cs.AI - 人工智能 cs.AR - 硬件体系结构 cs.CE - 计算工程、 金融和科学 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.DB - 数据库 cs.DC - 分布式、并行与集群计算 cs.DS - 数据结构与算法 cs.GR - 计算机图形学 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 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.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 hep-th - 高能物理理论 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 physics.bio-ph - 生物物理 physics.flu-dyn - 流体动力学 physics.soc-ph - 物理学与社会 q-bio.BM - 生物分子 quant-ph - 量子物理 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习

    • [cs.AI]AI solutions for drafting in Magic: the Gathering
    • [cs.AI]Action and Perception as Divergence Minimization
    • [cs.AI]Derived metrics for the game of Go — intrinsic network strength assessment and cheat-detection
    • [cs.AI]FairXGBoost: Fairness-aware Classification in XGBoost
    • [cs.AI]Fairness in the Eyes of the Data: Certifying Machine-Learning Models
    • [cs.AI]Grounded Language Learning Fast and Slow
    • [cs.AI]Learning to Infer User Hidden States for Online Sequential Advertising
    • [cs.AI]On Population-Based Algorithms for Distributed Constraint Optimization Problems
    • [cs.AI]SEDRo: A Simulated Environment for Developmental Robotics
    • [cs.AI]User Intention Recognition and Requirement Elicitation Method for Conversational AI Services
    • [cs.AR]An Ensemble Learning Approach for In-situ Monitoring of FPGA Dynamic Power
    • [cs.AR]Decision Tree Based Hardware Power Monitoring for Run Time Dynamic Power Management in FPGA
    • [cs.CE]Accelerating engineering design by automatic selection of simulation cases through Pool-Based Active Learning
    • [cs.CL]A Practical Chinese Dependency Parser Based on A Large-scale Dataset
    • [cs.CL]A Python Library for Exploratory Data Analysis and Knowledge Discovery on Twitter Data
    • [cs.CL]A Simple Global Neural Discourse Parser
    • [cs.CL]Biomedical named entity recognition using BERT in the machine reading comprehension framework
    • [cs.CL]Comparative Evaluation of Pretrained Transfer Learning Models on Automatic Short Answer Grading
    • [cs.CL]Learning to summarize from human feedback
    • [cs.CL]SRQA: Synthetic Reader for Factoid Question Answering
    • [cs.CL]The ADAPT Enhanced Dependency Parser at the IWPT 2020 Shared Task
    • [cs.CL]Too good to be true? Predicting author profiles from abusive language
    • [cs.CL]orgFAQ: A New Dataset and Analysis on Organizational FAQs and User Questions
    • [cs.CV]1st Place Solution of LVIS Challenge 2020: A Good Box is not a Guarantee of a Good Mask
    • [cs.CV]A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports
    • [cs.CV]Adherent Mist and Raindrop Removal from a Single Image Using Attentive Convolutional Network
    • [cs.CV]Auto-Classifier: A Robust Defect Detector Based on an AutoML Head
    • [cs.CV]Computational Analysis of Deformable Manifolds: from Geometric Modelling to Deep Learning
    • [cs.CV]DESC: Domain Adaptation for Depth Estimation via Semantic Consistency
    • [cs.CV]Efficiency in Real-time Webcam Gaze Tracking
    • [cs.CV]Few-shot Object Detection with Feature Attention Highlight Module in Remote Sensing Images
    • [cs.CV]Flow-edge Guided Video Completion
    • [cs.CV]Layer-specific Optimization for Mixed Data Flow with Mixed Precision in FPGA Design for CNN-based Object Detectors
    • [cs.CV]MIPGAN — Generating Robust and High QualityMorph Attacks Using Identity Prior Driven GAN
    • [cs.CV]Modeling Global Body Configurations in American Sign Language
    • [cs.CV]Modification method for single-stage object detectors that allows to exploit the temporal behaviour of a scene to improve detection accuracy
    • [cs.CV]Multi-Loss Weighting with Coefficient of Variations
    • [cs.CV]NITES: A Non-Parametric Interpretable Texture Synthesis Method
    • [cs.CV]Noise-Aware Texture-Preserving Low-Light Enhancement
    • [cs.CV]Physics-based Shading Reconstruction for Intrinsic Image Decomposition
    • [cs.CV]Ref-NMS: Breaking Proposal Bottlenecks in Two-Stage Referring Expression Grounding
    • [cs.CV]Robust Object Classification Approach using Spherical Harmonics
    • [cs.CV]SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation
    • [cs.CV]Spatial Transformer Point Convolution
    • [cs.CV]Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild
    • [cs.CV]TRACE: Transform Aggregate and Compose Visiolinguistic Representations for Image Search with Text Feedback
    • [cs.CV]Tasks Integrated Networks: Joint Detection and Retrieval for Image Search
    • [cs.CV]Towards Practical Implementations of Person Re-Identification from Full Video Frames
    • [cs.CV]Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation
    • [cs.CV]Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)
    • [cs.CY]A Theoretical Approach for a Novel Model to Realizing Empathy
    • [cs.CY]COVID-19: The Information Warfare Paradigm Shift
    • [cs.CY]Deep Learning in Science
    • [cs.CY]Gender Stereotype Reinforcement: Measuring the Gender Bias Conveyed by Ranking Algorithms
    • [cs.CY]Indoor Localization Techniques Within a Home Monitoring Platform
    • [cs.CY]Reading In-Between the Lines: An Analysis of Dissenter
    • [cs.CY]Unique Exams: Designing assessments for integrity and fairness
    • [cs.DB]HyperBench: A Benchmark and Tool for Hypergraphs and Empirical Findings
    • [cs.DC]Fast Byzantine Gathering with Visibility in Graphs
    • [cs.DC]Software-Distributed Shared Memory for Heterogeneous Machines: Design and Use Considerations
    • [cs.DS]Physarum Multi-Commodity Flow Dynamics
    • [cs.DS]Zuckerli: A New Compressed Representation for Graphs
    • [cs.GR]TAP-Net: Transport-and-Pack using Reinforcement Learning
    • [cs.GR]TopoMap: A 0-dimensional Homology Preserving Projection of High-Dimensional Data
    • [cs.GT]Bid Shading in The Brave New World of First-Price Auctions
    • [cs.HC]Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems
    • [cs.IR]Comparing Fair Ranking Metrics
    • [cs.IR]Exploring Artist Gender Bias in Music Recommendation
    • [cs.IT]A Design Framework for Epsilon-Private Data Disclosure
    • [cs.IT]Algebraic geometry codes and some applications
    • [cs.IT]Embedded Blockchains: A Synthesis of Blockchains, Spread Spectrum Watermarking, Perceptual Hashing & Digital Signatures
    • [cs.IT]On the Size of the Giant Component in Inhomogeneous Random K-out Graphs
    • [cs.IT]Optimal Streaming of 360 VR Videos with Perfect, Imperfect and Unknown FoV Viewing Probabilities
    • [cs.IT]Optimal Wireless Streaming of Multi-Quality 360 VR Video by Exploiting Natural, Relative Smoothness-enabled and Transcoding-enabled Multicast Opportunities
    • [cs.IT]Private Weighted Random Walk Stochastic Gradient Descent
    • [cs.IT]Remote Joint Strong Coordination and Reliable Communication
    • [cs.IT]Secure Strong Coordination
    • [cs.IT]Service Rate Region: A New Aspect of Coded Distributed System Design
    • [cs.IT]Smart Meter Data Privacy
    • [cs.LG]A Heaviside Function Approximation for Neural Network Binary Classification
    • [cs.LG]A Partial Regularization Method for Network Compression
    • [cs.LG]A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
    • [cs.LG]Algebraic Neural Networks: Stability Properties
