astro-ph.IM - 仪器仪表和天体物理学方法
cond-mat.dis-nn - 无序系统与神经网络 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.ET - 新兴技术 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.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.ST - 统计理论 physics.comp-ph - 计算物理学 physics.med-ph - 医学物理学 physics.soc-ph - 物理学与社会 q-bio.GN - 基因组学 q-bio.QM - 定量方法 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [astro-ph.IM]Realizing the potential of astrostatistics and astroinformatics
• [cond-mat.dis-nn]Information Scrambling in Quantum Neural Networks
• [cs.AI]A generic framework for task selection driven by synthetic emotions
• [cs.AI]Action Selection for MDPs: Anytime AO* vs. UCT
• [cs.AI]Artificial Intelligence BlockCloud (AIBC) Technical Whitepaper
• [cs.AI]Generalized Planning: Non-Deterministic Abstractions and Trajectory Constraints
• [cs.AI]Higher-Dimensional Potential Heuristics for Optimal Classical Planning
• [cs.AI]Query Optimization Properties of Modified VBS
• [cs.AI]Spoken Conversational Search for General Knowledge
• [cs.AI]Superintelligence Safety: A Requirements Engineering Perspective
• [cs.AI]Synergistic Team Composition: A Computational Approach to Foster Diversity in Teams
• [cs.AI]Towards Explainable Artificial Intelligence
• [cs.AI]Towards a Metric for Automated Conversational Dialogue System Evaluation and Improvement
• [cs.AI]V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
• [cs.CL]ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
• [cs.CL]An Investigation into the Effectiveness of Enhancement in ASR Training and Test for CHiME-5 Dinner Party Transcription
• [cs.CL]Aspect and Opinion Term Extraction for Aspect Based Sentiment Analysis of Hotel Reviews Using Transfer Learning
• [cs.CL]DARTS: Dialectal Arabic Transcription System
• [cs.CL]DisSim: A Discourse-Aware Syntactic Text Simplification Frameworkfor English and German
• [cs.CL]Extreme Language Model Compression with Optimal Subwords and Shared Projections
• [cs.CL]Fine-tune Bert for DocRED with Two-step Process
• [cs.CL]FreeLB: Enhanced Adversarial Training for Language Understanding
• [cs.CL]GECOR: An End-to-End Generative Ellipsis and Co-reference Resolution Model for Task-Oriented Dialogue
• [cs.CL]Improving Fine-grained Entity Typing with Entity Linking
• [cs.CL]Keyphrase Generation for Scientific Articles using GANs
• [cs.CL]Large-scale Pretraining for Neural Machine Translation with Tens of Billions of Sentence Pairs
• [cs.CL]Low-Resource Response Generation with Template Prior
• [cs.CL]MinWikiSplit: A Sentence Splitting Corpus with Minimal Propositions
• [cs.CL]Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation
• [cs.CL]SIM: A Slot-Independent Neural Model for Dialogue State Tracking
• [cs.CL]Selecting Artificially-Generated Sentences for Fine-Tuning Neural Machine Translation
• [cs.CL]Semantic Change and Emerging Tropes In a Large Corpus of New High German Poetry
• [cs.CL]Speech Recognition with Augmented Synthesized Speech
• [cs.CL]The Power of Communities: A Text Classification Model with Automated Labeling Process Using Network Community Detection
• [cs.CR]Differential Privacy for Evolving Almost-Periodic Datasets with Continual Linear Queries: Application to Energy Data Privacy
• [cs.CV]A Closer Look at Domain Shift for Deep Learning in Histopathology
• [cs.CV]Adaptive Class Weight based Dual Focal Loss for Improved Semantic Segmentation
• [cs.CV]Balanced Binary Neural Networks with Gated Residual
• [cs.CV]COPHY: Counterfactual Learning of Physical Dynamics
• [cs.CV]Compact Trilinear Interaction for Visual Question Answering
• [cs.CV]Convex Relaxations for Consensus and Non-Minimal Problems in 3D Vision
• [cs.CV]Convolutional Neural Networks with Dynamic Regularization
• [cs.CV]DISCOMAN: Dataset of Indoor SCenes for Odometry, Mapping And Navigation
• [cs.CV]Deep Aggregation of Regional Convolutional Activations for Content Based Image Retrieval
• [cs.CV]Deep Model Transferability from Attribution Maps
• [cs.CV]Deep Video Deblurring: The Devil is in the Details
• [cs.CV]Dual-Stream Pyramid Registration Network
• [cs.CV]Explicitly disentangling image content from translation and rotation with spatial-VAE
• [cs.CV]Fast and Effective Adaptation of Facial Action Unit Detection Deep Model
• [cs.CV]FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging
• [cs.CV]Implicit Semantic Data Augmentation for Deep Networks
• [cs.CV]In-field grape berries counting for yield estimation using dilated CNNs
• [cs.CV]Joint-task Self-supervised Learning for Temporal Correspondence
• [cs.CV]Learned Point Cloud Geometry Compression
• [cs.CV]Learning Energy-based Spatial-Temporal Generative ConvNets for Dynamic Patterns
• [cs.CV]Learning Pixel Representations for Generic Segmentation
• [cs.CV]Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
• [cs.CV]Multi-scale Dynamic Feature Encoding Network for Image Demoireing
• [cs.CV]Multiple Object Forecasting: Predicting Future Object Locations in Diverse Environments
• [cs.CV]Optimal Transport, CycleGAN, and Penalized LS for Unsupervised Learning in Inverse Problems
• [cs.CV]Overcoming Data Limitation in Medical Visual Question Answering
• [cs.CV]Range Adaptation for 3D Object Detection in LiDAR
• [cs.CV]Resolving Marker Pose Ambiguity by Robust Rotation Averaging with Clique Constraints
• [cs.CV]Revisit Knowledge Distillation: a Teacher-free Framework
• [cs.CV]The Stroke Correspondence Problem, Revisited
• [cs.CV]Two-stage Image Classification Supervised by a Single Teacher Single Student Model
• [cs.CV]UNITER: Learning UNiversal Image-TExt Representations
• [cs.CV]Unsupervised Image Translation using Adversarial Networks for Improved Plant Disease Recognition
• [cs.CY]This Thing Called Fairness: Disciplinary Confusion Realizing a Value in Technology
• [cs.DC]Elastic deep learning in multi-tenant GPU cluster
• [cs.DC]Extending the Message Passing Interface (MPI) with User-Level Schedules
• [cs.DC]MPCDF HPC Performance Monitoring System: Enabling Insight via Job-Specific Analysis
• [cs.DC]Ramanujan Graphs and the Spectral Gap of Supercomputing Topologies
• [cs.ET]K-Means Clustering on Noisy Intermediate Scale Quantum Computers
• [cs.ET]Support Vector Machines on Noisy Intermediate Scale Quantum Computers
• [cs.IR]Complex Network based Supervised Keyword Extractor
• [cs.IR]Pre-train, Interact, Fine-tune: A Novel Interaction Representation for Text Classification
• [cs.IT]Autoencoder-Based Error Correction Coding for One-Bit Quantization
• [cs.IT]Deep Learning-based Polar Code Design
• [cs.IT]Entropic matroids and their representation
• [cs.IT]Generalised Measures of Multivariate Information Content
• [cs.IT]Improved Lower Bounds for Pliable Index Coding using Absent Receivers
• [cs.IT]On the Optimality of Treating Inter-Cell Interference as Noise: Downlink Cellular Networks and Uplink-Downlink Duality
• [cs.IT]One-shot achievability and converse bounds of Gaussian random coding in AWGN channels under covert constraints
• [cs.IT]Optimal-Rate Characterisation for Pliable Index Coding using Absent Receivers
