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.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.DM - 离散数学 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SI - 社交网络与信息网络 econ.TH - 理论经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SY - 系统和控制 math.ST - 统计理论 physics.comp-ph - 计算物理学 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 stat.AP - 应用统计 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cond-mat.dis-nn]Clustering of solutions in the symmetric binary perceptron
• [cs.AI]”How do I fool you?”: Manipulating User Trust via Misleading Black Box Explanations
• [cs.AI]A Policy Editor for Semantic Sensor Networks
• [cs.AI]Fine-grained Qualitative Spatial Reasoning about Point Positions
• [cs.AI]Reusable neural skill embeddings for vision-guided whole body movement and object manipulation
• [cs.CL]Bootstrapping NLU Models with Multi-task Learning
• [cs.CL]CatGAN: Category-aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text Generation
• [cs.CL]DNNRE: A Dynamic Neural Network for Distant Supervised Relation Extraction
• [cs.CL]Sparse associative memory based on contextual code learning for disambiguating word senses
• [cs.CL]The Eighth Dialog System Technology Challenge
• [cs.CL]Towards Personalized Dialog Policies for Conversational Skill Discovery
• [cs.CL]Using natural language processing to extract health-related causality from Twitter messages
• [cs.CV]A3GAN: An Attribute-aware Attentive Generative Adversarial Network for Face Aging
• [cs.CV]AdvKnn: Adversarial Attacks On K-Nearest Neighbor Classifiers With Approximate Gradients
• [cs.CV]Automated Augmentation with Reinforcement Learning and GANs for Robust Identification of Traffic Signs using Front Camera Images
• [cs.CV]CenterMask : Real-Time Anchor-Free Instance Segmentation
• [cs.CV]Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma
• [cs.CV]Does Face Recognition Accuracy Get Better With Age? Deep Face Matchers Say No
• [cs.CV]Gated Variational AutoEncoders: Incorporating Weak Supervision to Encourage Disentanglement
• [cs.CV]GraphX-Convolution for Point Cloud Deformation in 2D-to-3D Conversion
• [cs.CV]Human Annotations Improve GAN Performances
• [cs.CV]In-domain representation learning for remote sensing
• [cs.CV]Learning To Characterize Adversarial Subspaces
• [cs.CV]Multiple Style-Transfer in Real-Time
• [cs.CV]OpenLORIS-Object: A Dataset and Benchmark towards Lifelong Object Recognition
• [cs.CV]Question-Conditioned Counterfactual Image Generation for VQA
• [cs.CV]Simple iterative method for generating targeted universal adversarial perturbations
• [cs.CV]Single Image Reflection Removal through Cascaded Refinement
• [cs.CV]Single View Distortion Correction using Semantic Guidance
• [cs.CV]You Only Watch Once: A Unified CNN Architecture for Real-Time Spatiotemporal Action Localization
• [cs.CY]By the user, for the user: A user-centric approach to quantifying the privacy of websites
• [cs.CY]Data Preparation in Agriculture Through Automated Semantic Annotation — Basis for a Wide Range of Smart Services
• [cs.CY]Putting Privacy into Perspective — Comparing Technical, Legal, and Users’ View of Data Sensitivity
• [cs.DC]HealthFog: An Ensemble Deep Learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in Integrated IoT and Fog Computing Environments
• [cs.DC]Resource-Competitive Sybil Defenses
• [cs.DC]Scalable and Reliable Multi-Dimensional Aggregation of Sensor Data Streams
• [cs.DC]Two-level Dynamic Load Balancing for High Performance Scientific Applications