    • [cs.LG]All Data Inclusive, Deep Learning Models to Predict Critical Events in the Medical Information Mart for Intensive Care III Database (MIMIC III)
    • [cs.LG]An Internal Cluster Validity Index Based on Distance-based Separability Measure
    • [cs.LG]Bounded Risk-Sensitive Markov Game and Its Inverse Reward Learning Problem
    • [cs.LG]CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning
    • [cs.LG]Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark
    • [cs.LG]Change Point Detection by Cross-Entropy Maximization
    • [cs.LG]Data Programming by Demonstration: A Framework for Interactively Learning Labeling Functions
    • [cs.LG]Error estimate for a universal function approximator of ReLU network with a local connection
    • [cs.LG]Explainable Empirical Risk Minimization
    • [cs.LG]FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information
    • [cs.LG]It’s Hard for Neural Networks To Learn the Game of Life
    • [cs.LG]Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints
    • [cs.LG]MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
    • [cs.LG]Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning
    • [cs.LG]Penalty and Augmented Lagrangian Methods for Layer-parallel Training of Residual Networks
    • [cs.LG]Physics-Consistent Data-driven Waveform Inversion with Adaptive Data Augmentation
    • [cs.LG]Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs
    • [cs.LG]Robust, Accurate Stochastic Optimization for Variational Inference
    • [cs.LG]Sample-Efficient Automated Deep Reinforcement Learning
    • [cs.LG]Select-ProtoNet: Learning to Select for Few-Shot Disease Subtype Prediction
    • [cs.LG]Towards Efficient and Scalable Acceleration of Online Decision Tree Learning on FPGA
    • [cs.LG]Understanding the wiring evolution in differentiable neural architecture search
    • [cs.LG]Yet Meta Learning Can Adapt Fast, It Can Also Break Easily
    • [cs.MA]DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control
    • [cs.MA]Quasi-synchronization of bounded confidence opinion dynamics with stochastic asynchronous rule
    • [cs.NE]End-to-End Learning of Neuromorphic Wireless Systems for Low-Power Edge Artificial Intelligence
    • [cs.NE]Multidisciplinary Design Optimization of Reusable Launch Vehicles for Different Propellants and Objectives
    • [cs.NE]Sparse Meta Networks for Sequential Adaptation and its Application to Adaptive Language Modelling
    • [cs.NE]Tree Neural Networks in HOL4
    • [cs.NI]Cost-aware Feature Selection for IoT Device Classification
    • [cs.NI]Local Fast Rerouting with Low Congestion: A Randomized Approach
    • [cs.RO]Detection-Aware Trajectory Generation for a Drone Cinematographer
    • [cs.RO]Dexterous Robotic Grasping with Object-Centric Visual Affordances
    • [cs.RO]Evaluation of a Skill-based Control Architecture for a Visual Inspection-oriented Aerial Platform
    • [cs.RO]Proposed Efficient Design for Unmanned Surface Vehicles
    • [cs.RO]Secure Encoded Instruction Graphs for End-to-End Data Validation in Autonomous Robots
    • [cs.SE]Automated identification of metamorphic test scenarios for an ocean-modeling application
    • [cs.SE]P6: A Declarative Language for Integrating Machine Learning in Visual Analytics
    • [cs.SE]Smoke Testing for Machine Learning: Simple Tests to Discover Severe Defects
    • [cs.SI]How Twitter affects the perception of public opinion: Two case studies
    • [cs.SI]Internal migration and mobile communication patterns among pairs with strong ties
    • [cs.SI]Online Community Detection for Event Streams on Networks
    • [econ.EM]A Robust Score-Driven Filter for Multivariate Time Series
    • [eess.AS]Convolutional Speech Recognition with Pitch and Voice Quality Features
    • [eess.AS]Detecting Parkinson’s Disease from Speech-task in an accessible and interpretable manner
    • [eess.AS]HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis
    • [eess.AS]Knowing What to Listen to: Early Attention for Deep Speech Representation Learning
    • [eess.IV]CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking
    • [eess.IV]Fundus Image Analysis for Age Related Macular Degeneration: ADAM-2020 Challenge Report
    • [eess.IV]Heightmap Reconstruction of Macula on Color Fundus Images Using Conditional Generative Adversarial Networks
    • [eess.IV]Limited View Tomographic Reconstruction Using a Deep Recurrent Framework with Residual Dense Spatial-Channel Attention Network and Sinogram Consistency
    • [eess.IV]Multimodal brain tumor classification
    • [eess.IV]Real Image Super Resolution Via Heterogeneous Model using GP-NAS
    • [eess.IV]When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method
    • [eess.SP]Deep Learning Based Antenna Selection for Channel Extrapolation in FDD Massive MIMO
    • [eess.SP]Deep Learning Optimized Sparse Antenna Activation for Reconfigurable Intelligent Surface Assisted Communication
    • [hep-th]Quantum stabilizer codes, lattices, and CFTs
    • [math.NA]Kernel Interpolation of High Dimensional Scattered Data
    • [math.OC]Distributed Online Optimization via Gradient Tracking with Adaptive Momentum
    • [math.OC]Heterogeneous Explore-Exploit Strategies on Multi-Star Networks
    • [math.ST]Inaccuracy measures for concomitants of GOS in Morgenstern family
    • [physics.bio-ph]Computational prediction of RNA tertiary structures using machine learning methods
    • [physics.flu-dyn]Transfer learning for nonlinear dynamics and its application to fluid turbulence
    • [physics.soc-ph]Adaptive Reinforcement Learning Model for Simulation of Urban Mobility during Crises
    • [q-bio.BM]Learning from Protein Structure with Geometric Vector Perceptrons
    • [quant-ph]Quantum Discriminator for Binary Classification
    • [quant-ph]Quantum Long Short-Term Memory
    • [stat.CO]Globally-centered autocovariances in MCMC
    • [stat.ME]A Hierarchical Meta-Analysis for Settings Involving Multiple Outcomes across Multiple Cohorts
    • [stat.ME]Adaptive Randomization in Network Data
    • [stat.ME]Fisher transformation based Confidence Intervals of Correlations in Fixed- and Random-Effects Meta-Analysis
    • [stat.ME]Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression
    • [stat.ME]Spectral estimation for spatial point patterns
    • [stat.ME]Statistical Inference for distributions with one Poisson conditional
    • [stat.ME]Statistical characterization and time-series modeling of seismic noise
    • [stat.ME]The sceptical Bayes factor for the assessment of replication success
    • [stat.ME]Unfolding-Model-Based Visualization: Theory, Method and Applications
    • [stat.ML]Bayesian Perceptron: Towards fully Bayesian Neural Networks
    • [stat.ML]Clustering of Nonnegative Data and an Application to Matrix Completion
    • [stat.ML]Large Dimensional Analysis and Improvement of Multi Task Learning
    • [stat.ML]Non-parametric generalized linear model
    • [stat.ML]On the study of the Beran estimator for generalized censoring indicators
    • [stat.ML]Quasi-symplectic Langevin Variational Autoencoder
    • [stat.ML]Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings
    • [stat.ML]Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools

    ·····································

    • [cs.AI]AI solutions for drafting in Magic: the Gathering
    Henry N. Ward, Daniel J. Brooks, Dan Troha, Bobby Mills, Arseny S. Khakhalin
    http://arxiv.org/abs/2009.00655v2

    • [cs.AI]Action and Perception as Divergence Minimization
    Danijar Hafner, Pedro A. Ortega, Jimmy Ba, Thomas Parr, Karl Friston, Nicolas Heess
    http://arxiv.org/abs/2009.01791v1

    • [cs.AI]Derived metrics for the game of Go — intrinsic network strength assessment and cheat-detection
    Attila Egri-Nagy, Antti Törmänen
    http://arxiv.org/abs/2009.01606v1

    • [cs.AI]FairXGBoost: Fairness-aware Classification in XGBoost
    Srinivasan Ravichandran, Drona Khurana, Bharath Venkatesh, Narayanan Unny Edakunni
    http://arxiv.org/abs/2009.01442v1

    • [cs.AI]Fairness in the Eyes of the Data: Certifying Machine-Learning Models
    Shahar Segal, Yossi Adi, Benny Pinkas, Carsten Baum, Chaya Ganesh, Joseph Keshet
    http://arxiv.org/abs/2009.01534v1

    • [cs.AI]Grounded Language Learning Fast and Slow
    Felix Hill, Olivier Tieleman, Tamara von Glehn, Nathaniel Wong, Hamza Merzic, Stephen Clark
    http://arxiv.org/abs/2009.01719v1

    • [cs.AI]Learning to Infer User Hidden States for Online Sequential Advertising
    Zhaoqing Peng, Junqi Jin, Lan Luo, Yaodong Yang, Rui Luo, Jun Wang, Weinan Zhang, Haiyang Xu, Miao Xu, Chuan Yu, Tiejian Luo, Han Li, Jian Xu, Kun Gai
    http://arxiv.org/abs/2009.01453v1

    • [cs.AI]On Population-Based Algorithms for Distributed Constraint Optimization Problems
    Saaduddin Mahmud, Md. Mosaddek Khan, Nicholas R. Jennings
    http://arxiv.org/abs/2009.01625v1

    • [cs.AI]SEDRo: A Simulated Environment for Developmental Robotics
    Aishwarya Pothula, Md Ashaduzzaman Rubel Mondol, Sanath Narasimhan, Sm Mazharul Islam, Deokgun Park
    http://arxiv.org/abs/2009.01810v1

    • [cs.AI]User Intention Recognition and Requirement Elicitation Method for Conversational AI Services
    Junrui Tian, Zhiying Tu, Zhongjie Wang, Xiaofei Xu, Min Liu
    http://arxiv.org/abs/2009.01509v1

    • [cs.AR]An Ensemble Learning Approach for In-situ Monitoring of FPGA Dynamic Power
    Zhe Lin, Sharad Sinha, Wei Zhang
    http://arxiv.org/abs/2009.01432v1

    • [cs.AR]Decision Tree Based Hardware Power Monitoring for Run Time Dynamic Power Management in FPGA
    Zhe Lin, Wei Zhang, Sharad Sinha
    http://arxiv.org/abs/2009.01434v1

    • [cs.CE]Accelerating engineering design by automatic selection of simulation cases through Pool-Based Active Learning
    José Hugo C. Gaspar Elsas, Nicholas A. G. Casaprima, Ivan F. M. Menezes
    http://arxiv.org/abs/2009.01420v1

    • [cs.CL]A Practical Chinese Dependency Parser Based on A Large-scale Dataset
    Shuai Zhang, Lijie Wang, Ke Sun, Xinyan Xiao
    http://arxiv.org/abs/2009.00901v2

    • [cs.CL]A Python Library for Exploratory Data Analysis and Knowledge Discovery on Twitter Data
    Mario Graff, Daniela Moctezuma, Sabino Miranda-Jiménez, Eric S. Tellez
    http://arxiv.org/abs/2009.01826v1

    • [cs.CL]A Simple Global Neural Discourse Parser
    Yichu Zhou, Omri Koshorek, Vivek Srikumar, Jonathan Berant
    http://arxiv.org/abs/2009.01312v1

    • [cs.CL]Biomedical named entity recognition using BERT in the machine reading comprehension framework
    Cong Sun, Zhihao Yang, Lei Wang, Yin Zhang, Hongfei Lin, Jian Wang
    http://arxiv.org/abs/2009.01560v1

    • [cs.CL]Comparative Evaluation of Pretrained Transfer Learning Models on Automatic Short Answer Grading
    Sasi Kiran Gaddipati, Deebul Nair, Paul G. Plöger
    http://arxiv.org/abs/2009.01303v1

    • [cs.CL]Learning to summarize from human feedback
    Nisan Stiennon, Long Ouyang, Jeff Wu, Daniel M. Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, Paul Christiano
    http://arxiv.org/abs/2009.01325v1

    • [cs.CL]SRQA: Synthetic Reader for Factoid Question Answering
    Jiuniu Wang, Wenjia Xu, Xingyu Fu, Yang Wei, Li Jin, Ziyan Chen, Guangluan Xu, Yirong Wu
    http://arxiv.org/abs/2009.01630v1

    • [cs.CL]The ADAPT Enhanced Dependency Parser at the IWPT 2020 Shared Task
    James Barry, Joachim Wagner, Jennifer Foster
    http://arxiv.org/abs/2009.01712v1

    • [cs.CL]Too good to be true? Predicting author profiles from abusive language
    Isabelle van der Vegt, Bennett Kleinberg, Paul Gill
    http://arxiv.org/abs/2009.01126v2