• [cs.IT]Optimizing Polar Codes Compatible with Off-the-Shelf LDPC Decoders
• [cs.LG]A Decision-Based Dynamic Ensemble Selection Method for Concept Drift
• [cs.LG]A Heuristic for Efficient Reduction in Hidden Layer Combinations For Feedforward Neural Networks
• [cs.LG]A Mean-Field Theory for Kernel Alignment with Random Features in Generative Adversarial Networks
• [cs.LG]A Theoretical Analysis of the Number of Shots in Few-Shot Learning
• [cs.LG]ALCNN: Attention-based Model for Fine-grained Demand Inference of Dock-less Shared Bike in New Cities
• [cs.LG]Adversarial Deep Embedded Clustering: on a better trade-off between Feature Randomness and Feature Drift
• [cs.LG]Adversarial Variational Domain Adaptation
• [cs.LG]Attention Forcing for Sequence-to-sequence Model Training
• [cs.LG]Attributed Graph Learning with 2-D Graph Convolution
• [cs.LG]B-Spline CNNs on Lie Groups
• [cs.LG]CLN2INV: Learning Loop Invariants with Continuous Logic Networks
• [cs.LG]Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network
• [cs.LG]DCTD: Deep Conditional Target Densities for Accurate Regression
• [cs.LG]Data Valuation using Reinforcement Learning
• [cs.LG]Deep Metric Learning using Similarities from Nonlinear Rank Approximations
• [cs.LG]Drawing early-bird tickets: Towards more efficient training of deep networks
• [cs.LG]Exascale Deep Learning to Accelerate Cancer Research
• [cs.LG]ExpertoCoder: Capturing Divergent Brain Regions Using Mixture of Regression Experts
• [cs.LG]Explainable Deep Learning for Augmentation of sRNA Expression Profiles
• [cs.LG]Explaining and Interpreting LSTMs
• [cs.LG]Function Preserving Projection for Scalable Exploration of High-Dimensional Data
• [cs.LG]GAMIN: An Adversarial Approach to Black-Box Model Inversion
• [cs.LG]Galaxy Image Simulation Using Progressive GANs
• [cs.LG]GradVis: Visualization and Second Order Analysis of Optimization Surfaces during the Training of Deep Neural Networks
• [cs.LG]GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning
• [cs.LG]Harnessing Structures for Value-Based Planning and Reinforcement Learning
• [cs.LG]High-Dimensional Control Using Generalized Auxiliary Tasks
• [cs.LG]Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network
• [cs.LG]Improving SAT Solver Heuristics with Graph Networks and Reinforcement Learning
• [cs.LG]Intensity-Free Learning of Temporal Point Processes
• [cs.LG]LAVAE: Disentangling Location and Appearance
• [cs.LG]Learning with Long-term Remembering: Following the Lead of Mixed Stochastic Gradient
• [cs.LG]Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks
• [cs.LG]Lower Bounds on Adversarial Robustness from Optimal Transport
• [cs.LG]MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit
• [cs.LG]Manifold Forests: Closing the Gap on Neural Networks
• [cs.LG]Mathematical Reasoning in Latent Space
• [cs.LG]Mildly Overparametrized Neural Nets can Memorize Training Data Efficiently
• [cs.LG]Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems
• [cs.LG]Model Imitation for Model-Based Reinforcement Learning
• [cs.LG]Overlapping Community Detection with Graph Neural Networks
• [cs.LG]PairNorm: Tackling Oversmoothing in GNNs
• [cs.LG]Polylogarithmic width suffices for gradient descent to achieve arbitrarily small test error with shallow ReLU networks
• [cs.LG]Probabilistic Forecasting using Deep Generative Models
• [cs.LG]RADE: Resource-Efficient Supervised Anomaly Detection Using Decision Tree-Based Ensemble Methods
• [cs.LG]Representation Learning with Ordered Relation Paths for Knowledge Graph Completion
• [cs.LG]Sequential Training of Neural Networks with Gradient Boosting
• [cs.LG]Set Functions for Time Series
• [cs.LG]Smart Ternary Quantization
• [cs.LG]StacNAS: Towards stable and consistent optimization for differentiable Neural Architecture Search
• [cs.LG]Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks
• [cs.LG]Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control
• [cs.LG]The Implicit Bias of Depth: How Incremental Learning Drives Generalization
• [cs.LG]Towards Understanding the Transferability of Deep Representations
• [cs.LG]Towards neural networks that provably know when they don’t know
• [cs.LG]Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples
• [cs.LG]Unsupervised Domain Adaptation through Self-Supervision
• [cs.LG]Unsupervised Universal Self-Attention Network for Graph Classification
• [cs.LG]dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance
• [cs.MA]$α^α$-Rank: Scalable Multi-agent Evaluation through Evolution
• [cs.NE]Military Dog Based Optimizer and its Application to Fake Review
• [cs.NE]The Ant Swarm Neuro-Evolution Procedure for Optimizing Recurrent Networks
• [cs.NI]Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments
• [cs.RO]”Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks via Reward Shaping
• [cs.RO]A Framework for Data-Driven Robotics
• [cs.RO]A fast, complete, point cloud based loop closure for LiDAR odometry and mapping
• [cs.RO]Balancing Domain Gap for Object Instance Detection
• [cs.RO]C-3PO: Cyclic-Three-Phase Optimization for Human-Robot Motion Retargeting based on Reinforcement Learning
• [cs.RO]Controlling an Autonomous Vehicle with Deep Reinforcement Learning
• [cs.RO]DOOR-SLAM: Distributed, Online, and Outlier Resilient SLAM for Robotic Teams
• [cs.RO]Efficient Large-Scale Multi-Drone Delivery Using Transit Networks
• [cs.RO]Exercising with an “Iron Man”: Design for a Robot Exercise Coach for Persons with Dementia
• [cs.RO]Fuzzy Gesture Expression Model for an Interactive and Safe Robot Partner
• [cs.RO]Information-Guided Robotic Maximum Seek-and-Sample in Partially Observable Continuous Environments
• [cs.RO]RLBench: The Robot Learning Benchmark & Learning Environment
• [cs.RO]Stabilization of Exoskeletons through Active Ankle Compensation
• [cs.SD]Improving the Intelligibility of Electric and Acoustic Stimulation Speech Using Fully Convolutional Networks Based Speech Enhancement
• [cs.SD]Multichannel Speech Enhancement by Raw Waveform-mapping using Fully Convolutional Networks
• [cs.SD]Seeing Voices in Noise: A Study of Audiovisual-Enhanced Vocoded Speech Intelligibility in Cochlear Implant Simulation
• [cs.SI]Social Network Analysis for Social Neuroscientists
• [eess.AS]Disentangling Speech and Non-Speech Components for Building Robust Acoustic Models from Found Data
• [eess.AS]Self-Adaptive Soft Voice Activity Detection using Deep Neural Networks for Robust Speaker Verification
• [eess.IV]A Hybrid Deep Learning Architecture for Leukemic B-lymphoblast Classification
• [eess.IV]A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
• [eess.IV]A Symmetric Equilibrium Generative Adversarial Network with Attention Refine Block for Retinal Vessel Segmentation
• [eess.IV]Breast Cancer Diagnosis with Transfer Learning and Global Pooling
• [eess.IV]Classification of Histopathological Biopsy Images Using Ensemble of Deep Learning Networks
• [eess.IV]Data consistency networks for (calibration-less) accelerated parallel MR image reconstruction
• [eess.IV]Follows Form: Regression from Complete Thoracic Computed Tomography Scans