• [cs.DM]Optimal adaptive group testing
• [cs.IT]Codes Correcting All Patterns of Tandem-Duplication Errors of Maximum Length 3
• [cs.IT]Entanglement-assisted Quantum Codes from Cyclic Codes
• [cs.IT]General Criteria for Successor Rules to Efficiently Generate Binary de Bruijn Sequences
• [cs.IT]Improving PHY-Security of UAV-Enabled Transmission with Wireless Energy Harvesting: Robust Trajectory Design and Power Allocation
• [cs.IT]Millimeter Wave Base Stations with Cameras: Vision Aided Beam and Blockage Prediction
• [cs.IT]Non-Orthogonal Multiple Access for Visible Light Communications with Ambient Light and User Mobility
• [cs.LG]$\ell_{\infty}$ Vector Contraction for Rademacher Complexity
• [cs.LG]ASCAI: Adaptive Sampling for acquiring Compact AI
• [cs.LG]CASTER: Predicting Drug Interactions with Chemical Substructure Representation
• [cs.LG]Explicit-Blurred Memory Network for Analyzing Patient Electronic Health Records
• [cs.LG]Forgetting to learn logic programs
• [cs.LG]Generative Models for Effective ML on Private, Decentralized Datasets
• [cs.LG]LIBRE: Learning Interpretable Boolean Rule Ensembles
• [cs.LG]MMGAN: Generative Adversarial Networks for Multi-Modal Distributions
• [cs.LG]Mining News Events from Comparable News Corpora: A Multi-Attribute Proximity Network Modeling Approach
• [cs.LG]Modelling EHR timeseries by restricting feature interaction
• [cs.LG]Multi-Label Learning with Deep Forest
• [cs.LG]Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings
• [cs.LG]On Model Robustness Against Adversarial Examples
• [cs.LG]Optimal Mini-Batch Size Selection for Fast Gradient Descent
• [cs.LG]Penalized k-means algorithms for finding the correct number of clusters in a dataset
• [cs.LG]Predicting Drug-Drug Interactions from Molecular Structure Images
• [cs.LG]Self-supervised Adversarial Training
• [cs.LG]Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling
• [cs.LG]Sequential Recommendation with Relation-Aware Kernelized Self-Attention
• [cs.LG]Stagewise Knowledge Distillation
• [cs.LG]Synthetic Event Time Series Health Data Generation
• [cs.LG]TinyCNN: A Tiny Modular CNN Accelerator for Embedded FPGA
• [cs.LG]Unsupervised Attributed Multiplex Network Embedding
• [cs.NE]Auto-encoding a Knowledge Graph Using a Deep Belief Network: A Random Fields Perspective
• [cs.NE]Performance evaluation of deep neural networks for forecasting time-series with multiple structural breaks and high volatility
• [cs.NI]Flexible Functional Split and Power Control for Energy Harvesting Cloud Radio Access Networks
• [cs.RO]Design Requirements of Generic Hand Exoskeletons and Survey of Hand Exoskeletons for Rehabilitation, Assistive or Haptic Use
• [cs.SI]Capturing the Production of the Innovative Ideas: An Online Social Network Experiment and “Idea Geography” Visualization
• [cs.SI]Graph Iso/Auto-morphism: A Divide-&-Conquer Approach
• [cs.SI]On a Centrality Maximization Game
• [cs.SI]Twitter Watch: Leveraging Social Media to Monitor and Predict Collective-Efficacy of Neighborhoods
• [econ.TH]A Generalized Markov Chain Model to Capture Dynamic Preferences and Choice Overload
• [eess.AS]Independent and automatic evaluation of acoustic-to-articulatory inversion models
• [eess.IV]Contrast Phase Classification with a Generative Adversarial Network
• [eess.IV]Fourier Spectrum Discrepancies in Deep Network Generated Images
• [eess.IV]Give me (un)certainty — An exploration of parameters that affect segmentation uncertainty
• [eess.IV]Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels
• [eess.SY]Safe Interactive Model-Based Learning
• [math.ST]A nonparametric estimator of the extremal index
• [math.ST]Estimation of dynamic networks for high-dimensional nonstationary time series
• [math.ST]Estimation via length-constrained generalized empirical principal curves under small noise
• [math.ST]Optimal Sequential Tests for Detection of Changes under Finite measure space for Finite Sequences of Networks
• [physics.comp-ph]Enforcing Boundary Conditions on Physical Fields in Bayesian Inversion
• [physics.comp-ph]Enforcing Deterministic Constraints on Generative Adversarial Networks for Emulating Physical Systems
• [physics.soc-ph]Random walks on hypergraphs
• [q-bio.NC]Radically Compositional Cognitive Concepts
• [stat.AP]Batch correction of high-dimensional data
• [stat.AP]Estimating adaptive cruise control model parameters from on-board radar units
• [stat.AP]Measurement Error Correction in Particle Tracking Microrheology
• [stat.AP]On Data Enriched Logistic Regression
• [stat.ME]A nonparametric framework for inferring orders of categorical data from category-real ordered pairs
• [stat.ME]Akaike’s Bayesian information criterion (ABIC) or not ABIC for geophysical inversion
• [stat.ME]Assessing the uncertainty in statistical evidence with the possibility of model misspecification using a non-parametric bootstrap
• [stat.ME]Asymptotically Exact Variational Bayes for High-Dimensional Binary Regression Models
• [stat.ME]Causal inference using Bayesian non-parametric quasi-experimental design
• [stat.ME]GET: Global envelopes in R
• [stat.ME]How bettering the best? Answers via blending models and cluster formulations in density-based clustering
• [stat.ML]Fair Data Adaptation with Quantile Preservation
• [stat.ML]Imputing missing values with unsupervised random trees
• [stat.ML]Likelihood Assignment for Out-of-Distribution Inputs in Deep Generative Models is Sensitive to Prior Distribution Choice
• [stat.ML]Solving Inverse Problems by Joint Posterior Maximization with a VAE Prior
·····································
• [cond-mat.dis-nn]Clustering of solutions in the symmetric binary perceptron
Carlo Baldassi, Riccardo Della Vecchia, Carlo Lucibello, Riccardo Zecchina
http://arxiv.org/abs/1911.06756v1
• [cs.AI]“How do I fool you?”: Manipulating User Trust via Misleading Black Box Explanations
Himabindu Lakkaraju, Osbert Bastani
http://arxiv.org/abs/1911.06473v1
• [cs.AI]A Policy Editor for Semantic Sensor Networks
Paolo Pareti, George Konstantinidis, Timothy J. Norman
http://arxiv.org/abs/1911.06657v1
• [cs.AI]Fine-grained Qualitative Spatial Reasoning about Point Positions
Sören Schwertfeger
http://arxiv.org/abs/1911.06543v1
• [cs.AI]Reusable neural skill embeddings for vision-guided whole body movement and object manipulation
Josh Merel, Saran Tunyasuvunakool, Arun Ahuja, Yuval Tassa, Leonard Hasenclever, Vu Pham, Tom Erez, Greg Wayne, Nicolas Heess
http://arxiv.org/abs/1911.06636v1
• [cs.CL]Bootstrapping NLU Models with Multi-task Learning
Shubham Kapoor, Caglar Tirkaz
http://arxiv.org/abs/1911.06673v1
• [cs.CL]CatGAN: Category-aware Generative Adversarial Networks with Hierarchical Evolutionary Learning for Category Text Generation
Zhiyue Liu, Jiahai Wang, Zhiwei Liang
http://arxiv.org/abs/1911.06641v1
• [cs.CL]DNNRE: A Dynamic Neural Network for Distant Supervised Relation Extraction
Yanjie Gou, Yinjie Lei, Lingqiao Liu, Pingping Zhang, Jingyi Zhang, Xi Peng
http://arxiv.org/abs/1911.06489v1
• [cs.CL]Sparse associative memory based on contextual code learning for disambiguating word senses