    • [cs.CL]orgFAQ: A New Dataset and Analysis on Organizational FAQs and User Questions
    Guy Lev, Michal Shmueli-Scheuer, Achiya Jerbi, David Konopnicki
    http://arxiv.org/abs/2009.01460v1

    • [cs.CV]1st Place Solution of LVIS Challenge 2020: A Good Box is not a Guarantee of a Good Mask
    Jingru Tan, Gang Zhang, Hanming Deng, Changbao Wang, Lewei Lu, Quanquan Li, Jifeng Dai
    http://arxiv.org/abs/2009.01559v1

    • [cs.CV]A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports
    Yikuan Li, Hanyin Wang, Yuan Luo
    http://arxiv.org/abs/2009.01523v1

    • [cs.CV]Adherent Mist and Raindrop Removal from a Single Image Using Attentive Convolutional Network
    Da He, Xiaoyu Shang, Jiajia Luo
    http://arxiv.org/abs/2009.01466v1

    • [cs.CV]Auto-Classifier: A Robust Defect Detector Based on an AutoML Head
    Vasco Lopes, Luís A. Alexandre
    http://arxiv.org/abs/2009.01573v1

    • [cs.CV]Computational Analysis of Deformable Manifolds: from Geometric Modelling to Deep Learning
    Stefan C Schonsheck
    http://arxiv.org/abs/2009.01786v1

    • [cs.CV]DESC: Domain Adaptation for Depth Estimation via Semantic Consistency
    Adrian Lopez-Rodriguez, Krystian Mikolajczyk
    http://arxiv.org/abs/2009.01579v1

    • [cs.CV]Efficiency in Real-time Webcam Gaze Tracking
    Amogh Gudi, Xin Li, Jan van Gemert
    http://arxiv.org/abs/2009.01270v1

    • [cs.CV]Few-shot Object Detection with Feature Attention Highlight Module in Remote Sensing Images
    Zixuan Xiao, Ping Zhong, Yuan Quan, Xuping Yin, Wei Xue
    http://arxiv.org/abs/2009.01616v1

    • [cs.CV]Flow-edge Guided Video Completion
    Chen Gao, Ayush Saraf, Jia-Bin Huang, Johannes Kopf
    http://arxiv.org/abs/2009.01835v1

    • [cs.CV]Layer-specific Optimization for Mixed Data Flow with Mixed Precision in FPGA Design for CNN-based Object Detectors
    Duy Thanh Nguyen, Hyun Kim, Hyuk-Jae Lee
    http://arxiv.org/abs/2009.01588v1

    • [cs.CV]MIPGAN — Generating Robust and High QualityMorph Attacks Using Identity Prior Driven GAN
    Haoyu Zhang, Sushma Venkatesh, Raghavendra Ramachandra, Kiran Raja, Naser Damer, Christoph Busch
    http://arxiv.org/abs/2009.01729v1

    • [cs.CV]Modeling Global Body Configurations in American Sign Language
    Nicholas Wilkins, Beck Cordes Galbraith, Ifeoma Nwogu
    http://arxiv.org/abs/2009.01468v1

    • [cs.CV]Modification method for single-stage object detectors that allows to exploit the temporal behaviour of a scene to improve detection accuracy
    Menua Gevorgyan
    http://arxiv.org/abs/2009.01617v1

    • [cs.CV]Multi-Loss Weighting with Coefficient of Variations
    Rick Groenendijk, Sezer Karaoglu, Theo Gevers, Thomas Mensink
    http://arxiv.org/abs/2009.01717v1

    • [cs.CV]NITES: A Non-Parametric Interpretable Texture Synthesis Method
    Xuejing Lei, Ganning Zhao, C. -C. Jay Kuo
    http://arxiv.org/abs/2009.01376v1

    • [cs.CV]Noise-Aware Texture-Preserving Low-Light Enhancement
    Zohreh Azizi, Xuejing Lei, C. -C Jay Kuo
    http://arxiv.org/abs/2009.01385v1

    • [cs.CV]Physics-based Shading Reconstruction for Intrinsic Image Decomposition
    Anil S. Baslamisli, Yang Liu, Sezer Karaoglu, Theo Gevers
    http://arxiv.org/abs/2009.01540v1

    • [cs.CV]Ref-NMS: Breaking Proposal Bottlenecks in Two-Stage Referring Expression Grounding
    Long Chen, Wenbo Ma, Jun Xiao, Hanwang Zhang, Wei Liu, Shih-Fu Chang
    http://arxiv.org/abs/2009.01449v1

    • [cs.CV]Robust Object Classification Approach using Spherical Harmonics
    Ayman Mukhaimar, Ruwan Tennakoon, Chow Yin Lai, Reza Hoseinnezhad, Alireza Bab-Hadiashar
    http://arxiv.org/abs/2009.01369v1

    • [cs.CV]SCG-Net: Self-Constructing Graph Neural Networks for Semantic Segmentation
    Qinghui Liu, Michael Kampffmeyer, Robert Jenssen, Arnt-Børre Salberg
    http://arxiv.org/abs/2009.01599v1

    • [cs.CV]Spatial Transformer Point Convolution
    Yuan Fang, Chunyan Xu, Zhen Cui, Yuan Zong, Jian Yang
    http://arxiv.org/abs/2009.01427v1

    • [cs.CV]Synthetic-to-Real Unsupervised Domain Adaptation for Scene Text Detection in the Wild
    Weijia Wu, Ning Lu, Enze Xie
    http://arxiv.org/abs/2009.01766v1

    • [cs.CV]TRACE: Transform Aggregate and Compose Visiolinguistic Representations for Image Search with Text Feedback
    Surgan Jandial, Ayush Chopra, Pinkesh Badjatiya, Pranit Chawla, Mausoom Sarkar, Balaji Krishnamurthy
    http://arxiv.org/abs/2009.01485v1

    • [cs.CV]Tasks Integrated Networks: Joint Detection and Retrieval for Image Search
    Lei Zhang, Zhenwei He, Yi Yang, Liang Wang, Xinbo Gao
    http://arxiv.org/abs/2009.01438v1

    • [cs.CV]Towards Practical Implementations of Person Re-Identification from Full Video Frames
    Felix O. Sumari, Luigy Machaca, Jose Huaman, Esteban W. G. Clua, Joris Guérin
    http://arxiv.org/abs/2009.01377v1

    • [cs.CV]Unsupervised Feedforward Feature (UFF) Learning for Point Cloud Classification and Segmentation
    Min Zhang, Pranav Kadam, Shan Liu, C. -C. Jay Kuo
    http://arxiv.org/abs/2009.01280v1

    • [cs.CV]Unsupervised Point Cloud Registration via Salient Points Analysis (SPA)
    Pranav Kadam, Min Zhang, Shan Liu, C. -C. Jay Kuo
    http://arxiv.org/abs/2009.01293v1

