Recovery and Enhanced Locality Driven Robust Flexible Discriminative Dictionary Learning
Zhao Zhang, Jiahuan Ren, Weiming Jiang, Zheng Zhang, Richang Hong, Shuicheng Yan, Meng Wang
http://arxiv.org/abs/1906.04598v1
• [cs.CV]Large-scale Landmark Retrieval/Recognition under a Noisy and Diverse Dataset
Kohei Ozaki, Shuhei Yokoo
http://arxiv.org/abs/1906.04087v2
• [cs.CV]Learning robust visual representations using data augmentation invariance
Alex Hernández-García, Peter König, Tim C. Kietzmann
http://arxiv.org/abs/1906.04547v1
• [cs.CV]Mimic and Fool: A Task Agnostic Adversarial Attack
Akshay Chaturvedi, Utpal Garain
http://arxiv.org/abs/1906.04606v1
• [cs.CV]NAS-FCOS: Fast Neural Architecture Search for Object Detection
Ning Wang, Yang Gao, Hao Chen, Peng Wang, Zhi Tian, Chunhua Shen
http://arxiv.org/abs/1906.04423v1
• [cs.CV]Object-aware Aggregation with Bidirectional Temporal Graph for Video Captioning
Junchao Zhang, Yuxin Peng
http://arxiv.org/abs/1906.04375v1
• [cs.CV]On Stabilizing Generative Adversarial Training with Noise
Simon Jenni, Paolo Favaro
http://arxiv.org/abs/1906.04612v1
• [cs.CV]On the Vector Space in Photoplethysmography Imaging
Christian S. Pilz, Vladimir Blazek, Steffen Leonhardt
http://arxiv.org/abs/1906.04431v1
• [cs.CV]Online Object Representations with Contrastive Learning
Sören Pirk, Mohi Khansari, Yunfei Bai, Corey Lynch, Pierre Sermanet
http://arxiv.org/abs/1906.04312v1
• [cs.CV]PAN: Projective Adversarial Network for Medical Image Segmentation
Naji Khosravan, Aliasghar Mortazi, Michael Wallace, Ulas Bagci
http://arxiv.org/abs/1906.04378v1
• [cs.CV]Patch Transformer for Multi-tagging Whole Slide Histopathology Images
Weijian Li, Viet-Duy Nguyen, Haofu Liao, Matt Wilder, Ke Cheng, Jiebo Luo
http://arxiv.org/abs/1906.04151v2
• [cs.CV]Polysemous Visual-Semantic Embedding for Cross-Modal Retrieval
Yale Song, Mohammad Soleymani
http://arxiv.org/abs/1906.04402v1
• [cs.CV]Recognizing License Plates in Real-Time
Xuewen Yang, Xin Wang
http://arxiv.org/abs/1906.04376v1
• [cs.CV]Rethinking Person Re-Identification with Confidence
George Adaimi, Sven Kreiss, Alexandre Alahi
http://arxiv.org/abs/1906.04692v1
• [cs.CV]Scale Invariant Fully Convolutional Network: Detecting Hands Efficiently
Dan Liu, Dawei Du, Libo Zhang, Tiejian Luo, Yanjun Wu, Feiyue Huang, Siwei Lyu
http://arxiv.org/abs/1906.04634v1
• [cs.CV]Semantic-guided Encoder Feature Learning for Blurry Boundary Delineation
Dong Nie, Dinggang Shen
http://arxiv.org/abs/1906.04306v1
• [cs.CV]Shapes and Context: In-the-Wild Image Synthesis & Manipulation
Aayush Bansal, Yaser Sheikh, Deva Ramanan
http://arxiv.org/abs/1906.04728v1
• [cs.CV]Simultaneously Learning Architectures and Features of Deep Neural Networks
Tinghuai Wang, Lixin Fan, Huiling Wang
http://arxiv.org/abs/1906.04505v1
• [cs.CV]Single Image Blind Deblurring Using Multi-Scale Latent Structure Prior
Yuanchao Bai, Huizhu Jia, Ming Jiang, Xianming Liu, Xiaodong Xie, Wen Gao
http://arxiv.org/abs/1906.04442v1
• [cs.CV]Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks
Ziang Yan, Yiwen Guo, Changshui Zhang
http://arxiv.org/abs/1906.04392v1
