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.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.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.NE - 神经与进化计算 cs.RO - 机器人学 cs.SD - 声音处理 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 eess.AS - 语音处理 eess.IV - 图像与视频处理 eess.SP - 信号处理 math.HO - 历史与概述 math.NA - 数值分析 math.OC - 优化与控制 math.ST - 统计理论 q-bio.PE - 人口与发展 q-bio.QM - 定量方法 q-fin.TR - 贸易与市场微观结构 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [cs.AI]A Theoretical Computer Science Perspective on Consciousness
• [cs.AI]Conservative Extensions in Horn Description Logics with Inverse Roles
• [cs.AI]Electric Vehicle Charging Infrastructure Planning: A Scalable Computational Framework
• [cs.AI]Explainable AI for System Failures: Generating Explanations that Improve Human Assistance in Fault Recovery
• [cs.AI]Explainable Incipient Fault Detection Systems for Photovoltaic Panels
• [cs.AI]Exploring Constraint Handling Techniques in Real-world Problems on MOEA/D with Limited Budget of Evaluations
• [cs.AI]First Order-Rewritability and Containment of Conjunctive Queries in Horn Description Logics
• [cs.AI]Improving Bayesian Network Structure Learning in the Presence of Measurement Error
• [cs.AI]Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?
• [cs.AI]Iterative Planning with Plan-Space Explanations: A Tool and User Study
• [cs.AI]Lifelong Knowledge Learning in Rule-based Dialogue Systems
• [cs.AI]Multi-Modal Subjective Context Modelling and Recognition
• [cs.AI]On the Relationship Between KR Approaches for Explainable Planning
• [cs.AI]RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions
• [cs.CL]A Sequence-to-Sequence Approach to Dialogue State Tracking
• [cs.CL]An Integrated Approach for Improving Brand Consistency of Web Content: Modeling, Analysis and Recommendation
• [cs.CL]Are Pre-trained Language Models Knowledgeable to Ground Open Domain Dialogues?
• [cs.CL]Do We Need Online NLU Tools?
• [cs.CL]Entity Recognition and Relation Extraction from Scientific and Technical Texts in Russian
• [cs.CL]Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP
• [cs.CL]Fact-level Extractive Summarization with Hierarchical Graph Mask on BERT
• [cs.CL]Persuasive Dialogue Understanding: the Baselines and Negative Results
• [cs.CL]Predicting metrical patterns in Spanish poetry with language models
• [cs.CL]Relation Extraction with Contextualized Relation Embedding (CRE)
• [cs.CL]SentiLSTM: A Deep Learning Approach for Sentiment Analysis of Restaurant Reviews
• [cs.CR]Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff
• [cs.CV]Abnormal Event Detection in Urban Surveillance Videos Using GAN and Transfer Learning
• [cs.CV]Adversarial Threats to DeepFake Detection: A Practical Perspective
• [cs.CV]An Efficient and Scalable Deep Learning Approach for Road Damage Detection
• [cs.CV]Attention-Based Transformers for Instance Segmentation of Cells in Microstructures
• [cs.CV]Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation
• [cs.CV]Contextual Fusion For Adversarial Robustness
• [cs.CV]Creative Sketch Generation
• [cs.CV]Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation
• [cs.CV]DCT-Mask: Discrete Cosine Transform Mask Representation for Instance Segmentation
• [cs.CV]Deep Multi-view Depth Estimation with Predicted Uncertainty
• [cs.CV]DeepMorph: A System for Hiding Bitstrings in Morphable Vector Drawings
• [cs.CV]Defocus Blur Detection via Salient Region Detection Prior
• [cs.CV]Dense Label Encoding for Boundary Discontinuity Free Rotation Detection
• [cs.CV]Differentiable Data Augmentation with Kornia
• [cs.CV]Everybody Sign Now: Translating Spoken Language to Photo Realistic Sign Language Video
• [cs.CV]Extracting and Learning Fine-Grained Labels from Chest Radiographs
• [cs.CV]Face Forgery Detection by 3D Decomposition
• [cs.CV]Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery
• [cs.CV]Geography-Aware Self-Supervised Learning
• [cs.CV]HMFlow: Hybrid Matching Optical Flow Network for Small and Fast-Moving Objects
• [cs.CV]Heterogeneous Contrastive Learning: Encoding Spatial Information for Compact Visual Representations
• [cs.CV]Latent-Separated Global Prediction for Learned Image Compression
• [cs.CV]Learning Deep Video Stabilization without Optical Flow
• [cs.CV]Learning to Predict the 3D Layout of a Scene
• [cs.CV]Multi-Plane Program Induction with 3D Box Priors
• [cs.CV]Multigrid-in-Channels Neural Network Architectures
• [cs.CV]Neuro-Symbolic Representations for Video Captioning: A Case for Leveraging Inductive Biases for Vision and Language
• [cs.CV]Patient-independent Epileptic Seizure Prediction using Deep Learning Models
• [cs.CV]Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning
• [cs.CV]Robustified Domain Adaptation
• [cs.CV]Scene text removal via cascaded text stroke detection and erasing
• [cs.CV]Semantic Scene Completion using Local Deep Implicit Functions on LiDAR Data
• [cs.CV]StressNet: Detecting Stress in Thermal Videos
• [cs.CV]Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators?