    • [cs.CY]A Theoretical Approach for a Novel Model to Realizing Empathy
    Marialejandra Garcia Corretjer, David Miralles, Raquel Ros
    http://arxiv.org/abs/2009.01229v1

    • [cs.CY]COVID-19: The Information Warfare Paradigm Shift
    Jan Kallberg, Rosemary A. Burk, Bhavani Thuraisingham
    http://arxiv.org/abs/2009.01267v1

    • [cs.CY]Deep Learning in Science
    Stefano Bianchini, Moritz Müller, Pierre Pelletier
    http://arxiv.org/abs/2009.01575v1

    • [cs.CY]Gender Stereotype Reinforcement: Measuring the Gender Bias Conveyed by Ranking Algorithms
    Alessandro Fabris, Alberto Purpura, Gianmaria Silvello, Gian Antonio Susto
    http://arxiv.org/abs/2009.01334v1

    • [cs.CY]Indoor Localization Techniques Within a Home Monitoring Platform
    Iuliana Marin, Maria-Iuliana Bocicor, Arthur-Jozsef Molnar
    http://arxiv.org/abs/2009.01654v1

    • [cs.CY]Reading In-Between the Lines: An Analysis of Dissenter
    Erik Rye, Jeremy Blackburn, Robert Beverly
    http://arxiv.org/abs/2009.01772v1

    • [cs.CY]Unique Exams: Designing assessments for integrity and fairness
    Gili Rusak, Lisa Yan
    http://arxiv.org/abs/2009.01713v1

    • [cs.DB]HyperBench: A Benchmark and Tool for Hypergraphs and Empirical Findings
    Wolfgang Fischl, Georg Gottlob, Davide Mario Longo, Reinhard Pichler
    http://arxiv.org/abs/2009.01769v1

    • [cs.DC]Fast Byzantine Gathering with Visibility in Graphs
    Avery Miller, Ullash Saha
    http://arxiv.org/abs/2009.01544v1

    • [cs.DC]Software-Distributed Shared Memory for Heterogeneous Machines: Design and Use Considerations
    Loïc Cudennec
    http://arxiv.org/abs/2009.01507v1

    • [cs.DS]Physarum Multi-Commodity Flow Dynamics
    Vincenzo Bonifaci, Enrico Facca, Frederic Folz, Andreas Karrenbauer, Pavel Kolev, Kurt Mehlhorn, Giovanna Morigi, Golnoosh Shahkarami, Quentin Vermande
    http://arxiv.org/abs/2009.01498v1

    • [cs.DS]Zuckerli: A New Compressed Representation for Graphs
    Luca Versari, Iulia M. Comsa, Alessio Conte, Roberto Grossi
    http://arxiv.org/abs/2009.01353v1

    • [cs.GR]TAP-Net: Transport-and-Pack using Reinforcement Learning
    Ruizhen Hu, Juzhan Xu, Bin Chen, Minglun Gong, Hao Zhang, Hui Huang
    http://arxiv.org/abs/2009.01469v1

    • [cs.GR]TopoMap: A 0-dimensional Homology Preserving Projection of High-Dimensional Data
    Harish Doraiswamy, Julien Tierny, Paulo J. S. Silva, Luis Gustavo Nonato, Claudio Silva
    http://arxiv.org/abs/2009.01512v1

    • [cs.GT]Bid Shading in The Brave New World of First-Price Auctions
    Djordje Gligorijevic, Tian Zhou, Bharatbhushan Shetty, Brendan Kitts, Shengjun Pan, Junwei Pan, Aaron Flores
    http://arxiv.org/abs/2009.01360v1

    • [cs.HC]Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems
    Jeremy E. Block, Eric D. Ragan
    http://arxiv.org/abs/2009.01282v1

    • [cs.IR]Comparing Fair Ranking Metrics
    Amifa Raj, Connor Wood, Ananda Montoly, Michael D. Ekstrand
    http://arxiv.org/abs/2009.01311v1

    • [cs.IR]Exploring Artist Gender Bias in Music Recommendation
    Dougal Shakespeare, Lorenzo Porcaro, Emilia Gómez, Carlos Castillo
    http://arxiv.org/abs/2009.01715v1

    • [cs.IT]A Design Framework for Epsilon-Private Data Disclosure
    Amirreza Zamani, Tobias J. Oechtering, Mikael Skoglund
    http://arxiv.org/abs/2009.01704v1

    • [cs.IT]Algebraic geometry codes and some applications
    Alain Couvreur, Hugues Randriambololona
    http://arxiv.org/abs/2009.01281v1

    • [cs.IT]Embedded Blockchains: A Synthesis of Blockchains, Spread Spectrum Watermarking, Perceptual Hashing & Digital Signatures
    Sam Blake
    http://arxiv.org/abs/2009.00951v2

    • [cs.IT]On the Size of the Giant Component in Inhomogeneous Random K-out Graphs
    Mansi Sood, Osman Yagan
    http://arxiv.org/abs/2009.01610v1

    • [cs.IT]Optimal Streaming of 360 VR Videos with Perfect, Imperfect and Unknown FoV Viewing Probabilities
    Lingzhi Zhao, Ying Cui, Chengjun Guo, Zhi Liu
    http://arxiv.org/abs/2009.01753v1

    • [cs.IT]Optimal Wireless Streaming of Multi-Quality 360 VR Video by Exploiting Natural, Relative Smoothness-enabled and Transcoding-enabled Multicast Opportunities
    Kaixuan Long, Ying Cui, Chencheng Ye, Zhi Liu
    http://arxiv.org/abs/2009.01632v1

    • [cs.IT]Private Weighted Random Walk Stochastic Gradient Descent
    Ghadir Ayache, Salim El Rouayheb
    http://arxiv.org/abs/2009.01790v1

    • [cs.IT]Remote Joint Strong Coordination and Reliable Communication
    Giulia Cervia, Tobias J. Oechtering, Mikael Skoglund
    http://arxiv.org/abs/2009.01569v1

    • [cs.IT]Secure Strong Coordination
    Giulia Cervia, German Bassi, Mikael Skoglund
    http://arxiv.org/abs/2009.01572v1

    • [cs.IT]Service Rate Region: A New Aspect of Coded Distributed System Design
    Mehmet Aktas, Gauri Joshi, Swanand Kadhe, Fatemeh Kazemi, Emina Soljanin
    http://arxiv.org/abs/2009.01598v1

    • [cs.IT]Smart Meter Data Privacy
    Giulio Giaconi, Deniz Gunduz, H. Vincent Poor
    http://arxiv.org/abs/2009.01364v1

    • [cs.LG]A Heaviside Function Approximation for Neural Network Binary Classification
    Nathan Tsoi, Yofti Milkessa, Marynel Vázquez
    http://arxiv.org/abs/2009.01367v1