• [eess.IV]Lightweight Image Super-Resolution with Information Multi-distillation Network
• [eess.IV]Multi-grained Attention Networks for Single Image Super-Resolution
• [eess.IV]Rank Constrained Diffeomorphic Density Motion Estimation for Respiratory Correlated Computed Tomography
• [eess.IV]Segmentation of points of interest during fetal cardiac assesment in the first trimester from color Doppler ultrasound
• [eess.IV]Subjective and Objective De-raining Quality Assessment Towards Authentic Rain Image
• [eess.SP]A Simulation of UAV Power Optimization via Reinforcement Learning
• [eess.SY]Modeling Electromagnetic Navigation Systems for Medical Applications using Random Forests and Artificial Neural Networks
• [eess.SY]Probabilistic duck curve in high PV penetration power system: Concept, modeling, and empirical analysis in China
• [eess.SY]Relationship Explainable Multi-objective Reinforcement Learning with Semantic Explainability Generation
• [math.CO]A moment ratio bound for polynomials and some extremal properties of Krawchouk polynomials and Hamming spheres
• [math.NA]Shifted and extrapolated power methods for tensor $\ell^p$-eigenpairs
• [math.OC]Optimal Transport to a Variety
• [math.OC]Path Planning in Unknown Environments Using Optimal Transport Theory
• [math.OC]Randomized Iterative Methods for Linear Systems: Momentum, Inexactness and Gossip
• [math.ST]A new coefficient of correlation
• [math.ST]Estimating covariance and precision matrices along subspaces
• [math.ST]On the spectral property of kernel-based sensor fusion algorithms of high dimensional data
• [math.ST]Rapid mixing of a Markov chain for an exponentially weighted aggregation estimator
• [math.ST]The $f$-Divergence Expectation Iteration Scheme
• [math.ST]The Trimmed Mean in Non-parametric Regression Function Estimation
• [physics.comp-ph]DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems
• [physics.med-ph]Deep-learning-based Breast CT for Radiation Dose Reduction
• [physics.med-ph]Non-Invasive Fuhrman Grading of Clear Cell Renal Cell Carcinoma Using Computed Tomography Radiomics Features and Machine Learning
• [physics.soc-ph]Strategic reciprocity improves academic performance in public elementary school children
• [q-bio.GN]Deep Learning and Random Forest-Based Augmentation of sRNA Expression Profiles
• [q-bio.QM]Single-modal and Multi-modal False Arrhythmia Alarm Reduction using Attention-based Convolutional and Recurrent Neural Networks
• [quant-ph]Quantum Bicyclic Hyperbolic Codes
• [quant-ph]Quantum Graph Neural Networks
• [stat.AP]Enhancing Model Interpretability and Accuracy for Disease Progression Prediction via Phenotype-Based Patient Similarity Learning
• [stat.AP]Identify More, Observe Less: Mediation Analysis Synthetic Control
• [stat.CO]Exact Inference with Approximate Computation for Differentially Private Data via Perturbations
• [stat.CO]bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond)
• [stat.ME]A bivariate logistic regression model based on latent variables
• [stat.ME]Bayesian Pseudo Posterior Mechanism under Differential Privacy
• [stat.ME]Compound vectors of subordinators and their associated positive Lévy copulas
• [stat.ME]Cross-Validation, Risk Estimation, and Model Selection
• [stat.ME]Dynamic Partial Sufficient Dimension Reduction
• [stat.ME]Survival analysis as a classification problem
• [stat.ML]Benefit of Interpolation in Nearest Neighbor Algorithms
• [stat.ML]Data Smashing 2.0: Sequence Likelihood (SL) Divergence For Fast Time Series Comparison
• [stat.ML]Debiased Bayesian inference for average treatment effects
• [stat.ML]Probabilistic Modeling of Deep Features for Out-of-Distribution and Adversarial Detection
• [stat.ML]Residual Networks Behave Like Boosting Algorithms
• [stat.ML]Stochastic Prototype Embeddings
·····································
• [astro-ph.IM]Realizing the potential of astrostatistics and astroinformatics
Gwendolyn Eadie, Thomas J. Loredo, Ashish A. Mahabal, Aneta Siemiginowska, Eric Feigelson, Eric B. Ford, S. G. Djorgovski, Matthew Graham, Zeljko Ivezic, Kirk Borne, Jessi Cisewski-Kehe, J. E. G. Peek, Chad Schafer, Padma A. Yanamandra-Fisher, C. Alex Young
http://arxiv.org/abs/1909.11714v1
• [cond-mat.dis-nn]Information Scrambling in Quantum Neural Networks
Huitao Shen, Pengfei Zhang, Yi-Zhuang You, Hui Zhai
http://arxiv.org/abs/1909.11887v1
• [cs.AI]A generic framework for task selection driven by synthetic emotions
Claudius Gros
http://arxiv.org/abs/1909.11700v1
• [cs.AI]**Action Selection for MDPs: Anytime AO vs. UCT
Blai Bonet, Hector Geffner
http://arxiv.org/abs/1909.12104v1
• [cs.AI]Artificial Intelligence BlockCloud (AIBC) Technical Whitepaper
Qi Deng
http://arxiv.org/abs/1909.12063v1
• [cs.AI]Generalized Planning: Non-Deterministic Abstractions and Trajectory Constraints
Blai Bonet, Giuseppe De Giacomo, Hector Geffner, Sasha Rubin
http://arxiv.org/abs/1909.12135v1
• [cs.AI]Higher-Dimensional Potential Heuristics for Optimal Classical Planning
Florian Pommerening, Malte Helmert, Blai Bonet
http://arxiv.org/abs/1909.12142v1
• [cs.AI]Query Optimization Properties of Modified VBS
Mieczysław A. Kłopotek, Sławomir T. Wierzchoń
http://arxiv.org/abs/1909.12032v1
• [cs.AI]Spoken Conversational Search for General Knowledge
Lina M. Rojas-Barahona, Pascal Bellec, Benoit Besset, Martinho Dos-Santos, Johannes Heinecke, Munshi Asadullah, Olivier Le-Blouch, Jean Y. Lancien, Géraldine Damnati, Emmanuel Mory, Frédéric Herledan
http://arxiv.org/abs/1909.11980v1
• [cs.AI]Superintelligence Safety: A Requirements Engineering Perspective
Hermann Kaindl, Jonas Ferdigg
http://arxiv.org/abs/1909.12152v1
• [cs.AI]Synergistic Team Composition: A Computational Approach to Foster Diversity in Teams
Ewa Andrejczuk, Filippo Bistaffa, Christian Blum, Juan A. Rodríguez-Aguilar, Carles Sierra
http://arxiv.org/abs/1909.11994v1
• [cs.AI]Towards Explainable Artificial Intelligence
Wojciech Samek, Klaus-Robert Müller
http://arxiv.org/abs/1909.12072v1
• [cs.AI]Towards a Metric for Automated Conversational Dialogue System Evaluation and Improvement
Jan Deriu, Mark Cieliebak
http://arxiv.org/abs/1909.12066v1
• [cs.AI]V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
H. Francis Song, Abbas Abdolmaleki, Jost Tobias Springenberg, Aidan Clark, Hubert Soyer, Jack W. Rae, Seb Noury, Arun Ahuja, Siqi Liu, Dhruva Tirumala, Nicolas Heess, Dan Belov, Martin Riedmiller, Matthew M. Botvinick
http://arxiv.org/abs/1909.12238v1
• [cs.CL]ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, Radu Soricut
http://arxiv.org/abs/1909.11942v1
• [cs.CL]An Investigation into the Effectiveness of Enhancement in ASR Training and Test for CHiME-5 Dinner Party Transcription
Catalin Zorila, Christoph Boeddeker, Rama Doddipatla, Reinhold Haeb-Umbach
http://arxiv.org/abs/1909.12208v1
• [cs.CL]Aspect and Opinion Term Extraction for Aspect Based Sentiment Analysis of Hotel Reviews Using Transfer Learning
Ali Akbar Septiandri, Arie Pratama Sutiono
http://arxiv.org/abs/1909.11879v1
• [cs.CL]DARTS: Dialectal Arabic Transcription System
Sameer Khurana, Ahmed Ali, James Glass