• [cs.CV]TRAT: Tracking by Attention Using Spatio-Temporal Features
• [cs.CV]The Cube++ Illumination Estimation Dataset
• [cs.CV]Towards Spatio-Temporal Video Scene Text Detection via Temporal Clustering
• [cs.CV]Unifying Instance and Panoptic Segmentation with Dynamic Rank-1 Convolutions
• [cs.CV]Unmixing Convolutional Features for Crisp Edge Detection
• [cs.CV]Watch and Learn: Mapping Language and Noisy Real-world Videos with Self-supervision
• [cs.CY]The Influences of Pre-birth Factors in Early Assessment of Child Mortality using Machine Learning Techniques
• [cs.CY]Using Ordinal Data to Assess Distance Learning
• [cs.DB]Checking Causal Consistency of Distributed Databases
• [cs.DC]heSRPT: Parallel Scheduling to Minimize Mean Slowdown
• [cs.DS]Approximate Bipartite Vertex Cover in the CONGEST Model
• [cs.DS]List-Decodable Mean Estimation in Nearly-PCA Time
• [cs.DS]Online Paging with a Vanishing Regret
• [cs.DS]Redistricting Algorithms
• [cs.HC]Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface
• [cs.IR]From Protocol to Screening: A Hybrid Learning Approach for Technology-Assisted Systematic Literature Reviews
• [cs.IR]Non-Linear Multiple Field Interactions Neural Document Ranking
• [cs.IT]Approximate Weighted $CR$ Coded Matrix Multiplication
• [cs.IT]Energy Efficiency and Spectral Efficiency Tradeoff in RIS-Aided Multiuser MIMO Uplink Transmission
• [cs.IT]Error Exponents in the Bee Identification Problem
• [cs.IT]Hardware Implementation of Fano Decoder for PAC Codes
• [cs.IT]Hidden chaos factors inducing random walks as a factor restricting hospital operative efficiency
• [cs.IT]Reconfigurable Intelligent Surface Optimal Placement in Millimeter-Wave Networks
• [cs.IT]Reconfigurable Intelligent Surface-Assisted Uplink Sparse Code Multiple Access
• [cs.LG]A Cognitive Approach based on the Actionable Knowledge Graph for supporting Maintenance Operations
• [cs.LG]A Stable High-order Tuner for General Convex Functions
• [cs.LG]A Temporal Convolution Network Approach to State-of-Charge Estimation in Li-ion Batteries
• [cs.LG]Adversarial Examples for $k$-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams
• [cs.LG]An Experimental Study of Semantic Continuity for Deep Learning Models
• [cs.LG]Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification
• [cs.LG]Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning
• [cs.LG]Challenges in Deploying Machine Learning: a Survey of Case Studies
• [cs.LG]Data Representing Ground-Truth Explanations to Evaluate XAI Methods
• [cs.LG]Deep Reinforcement Learning for Stochastic Computation Offloading in Digital Twin Networks
• [cs.LG]DeepRepair: Style-Guided Repairing for DNNs in the Real-world Operational Environment
• [cs.LG]DiffusionNet: Accelerating the solution of Time-Dependent partial differential equations using deep learning
• [cs.LG]Effective, Efficient and Robust Neural Architecture Search
• [cs.LG]End-To-End Dilated Variational Autoencoder with Bottleneck Discriminative Loss for Sound Morphing — A Preliminary Study
• [cs.LG]Energy Aware Deep Reinforcement Learning Scheduling for Sensors Correlated in Time and Space
• [cs.LG]Estimation of Shortest Path Covariance Matrices
• [cs.LG]FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning
• [cs.LG]Finding the Homology of Decision Boundaries with Active Learning
• [cs.LG]Fully Gap-Dependent Bounds for Multinomial Logit Bandit
• [cs.LG]GRAPHSPY: Fused Program Semantic-Level Embedding via Graph Neural Networks for Dead Store Detection
• [cs.LG]High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records
• [cs.LG]Impact of Accuracy on Model Interpretations
• [cs.LG]Improved rates for identification of partially observed linear dynamical systems
• [cs.LG]Inverse Constrained Reinforcement Learning
• [cs.LG]Inverse Reinforcement Learning via Matching of Optimality Profiles
• [cs.LG]KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation
• [cs.LG]Learning Recurrent Neural Net Models of Nonlinear Systems