• [cs.CV]SymNet: Symmetrical Filters in Convolutional Neural Networks
Gregory Dzhezyan, Hubert Cecotti
http://arxiv.org/abs/1906.04252v1
• [cs.CV]TW-SMNet: Deep Multitask Learning of Tele-Wide Stereo Matching
Mostafa El-Khamy, Haoyu Ren, Xianzhi Du, Jungwon Lee
http://arxiv.org/abs/1906.04463v1
• [cs.CV]iProStruct2D: Identifying protein structural classes by deep learning via 2D representations
Loris Nanni, Alessandra Lumini, Federica Pasquali, Sheryl Brahnam
http://arxiv.org/abs/1906.04407v1
• [cs.CY]Creation of User Friendly Datasets: Insights from a Case Study concerning Explanations of Loan Denials
Ajay Chander, Ramya Srinivasan
http://arxiv.org/abs/1906.04643v1
• [cs.DC]Anomaly Detection in High Performance Computers: A Vicinity Perspective
Siavash Ghiasvand, Florina M. Ciorba
http://arxiv.org/abs/1906.04550v1
• [cs.DC]Membership-based Manoeuvre Negotiation in Autonomous and Safety-critical Vehicular Systems
Antonio Casimiro, Emelie Ekenstedt, Elad Michael Schiller
http://arxiv.org/abs/1906.04703v1
• [cs.DC]Window Based BFT Blockchain Consensus
Mohammad M. Jalalzai, Costas Busch
http://arxiv.org/abs/1906.04381v1
• [cs.DL]EXmatcher: Combining Features Based on Reference Strings and Segments to Enhance Citation Matching
Behnam Ghavimi, Wolfgang Otto, Philipp Mayr
http://arxiv.org/abs/1906.04484v1
• [cs.GR]Differentiable Surface Splatting for Point-based Geometry Processing
Wang Yifan, Felice Serena, Shihao Wu, Cengiz Öztireli, Olga Sorkine-Hornung
http://arxiv.org/abs/1906.04173v1
• [cs.HC]Human-Machine Collaboration for Fast Land Cover Mapping
Caleb Robinson, Anthony Ortiz, Kolya Malkin, Blake Elias, Andi Peng, Dan Morris, Bistra Dilkina, Nebojsa Jojic
http://arxiv.org/abs/1906.04176v1
• [cs.IR]Evaluation of Seed Set Selection Approaches and Active Learning Strategies in Predictive Coding
Christian J. Mahoney, Nathaniel Huber-Fliflet, Haozhen Zhao, Jianping Zhang, Peter Gronvall, Shi Ye
http://arxiv.org/abs/1906.04367v1
• [cs.IR]Modeling the Past and Future Contexts for Session-based Recommendation
Yuan Fajie, He Xiangnan, Guo Guibing, Xu Zhezhao, Xiong Jian, He Xiuqiang
http://arxiv.org/abs/1906.04473v1
• [cs.IR]The snippets taxonomy in web search engines
Artur Strzelecki, Paulina Rutecka
http://arxiv.org/abs/1906.04497v1
• [cs.IT]Artificial Noisy MIMO Systems under Correlated Scattering Rayleigh Fading — A Physical Layer Security Approach
Yiliang Liu, Hsiao-Hwa Chen, Liangmin Wang, Weixiao Meng
http://arxiv.org/abs/1906.04289v1
• [cs.IT]Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface with Discrete Phase Shifts
Qingqing Wu, Rui Zhang
http://arxiv.org/abs/1906.03165v2
• [cs.IT]Dual-Band Fading Multiple Access Relay Channels
Subhajit Majhi, Patrick Mitran
http://arxiv.org/abs/1906.04609v1
• [cs.IT]Orthogonal Cocktail BPSK: Exceeding Shannon Capacity of QPSK Input
Bingli Jiao
http://arxiv.org/abs/1906.04440v1
• [cs.IT]Rate-Splitting Unifying SDMA, OMA, NOMA, and Multicasting in MISO Broadcast Channel: A Simple Two-User Rate Analysis
Bruno Clerckx, Yijie Mao, Robert Schober, H. Vincent Poor
http://arxiv.org/abs/1906.04474v1
• [cs.IT]Reinforcement Learning for Channel Coding: Learned Bit-Flipping Decoding