http://arxiv.org/abs/1909.12163v1
• [cs.CL]DisSim: A Discourse-Aware Syntactic Text Simplification Frameworkfor English and German
Christina Niklaus, Matthias Cetto, Andre Freitas, Siegfried Handschuh
http://arxiv.org/abs/1909.12140v1
• [cs.CL]Extreme Language Model Compression with Optimal Subwords and Shared Projections
Sanqiang Zhao, Raghav Gupta, Yang Song, Denny Zhou
http://arxiv.org/abs/1909.11687v1
• [cs.CL]Fine-tune Bert for DocRED with Two-step Process
Hong Wang, Christfried Focke, Rob Sylvester, Nilesh Mishra, William Wang
http://arxiv.org/abs/1909.11898v1
• [cs.CL]FreeLB: Enhanced Adversarial Training for Language Understanding
Chen Zhu, Yu Cheng, Zhe Gan, Siqi Sun, Thomas Goldstein, Jingjing Liu
http://arxiv.org/abs/1909.11764v1
• [cs.CL]GECOR: An End-to-End Generative Ellipsis and Co-reference Resolution Model for Task-Oriented Dialogue
Jun Quan, Deyi Xiong, Bonnie Webber, Changjian Hu
http://arxiv.org/abs/1909.12086v1
• [cs.CL]Improving Fine-grained Entity Typing with Entity Linking
Hongliang Dai, Donghong Du, Xin Li, Yangqiu Song
http://arxiv.org/abs/1909.12079v1
• [cs.CL]Keyphrase Generation for Scientific Articles using GANs
Avinash Swaminathan, Raj Kuwar Gupta, Haimin Zhang, Debanjan Mahata, Rakesh Gosangi, Rajiv Ratn Shah
http://arxiv.org/abs/1909.12229v1
• [cs.CL]Large-scale Pretraining for Neural Machine Translation with Tens of Billions of Sentence Pairs
Yuxian Meng, Xiangyuan Ren, Zijun Sun, Xiaoya Li, Arianna Yuan, Fei Wu, Jiwei Li
http://arxiv.org/abs/1909.11861v1
• [cs.CL]Low-Resource Response Generation with Template Prior
Ze Yang, Wei Wu, Jian Yang, Can Xu, Zhoujun Li
http://arxiv.org/abs/1909.11968v1
• [cs.CL]MinWikiSplit: A Sentence Splitting Corpus with Minimal Propositions
Christina Niklaus, Andre Freitas, Siegfried Handschuh
http://arxiv.org/abs/1909.12131v1
• [cs.CL]Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation
Ze Yang, Can Xu, Wei Wu, Zhoujun Li
http://arxiv.org/abs/1909.11974v1
• [cs.CL]SIM: A Slot-Independent Neural Model for Dialogue State Tracking
Chenguang Zhu, Michael Zeng, Xuedong Huang
http://arxiv.org/abs/1909.11833v1
• [cs.CL]Selecting Artificially-Generated Sentences for Fine-Tuning Neural Machine Translation
Alberto Poncelas, Andy Way
http://arxiv.org/abs/1909.12016v1
• [cs.CL]Semantic Change and Emerging Tropes In a Large Corpus of New High German Poetry
Thomas Haider, Steffen Eger
http://arxiv.org/abs/1909.12136v1
• [cs.CL]Speech Recognition with Augmented Synthesized Speech
Andrew Rosenberg, Yu Zhang, Bhuvana Ramabhadran, Ye Jia, Pedro Moreno, Yonghui Wu, Zelin Wu
http://arxiv.org/abs/1909.11699v1
• [cs.CL]The Power of Communities: A Text Classification Model with Automated Labeling Process Using Network Community Detection
Minjun Kim, Hiroki Sayama
http://arxiv.org/abs/1909.11706v1
• [cs.CR]Differential Privacy for Evolving Almost-Periodic Datasets with Continual Linear Queries: Application to Energy Data Privacy
Farhad Farokhi
http://arxiv.org/abs/1909.11812v1
• [cs.CV]A Closer Look at Domain Shift for Deep Learning in Histopathology
Karin Stacke, Gabriel Eilertsen, Jonas Unger, Claes Lundström
http://arxiv.org/abs/1909.11575v2
• [cs.CV]Adaptive Class Weight based Dual Focal Loss for Improved Semantic Segmentation
Md Sazzad Hossain, Andrew P Paplinski, John M Betts
http://arxiv.org/abs/1909.11932v1
• [cs.CV]Balanced Binary Neural Networks with Gated Residual
Mingzhu Shen, Xianglong Liu, Kai Han, Ruihao Gong, Yunhe Wang, Chang Xu
http://arxiv.org/abs/1909.12117v1
• [cs.CV]COPHY: Counterfactual Learning of Physical Dynamics
Fabien Baradel, Natalia Neverova, Julien Mille, Greg Mori, Christian Wolf
http://arxiv.org/abs/1909.12000v1
• [cs.CV]Compact Trilinear Interaction for Visual Question Answering
Tuong Do, Thanh-Toan Do, Huy Tran, Erman Tjiputra, Quang D. Tran
http://arxiv.org/abs/1909.11874v1
• [cs.CV]Convex Relaxations for Consensus and Non-Minimal Problems in 3D Vision
Thomas Probst, Danda Pani Paudel, Ajad Chhatkuli, Luc Van Gool
http://arxiv.org/abs/1909.12034v1
• [cs.CV]Convolutional Neural Networks with Dynamic Regularization
Yi Wang, Zhen-Peng Bian, Junhui Hou, Lap-Pui Chau
http://arxiv.org/abs/1909.11862v1
• [cs.CV]DISCOMAN: Dataset of Indoor SCenes for Odometry, Mapping And Navigation
Pavel Kirsanov, Airat Gaskarov, Filipp Konokhov, Konstantin Sofiiuk, Anna Vorontsova, Igor Slinko, Dmitry Zhukov, Sergey Bykov, Olga Barinova, Anton Konushin
http://arxiv.org/abs/1909.12146v1
• [cs.CV]Deep Aggregation of Regional Convolutional Activations for Content Based Image Retrieval
Konstantin Schall, Kai Uwe Barthel, Nico Hezel, Klaus Jung
http://arxiv.org/abs/1909.09420v2
• [cs.CV]Deep Model Transferability from Attribution Maps
Jie Song, Yixin Chen, Xinchao Wang, Chengchao Shen, Mingli Song
http://arxiv.org/abs/1909.11902v1
• [cs.CV]Deep Video Deblurring: The Devil is in the Details
Jochen Gast, Stefan Roth
http://arxiv.org/abs/1909.12196v1
• [cs.CV]Dual-Stream Pyramid Registration Network
Xiaojun Hu, Miao Kang, Weilin Huang, Matthew R. Scott, Roland Wiest, Mauricio Reyes
http://arxiv.org/abs/1909.11966v1
• [cs.CV]Explicitly disentangling image content from translation and rotation with spatial-VAE
Tristan Bepler, Ellen D. Zhong, Kotaro Kelley, Edward Brignole, Bonnie Berger
http://arxiv.org/abs/1909.11663v1
• [cs.CV]Fast and Effective Adaptation of Facial Action Unit Detection Deep Model
Mihee Lee, Ognjen, Rudovic, Vladimir Pavlovic, Maja Pantic
http://arxiv.org/abs/1909.12158v1
• [cs.CV]FoodAI: Food Image Recognition via Deep Learning for Smart Food Logging
Doyen Sahoo, Wang Hao, Shu Ke, Wu Xiongwei, Hung Le, Palakorn Achananuparp, Ee-Peng Lim, Steven C. H. Hoi
http://arxiv.org/abs/1909.11946v1
• [cs.CV]Implicit Semantic Data Augmentation for Deep Networks
Yulin Wang, Xuran Pan, Shiji Song, Hong Zhang, Cheng Wu, Gao Huang
http://arxiv.org/abs/1909.12220v1
• [cs.CV]In-field grape berries counting for yield estimation using dilated CNNs
L. Coviello, M. Cristoforetti, G. Jurman, C. Furlanello
http://arxiv.org/abs/1909.12083v1
• [cs.CV]Joint-task Self-supervised Learning for Temporal Correspondence
Xueting Li, Sifei Liu, Shalini De Mello, Xiaolong Wang, Jan Kautz, Ming-Hsuan Yang
http://arxiv.org/abs/1909.11895v1
• [cs.CV]Learned Point Cloud Geometry Compression
Jianqiang Wang, Hao Zhu, Zhan Ma, Tong Chen, Haojie Liu, Qiu Shen
http://arxiv.org/abs/1909.12037v1
• [cs.CV]Learning Energy-based Spatial-Temporal Generative ConvNets for Dynamic Patterns
Jianwen Xie, Song-Chun Zhu, Ying Nian Wu
http://arxiv.org/abs/1909.11975v1
• [cs.CV]Learning Pixel Representations for Generic Segmentation
Oran Shayer, Michael Lindenbaum
http://arxiv.org/abs/1909.11735v1
• [cs.CV]Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
Wen Liu, Zhixin Piao, Jie Min, Wenhan Luo, Lin Ma, Shenghua Gao
http://arxiv.org/abs/1909.12224v1
• [cs.CV]Multi-scale Dynamic Feature Encoding Network for Image Demoireing
Xi Cheng, Zhenyong Fu, Jian Yang
http://arxiv.org/abs/1909.11947v1
• [cs.CV]Multiple Object Forecasting: Predicting Future Object Locations in Diverse Environments
Olly Styles, Tanaya Guha, Victor Sanchez