    • [cs.LG]A Partial Regularization Method for Network Compression
    E Zhenqian, Gao Weiguo
    http://arxiv.org/abs/2009.01395v1

    • [cs.LG]A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning
    Martin Mundt, Yong Won Hong, Iuliia Pliushch, Visvanathan Ramesh
    http://arxiv.org/abs/2009.01797v1

    • [cs.LG]Algebraic Neural Networks: Stability Properties
    Alejandro Parada-Mayorga, Alejandro Ribeiro
    http://arxiv.org/abs/2009.01433v1

    • [cs.LG]All Data Inclusive, Deep Learning Models to Predict Critical Events in the Medical Information Mart for Intensive Care III Database (MIMIC III)
    Anubhav Reddy Nallabasannagari, Madhu Reddiboina, Ryan Seltzer, Trevor Zeffiro, Ajay Sharma, Mahendra Bhandari
    http://arxiv.org/abs/2009.01366v1

    • [cs.LG]An Internal Cluster Validity Index Based on Distance-based Separability Measure
    Shuyue Guan, Murray Loew
    http://arxiv.org/abs/2009.01328v1

    • [cs.LG]Bounded Risk-Sensitive Markov Game and Its Inverse Reward Learning Problem
    Ran Tian, Liting Sun, Masayoshi Tomizuka
    http://arxiv.org/abs/2009.01495v1

    • [cs.LG]CAGNN: Cluster-Aware Graph Neural Networks for Unsupervised Graph Representation Learning
    Yanqiao Zhu, Yichen Xu, Feng Yu, Shu Wu, Liang Wang
    http://arxiv.org/abs/2009.01674v1

    • [cs.LG]Can AutoML outperform humans? An evaluation on popular OpenML datasets using AutoML Benchmark
    Marc Hanussek, Matthias Blohm, Maximilien Kintz
    http://arxiv.org/abs/2009.01564v1

    • [cs.LG]Change Point Detection by Cross-Entropy Maximization
    Aurélien Serre, Didier Chételat, Andrea Lodi
    http://arxiv.org/abs/2009.01358v1

    • [cs.LG]Data Programming by Demonstration: A Framework for Interactively Learning Labeling Functions
    Sara Evensen, Chang Ge, Dongjin Choi, Çağatay Demiralp
    http://arxiv.org/abs/2009.01444v1

    • [cs.LG]Error estimate for a universal function approximator of ReLU network with a local connection
    Jae-Mo Kang, Sunghwan Moon
    http://arxiv.org/abs/2009.01461v1

    • [cs.LG]Explainable Empirical Risk Minimization
    A. Jung
    http://arxiv.org/abs/2009.01492v1

    • [cs.LG]FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information
    Enyan Dai, Suhang Wang
    http://arxiv.org/abs/2009.01454v1

    • [cs.LG]It’s Hard for Neural Networks To Learn the Game of Life
    Jacob M. Springer, Garrett T. Kenyon
    http://arxiv.org/abs/2009.01398v1

    • [cs.LG]Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints
    Syrine Belakaria, Aryan Deshwal, Janardhan Rao Doppa
    http://arxiv.org/abs/2009.01721v1

    • [cs.LG]MixBoost: Synthetic Oversampling with Boosted Mixup for Handling Extreme Imbalance
    Anubha Kabra, Ayush Chopra, Nikaash Puri, Pinkesh Badjatiya, Sukriti Verma, Piyush Gupta, Balaji K
    http://arxiv.org/abs/2009.01571v1

    • [cs.LG]Optimality-based Analysis of XCSF Compaction in Discrete Reinforcement Learning
    Jordan T. Bishop, Marcus Gallagher
    http://arxiv.org/abs/2009.01476v1

    • [cs.LG]Penalty and Augmented Lagrangian Methods for Layer-parallel Training of Residual Networks
    Qi Sun, Hexing Dong, Zewei Chen, Weizhen Dian, Jiacheng Sun, Yitong Sun, Zhenguo Li, Bin Dong
    http://arxiv.org/abs/2009.01462v1

    • [cs.LG]Physics-Consistent Data-driven Waveform Inversion with Adaptive Data Augmentation
    Renán Rojas-Gómez, Jihyun Yang, Youzuo Lin, James Theiler, Brendt Wohlberg
    http://arxiv.org/abs/2009.01807v1

    • [cs.LG]Process Mining Meets Causal Machine Learning: Discovering Causal Rules from Event Logs
    Zahra Dasht Bozorgi, Irene Teinemaa, Marlon Dumas, Marcello La Rosa, Artem Polyvyanyy
    http://arxiv.org/abs/2009.01561v1

    • [cs.LG]Robust, Accurate Stochastic Optimization for Variational Inference
    Akash Kumar Dhaka, Alejandro Catalina, Michael Riis Andersen, Måns Magnusson, Jonathan H. Huggins, Aki Vehtari
    http://arxiv.org/abs/2009.00666v2

    • [cs.LG]Sample-Efficient Automated Deep Reinforcement Learning
    Jörg K. H. Franke, Gregor Köhler, André Biedenkapp, Frank Hutter
    http://arxiv.org/abs/2009.01555v1

    • [cs.LG]Select-ProtoNet: Learning to Select for Few-Shot Disease Subtype Prediction
    Ziyi Yang, Jun Shu, Yong Liang, Deyu Meng, Zongben Xu
    http://arxiv.org/abs/2009.00792v2

    • [cs.LG]Towards Efficient and Scalable Acceleration of Online Decision Tree Learning on FPGA
    Zhe Lin, Sharad Sinha, Wei Zhang
    http://arxiv.org/abs/2009.01431v1

    • [cs.LG]Understanding the wiring evolution in differentiable neural architecture search
    Sirui Xie, Shoukang Hu, Xinjiang Wang, Chunxiao Liu, Jianping Shi, Xunying Liu, Dahua Lin
    http://arxiv.org/abs/2009.01272v1

    • [cs.LG]Yet Meta Learning Can Adapt Fast, It Can Also Break Easily
    Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu, Jiliang Tang
    http://arxiv.org/abs/2009.01672v1

    • [cs.MA]DRLE: Decentralized Reinforcement Learning at the Edge for Traffic Light Control
    Pengyuan Zhou, Xianfu Chen, Zhi Liu, Tristan Braud, Pan Hui, Jussi Kangasharju
    http://arxiv.org/abs/2009.01502v1

    • [cs.MA]Quasi-synchronization of bounded confidence opinion dynamics with stochastic asynchronous rule
    Wei Su, Xueqiao Wang, Ge Chen, Kai Shen
    http://arxiv.org/abs/2009.01455v1

    • [cs.NE]End-to-End Learning of Neuromorphic Wireless Systems for Low-Power Edge Artificial Intelligence
    Nicolas Skatchkovsky, Hyeryung Jang, Osvaldo Simeone
    http://arxiv.org/abs/2009.01527v1