Fabrizio Carpi, Christian Häger, Marco Martalò, Riccardo Raheli, Henry D. Pfister
http://arxiv.org/abs/1906.04448v1
• [cs.IT]Stability and Metastability of Traffic Dynamics in Uplink Random Access Networks
Ahmad AlAmmouri, Jeffrey G. Andrews, Francois Baccelli
http://arxiv.org/abs/1906.04683v1
• [cs.LG]A Taxonomy of Channel Pruning Signals in CNNs
Kaveena Persand, Andrew Anderson, David Gregg
http://arxiv.org/abs/1906.04675v1
• [cs.LG]A refined primal-dual analysis of the implicit bias
Ziwei Ji, Matus Telgarsky
http://arxiv.org/abs/1906.04540v1
• [cs.LG]Adaptively Preconditioned Stochastic Gradient Langevin Dynamics
Chandrasekaran Anirudh Bhardwaj
http://arxiv.org/abs/1906.04324v1
• [cs.LG]An Improved Analysis of Training Over-parameterized Deep Neural Networks
Difan Zou, Quanquan Gu
http://arxiv.org/abs/1906.04688v1
• [cs.LG]Analysis Of Momentum Methods
Nikola B. Kovachki, Andrew M. Stuart
http://arxiv.org/abs/1906.04285v1
• [cs.LG]Associative Convolutional Layers
Hamed Omidvar, Vahideh Akhlaghi, Massimo Franceschetti, Rajesh K. Gupta
http://arxiv.org/abs/1906.04309v1
• [cs.LG]BasisConv: A method for compressed representation and learning in CNNs
Muhammad Tayyab, Abhijit Mahalanobis
http://arxiv.org/abs/1906.04509v1
• [cs.LG]Building High-Quality Auction Fraud Dataset
Sulaf Elshaar, Samira Sadaoui
http://arxiv.org/abs/1906.04272v1
• [cs.LG]Causal Discovery with Reinforcement Learning
Shengyu Zhu, Zhitang Chen
http://arxiv.org/abs/1906.04477v1
• [cs.LG]Communication and Memory Efficient Testing of Discrete Distributions
Ilias Diakonikolas, Themis Gouleakis, Daniel M. Kane, Sankeerth Rao
http://arxiv.org/abs/1906.04709v1
• [cs.LG]Continual Reinforcement Learning deployed in Real-life using Policy Distillation and Sim2Real Transfer
René Traoré, Hugo Caselles-Dupré, Timothée Lesort, Te Sun, Natalia Díaz-Rodríguez, David Filliat
http://arxiv.org/abs/1906.04452v1
• [cs.LG]Coupled Variational Recurrent Collaborative Filtering
Qingquan Song, Shiyu Chang, Xia Hu
http://arxiv.org/abs/1906.04386v1
• [cs.LG]Data-Free Quantization through Weight Equalization and Bias Correction
Markus Nagel, Mart van Baalen, Tijmen Blankevoort, Max Welling
http://arxiv.org/abs/1906.04721v1
• [cs.LG]DropConnect Is Effective in Modeling Uncertainty of Bayesian Deep Networks
Aryan Mobiny, Hien V. Nguyen, Supratik Moulik, Naveen Garg, Carol C. Wu
http://arxiv.org/abs/1906.04569v1
• [cs.LG]Dynamical Anatomy of NARMA10 Benchmark Task
Tomoyuki Kubota, Kohei Nakajima, Hirokazu Takahashi
http://arxiv.org/abs/1906.04608v1
• [cs.LG]Efficient Kernel-based Subsequence Search for User Identification from Walking Activity
Candelieri Antonio, Fedorov Stanislav, Messina Vincenzina
http://arxiv.org/abs/1906.04680v1
• [cs.LG]Evaluating aleatoric and epistemic uncertainties of time series deep learning models for soil moisture predictions
Kuai Fang, Chaopeng Shen, Daniel Kifer
http://arxiv.org/abs/1906.04595v1
• [cs.LG]Evolutionary Trigger Set Generation for DNN Black-Box Watermarking
Jia Guo, Miodrag Potkonjak
http://arxiv.org/abs/1906.04411v1
• [cs.LG]Exploration via Hindsight Goal Generation
Zhizhou Ren, Kefan Dong, Yuan Zhou, Qiang Liu, Jian Peng