http://arxiv.org/abs/1909.11944v1
• [cs.CV]Optimal Transport, CycleGAN, and Penalized LS for Unsupervised Learning in Inverse Problems
Byeongsu Sim, Gyutaek Oh, Sungjun Lim, Jong Chul Ye
http://arxiv.org/abs/1909.12116v1
• [cs.CV]Overcoming Data Limitation in Medical Visual Question Answering
Binh D. Nguyen, Thanh-Toan Do, Binh X. Nguyen, Tuong Do, Erman Tjiputra, Quang D. Tran
http://arxiv.org/abs/1909.11867v1
• [cs.CV]Range Adaptation for 3D Object Detection in LiDAR
Ze Wang, Sihao Ding, Ying Li, Minming Zhao, Sohini Roychowdhury, Andreas Wallin, Guillermo Sapiro, Qiang Qiu
http://arxiv.org/abs/1909.12249v1
• [cs.CV]Resolving Marker Pose Ambiguity by Robust Rotation Averaging with Clique Constraints
Shin-Fang Ch’ng, Naoya Sogi, Pulak Purkait, Tat-Jun Chin, Kazuhiro Fukui
http://arxiv.org/abs/1909.11888v1
• [cs.CV]Revisit Knowledge Distillation: a Teacher-free Framework
Li Yuan, Francis E. H. Tay, Guilin Li, Tao Wang, Jiashi Feng
http://arxiv.org/abs/1909.11723v1
• [cs.CV]The Stroke Correspondence Problem, Revisited
Dominik Klein
http://arxiv.org/abs/1909.11995v1
• [cs.CV]Two-stage Image Classification Supervised by a Single Teacher Single Student Model
Jianhang Zhou, Shaoning Zeng, Bob Zhang
http://arxiv.org/abs/1909.12111v1
• [cs.CV]UNITER: Learning UNiversal Image-TExt Representations
Yen-Chun Chen, Linjie Li, Licheng Yu, Ahmed El Kholy, Faisal Ahmed, Zhe Gan, Yu Cheng, Jingjing Liu
http://arxiv.org/abs/1909.11740v1
• [cs.CV]Unsupervised Image Translation using Adversarial Networks for Improved Plant Disease Recognition
Haseeb Nazki, Sook Yoon, Alvaro Fuentes, Dong Sun Park
http://arxiv.org/abs/1909.11915v1
• [cs.CY]This Thing Called Fairness: Disciplinary Confusion Realizing a Value in Technology
Deirdre K. Mulligan, Joshua A. Kroll, Nitin Kohli, Richmond Y. Wong
http://arxiv.org/abs/1909.11869v1
• [cs.DC]Elastic deep learning in multi-tenant GPU cluster
Yidi Wu, Kaihao Ma, Xiao Yan, Zhi Liu, James Cheng
http://arxiv.org/abs/1909.11985v1
• [cs.DC]Extending the Message Passing Interface (MPI) with User-Level Schedules
Derek Schafer, Sheikh Ghafoor, Daniel Holmes, Martin Ruefenacht, Anthony Skjellum
http://arxiv.org/abs/1909.11762v1
• [cs.DC]MPCDF HPC Performance Monitoring System: Enabling Insight via Job-Specific Analysis
Luka Stanisic, Klaus Reuter
http://arxiv.org/abs/1909.11704v1
• [cs.DC]Ramanujan Graphs and the Spectral Gap of Supercomputing Topologies
Sinan G. Aksoy, Paul Bruillard, Stephen J. Young, Mark Raugas
http://arxiv.org/abs/1909.11694v1
• [cs.ET]K-Means Clustering on Noisy Intermediate Scale Quantum Computers
Sumsam Ullah Khan, Ahsan Javed Awan, Gemma Vall-Llosera
http://arxiv.org/abs/1909.12183v1
• [cs.ET]Support Vector Machines on Noisy Intermediate Scale Quantum Computers
Jiaying Yang, Ahsan Javed Awan, Gemma Vall-Llosera
http://arxiv.org/abs/1909.11988v1
• [cs.IR]Complex Network based Supervised Keyword Extractor
Swagata Duari, Vasudha Bhatnagar
http://arxiv.org/abs/1909.12009v1
• [cs.IR]Pre-train, Interact, Fine-tune: A Novel Interaction Representation for Text Classification
Jianming Zheng, Fei Cai, Honghui Chen, Maarten de Rijke
http://arxiv.org/abs/1909.11824v1
• [cs.IT]Autoencoder-Based Error Correction Coding for One-Bit Quantization
Eren Balevi, Jeffrey G. Andrews
http://arxiv.org/abs/1909.12120v1
• [cs.IT]Deep Learning-based Polar Code Design
Moustafa Ebada, Sebastian Cammerer, Ahmed Elkelesh, Stephan ten Brink
http://arxiv.org/abs/1909.12035v1
• [cs.IT]Entropic matroids and their representation
Emmanuel Abbe, Sophie Spirkl
http://arxiv.org/abs/1909.12175v1
• [cs.IT]Generalised Measures of Multivariate Information Content
Conor Finn, Joseph T. Lizier
http://arxiv.org/abs/1909.12166v1
• [cs.IT]Improved Lower Bounds for Pliable Index Coding using Absent Receivers
Lawrence Ong, Badri N. Vellambi, Jörg Kliewer, Parastoo Sadeghi
http://arxiv.org/abs/1909.11850v1
• [cs.IT]On the Optimality of Treating Inter-Cell Interference as Noise: Downlink Cellular Networks and Uplink-Downlink Duality
Hamdi Joudeh, Xinping Yi, Bruno Clerckx, Giuseppe Caire
http://arxiv.org/abs/1909.12275v1
• [cs.IT]One-shot achievability and converse bounds of Gaussian random coding in AWGN channels under covert constraints
Xinchun Yu, Shuangqin Wei, Yuan Luo
http://arxiv.org/abs/1909.11324v2
• [cs.IT]Optimal-Rate Characterisation for Pliable Index Coding using Absent Receivers
Lawrence Ong, Badri N. Vellambi, Jörg Kliewer
http://arxiv.org/abs/1909.11847v1
• [cs.IT]Optimizing Polar Codes Compatible with Off-the-Shelf LDPC Decoders
Moustafa Ebada, Ahmed Elkelesh, Stephan ten Brink
http://arxiv.org/abs/1909.12030v1
• [cs.LG]A Decision-Based Dynamic Ensemble Selection Method for Concept Drift
Regis Antonio Saraiva Albuquerque, Albert Franca Josua Costa, Eulanda Miranda dos Santos, Robert Sabourin, Rafael Giusti
http://arxiv.org/abs/1909.12185v1
• [cs.LG]A Heuristic for Efficient Reduction in Hidden Layer Combinations For Feedforward Neural Networks
Wei Hao Khoong
http://arxiv.org/abs/1909.12226v1
• [cs.LG]A Mean-Field Theory for Kernel Alignment with Random Features in Generative Adversarial Networks
Masoud Badiei Khuzani, Liyue Shen, Shahin Shahrampour, Lei Xing
http://arxiv.org/abs/1909.11820v1
• [cs.LG]A Theoretical Analysis of the Number of Shots in Few-Shot Learning
Tianshi Cao, Marc Law, Sanja Fidler
http://arxiv.org/abs/1909.11722v1
• [cs.LG]ALCNN: Attention-based Model for Fine-grained Demand Inference of Dock-less Shared Bike in New Cities
Chang Liu, Yanan Xu, Yanmin Zhu
http://arxiv.org/abs/1909.11760v1
• [cs.LG]Adversarial Deep Embedded Clustering: on a better trade-off between Feature Randomness and Feature Drift
Nairouz Mrabah, Mohamed Bouguessa, Riadh Ksantini
http://arxiv.org/abs/1909.11832v1
• [cs.LG]Adversarial Variational Domain Adaptation
Manuel Pérez-Carrasco, Guillermo Cabrera-Vives, Pavlos Protopapas, Nicolás Astorga, Marouan Belhaj
http://arxiv.org/abs/1909.11651v2
• [cs.LG]Attention Forcing for Sequence-to-sequence Model Training
Qingyun Dou, Yiting Lu, Joshua Efiong, Mark J. F. Gales
http://arxiv.org/abs/1909.12289v1
• [cs.LG]Attributed Graph Learning with 2-D Graph Convolution
Qimai Li, Xiaotong Zhang, Han Liu, Xiao-Ming Wu
http://arxiv.org/abs/1909.12038v1
• [cs.LG]B-Spline CNNs on Lie Groups
Erik J Bekkers
http://arxiv.org/abs/1909.12057v1
• [cs.LG]CLN2INV: Learning Loop Invariants with Continuous Logic Networks
Gabriel Ryan, Justin Wong, Jianan Yao, Ronghui Gu, Suman Jana
http://arxiv.org/abs/1909.11542v2
• [cs.LG]Compression based bound for non-compressed network: unified generalization error analysis of large compressible deep neural network
Taiji Suzuki
http://arxiv.org/abs/1909.11274v2
• [cs.LG]DCTD: Deep Conditional Target Densities for Accurate Regression
Fredrik K. Gustafsson, Martin Danelljan, Goutam Bhat, Thomas B. Schön
http://arxiv.org/abs/1909.12297v1
• [cs.LG]Data Valuation using Reinforcement Learning
Jinsung Yoon, Sercan O. Arik, Tomas Pfister
http://arxiv.org/abs/1909.11671v1
• [cs.LG]Deep Metric Learning using Similarities from Nonlinear Rank Approximations
Konstantin Schall, Kai Uwe Barthel, Nico Hezel, Klaus Jung