    • [cs.NE]Multidisciplinary Design Optimization of Reusable Launch Vehicles for Different Propellants and Objectives
    Kai Dresia, Simon Jentzsch, Günther Waxenegger-Wilfing, Robson Hahn, Jan Deeken, Michael Oschwald, Fabio Mota
    http://arxiv.org/abs/2009.01664v1

    • [cs.NE]Sparse Meta Networks for Sequential Adaptation and its Application to Adaptive Language Modelling
    Tsendsuren Munkhdalai
    http://arxiv.org/abs/2009.01803v1

    • [cs.NE]Tree Neural Networks in HOL4
    Thibault Gauthier
    http://arxiv.org/abs/2009.01827v1

    • [cs.NI]Cost-aware Feature Selection for IoT Device Classification
    Biswadeep Chakraborty, Dinil Mon Divakaran, Ido Nevat, Gareth W. Peters, Mohan Gurusamy
    http://arxiv.org/abs/2009.01368v1

    • [cs.NI]Local Fast Rerouting with Low Congestion: A Randomized Approach
    Gregor Bankhamer, Robert Elsässer, Stefan Schmid
    http://arxiv.org/abs/2009.01497v1

    • [cs.RO]Detection-Aware Trajectory Generation for a Drone Cinematographer
    Boseong Felipe Jeon, Dongseok Shim, H. Jin Kim
    http://arxiv.org/abs/2009.01565v1

    • [cs.RO]Dexterous Robotic Grasping with Object-Centric Visual Affordances
    Priyanka Mandikal, Kristen Grauman
    http://arxiv.org/abs/2009.01439v1

    • [cs.RO]Evaluation of a Skill-based Control Architecture for a Visual Inspection-oriented Aerial Platform
    Emilio Garcia-Fidalgo, Francisco Bonnin-Pascual, Joan P. Company-Corcoles, Alberto Ortiz
    http://arxiv.org/abs/2009.01612v1

    • [cs.RO]Proposed Efficient Design for Unmanned Surface Vehicles
    Pouyan Asgharian, Zati Hakim Azizul
    http://arxiv.org/abs/2009.01284v1

    • [cs.RO]Secure Encoded Instruction Graphs for End-to-End Data Validation in Autonomous Robots
    Jorge Peña Queralta, Li Qingqing, Eduardo Castelló Ferrer, Tomi Westerlund
    http://arxiv.org/abs/2009.01341v1

    • [cs.SE]Automated identification of metamorphic test scenarios for an ocean-modeling application
    Dilip J. Hiremath, Martin Claus, Wilhelm Hasselbring, Willi Rath
    http://arxiv.org/abs/2009.01554v1

    • [cs.SE]P6: A Declarative Language for Integrating Machine Learning in Visual Analytics
    Jianping Kelvin Li, Kwan-Liu Ma
    http://arxiv.org/abs/2009.01399v1

    • [cs.SE]Smoke Testing for Machine Learning: Simple Tests to Discover Severe Defects
    Steffen Herbold, Tobias Haar
    http://arxiv.org/abs/2009.01521v1

    • [cs.SI]How Twitter affects the perception of public opinion: Two case studies
    Felix Gaisbauer, Armin Pournaki, Sven Banisch, Eckehard Olbrich
    http://arxiv.org/abs/2009.01666v1

    • [cs.SI]Internal migration and mobile communication patterns among pairs with strong ties
    Mikaela Irene D. Fudolig, Daniel Monsivais, Kunal Bhattacharya, Hang-Hyun Jo, Kimmo Kaski
    http://arxiv.org/abs/2009.00252v2

    • [cs.SI]Online Community Detection for Event Streams on Networks
    Guanhua Fang, Owen G. Ward, Tian Zheng
    http://arxiv.org/abs/2009.01742v1

    • [econ.EM]A Robust Score-Driven Filter for Multivariate Time Series
    Enzo D’Innocenzo, Alessandra Luati, Mario Mazzocchi
    http://arxiv.org/abs/2009.01517v1

    • [eess.AS]Convolutional Speech Recognition with Pitch and Voice Quality Features
    Guillermo Cámbara, Jordi Luque, Mireia Farrús
    http://arxiv.org/abs/2009.01309v1

    • [eess.AS]Detecting Parkinson’s Disease from Speech-task in an accessible and interpretable manner
    Wasifur Rahman, Sangwu Lee, Md. Saiful Islam, Abdullah Al Mamun, Victor Antony, Harshil Ratnu, Mohammad Rafayet Ali, Ehsan Hoque
    http://arxiv.org/abs/2009.01231v1

    • [eess.AS]HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis
    Jiawei Chen, Xu Tan, Jian Luan, Tao Qin, Tie-Yan Liu
    http://arxiv.org/abs/2009.01776v1

    • [eess.AS]Knowing What to Listen to: Early Attention for Deep Speech Representation Learning
    Amirhossein Hajavi, Ali Etemad
    http://arxiv.org/abs/2009.01822v1

    • [eess.IV]CNN-Based Ultrasound Image Reconstruction for Ultrafast Displacement Tracking
    Dimitris Perdios, Manuel Vonlanthen, Florian Martinez, Marcel Arditi, Jean-Philippe Thiran
    http://arxiv.org/abs/2009.01816v1

    • [eess.IV]Fundus Image Analysis for Age Related Macular Degeneration: ADAM-2020 Challenge Report
    Sharath M Shankaranarayana
    http://arxiv.org/abs/2009.01548v1

    • [eess.IV]Heightmap Reconstruction of Macula on Color Fundus Images Using Conditional Generative Adversarial Networks
    Peyman Tahghighi, Reza A. Zoroofi, Sareh Saffi, Alireza Ramezani
    http://arxiv.org/abs/2009.01601v1

    • [eess.IV]Limited View Tomographic Reconstruction Using a Deep Recurrent Framework with Residual Dense Spatial-Channel Attention Network and Sinogram Consistency
    Bo Zhou, S. Kevin Zhou, James S. Duncan, Chi Liu
    http://arxiv.org/abs/2009.01782v1

    • [eess.IV]Multimodal brain tumor classification
    Marvin Lerousseau, Eric Deutsh, Nikos Paragios
    http://arxiv.org/abs/2009.01592v1

    • [eess.IV]Real Image Super Resolution Via Heterogeneous Model using GP-NAS
    Zhihong Pan, Baopu Li, Teng Xi, Yanwen Fan, Gang Zhang, Jingtuo Liu, Junyu Han, Errui Ding
    http://arxiv.org/abs/2009.01371v1

    • [eess.IV]When Image Decomposition Meets Deep Learning: A Novel Infrared and Visible Image Fusion Method
    Zixiang Zhao, Shuang Xu, Rui Feng, Chunxia Zhang, Junmin Liu, Jiangshe Zhang
    http://arxiv.org/abs/2009.01315v1