http://arxiv.org/abs/1906.04279v1
• [cs.LG]Extracting Interpretable Concept-Based Decision Trees from CNNs
Conner Chyung, Michael Tsang, Yan Liu
http://arxiv.org/abs/1906.04664v1
• [cs.LG]Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise
Henry W. J. Reeve, Ata Kaban
http://arxiv.org/abs/1906.04542v1
• [cs.LG]Fast and Accurate Least-Mean-Squares Solvers
Alaa Maalouf, Ibrahim Jubran, Dan Feldman
http://arxiv.org/abs/1906.04705v1
• [cs.LG]Faster Algorithms for High-Dimensional Robust Covariance Estimation
Yu Cheng, Ilias Diakonikolas, Rong Ge, David Woodruff
http://arxiv.org/abs/1906.04661v1
• [cs.LG]Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning
Mahmoud Assran, Joshua Romoff, Nicolas Ballas, Joelle Pineau, Mike Rabbat
http://arxiv.org/abs/1906.04585v1
• [cs.LG]Graph Convolutional Transformer: Learning the Graphical Structure of Electronic Health Records
Edward Choi, Zhen Xu, Yujia Li, Michael W. Dusenberry, Gerardo Flores, Yuan Xue, Andrew M. Dai
http://arxiv.org/abs/1906.04716v1
• [cs.LG]Importance Resampling for Off-policy Prediction
Matthew Schlegel, Wesley Chung, Daniel Graves, Jian Qian, Martha White
http://arxiv.org/abs/1906.04328v1
• [cs.LG]Large Scale Structure of Neural Network Loss Landscapes
Stanislav Fort, Stanislaw Jastrzebski
http://arxiv.org/abs/1906.04724v1
• [cs.LG]Learning Powerful Policies by Using Consistent Dynamics Model
Shagun Sodhani, Anirudh Goyal, Tristan Deleu, Yoshua Bengio, Sergey Levine, Jian Tang
http://arxiv.org/abs/1906.04355v1
• [cs.LG]Learning Selection Masks for Deep Neural Networks
Stefan Oehmcke, Fabian Gieseke
http://arxiv.org/abs/1906.04673v1
• [cs.LG]Meta-Learning Neural Bloom Filters
Jack W Rae, Sergey Bartunov, Timothy P Lillicrap
http://arxiv.org/abs/1906.04304v1
• [cs.LG]Metrics for Learning in Topological Persistence
Henri Riihimäki, José Licón-Saláiz
http://arxiv.org/abs/1906.04436v1
• [cs.LG]On Single Source Robustness in Deep Fusion Models
Taewan Kim, Joydeep Ghosh
http://arxiv.org/abs/1906.04691v1
• [cs.LG]Optimizing Pipelined Computation and Communication for Latency-Constrained Edge Learning
Nicolas Skatchkovsky, Osvaldo Simeone
http://arxiv.org/abs/1906.04488v1
• [cs.LG]Performance Analysis and Characterization of Training Deep Learning Models on NVIDIA TX2
Jie Liu, Jiawen Liu, Wan Du, Dong Li
http://arxiv.org/abs/1906.04278v1
• [cs.LG]Quantifying Intrinsic Uncertainty in Classification via Deep Dirichlet Mixture Networks
Qingyang Wu, He Li, Weijie Su, Lexin Li, Zhou Yu
http://arxiv.org/abs/1906.04450v1
• [cs.LG]Representation Learning-Assisted Click-Through Rate Prediction
Wentao Ouyang, Xiuwu Zhang, Shukui Ren, Chao Qi, Zhaojie Liu, Yanlong Du
http://arxiv.org/abs/1906.04365v1
• [cs.LG]Scaling Laws for the Principled Design, Initialization and Preconditioning of ReLU Networks
Aaron Defazio, Léon Bottou
http://arxiv.org/abs/1906.04267v1
• [cs.LG]Stochastic Neural Network with Kronecker Flow
Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron Courville
http://arxiv.org/abs/1906.04282v1
• [cs.LG]Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective
Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin
http://arxiv.org/abs/1906.04214v1
• [cs.LG]Towards Amortized Ranking-Critical Training for Collaborative Filtering
Sam Lobel, Chunyuan Li, Jianfeng Gao, Lawrence Carin
http://arxiv.org/abs/1906.04281v1
• [cs.LG]Transfer Learning for Ultrasound Tongue Contour Extraction with Different Domains
M. Hamed Mozaffari, Won-Sook Lee
http://arxiv.org/abs/1906.04301v1
• [cs.LG]Ultra Fast Medoid Identification via Correlated Sequential Halving
Tavor Z. Baharav, David N. Tse
http://arxiv.org/abs/1906.04356v1
• [cs.LG]Variance-reduced $Q$-learning is minimax optimal
Martin J. Wainwright
http://arxiv.org/abs/1906.04697v1
• [cs.LG]Wasserstein Reinforcement Learning
Aldo Pacchiano, Jack Parker-Holder, Yunhao Tang, Anna Choromanska, Krzysztof Choromanski, Michael Jordan
http://arxiv.org/abs/1906.04349v1
• [cs.LG]Weight Agnostic Neural Networks
Adam Gaier, David Ha
http://arxiv.org/abs/1906.04358v1
• [cs.LG]WikiDataSets : Standardized sub-graphs from WikiData
Armand Boschin
http://arxiv.org/abs/1906.04536v1
• [cs.LG]k-Nearest Neighbor Optimization via Randomized Hyperstructure Convex Hull
Jasper Kyle Catapang
http://arxiv.org/abs/1906.04559v1
• [cs.NE]Classification of EEG Signals using Genetic Programming for Feature Construction
Icaro Marcelino Miranda, Claus Aranha, Marcelo Ladeira
http://arxiv.org/abs/1906.04403v1
• [cs.NE]Unsupervised Minimax: Adversarial Curiosity, Generative Adversarial Networks, and Predictability Minimization
Juergen Schmidhuber
http://arxiv.org/abs/1906.04493v1
• [cs.PF]ROOT I/O compression algorithms and their performance impact within Run 3
Oksana Shadura, Brian Paul Bockelman
http://arxiv.org/abs/1906.04624v1
• [cs.PL]Write, Execute, Assess: Program Synthesis with a REPL
Kevin Ellis, Maxwell Nye, Yewen Pu, Felix Sosa, Josh Tenenbaum, Armando Solar-Lezama
http://arxiv.org/abs/1906.04604v1
• [cs.RO]Automatic Multi-Sensor Extrinsic Calibration for Mobile Robots
David Zuñiga-Noël, Jose-Raul Ruiz-Sarmiento, Ruben Gomez-Ojeda, Javier Gonzalez-Jimenez
http://arxiv.org/abs/1906.04670v1
• [cs.RO]Bilevel Optimization for Planning through Contact: A Semidirect Method
Benoit Landry, Joseph Lorenzetti, Zachary Manchester, Marco Pavone
http://arxiv.org/abs/1906.04292v1
• [cs.RO]Design and integration of a parallel, soft robotic end-effector for extracorporeal ultrasound
Lukas Lindenroth, Richard James Housden, Shuangyi Wang, Junghwan Back, Kawal Rhode, Hongbin Liu
http://arxiv.org/abs/1906.04526v1
• [cs.RO]Gait modeling and optimization for the perturbed Stokes regime
Matthew D. Kvalheim, Brian Bittner, Shai Revzen
http://arxiv.org/abs/1906.04384v1
• [cs.RO]Visual-Inertial Odometry of Aerial Robots
Davide Scaramuzza, Zichao Zhang
http://arxiv.org/abs/1906.03289v1
• [cs.SI]Boosting Students’ Performance With The Aid Of Social Network Analysis
R. U. Gobithaasan, Nurul Syaheera Din, Lingeswaran Ramachandra, Roslan Hasni
http://arxiv.org/abs/1906.04352v1
• [cs.SI]Control contribution identifies top driver nodes in complex networks
Yan Zhang, Antonios Garas, Frank Schweitzer
http://arxiv.org/abs/1906.04663v1
• [cs.SI]Corrected overlap weight and clustering coefficient