Max Raphael Sobroza, Tales Marra, Deok-Hee Kim-Dufor, Claude Berrou
http://arxiv.org/abs/1911.06415v1
• [cs.CL]The Eighth Dialog System Technology Challenge
Seokhwan Kim, Michel Galley, Chulaka Gunasekara, Sungjin Lee, Adam Atkinson, Baolin Peng, Hannes Schulz, Jianfeng Gao, Jinchao Li, Mahmoud Adada, Minlie Huang, Luis Lastras, Jonathan K. Kummerfeld, Walter S. Lasecki, Chiori Hori, Anoop Cherian, Tim K. Marks, Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta
http://arxiv.org/abs/1911.06394v1
• [cs.CL]Towards Personalized Dialog Policies for Conversational Skill Discovery
Maryam Fazel-Zarandi, Sampat Biswas, Ryan Summers, Ahmed Elmalt, Andy McCraw, Michael McPhilips, John Peach
http://arxiv.org/abs/1911.06747v1
• [cs.CL]Using natural language processing to extract health-related causality from Twitter messages
Son Doan, Elly W Yang, Sameer Tilak, Manabu Torii
http://arxiv.org/abs/1911.06488v1
• [cs.CV]A3GAN: An Attribute-aware Attentive Generative Adversarial Network for Face Aging
Yunfan Liu, Qi Li, Zhenan Sun, Tieniu Tan
http://arxiv.org/abs/1911.06531v1
• [cs.CV]AdvKnn: Adversarial Attacks On K-Nearest Neighbor Classifiers With Approximate Gradients
Xiaodan Li, Yuefeng Chen, Yuan He, Hui Xue
http://arxiv.org/abs/1911.06591v1
• [cs.CV]Automated Augmentation with Reinforcement Learning and GANs for Robust Identification of Traffic Signs using Front Camera Images
Sohini Roy Chowdhury, Lars Tornberg, Robin Halvfordsson, Jonatan Nordh, Adam Suhren Gustafsson, Joel Wall, Mattias Westerberg, Adam Wirehed, Louis Tilloy, Zhanying Hu, Haoyuan Tan, Meng Pan, Jonas Sjoberg
http://arxiv.org/abs/1911.06486v1
• [cs.CV]CenterMask : Real-Time Anchor-Free Instance Segmentation
Youngwan Lee, Jongyoul Park
http://arxiv.org/abs/1911.06667v1
• [cs.CV]Deep radiomic features from MRI scans predict survival outcome of recurrent glioblastoma
Ahmad Chaddad, Saima Rathore, Mingli Zhang, Christian Desrosiers, Tamim Niazi
http://arxiv.org/abs/1911.06687v1
• [cs.CV]Does Face Recognition Accuracy Get Better With Age? Deep Face Matchers Say No
Vítor Albiero, Kevin W. Bowyer, Kushal Vangara, Michael C. King
http://arxiv.org/abs/1911.06396v1
• [cs.CV]Gated Variational AutoEncoders: Incorporating Weak Supervision to Encourage Disentanglement
Matthew J. Vowels, Necati Cihan Camgoz, Richard Bowden
http://arxiv.org/abs/1911.06443v1
• [cs.CV]GraphX-Convolution for Point Cloud Deformation in 2D-to-3D Conversion
Anh-Duc Nguyen, Seonghwa Choi, Woojae Kim, Sanghoon Lee
http://arxiv.org/abs/1911.06600v1
• [cs.CV]Human Annotations Improve GAN Performances
Juanyong Duan, Sim Heng Ong, Qi Zhao
http://arxiv.org/abs/1911.06460v1
• [cs.CV]In-domain representation learning for remote sensing
Maxim Neumann, Andre Susano Pinto, Xiaohua Zhai, Neil Houlsby
http://arxiv.org/abs/1911.06721v1
• [cs.CV]Learning To Characterize Adversarial Subspaces
Xiaofeng Mao, Yuefeng Chen, Yuhong Li, Yuan He, Hui Xue
http://arxiv.org/abs/1911.06587v1
• [cs.CV]Multiple Style-Transfer in Real-Time
Michael Maring, Kaustav Chakraborty
http://arxiv.org/abs/1911.06464v1
• [cs.CV]OpenLORIS-Object: A Dataset and Benchmark towards Lifelong Object Recognition
Qi She, Fan Feng, Xinyue Hao, Qihan Yang, Chuanlin Lan, Vincenzo Lomonaco, Xuesong Shi, Zhengwei Wang, Yao Guo, Yimin Zhang, Fei Qiao, Rosa H. M. Chan
http://arxiv.org/abs/1911.06487v1
• [cs.CV]Question-Conditioned Counterfactual Image Generation for VQA
Jingjing Pan, Yash Goyal, Stefan Lee
http://arxiv.org/abs/1911.06352v1