http://arxiv.org/abs/1909.09427v2
• [cs.LG]Drawing early-bird tickets: Towards more efficient training of deep networks
Haoran You, Chaojian Li, Pengfei Xu, Yonggan Fu, Yue Wang, Xiaohan Chen, Yingyan Lin, Zhangyang Wang, Richard G. Baraniuk
http://arxiv.org/abs/1909.11957v1
• [cs.LG]Exascale Deep Learning to Accelerate Cancer Research
Robert M. Patton, J. Travis Johnston, Steven R. Young, Catherine D. Schuman, Thomas E. Potok, Derek C. Rose, Seung-Hwan Lim, Junghoon Chae, Le Hou, Shahira Abousamra, Dimitris Samaras, Joel Saltz
http://arxiv.org/abs/1909.12291v1
• [cs.LG]ExpertoCoder: Capturing Divergent Brain Regions Using Mixture of Regression Experts
Subba Reddy Oota, Naresh Manwani, Raju S. Bapi
http://arxiv.org/abs/1909.12299v1
• [cs.LG]Explainable Deep Learning for Augmentation of sRNA Expression Profiles
Jelena Fiosina, Maksims Fiosins, Stefan Bonn
http://arxiv.org/abs/1909.11956v1
• [cs.LG]Explaining and Interpreting LSTMs
Leila Arras, Jose A. Arjona-Medina, Michael Widrich, Grégoire Montavon, Michael Gillhofer, Klaus-Robert Müller, Sepp Hochreiter, Wojciech Samek
http://arxiv.org/abs/1909.12114v1
• [cs.LG]Function Preserving Projection for Scalable Exploration of High-Dimensional Data
Shusen Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Peer-Timo Bremer
http://arxiv.org/abs/1909.11804v1
• [cs.LG]GAMIN: An Adversarial Approach to Black-Box Model Inversion
Ulrich Aïvodji, Sébastien Gambs, Timon Ther
http://arxiv.org/abs/1909.11835v1
• [cs.LG]Galaxy Image Simulation Using Progressive GANs
Mohamad Dia, Elodie Savary, Martin Melchior, Frederic Courbin
http://arxiv.org/abs/1909.12160v1
• [cs.LG]GradVis: Visualization and Second Order Analysis of Optimization Surfaces during the Training of Deep Neural Networks
Avraam Chatzimichailidis, Franz-Josef Pfreundt, Nicolas R. Gauger, Janis Keuper
http://arxiv.org/abs/1909.12108v1
• [cs.LG]GraphMix: Regularized Training of Graph Neural Networks for Semi-Supervised Learning
Vikas Verma, Meng Qu, Alex Lamb, Yoshua Bengio, Juho Kannala, Jian Tang
http://arxiv.org/abs/1909.11715v1
• [cs.LG]Harnessing Structures for Value-Based Planning and Reinforcement Learning
Yuzhe Yang, Guo Zhang, Zhi Xu, Dina Katabi
http://arxiv.org/abs/1909.12255v1
• [cs.LG]High-Dimensional Control Using Generalized Auxiliary Tasks
Yannis Flet-Berliac, Philippe Preux
http://arxiv.org/abs/1909.11939v1
• [cs.LG]Hyperspectral Image Classification With Context-Aware Dynamic Graph Convolutional Network
Sheng Wan, Chen Gong, Ping Zhong, Shirui Pan, Guangyu Li, Jian Yang
http://arxiv.org/abs/1909.11953v1
• [cs.LG]Improving SAT Solver Heuristics with Graph Networks and Reinforcement Learning
Vitaly Kurin, Saad Godil, Shimon Whiteson, Bryan Catanzaro
http://arxiv.org/abs/1909.11830v1
• [cs.LG]Intensity-Free Learning of Temporal Point Processes
Oleksandr Shchur, Marin Biloš, Stephan Günnemann
http://arxiv.org/abs/1909.12127v1
• [cs.LG]LAVAE: Disentangling Location and Appearance
Andrea Dittadi, Ole Winther
http://arxiv.org/abs/1909.11813v1
• [cs.LG]Learning with Long-term Remembering: Following the Lead of Mixed Stochastic Gradient
Yunhui Guo, Mingrui Liu, Tianbao Yang, Tajana Rosing
http://arxiv.org/abs/1909.11763v1
• [cs.LG]Locally adaptive activation functions with slope recovery term for deep and physics-informed neural networks
Ameya D. Jagtap, Kenji Kawaguchi, George Em Karniadakis
http://arxiv.org/abs/1909.12228v1
• [cs.LG]Lower Bounds on Adversarial Robustness from Optimal Transport
Arjun Nitin Bhagoji, Daniel Cullina, Prateek Mittal
http://arxiv.org/abs/1909.12272v1
• [cs.LG]MONET: Debiasing Graph Embeddings via the Metadata-Orthogonal Training Unit
John Palowitch, Bryan Perozzi
http://arxiv.org/abs/1909.11793v1
• [cs.LG]Manifold Forests: Closing the Gap on Neural Networks
Ronan Perry, Tyler M. Tomita, Jesse Patsolic, Benjamin Falk, Joshua T. Vogelstein
http://arxiv.org/abs/1909.11799v1
• [cs.LG]Mathematical Reasoning in Latent Space
Dennis Lee, Christian Szegedy, Markus N. Rabe, Sarah M. Loos, Kshitij Bansal
http://arxiv.org/abs/1909.11851v1
• [cs.LG]Mildly Overparametrized Neural Nets can Memorize Training Data Efficiently
Rong Ge, Runzhe Wang, Haoyu Zhao
http://arxiv.org/abs/1909.11837v1
• [cs.LG]Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems
Antonio Ginart, Maxim Naumov, Dheevatsa Mudigere, Jiyan Yang, James Zou
http://arxiv.org/abs/1909.11810v1
• [cs.LG]Model Imitation for Model-Based Reinforcement Learning
Yueh-Hua Wu, Ting-Han Fan, Peter J. Ramadge, Hao Su
http://arxiv.org/abs/1909.11821v1
• [cs.LG]Overlapping Community Detection with Graph Neural Networks
Oleksandr Shchur, Stephan Günnemann
http://arxiv.org/abs/1909.12201v1
• [cs.LG]PairNorm: Tackling Oversmoothing in GNNs
Lingxiao Zhao, Leman Akoglu
http://arxiv.org/abs/1909.12223v1
• [cs.LG]Polylogarithmic width suffices for gradient descent to achieve arbitrarily small test error with shallow ReLU networks
Ziwei Ji, Matus Telgarsky
http://arxiv.org/abs/1909.12292v1
• [cs.LG]Probabilistic Forecasting using Deep Generative Models
Alessandro Fanfarillo, Behrooz Roozitalab, Weiming Hu, Guido Cervone
http://arxiv.org/abs/1909.11865v1
• [cs.LG]RADE: Resource-Efficient Supervised Anomaly Detection Using Decision Tree-Based Ensemble Methods
Shay Vargaftik, Isaac Keslassy, Yaniv Ben-Itzhak
http://arxiv.org/abs/1909.11877v1
• [cs.LG]Representation Learning with Ordered Relation Paths for Knowledge Graph Completion
Yao Zhu, Hongzhi Liu, Zhonghai Wu, Yang Song, Tao Zhang
http://arxiv.org/abs/1909.11864v1
• [cs.LG]Sequential Training of Neural Networks with Gradient Boosting
Gonzalo Martínez-Muñoz
http://arxiv.org/abs/1909.12098v1
• [cs.LG]Set Functions for Time Series
Max Horn, Michael Moor, Christian Bock, Bastian Rieck, Karsten Borgwardt
http://arxiv.org/abs/1909.12064v1
• [cs.LG]Smart Ternary Quantization
Grégoire Morin, Ryan Razani, Vahid Partovi Nia, Eyyüb Sari
http://arxiv.org/abs/1909.12205v1
• [cs.LG]StacNAS: Towards stable and consistent optimization for differentiable Neural Architecture Search
Guilin Li, Xing Zhang, Zitong Wang, Zhenguo Li, Tong Zhang
http://arxiv.org/abs/1909.11926v1
• [cs.LG]Stochastic Weight Matrix-based Regularization Methods for Deep Neural Networks
Patrik Reizinger, Bálint Gyires-Tóth
http://arxiv.org/abs/1909.11977v1
• [cs.LG]Symplectic ODE-Net: Learning Hamiltonian Dynamics with Control
Yaofeng Desmond Zhong, Biswadip Dey, Amit Chakraborty
http://arxiv.org/abs/1909.12077v1
• [cs.LG]The Implicit Bias of Depth: How Incremental Learning Drives Generalization
Daniel Gissin, Shai Shalev-Shwartz, Amit Daniely
http://arxiv.org/abs/1909.12051v1
• [cs.LG]Towards Understanding the Transferability of Deep Representations
Hong Liu, Mingsheng Long, Jianmin Wang, Michael I. Jordan
http://arxiv.org/abs/1909.12031v1
• [cs.LG]Towards neural networks that provably know when they don’t know
Alexander Meinke, Matthias Hein
http://arxiv.org/abs/1909.12180v1
• [cs.LG]Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples
Tengyu Xu, Shaofeng Zou, Yingbin Liang
http://arxiv.org/abs/1909.11907v1
• [cs.LG]Unsupervised Domain Adaptation through Self-Supervision