Vladimir Batagelj
http://arxiv.org/abs/1906.04581v1
• [cs.SI]Examining Untempered Social Media: Analyzing Cascades of Polarized Conversations
Arunkumar Bagavathi, Pedram Bashiri, Shannon Reid, Matthew Phillips, Siddharth Krishnan
http://arxiv.org/abs/1906.04261v1
• [cs.SI]Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks
Hao Peng, Jianxin Li, Qiran Gong, Yangqiu Song, Yuanxing Ning, Kunfeng Lai, Philip S. Yu
http://arxiv.org/abs/1906.04580v1
• [cs.SI]Heterogeneous network approach to predict individuals’ mental health
Shikang Liu, Fatemeh Vahedian, David Hachen, Omar Lizardo, Christian Poellabauer, Aaron Striegel, Tijana Milenkovic
http://arxiv.org/abs/1906.04346v1
• [cs.SI]Latent Channel Networks
Clifford Anderson-Bergman
http://arxiv.org/abs/1906.04563v1
• [cs.SI]Network-based Fake News Detection: A Pattern-driven Approach
Xinyi Zhou, Reza Zafarani
http://arxiv.org/abs/1906.04210v1
• [cs.SI]StRE: Self Attentive Edit Quality Prediction in Wikipedia
Soumya Sarkar, Bhanu Prakash Reddy, Sandipan Sikdar, Animesh Mukherjee
http://arxiv.org/abs/1906.04678v1
• [econ.EM]Bias-Aware Inference in Fuzzy Regression Discontinuity Designs
Claudia Noack, Christoph Rothe
http://arxiv.org/abs/1906.04631v1
• [econ.EM]The Regression Discontinuity Design
Matias D. Cattaneo, Rocio Titiunik, Gonzalo Vazquez-Bare
http://arxiv.org/abs/1906.04242v1
• [econ.GN]ProPublica’s COMPAS Data Revisited
Matias Barenstein
http://arxiv.org/abs/1906.04711v1
• [eess.AS]Using generative modelling to produce varied intonation for speech synthesis
Zack Hodari, Oliver Watts, Simon King
http://arxiv.org/abs/1906.04233v1
• [eess.IV]A Hybrid Approach Between Adversarial Generative Networks and Actor-Critic Policy Gradient for Low Rate High-Resolution Image Compression
Nicoló Savioli
http://arxiv.org/abs/1906.04681v1
• [eess.IV]A Novel Cost Function for Despeckling using Convolutional Neural Networks
Giampaolo Ferraioli, Vito Pascazio, Sergio Vitale
http://arxiv.org/abs/1906.04441v1
• [eess.IV]Alzheimer’s Disease Brain MRI Classification: Challenges and Insights
Yi Ren Fung, Ziqiang Guan, Ritesh Kumar, Joie Yeahuay Wu, Madalina Fiterau
http://arxiv.org/abs/1906.04231v1
• [eess.IV]Automatic brain tissue segmentation in fetal MRI using convolutional neural networks
N. Khalili, N. Lessmann, E. Turk, N. Claessens, R. de Heus, T. Kolk, M. A. Viergever, M. J. N. L. Benders, I. Isgum
http://arxiv.org/abs/1906.04713v1
• [eess.IV]BowNet: Dilated Convolution Neural Network for Ultrasound Tongue Contour Extraction
M. Hamed Mozaffari, Won-Sook Lee
http://arxiv.org/abs/1906.04232v1
• [eess.IV]Deep learning analysis of cardiac CT angiography for detection of coronary arteries with functionally significant stenosis
Majd Zreik, Robbert W. van Hamersvelt, Nadieh Khalili, Jelmer M. Wolterink, Michiel Voskuil, Max A. Viergever, Tim Leiner, Ivana Išgum
http://arxiv.org/abs/1906.04419v1
• [eess.IV]DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution
Shanshan Wang, Huitao Cheng, Leslie Ying, Taohui Xiao, Ziwen Ke, Xin Liu, Hairong Zheng, Dong Liang
http://arxiv.org/abs/1906.04359v1
• [eess.IV]Generative adversarial network for segmentation of motion affected neonatal brain MRI