    • [eess.SP]Deep Learning Based Antenna Selection for Channel Extrapolation in FDD Massive MIMO
    Yindi Yang, Shun Zhang, Feifei Gao, Chao Xu, Jianpeng Ma, Octavia A. Dobre
    http://arxiv.org/abs/2009.01653v1

    • [eess.SP]Deep Learning Optimized Sparse Antenna Activation for Reconfigurable Intelligent Surface Assisted Communication
    Shunbo Zhang, Shun Zhang, Feifei Gao, Jianpeng Ma, Octavia A. Dobre
    http://arxiv.org/abs/2009.01607v1

    • [hep-th]Quantum stabilizer codes, lattices, and CFTs
    Anatoly Dymarsky, Alfred Shapere
    http://arxiv.org/abs/2009.01244v1

    • [math.NA]Kernel Interpolation of High Dimensional Scattered Data
    Shao-Bo Lin, Xiangyu Chang, Xingping Sun
    http://arxiv.org/abs/2009.01514v1

    • [math.OC]Distributed Online Optimization via Gradient Tracking with Adaptive Momentum
    Guido Carnevale, Francesco Farina, Ivano Notarnicola, Giuseppe Notarstefano
    http://arxiv.org/abs/2009.01745v1

    • [math.OC]Heterogeneous Explore-Exploit Strategies on Multi-Star Networks
    Udari Madhushani, Naomi Leonard
    http://arxiv.org/abs/2009.01339v1

    • [math.ST]Inaccuracy measures for concomitants of GOS in Morgenstern family
    S. Daneshi, A. Nezakati, S. Tahmasebi, M. Longobardi
    http://arxiv.org/abs/2009.01800v1

    • [physics.bio-ph]Computational prediction of RNA tertiary structures using machine learning methods
    Bin Huang, Yuanyang Du, Shuai Zhang, Wenfei Li, Jun Wang, Jian Zhang
    http://arxiv.org/abs/2009.01440v1

    • [physics.flu-dyn]Transfer learning for nonlinear dynamics and its application to fluid turbulence
    Masanobu Inubushi, Susumu Goto
    http://arxiv.org/abs/2009.01407v1

    • [physics.soc-ph]Adaptive Reinforcement Learning Model for Simulation of Urban Mobility during Crises
    Chao Fan, Xiangqi Jiang, Ali Mostafavi
    http://arxiv.org/abs/2009.01359v1

    • [q-bio.BM]Learning from Protein Structure with Geometric Vector Perceptrons
    Bowen Jing, Stephan Eismann, Patricia Suriana, Raphael J. L. Townshend, Ron Dror
    http://arxiv.org/abs/2009.01411v1

    • [quant-ph]Quantum Discriminator for Binary Classification
    Prasanna Date
    http://arxiv.org/abs/2009.01235v1

    • [quant-ph]Quantum Long Short-Term Memory
    Samuel Yen-Chi Chen, Shinjae Yoo, Yao-Lung L. Fang
    http://arxiv.org/abs/2009.01783v1

    • [stat.CO]Globally-centered autocovariances in MCMC
    Medha Agarwal, Dootika Vats
    http://arxiv.org/abs/2009.01799v1

    • [stat.ME]A Hierarchical Meta-Analysis for Settings Involving Multiple Outcomes across Multiple Cohorts
    Tugba Akkaya Hocagil, Louise M. Ryan, Richard J. Cook, Gale A. Richardson, Nancy L. Day, Claire D. Coles, Heather Carmichael Olson, Sandra W. Jacobson, Joseph L. Jacobson
    http://arxiv.org/abs/2009.01323v1

    • [stat.ME]Adaptive Randomization in Network Data
    Zhixin Zhou, Ping Li, Feifang Hu
    http://arxiv.org/abs/2009.01273v1

    • [stat.ME]Fisher transformation based Confidence Intervals of Correlations in Fixed- and Random-Effects Meta-Analysis
    Thilo Welz, Philipp Doebler, Markus Pauly
    http://arxiv.org/abs/2009.01522v1

    • [stat.ME]Probabilistic Forecasting for Daily Electricity Loads and Quantiles for Curve-to-Curve Regression
    Xiuqin Xu, Ying Chen, Yannig Goude, Qiwei Yao
    http://arxiv.org/abs/2009.01595v1

    • [stat.ME]Spectral estimation for spatial point patterns
    Tuomas A. Rajala, Sofia C. Olhede, David J. Murrell
    http://arxiv.org/abs/2009.01474v1

    • [stat.ME]Statistical Inference for distributions with one Poisson conditional
    Barry C. Arnold, B. G. Manjunath
    http://arxiv.org/abs/2009.01296v1

    • [stat.ME]Statistical characterization and time-series modeling of seismic noise
    Kanchan Aggarwal, Siddhartha Mukhopadhyay, Arun K Tangirala
    http://arxiv.org/abs/2009.01549v1

    • [stat.ME]The sceptical Bayes factor for the assessment of replication success
    Samuel Pawel, Leonhard Held
    http://arxiv.org/abs/2009.01520v1

    • [stat.ME]Unfolding-Model-Based Visualization: Theory, Method and Applications
    Yunxiao Chen, Zhiliang Ying, Haoran Zhang
    http://arxiv.org/abs/2009.01551v1

    • [stat.ML]Bayesian Perceptron: Towards fully Bayesian Neural Networks
    Marco F. Huber
    http://arxiv.org/abs/2009.01730v1

    • [stat.ML]Clustering of Nonnegative Data and an Application to Matrix Completion
    C. Strohmeier, D. Needell
    http://arxiv.org/abs/2009.01279v1

    • [stat.ML]Large Dimensional Analysis and Improvement of Multi Task Learning
    Malik Tiomoko, Romain Couillet, Hafiz Tiomoko
    http://arxiv.org/abs/2009.01591v1

    • [stat.ML]Non-parametric generalized linear model
    Matthew Dowling, Yuan Zhao, Il Memming Park
    http://arxiv.org/abs/2009.01362v1

    • [stat.ML]On the study of the Beran estimator for generalized censoring indicators
    Mikael Escobar-Bach, Olivier Goudet
    http://arxiv.org/abs/2009.01726v1

    • [stat.ML]Quasi-symplectic Langevin Variational Autoencoder
    Zihao Wang, Hervé Delingette
    http://arxiv.org/abs/2009.01675v1

    • [stat.ML]Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings
    John Mitros, Arjun Pakrashi, Brian Mac Namee
    http://arxiv.org/abs/2009.01798v1

    • [stat.ML]Simulation of an Elevator Group Control Using Generative Adversarial Networks and Related AI Tools
    Tom Peetz, Sebastian Vogt, Martin Zaefferer, Thomas Bartz-Beielstein

    http://arxiv.org/abs/2009.01696v1