• [cs.LG]Learning in School: Multi-teacher Knowledge Inversion for Data-Free Quantization
• [cs.LG]MG-GCN: Fast and Effective Learning with Mix-grained Aggregators for Training Large Graph Convolutional Networks
• [cs.LG]MOFA: Modular Factorial Design for Hyperparameter Optimization
• [cs.LG]Modular Multi Target Tracking Using LSTM Networks
• [cs.LG]Multi-Task Adversarial Attack
• [cs.LG]NeVer 2.0: Learning, Verification and Repair of Deep Neural Networks
• [cs.LG]Node Similarity Preserving Graph Convolutional Networks
• [cs.LG]On the Dynamics of Training Attention Models
• [cs.LG]On tuning deep learning models: a data mining perspective
• [cs.LG]Online Model Selection for Reinforcement Learning with Function Approximation
• [cs.LG]Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
• [cs.LG]Robustness to Missing Features using Hierarchical Clustering with Split Neural Networks
• [cs.LG]SOCAIRE: Forecasting and Monitoring Urban Air Quality in Madrid
• [cs.LG]Scalable Graph Neural Networks for Heterogeneous Graphs
• [cs.LG]Self-Gradient Networks
• [cs.LG]Similarity-based Distance for Categorical Clustering using Space Structure
• [cs.LG]Using Text to Teach Image Retrieval
• [cs.LG]Vector Embeddings with Subvector Permutation Invariance using a Triplet Enhanced Autoencoder
• [cs.LG]Wasserstein Learning of Determinantal Point Processes
• [cs.NE]Neural network algorithm and its application in reactive distillation
• [cs.NE]Proposing method to Increase the detection accuracy of stomach cancer based on colour and lint features of tongue using CNN and SVM
• [cs.NE]Randomized Self Organizing Map
• [cs.NE]Temporal Surrogate Back-propagation for Spiking Neural Networks
• [cs.NE]Towards Metaheuristics “In the Large”
• [cs.NE]Transfer learning of chaotic systems
• [cs.RO]ACRONYM: A Large-Scale Grasp Dataset Based on Simulation
• [cs.RO]Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics
• [cs.RO]Decentralized Task and Path Planning for Multi-Robot Systems
• [cs.RO]SAFARI: Safe and Active Robot Imitation Learning with Imagination
• [cs.RO]Seeing Through your Skin: Recognizing Objects with a Novel Visuotactile Sensor
• [cs.RO]Solving Footstep Planning as a Feasibility Problem using L1-norm Minimization
• [cs.RO]The Robot Household Marathon Experiment
• [cs.RO]Visual Diver Face Recognition for Underwater Human-Robot Interaction
• [cs.SD]Deep Residual Local Feature Learning for Speech Emotion Recognition
• [cs.SE]ReAssert: Deep Learning for Assert Generation
• [cs.SI]A Deterministic Hitting-Time Moment Approach to Seed-set Expansion over a Graph
• [cs.SI]A Distributed Privacy-Preserving Learning Dynamics in General Social Networks
• [cs.SI]A First Look at COVID-19 Messages on WhatsApp in Pakistan
• [cs.SI]Contextual Stochastic Block Model: Sharp Thresholds and Contiguity
• [cs.SI]Evolution of the political opinion landscape during electoral periods
• [cs.SI]Time-Series Snapshot Network as A New Model for Role Recommendation in OSS
• [cs.SI]Towards mmWave V2X in 5G and Beyond to Support Automated Driving
• [eess.AS]Multi-stage Speaker Extraction with Utterance and Frame-Level Reference Signals
• [eess.AS]TaL: a synchronised multi-speaker corpus of ultrasound tongue imaging, audio, and lip videos
• [eess.AS]Universal MelGAN: A Robust Neural Vocoder for High-Fidelity Waveform Generation in Multiple Domains
• [eess.IV]A Preliminary Comparison Between Compressive Sampling and Anisotropic Mesh-based Image Representation
• [eess.IV]All-in-Focus Iris Camera With a Great Capture Volume
• [eess.IV]Deep LF-Net: Semantic Lung Segmentation from Indian Chest Radiographs Including Severely Unhealthy Images
• [eess.IV]Deep Learning for Automated Screening of Tuberculosis from Indian Chest X-rays: Analysis and Update
• [eess.IV]Recursive Deep Prior Video: a Super Resolution algorithm for Time-Lapse Microscopy of organ-on-chip experiments
• [eess.IV]Spectral Response Function Guided Deep Optimization-driven Network for Spectral Super-resolution