N. Khalili, E. Turk, M. Zreik, M. A. Viergever, M. J. N. L. Benders, I. Isgum
http://arxiv.org/abs/1906.04704v1
• [eess.IV]Multiscale Nakagami parametric imaging for improved liver tumor localization
Omar S. Al-Kadi
http://arxiv.org/abs/1906.04333v1
• [eess.IV]`Project & Excite’ Modules for Segmentation of Volumetric Medical Scans
Anne-Marie Rickmann, Abhijit Guha Roy, Ignacio Sarasua, Nassir Navab, Christian Wachinger
http://arxiv.org/abs/1906.04649v1
• [eess.SP]Adaptive Neural Signal Detection for Massive MIMO
Mehrdad Khani, Mohammad Alizadeh, Jakob Hoydis, Phil Fleming
http://arxiv.org/abs/1906.04610v1
• [eess.SP]Beam Learning — Using Machine Learning for Finding Beam Directions
Saidhiraj Amuru
http://arxiv.org/abs/1906.04368v1
• [eess.SP]Transport Triggered Array Processor for Vision Applications
Mehdi Safarpour, Ilkka Hautala, Miguel Bordallo Lopez, Olli Silven
http://arxiv.org/abs/1906.04258v1
• [eess.SY]Sequential Source Coding for Stochastic Systems Subject to Finite Rate Constraints
Photios A. Stavrou, Mikael Skoglund, Takashi Tanaka
http://arxiv.org/abs/1906.04217v1
• [math.CO]Schur ring and Codes for $S$-subgroups over $\Z_{2}^{n}$
Ronald Orozco López
http://arxiv.org/abs/1906.04250v1
• [math.OC]Hybrid Nonlinear Observers for Inertial Navigation Using Landmark Measurements
Miaomiao Wang, Abdelhamid Tayebi
http://arxiv.org/abs/1906.04689v1
• [math.ST]Convergence of Dümbgen’s Algorithm for Estimation of Tail Inflation
Jasha Sommer-Simpson
http://arxiv.org/abs/1906.04544v1
• [math.ST]Detection and estimation of parameters in high dimensional multiple change point regression models via $\ell_1/\ell_0$ regularization and discrete optimization
Abhishek Kaul, Venkata K Jandhyala, Stergios B Fotopoulos
http://arxiv.org/abs/1906.04396v1
• [math.ST]Mean estimation and regression under heavy-tailed distributions—a survey
Gabor Lugosi, Shahar Mendelson
http://arxiv.org/abs/1906.04280v1
• [math.ST]Monte Carlo and Quasi-Monte Carlo Density Estimation via Conditioning
Pierre L’Ecuyer, Florian Puchhammer, Amal Ben Abdellah
http://arxiv.org/abs/1906.04607v1
• [math.ST]Selection consistency of Lasso-based procedures for misspecified high-dimensional binary model and random regressors
Mariusz Kubkowski, Jan Mielniczuk
http://arxiv.org/abs/1906.04175v1
• [physics.soc-ph]Achieving competitive advantage in academia through early career coauthorship with top scientists
Weihua Li, Tomaso Aste, Fabio Caccioli, Giacomo Livan
http://arxiv.org/abs/1906.04619v1
• [physics.soc-ph]Analysis of the susceptible-infected-susceptible epidemic dynamics in networks via the non-backtracking matrix
Naoki Masuda, Masaki Ogura, Victor M. Preciado
http://arxiv.org/abs/1906.04269v1
• [physics.soc-ph]Intertemporal Community Detection in Bikeshare Networks
Mark He, Joseph Glasser, Shankar Bhamidi, Nikhil Kaza
http://arxiv.org/abs/1906.04582v1
• [q-fin.ST]Likelihood Evaluation of Jump-Diffusion Models Using Deterministic Nonlinear Filters
Jean-François Bégin, Mathieu Boudreault
http://arxiv.org/abs/1906.04322v1
• [quant-ph]Quantum Random Numbers generated by the Cloud Superconducting Quantum Computer