Yu Sun, Eric Tzeng, Trevor Darrell, Alexei A. Efros
http://arxiv.org/abs/1909.11825v1
• [cs.LG]Unsupervised Universal Self-Attention Network for Graph Classification
Dai Quoc Nguyen, Tu Dinh Nguyen, Dinh Phung
http://arxiv.org/abs/1909.11855v1
• [cs.LG]dAUTOMAP: decomposing AUTOMAP to achieve scalability and enhance performance
Jo Schlemper, Ilkay Oksuz, James R. Clough, Jinming Duan, Andrew P. King, Julia A. Schnabel, Joseph V. Hajnal, Daniel Rueckert
http://arxiv.org/abs/1909.10995v2
• [cs.MA]$α^α$-Rank: Scalable Multi-agent Evaluation through Evolution
Yaodong Yang, Rasul Tutunov, Phu Sakulwongtana, Haitham Bou Ammar, Jun Wang
http://arxiv.org/abs/1909.11628v2
• [cs.NE]Military Dog Based Optimizer and its Application to Fake Review
Ashish Kumar Tripathi, Kapil Sharma, Manju Bala
http://arxiv.org/abs/1909.11890v1
• [cs.NE]The Ant Swarm Neuro-Evolution Procedure for Optimizing Recurrent Networks
AbdElRahman A. ElSaid, Alexander G. Ororbia, Travis J. Desell
http://arxiv.org/abs/1909.11849v1
• [cs.NI]Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments
Yi Shi, Kemal Davaslioglu, Yalin E. Sagduyu, William C. Headley, Michael Fowler, Gilbert Green
http://arxiv.org/abs/1909.11800v1
• [cs.RO]“Good Robot!”: Efficient Reinforcement Learning for Multi-Step Visual Tasks via Reward Shaping
Andrew Hundt, Benjamin Killeen, Heeyeon Kwon, Chris Paxton, Gregory D. Hager
http://arxiv.org/abs/1909.11730v1
• [cs.RO]A Framework for Data-Driven Robotics
Serkan Cabi, Sergio Gómez Colmenarejo, Alexander Novikov, Ksenia Konyushkova, Scott Reed, Rae Jeong, Konrad Żołna, Yusuf Aytar, David Budden, Mel Vecerik, Oleg Sushkov, David Barker, Jonathan Scholz, Misha Denil, Nando de Freitas, Ziyu Wang
http://arxiv.org/abs/1909.12200v1
• [cs.RO]A fast, complete, point cloud based loop closure for LiDAR odometry and mapping
Jiarong Lin, Fu Zhang
http://arxiv.org/abs/1909.11811v1
• [cs.RO]Balancing Domain Gap for Object Instance Detection
Woo-han Yun, Jaeyeon Lee, Jaehong Kim, Junmo Kim
http://arxiv.org/abs/1909.11972v1
• [cs.RO]C-3PO: Cyclic-Three-Phase Optimization for Human-Robot Motion Retargeting based on Reinforcement Learning
Taewoo Kim, Joo-Haeng Lee
http://arxiv.org/abs/1909.11303v2
• [cs.RO]Controlling an Autonomous Vehicle with Deep Reinforcement Learning
Andreas Folkers, Matthias Rick, Christof Büskens
http://arxiv.org/abs/1909.12153v1
• [cs.RO]DOOR-SLAM: Distributed, Online, and Outlier Resilient SLAM for Robotic Teams
Pierre-Yves Lajoie, Benjamin Ramtoula, Yun Chang, Luca Carlone, Giovanni Beltrame
http://arxiv.org/abs/1909.12198v1
• [cs.RO]Efficient Large-Scale Multi-Drone Delivery Using Transit Networks
Shushman Choudhury, Kiril Solovey, Mykel J. Kochenderfer, Marco Pavone
http://arxiv.org/abs/1909.11840v1
• [cs.RO]Exercising with an “Iron Man”: Design for a Robot Exercise Coach for Persons with Dementia
Martin Cooney, Jacob Pihl, Hanna Larsson, Abbas Orand, Eren Erdal Aksoy
http://arxiv.org/abs/1909.12262v1
• [cs.RO]Fuzzy Gesture Expression Model for an Interactive and Safe Robot Partner
Alexis Stoven-Dubois, Janos Botzheim, Naoyuki Kubota
http://arxiv.org/abs/1909.12054v1
• [cs.RO]Information-Guided Robotic Maximum Seek-and-Sample in Partially Observable Continuous Environments
Genevieve Flaspohler, Victoria Preston, Anna P. M. Michel, Yogesh Girdhar, Nicholas Roy
http://arxiv.org/abs/1909.12216v1
• [cs.RO]RLBench: The Robot Learning Benchmark & Learning Environment
Stephen James, Zicong Ma, David Rovick Arrojo, Andrew J. Davison
http://arxiv.org/abs/1909.12271v1
• [cs.RO]Stabilization of Exoskeletons through Active Ankle Compensation
Thomas Gurriet, Maegan Tucker, Claudia Kann, Guilhem Boeris, Aaron D. Ames
http://arxiv.org/abs/1909.11848v1
• [cs.SD]Improving the Intelligibility of Electric and Acoustic Stimulation Speech Using Fully Convolutional Networks Based Speech Enhancement
Natalie Yu-Hsien Wang, Hsiao-Lan Sharon Wang, Tao-Wei Wang, Szu-Wei Fu, Xugan Lu, Yu Tsao, Hsin-Min Wang
http://arxiv.org/abs/1909.11912v1
• [cs.SD]Multichannel Speech Enhancement by Raw Waveform-mapping using Fully Convolutional Networks
Chang-Le Liu, Szu-Wei Fu, You-Jin Lee, Yu Tsao, Jen-Wei Huang, Hsin-Min Wang
http://arxiv.org/abs/1909.11909v1
• [cs.SD]Seeing Voices in Noise: A Study of Audiovisual-Enhanced Vocoded Speech Intelligibility in Cochlear Implant Simulation
Rung-Yu Tseng, Tao-Wei Wang, Szu-Wei Fu, Yu Tsao, Chia-Ying Lee
http://arxiv.org/abs/1909.11919v1
• [cs.SI]Social Network Analysis for Social Neuroscientists
Elisa C. Baek, Mason A. Porter, Carolyn Parkinson
http://arxiv.org/abs/1909.11894v1
• [eess.AS]Disentangling Speech and Non-Speech Components for Building Robust Acoustic Models from Found Data
Nishant Gurunath, Sai Krishna Rallabandi, Alan Black
http://arxiv.org/abs/1909.11727v1
• [eess.AS]Self-Adaptive Soft Voice Activity Detection using Deep Neural Networks for Robust Speaker Verification
Youngmoon Jung, Yeunju Choi, Hoirin Kim
http://arxiv.org/abs/1909.11886v1
• [eess.IV]A Hybrid Deep Learning Architecture for Leukemic B-lymphoblast Classification
Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh kassani, Michal J. Wesolowski, Kevin A. Schneider, Ralph Deters
http://arxiv.org/abs/1909.11866v1
• [eess.IV]A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
Irem Cetin, Gerard Sanroma, Steffen E. Petersen, Sandy Napel, Oscar Camara, Miguel-Angel Gonzalez Ballester, Karim Lekadir
http://arxiv.org/abs/1909.11854v1
• [eess.IV]A Symmetric Equilibrium Generative Adversarial Network with Attention Refine Block for Retinal Vessel Segmentation
Yukun Zhou, Zailiang Chen, Hailan Shen, Peng Peng, Ziyang Zeng, Xianxian Zheng
http://arxiv.org/abs/1909.11936v1
• [eess.IV]Breast Cancer Diagnosis with Transfer Learning and Global Pooling
Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassani, Michal J. Wesolowski, Kevin A. Schneider, Ralph Deters
http://arxiv.org/abs/1909.11839v1
• [eess.IV]Classification of Histopathological Biopsy Images Using Ensemble of Deep Learning Networks
Sara Hosseinzadeh Kassani, Peyman Hosseinzadeh Kassani, Michal J. Wesolowski, Kevin A. Schneider, Ralph Deters
http://arxiv.org/abs/1909.11870v1
• [eess.IV]Data consistency networks for (calibration-less) accelerated parallel MR image reconstruction
Jo Schlemper, Jinming Duan, Cheng Ouyang, Chen Qin, Jose Caballero, Joseph V. Hajnal, Daniel Rueckert
http://arxiv.org/abs/1909.11795v1
• [eess.IV]Follows Form: Regression from Complete Thoracic Computed Tomography Scans
Max Argus, Cornelia Schaefer-Prokop, David A. Lynch, Bram van Ginneken
http://arxiv.org/abs/1909.12047v1
• [eess.IV]Lightweight Image Super-Resolution with Information Multi-distillation Network
Zheng Hui, Xinbo Gao, Yunchu Yang, Xiumei Wang
http://arxiv.org/abs/1909.11856v1
• [eess.IV]Multi-grained Attention Networks for Single Image Super-Resolution
Huapeng Wu, Zhengxia Zou, Jie Gui, Senior Member, IEEE, Wen-Jun Zeng, Jieping Ye, Senior Member, IEEE, Jun Zhang, Member IEEE, Hongyi Liu, Member IEEE, Zhihui Wei
http://arxiv.org/abs/1909.11937v1
• [eess.IV]Rank Constrained Diffeomorphic Density Motion Estimation for Respiratory Correlated Computed Tomography