• [cs.CV]Simple iterative method for generating targeted universal adversarial perturbations
Hokuto Hirano, Kazuhiro Takemoto
http://arxiv.org/abs/1911.06502v1
• [cs.CV]Single Image Reflection Removal through Cascaded Refinement
Chao Li, Yixiao Yang, Kun He, Stephen Lin, John E. Hopcroft
http://arxiv.org/abs/1911.06634v1
• [cs.CV]Single View Distortion Correction using Semantic Guidance
Szabolcs-Botond Lőrincz, Szabolcs Pável, Lehel Csató
http://arxiv.org/abs/1911.06505v1
• [cs.CV]You Only Watch Once: A Unified CNN Architecture for Real-Time Spatiotemporal Action Localization
Okan Köpüklü, Xiangyu Wei, Gerhard Rigoll
http://arxiv.org/abs/1911.06644v1
• [cs.CY]By the user, for the user: A user-centric approach to quantifying the privacy of websites
Matius Chairani, Mathieu Chevalley, Abderrahmane Lazraq, Sruti Bhagavatula
http://arxiv.org/abs/1911.05798v2
• [cs.CY]Data Preparation in Agriculture Through Automated Semantic Annotation — Basis for a Wide Range of Smart Services
Julian Klose, Markus Schröder, Silke Becker, Ansgar Bernardi, Arno Ruckelshausen
http://arxiv.org/abs/1911.06606v1
• [cs.CY]Putting Privacy into Perspective — Comparing Technical, Legal, and Users’ View of Data Sensitivity
Eva-Maria Schomakers, Chantal Lidynia, Dirk Müllmann, Roman Matzutt, Klaus Wehrle, Indra Spiecker gen. Döhmann, Martina Ziefle
http://arxiv.org/abs/1911.06569v1
• [cs.DC]HealthFog: An Ensemble Deep Learning based Smart Healthcare System for Automatic Diagnosis of Heart Diseases in Integrated IoT and Fog Computing Environments
Shreshth Tuli, Nipam Basumatary, Sukhpal Singh Gill, Mohsen Kahani, Rajesh Chand Arya, Gurpreet Singh Wander, Rajkumar Buyya
http://arxiv.org/abs/1911.06633v1
• [cs.DC]Resource-Competitive Sybil Defenses
Diksha Gupta, Jared Saia, Maxwell Young
http://arxiv.org/abs/1911.06462v1
• [cs.DC]Scalable and Reliable Multi-Dimensional Aggregation of Sensor Data Streams
Sören Henning, Wilhelm Hasselbring
http://arxiv.org/abs/1911.06525v1
• [cs.DC]Two-level Dynamic Load Balancing for High Performance Scientific Applications
Ali Mohammed, Aurelien Cavelan, Florina M. Ciorba, Ruben M. Cabezon, Ioana Banicesu
http://arxiv.org/abs/1911.06714v1
• [cs.DM]Optimal adaptive group testing
Max Hahn-Klimroth, Philipp Loick
http://arxiv.org/abs/1911.06647v1
• [cs.IT]Codes Correcting All Patterns of Tandem-Duplication Errors of Maximum Length 3
Mladen Kovačević
http://arxiv.org/abs/1911.06561v1
• [cs.IT]Entanglement-assisted Quantum Codes from Cyclic Codes
Francisco Revson F. Pereira
http://arxiv.org/abs/1911.06384v1
• [cs.IT]General Criteria for Successor Rules to Efficiently Generate Binary de Bruijn Sequences
Zuling Chang, Martianus Frederic Ezerman, Pinhui Ke, Qiang Wang
http://arxiv.org/abs/1911.06670v1
• [cs.IT]Improving PHY-Security of UAV-Enabled Transmission with Wireless Energy Harvesting: Robust Trajectory Design and Power Allocation
Milad Tatar Mamaghani, Yi Hong
http://arxiv.org/abs/1911.06516v1
• [cs.IT]Millimeter Wave Base Stations with Cameras: Vision Aided Beam and Blockage Prediction
Muhammad Alrabeiah, Andrew Hredzak, Ahmed Alkhateeb
http://arxiv.org/abs/1911.06255v2
• [cs.IT]Non-Orthogonal Multiple Access for Visible Light Communications with Ambient Light and User Mobility
Rangeet Mitra, Paschalis. C. Sofotasios, Vimal Bhatia, Sami Muhaidat
http://arxiv.org/abs/1911.06765v1
• [cs.LG]$\ell_{\infty}$ Vector Contraction for Rademacher Complexity
Dylan J. Foster, Alexander Rakhlin
http://arxiv.org/abs/1911.06468v1
• [cs.LG]ASCAI: Adaptive Sampling for acquiring Compact AI