Kentaro Tamura, Yutaka Shikano
http://arxiv.org/abs/1906.04410v1
• [stat.AP]Assessing the effects of exposure to sulfuric acid aerosol on respiratory function in adults
Lamin Juwara, Jennifer Boateng
http://arxiv.org/abs/1906.04296v1
• [stat.AP]Causal Inference in Higher Education: Building Better Curriculums
Prableen Kaur, Agoritsa Polyzou, George Karypis
http://arxiv.org/abs/1906.04698v1
• [stat.AP]Characterization and valuation of uncertainty of calibrated parameters in stochastic decision models
Fernando Alarid-Escudero, Amy B. Knudsen, Jonathan Ozik, Nicholson Collier, Karen M. Kuntz
http://arxiv.org/abs/1906.04668v1
• [stat.AP]Regional economic convergence and spatial quantile regression
Alfredo Cartone, Geoffrey JD Hewings, Paolo Postiglione
http://arxiv.org/abs/1906.04613v1
• [stat.AP]Statistical Species Identification
Måns Karlsson, Ola Hössjer
http://arxiv.org/abs/1906.04538v1
• [stat.AP]Technical Preprint: Rationale and Design of a Planned Observational Study to Evaluate the Impact of Hydrocodone Rescheduling on Opioid Prescribing After Surgery
Mark D. Neuman, Sean Hennessy, Dylan Small, Colleen Brensinger, Craig Newcomb, Lakisha Gaskins, Duminda Wijeysundera, Brian T. Bateman, Hannah Wunsch
http://arxiv.org/abs/1906.04246v1
• [stat.CO]Likelihood-free approximate Gibbs sampling
G. S. Rodrigues, D. J. Nott, S. A. Sisson
http://arxiv.org/abs/1906.04347v1
• [stat.ME]Adaptative significance levels in linear regression models with known variance
Alejandra Estefanía Patiño Hoyos, Victor Fossaluza
http://arxiv.org/abs/1906.04222v1
• [stat.ME]An approximate Bayesian approach to regression estimation with many auxiliary variables
Shonosuke Sugasawa, Jae Kwang Kim
http://arxiv.org/abs/1906.04398v1
• [stat.ML]Approximate Variational Inference Based on a Finite Sample of Gaussian Latent Variables
Nikolaos Gianniotis, Christoph Schnörr, Christian Molkenthin, Sanjay Singh Bora
http://arxiv.org/abs/1906.04507v1
• [stat.ML]Asymptotic Guarantees for Learning Generative Models with the Sliced-Wasserstein Distance
Kimia Nadjahi, Alain Durmus, Umut Şimşekli, Roland Badeau
http://arxiv.org/abs/1906.04516v1
• [stat.ML]Efficient structure learning with automatic sparsity selection for causal graph processes
Théophile Griveau-Billion, Ben Calderhead
http://arxiv.org/abs/1906.04479v1
• [stat.ML]Maximum Mean Discrepancy Gradient Flow
Michael Arbel, Anna Korba, Adil Salim, Arthur Gretton
http://arxiv.org/abs/1906.04370v1
• [stat.ML]Principled Training of Neural Networks with Direct Feedback Alignment
Julien Launay, Iacopo Poli, Florent Krzakala
http://arxiv.org/abs/1906.04554v1
• [stat.ML]Probabilistic Forecasting with Temporal Convolutional Neural Network
Yitian Chen, Yanfei Kang, Yixiong Chen, Zizhuo Wang
http://arxiv.org/abs/1906.04397v1
• [stat.ML]SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation
Kowshik Thopalli, Jayaraman J. Thiagarajan, Rushil Anirudh, Pavan Turaga
http://arxiv.org/abs/1906.04338v1
• [stat.ML]Stable Rank Normalization for Improved Generalization in Neural Networks and GANs
Amartya Sanyal, Philip H. S. Torr, Puneet K. Dokania
http://arxiv.org/abs/1906.04659v1