Markus D. Foote, Pouya Sabouri, Amit Sawant, Sarang C. Joshi
http://arxiv.org/abs/1909.11841v1
• [eess.IV]Segmentation of points of interest during fetal cardiac assesment in the first trimester from color Doppler ultrasound
Ruxandra Stoean, Dominic Iliescu, Catalin Stoean
http://arxiv.org/abs/1909.11903v1
• [eess.IV]Subjective and Objective De-raining Quality Assessment Towards Authentic Rain Image
Qingbo Wu, Lei Wang, King N. Ngan, Hongliang Li, Fanman Meng
http://arxiv.org/abs/1909.11983v1
• [eess.SP]A Simulation of UAV Power Optimization via Reinforcement Learning
AE. Niaraki Asli, A. Jannesari
http://arxiv.org/abs/1909.12217v1
• [eess.SY]Modeling Electromagnetic Navigation Systems for Medical Applications using Random Forests and Artificial Neural Networks
Ruoxi Yu, Samuel L. Charreyron, Quentin Boehler, Cameron Weibel, Carmen C. Y. Poon, Bradley J. Nelson
http://arxiv.org/abs/1909.12028v1
• [eess.SY]Probabilistic duck curve in high PV penetration power system: Concept, modeling, and empirical analysis in China
Qingchun Hou, Ning Zhang, Ershun Du, Miao Miao, Fei Peng, Chongqing Kang
http://arxiv.org/abs/1909.11711v1
• [eess.SY]Relationship Explainable Multi-objective Reinforcement Learning with Semantic Explainability Generation
Huixin Zhan, Yongcan Cao
http://arxiv.org/abs/1909.12268v1
• [math.CO]A moment ratio bound for polynomials and some extremal properties of Krawchouk polynomials and Hamming spheres
Naomi Kirshner, Alex Samorodnitsky
http://arxiv.org/abs/1909.11929v1
• [math.NA]Shifted and extrapolated power methods for tensor $\ell^p$-eigenpairs
Stefano Cipolla, Michela Redivo-Zaglia, Francesco Tudisco
http://arxiv.org/abs/1909.11964v1
• [math.OC]Optimal Transport to a Variety
T. Ö. Çelik, A. Jamneshan, G. Montúfar, B. Sturmfels, L. Venturello
http://arxiv.org/abs/1909.11716v1
• [math.OC]Path Planning in Unknown Environments Using Optimal Transport Theory
Haoyan Zhai, Magnus Egerstedt, Haomin Zhou
http://arxiv.org/abs/1909.11235v1
• [math.OC]Randomized Iterative Methods for Linear Systems: Momentum, Inexactness and Gossip
Nicolas Loizou
http://arxiv.org/abs/1909.12176v1
• [math.ST]A new coefficient of correlation
Sourav Chatterjee
http://arxiv.org/abs/1909.10140v2
• [math.ST]Estimating covariance and precision matrices along subspaces
Zeljko Kereta, Timo Klock
http://arxiv.org/abs/1909.12218v1
• [math.ST]On the spectral property of kernel-based sensor fusion algorithms of high dimensional data
Xiucai Ding, Hau-Tieng Wu
http://arxiv.org/abs/1909.11734v1
• [math.ST]Rapid mixing of a Markov chain for an exponentially weighted aggregation estimator
David Pollard, Dana Yang
http://arxiv.org/abs/1909.11773v1
• [math.ST]The $f$-Divergence Expectation Iteration Scheme
Kamélia Daudel, Randal Douc, François Portier, François Roueff
http://arxiv.org/abs/1909.12239v1
• [math.ST]The Trimmed Mean in Non-parametric Regression Function Estimation
Subhra Sankar Dhar, Prashant Jha, Prabrisha Rakhshit
http://arxiv.org/abs/1909.10734v2
• [physics.comp-ph]DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems
Adam Rupe, Nalini Kumar, Vladislav Epifanov, Karthik Kashinath, Oleksandr Pavlyk, Frank Schlimbach, Mostofa Patwary, Sergey Maidanov, Victor Lee, Prabhat, James P. Crutchfield
http://arxiv.org/abs/1909.11822v1
• [physics.med-ph]Deep-learning-based Breast CT for Radiation Dose Reduction
Wenxiang Cong, Hongming Shan, Xiaohua Zhang, Shaohua Liu, Ruola Ning, Ge Wang
http://arxiv.org/abs/1909.11721v1
• [physics.med-ph]Non-Invasive Fuhrman Grading of Clear Cell Renal Cell Carcinoma Using Computed Tomography Radiomics Features and Machine Learning
Mostafa Nazari, Isaac Shiri, Ghasem Hajianfar, Niki Oveisi, Hamid Abdollahi, Mohammad Reza Deevband, Mehrdad Oveisi
http://arxiv.org/abs/1909.12286v1
• [physics.soc-ph]Strategic reciprocity improves academic performance in public elementary school children
Cristian Candia, Víctor Landaeta-Torres, César A. Hidalgo, Carlos Rodriguez-Sickert
http://arxiv.org/abs/1909.11713v1
• [q-bio.GN]Deep Learning and Random Forest-Based Augmentation of sRNA Expression Profiles
Jelena Fiosina, Maksims Fiosins, Stefan Bonn
http://arxiv.org/abs/1909.11943v1
• [q-bio.QM]Single-modal and Multi-modal False Arrhythmia Alarm Reduction using Attention-based Convolutional and Recurrent Neural Networks
Sajad Mousavi, Atiyeh Fotoohinasab, Fatemeh Afghah
http://arxiv.org/abs/1909.11791v1
• [quant-ph]Quantum Bicyclic Hyperbolic Codes
Sankara Sai Chaithanya Rayudu, Pradeep Kiran Sarvepalli
http://arxiv.org/abs/1909.11846v1
• [quant-ph]Quantum Graph Neural Networks
Guillaume Verdon, Trevor McCourt, Enxhell Luzhnica, Vikash Singh, Stefan Leichenauer, Jack Hidary
http://arxiv.org/abs/1909.12264v1
• [stat.AP]Enhancing Model Interpretability and Accuracy for Disease Progression Prediction via Phenotype-Based Patient Similarity Learning
Yue Wang, Tong Wu, Yunlong Wang, Gao Wang
http://arxiv.org/abs/1909.11913v1
• [stat.AP]Identify More, Observe Less: Mediation Analysis Synthetic Control
Giovanni Mellace, Alessandra Pasquini
http://arxiv.org/abs/1909.12073v1
• [stat.CO]Exact Inference with Approximate Computation for Differentially Private Data via Perturbations
Ruobin Gong
http://arxiv.org/abs/1909.12237v1
• [stat.CO]bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond)
Nikolaus Umlauf, Nadja Klein, Thorsten Simon, Achim Zeileis
http://arxiv.org/abs/1909.11784v1
• [stat.ME]A bivariate logistic regression model based on latent variables
Simon Bang Kristensen, Bo Martin Bibby
http://arxiv.org/abs/1909.12049v1
• [stat.ME]Bayesian Pseudo Posterior Mechanism under Differential Privacy
Terrance D. Savitsky, Matthew R. Williams, Jingchen Hu
http://arxiv.org/abs/1909.11796v1
• [stat.ME]Compound vectors of subordinators and their associated positive Lévy copulas
Alan Riva Palacio, Fabrizio Leisen
http://arxiv.org/abs/1909.12112v1
• [stat.ME]Cross-Validation, Risk Estimation, and Model Selection
Stefan Wager
http://arxiv.org/abs/1909.11696v1
• [stat.ME]Dynamic Partial Sufficient Dimension Reduction
Lu Li, Kai Tan, Xuerong Meggie Wen, Zhou Yu
http://arxiv.org/abs/1909.11948v1
• [stat.ME]Survival analysis as a classification problem
Chenyang Zhong, Robert Tibshirani
http://arxiv.org/abs/1909.11171v2
• [stat.ML]Benefit of Interpolation in Nearest Neighbor Algorithms
Yue Xing, Qifan Song, Guang Cheng
http://arxiv.org/abs/1909.11720v1
• [stat.ML]Data Smashing 2.0: Sequence Likelihood (SL) Divergence For Fast Time Series Comparison
Yi Huang, Ishanu Chattopadhyay
http://arxiv.org/abs/1909.12243v1
• [stat.ML]Debiased Bayesian inference for average treatment effects
Kolyan Ray, Botond Szabo
http://arxiv.org/abs/1909.12078v1
• [stat.ML]Probabilistic Modeling of Deep Features for Out-of-Distribution and Adversarial Detection
Nilesh A. Ahuja, Ibrahima Ndiour, Trushant Kalyanpur, Omesh Tickoo
http://arxiv.org/abs/1909.11786v1
• [stat.ML]Residual Networks Behave Like Boosting Algorithms
Chapman Siu
http://arxiv.org/abs/1909.11790v1
• [stat.ML]Stochastic Prototype Embeddings
Tyler R. Scott, Karl Ridgeway, Michael C. Mozer
http://arxiv.org/abs/1909.11702v1
若有收获，就点个赞吧
0 人点赞