Mojan Javaheripi, Mohammad Samragh, Tara Javidi, Farinaz Koushanfar
http://arxiv.org/abs/1911.06471v1
• [cs.LG]CASTER: Predicting Drug Interactions with Chemical Substructure Representation
Kexin Huang, Cao Xiao, Trong Nghia Hoang, Lucas M. Glass, Jimeng Sun
http://arxiv.org/abs/1911.06446v1
• [cs.LG]Explicit-Blurred Memory Network for Analyzing Patient Electronic Health Records
Prithwish Chakraborty, Fei Wang, Jianying Hu, Daby Sow
http://arxiv.org/abs/1911.06472v1
• [cs.LG]Forgetting to learn logic programs
Andrew Cropper
http://arxiv.org/abs/1911.06643v1
• [cs.LG]Generative Models for Effective ML on Private, Decentralized Datasets
Sean Augenstein, H. Brendan McMahan, Daniel Ramage, Swaroop Ramaswamy, Peter Kairouz, Mingqing Chen, Rajiv Mathews, Blaise Aguera y Arcas
http://arxiv.org/abs/1911.06679v1
• [cs.LG]LIBRE: Learning Interpretable Boolean Rule Ensembles
Graziano Mita, Paolo Papotti, Maurizio Filippone, Pietro Michiardi
http://arxiv.org/abs/1911.06537v1
• [cs.LG]MMGAN: Generative Adversarial Networks for Multi-Modal Distributions
Teodora Pandeva, Matthias Schubert
http://arxiv.org/abs/1911.06663v1
• [cs.LG]Mining News Events from Comparable News Corpora: A Multi-Attribute Proximity Network Modeling Approach
Hyungsul Kim, Ahmed El-Kishky, Xiang Ren, Jiawei Han
http://arxiv.org/abs/1911.06407v1
• [cs.LG]Modelling EHR timeseries by restricting feature interaction
Kun Zhang, Yuan Xue, Gerardo Flores, Alvin Rajkomar, Claire Cui, Andrew M. Dai
http://arxiv.org/abs/1911.06410v1
• [cs.LG]Multi-Label Learning with Deep Forest
Liang Yang, Xi-Zhu Wu, Yuan Jiang, Zhi-Hua Zhou
http://arxiv.org/abs/1911.06557v1
• [cs.LG]Non-Monotone Submodular Maximization with Multiple Knapsacks in Static and Dynamic Settings
Vanja Doskoč, Tobias Friedrich, Andreas Göbel, Frank Neumann, Aneta Neumann, Francesco Quinzan
http://arxiv.org/abs/1911.06791v1
• [cs.LG]On Model Robustness Against Adversarial Examples
Shufei Zhang, Kaizhu Huang, Zenglin Xu
http://arxiv.org/abs/1911.06479v1
• [cs.LG]Optimal Mini-Batch Size Selection for Fast Gradient Descent
Michael P. Perrone, Haidar Khan, Changhoan Kim, Anastasios Kyrillidis, Jerry Quinn, Valentina Salapura
http://arxiv.org/abs/1911.06459v1
• [cs.LG]Penalized k-means algorithms for finding the correct number of clusters in a dataset
Behzad Kamgar-Parsi, Behrooz Kamgar-Parsi
http://arxiv.org/abs/1911.06741v1
• [cs.LG]Predicting Drug-Drug Interactions from Molecular Structure Images
Devendra Singh Dhami, Gautam Kunapuli, David Page, Sriraam Natarajan
http://arxiv.org/abs/1911.06356v1
• [cs.LG]Self-supervised Adversarial Training
Kejiang Chen, Hang Zhou, Yuefeng Chen, Xiaofeng Mao, Yuhong Li, Yuan He, Hui Xue, Weiming Zhang, Nenghai Yu
http://arxiv.org/abs/1911.06470v1
• [cs.LG]Seq-U-Net: A One-Dimensional Causal U-Net for Efficient Sequence Modelling
Daniel Stoller, Mi Tian, Sebastian Ewert, Simon Dixon
http://arxiv.org/abs/1911.06393v1
• [cs.LG]Sequential Recommendation with Relation-Aware Kernelized Self-Attention
Mingi Ji, Weonyoung Joo, Kyungwoo Song, Yoon-Yeong Kim, Il-Chul Moon
http://arxiv.org/abs/1911.06478v1
• [cs.LG]Stagewise Knowledge Distillation
Akshay Kulkarni, Navid Panchi, Shital Chiddarwar
http://arxiv.org/abs/1911.06786v1
• [cs.LG]Synthetic Event Time Series Health Data Generation
Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, Andrew Yale, Kristin P. Bennett
http://arxiv.org/abs/1911.06411v1
• [cs.LG]TinyCNN: A Tiny Modular CNN Accelerator for Embedded FPGA
Ali Jahanshahi
http://arxiv.org/abs/1911.06777v1
• [cs.LG]Unsupervised Attributed Multiplex Network Embedding
Chanyoung Park, Donghyun Kim, Jiawei Han, Hwanjo Yu
http://arxiv.org/abs/1911.06750v1
• [cs.NE]Auto-encoding a Knowledge Graph Using a Deep Belief Network: A Random Fields Perspective
Robert A. Murphy
http://arxiv.org/abs/1911.06322v1
• [cs.NE]Performance evaluation of deep neural networks for forecasting time-series with multiple structural breaks and high volatility
Shikhar Jain, Rohit Kaushik, Siddhant Jain, Tirtharaj Dash
http://arxiv.org/abs/1911.06704v1
• [cs.NI]Flexible Functional Split and Power Control for Energy Harvesting Cloud Radio Access Networks
Liumeng Wang, Sheng Zhou
http://arxiv.org/abs/1911.06463v1
• [cs.RO]Design Requirements of Generic Hand Exoskeletons and Survey of Hand Exoskeletons for Rehabilitation, Assistive or Haptic Use
Mine Sarac, Massimiliano Solazzi, Antonio Frisoli
http://arxiv.org/abs/1911.06408v1
• [cs.SI]Capturing the Production of the Innovative Ideas: An Online Social Network Experiment and “Idea Geography” Visualization
Yiding Cao, Yingjun Dong, Minjun Kim, Neil G. MacLaren, Ankita Kulkarni, Shelley D. Dionne, Francis J. Yammarino, Hiroki Sayama
http://arxiv.org/abs/1911.06353v1
• [cs.SI]Graph Iso/Auto-morphism: A Divide-&-Conquer Approach
Can Lu, Jeffrey Xu Yu, Zhiwei Zhang, Hong Cheng
http://arxiv.org/abs/1911.06511v1
• [cs.SI]On a Centrality Maximization Game
Maria Castaldo, Costanza Catalano, Giacomo Como, Fabio Fagnani
http://arxiv.org/abs/1911.06737v1
• [cs.SI]Twitter Watch: Leveraging Social Media to Monitor and Predict Collective-Efficacy of Neighborhoods
Moniba Keymanesh, Saket Gurukar, Bethany Boettner, Christopher Browning, Catherine Calder, Srinivasan Parthasarathy
http://arxiv.org/abs/1911.06359v1
• [econ.TH]A Generalized Markov Chain Model to Capture Dynamic Preferences and Choice Overload
Kumar Goutam, Vineet Goyal, Agathe Soret
http://arxiv.org/abs/1911.06716v1
• [eess.AS]Independent and automatic evaluation of acoustic-to-articulatory inversion models
Parrot Maud, Millet Juliette, Dunbar Ewan
http://arxiv.org/abs/1911.06573v1
• [eess.IV]Contrast Phase Classification with a Generative Adversarial Network
Yucheng Tang, Ho Hin Lee, Yuchen Xu, Olivia Tang, Yunqiang Chen, Dashan Gao, Shizhong Han, Riqiang Gao, Camilo Bermudez, Michael R. Savona, Richard G. Abramson, Yuankai Huo, Bennett A. Landman
http://arxiv.org/abs/1911.06395v1
• [eess.IV]Fourier Spectrum Discrepancies in Deep Network Generated Images
Tarik Dzanic, Freddie Witherden
http://arxiv.org/abs/1911.06465v1
• [eess.IV]Give me (un)certainty — An exploration of parameters that affect segmentation uncertainty
Katharina Hoebel, Ken Chang, Jay Patel, Praveer Singh, Jayashree Kalpathy-Cramer
http://arxiv.org/abs/1911.06357v1
• [eess.IV]Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels
Hieu H. Pham, Tung T. Le, Dat Q. Tran, Dat T. Ngo, Ha Q. Nguyen
http://arxiv.org/abs/1911.06475v1
• [eess.SY]Safe Interactive Model-Based Learning
Marco Gallieri, Seyed Sina Mirrazavi Salehian, Nihat Engin Toklu, Alessio Quaglino, Jonathan Masci, Jan Koutník, Faustino Gomez
http://arxiv.org/abs/1911.06556v1
• [math.ST]A nonparametric estimator of the extremal index
Juan Juan Cai
http://arxiv.org/abs/1911.06674v1
• [math.ST]Estimation of dynamic networks for high-dimensional nonstationary time series
Mengyu Xu, Xiaohui Chen, Weibiao Wu
http://arxiv.org/abs/1911.06385v1
• [math.ST]Estimation via length-constrained generalized empirical principal curves under small noise
Sylvain Delattre, Aurélie Fischer
http://arxiv.org/abs/1911.06728v1
• [math.ST]Optimal Sequential Tests for Detection of Changes under Finite measure space for Finite Sequences of Networks
Lei Qiao, Dong Han
http://arxiv.org/abs/1911.06545v1
• [physics.comp-ph]Enforcing Boundary Conditions on Physical Fields in Bayesian Inversion
Carlos A. Michelén Ströfer, Xinlei Zhang, Heng Xiao, Olivier Coutier-Delgosha
http://arxiv.org/abs/1911.06683v1
• [physics.comp-ph]Enforcing Deterministic Constraints on Generative Adversarial Networks for Emulating Physical Systems
Zeng Yang, Jin-Long Wu, Heng Xiao
http://arxiv.org/abs/1911.06671v1
• [physics.soc-ph]Random walks on hypergraphs
Timoteo Carletti, Federico Battiston, Giulia Cencetti, Duccio Fanelli
http://arxiv.org/abs/1911.06523v1
• [q-bio.NC]Radically Compositional Cognitive Concepts
Toby B. St Clere Smithe
http://arxiv.org/abs/1911.06602v1
• [stat.AP]Batch correction of high-dimensional data
Emanuele Aliverti, Jeff Tilson, Dayne Filer, Benjamin Babcock, Alejandro Colaneri, Jennifer Ocasio, Timothy R. Gershon, Kirk C. Wilhelmsen, David B. Dunson
http://arxiv.org/abs/1911.06708v1
• [stat.AP]Estimating adaptive cruise control model parameters from on-board radar units
Yanbing Wang, George Gunter, Matthew Nice, Daniel B. Work
http://arxiv.org/abs/1911.06454v1
• [stat.AP]Measurement Error Correction in Particle Tracking Microrheology
Yun Ling, Martin Lysy, Ian Seim, Jay M. Newby, David B. Hill, Jeremy Cribb, M. Gregory Forest
http://arxiv.org/abs/1911.06451v1
• [stat.AP]On Data Enriched Logistic Regression
Cheng Zheng, Sayan Dasgupta, Yuxiang Xie, Asad Haris, Ying Qing Chen
http://arxiv.org/abs/1911.06380v1
• [stat.ME]A nonparametric framework for inferring orders of categorical data from category-real ordered pairs
Chainarong Amornbunchornvej, Navaporn Surasvadi, Anon Plangprasopchok, Suttipong Thajchayapong
http://arxiv.org/abs/1911.06723v1
• [stat.ME]Akaike’s Bayesian information criterion (ABIC) or not ABIC for geophysical inversion
Peiliang Xu
http://arxiv.org/abs/1911.06564v1
• [stat.ME]Assessing the uncertainty in statistical evidence with the possibility of model misspecification using a non-parametric bootstrap
Mark L. Taper, Subhash R Lele, José-Miguel Ponciano, Brian Dennis
http://arxiv.org/abs/1911.06421v1
• [stat.ME]Asymptotically Exact Variational Bayes for High-Dimensional Binary Regression Models
Augusto Fasano, Daniele Durante, Giacomo Zanella
http://arxiv.org/abs/1911.06743v1
• [stat.ME]Causal inference using Bayesian non-parametric quasi-experimental design
Max Hinne, Marcel A. J. van Gerven, Luca Ambrogioni
http://arxiv.org/abs/1911.06722v1
• [stat.ME]GET: Global envelopes in R
Mari Myllymäki, Tomáš Mrkvička
http://arxiv.org/abs/1911.06583v1
• [stat.ME]How bettering the best? Answers via blending models and cluster formulations in density-based clustering
Alessandro Casa, Luca Scrucca, Giovanna Menardi
http://arxiv.org/abs/1911.06726v1
• [stat.ML]Fair Data Adaptation with Quantile Preservation
Drago Plečko, Nicolai Meinshausen
http://arxiv.org/abs/1911.06685v1
• [stat.ML]Imputing missing values with unsupervised random trees
David Cortes
http://arxiv.org/abs/1911.06646v1
• [stat.ML]Likelihood Assignment for Out-of-Distribution Inputs in Deep Generative Models is Sensitive to Prior Distribution Choice
Ryo Kamoi, Kei Kobayashi
http://arxiv.org/abs/1911.06515v1
• [stat.ML]Solving Inverse Problems by Joint Posterior Maximization with a VAE Prior
Mario González, Andrés Almansa, Mauricio Delbracio, Pablo Musé, Pauline Tan
http://arxiv.org/abs/1911.06379v1