• [eess.SP]Novel Classification of Ischemic Heart Disease Using Artificial Neural Network
• [math.HO]Finding Your Way: Shortest Paths on Networks
• [math.NA]GL-Coarsener: A Graph representation learning framework to construct coarse grid hierarchy for AMG solvers
• [math.OC]Data-Driven Robust Optimization using Unsupervised Deep Learning
• [math.OC]On Uninformative Optimal Policies in Adaptive LQR with Unknown B-Matrix
• [math.ST]In- and Equivariance for Optimal Designs in Generalized Linear Models: The Gamma Model
• [math.ST]On the asymptotic rate of convergence of Stochastic Newton algorithms and their Weighted Averaged versions
• [math.ST]Sharp bounds for variance of treatment effect estimators in the finite population in the presence of covariates
• [q-bio.PE]A Generalized Epidemiological Model for COVID-19 with Dynamic and Asymptomatic Population
• [q-bio.QM]Freecyto: Quantized Flow Cytometry Analysis for the Web
• [q-fin.TR]FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance
• [quant-ph]Classical-Quantum Differentially Private Mechanisms Beyond Classical Ones
• [quant-ph]Quantum Multiple Kernel Learning
• [stat.AP]Modelling fertility potential in survivors of childhood cancer: An introduction to modern statistical and computational methods
• [stat.AP]Stochastic Tropical Cyclone Precipitation Field Generation
• [stat.AP]The Development and Deployment of a Model for Hospital-level COVID-19 Associated Patient Demand Intervals from Consistent Estimators (DICE)
• [stat.AP]Variational Bayes method for ODE parameter estimation with application to time-varying SIR model for Covid-19 epidemic
• [stat.CO]The Pearson Bayes factor: An analytic formula for computing evidential value from minimal summary statistics
• [stat.ME]A general theory of regression adjustment for covariate-adaptive randomization: OLS, Lasso, and beyond
• [stat.ME]A systematic review of causal methods enabling predictions under hypothetical interventions
• [stat.ME]Clarifying causal mediation analysis for the applied researcher: Effect identification via three assumptions and five potential outcomes
• [stat.ME]Positively Correlated Samples Save Pooled Testing Costs
• [stat.ME]Robust, multiple change-point detection for covariance matrices using data depth
• [stat.ME]Some Doubly and Multiply Robust Estimators of Controlled Direct Effects
• [stat.ML]Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry
• [stat.ML]Categorical exploratory data analysis on goodness-of-fit issues
• [stat.ML]Preparing Weather Data for Real-Time Building Energy Simulation
• [stat.ML]Variational Bayes Neural Network: Posterior Consistency, Classification Accuracy and Computational Challenges
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• [cs.AI]A Theoretical Computer Science Perspective on Consciousness
Manuel Blum, Lenore Blum
http://arxiv.org/abs/2011.09850v1
• [cs.AI]Conservative Extensions in Horn Description Logics with Inverse Roles
Jean Christoph Jung, Carsten Lutz, Mauricio Martel, Thomas Schneider
http://arxiv.org/abs/2011.09858v1
• [cs.AI]Electric Vehicle Charging Infrastructure Planning: A Scalable Computational Framework
Wanshi Hong, Cong Zhang, Cy Chan, Bin Wang
http://arxiv.org/abs/2011.09967v1
• [cs.AI]Explainable AI for System Failures: Generating Explanations that Improve Human Assistance in Fault Recovery
Devleena Das, Siddhartha Banerjee, Sonia Chernova
http://arxiv.org/abs/2011.09407v2
• [cs.AI]Explainable Incipient Fault Detection Systems for Photovoltaic Panels
S. Sairam, Seshadhri Srinivasan, G. Marafioti, B. Subathra, G. Mathisen, Korkut Bekiroglu
http://arxiv.org/abs/2011.09843v1
• [cs.AI]Exploring Constraint Handling Techniques in Real-world Problems on MOEA/D with Limited Budget of Evaluations
Felipe Vaz, Yuri Lavinas, Claus Aranha, Marcelo Ladeira
http://arxiv.org/abs/2011.09722v1
• [cs.AI]First Order-Rewritability and Containment of Conjunctive Queries in Horn Description Logics
Meghyn Bienvenu, Peter Hansen, Carsten Lutz, Frank Wolter
http://arxiv.org/abs/2011.09836v1
• [cs.AI]Improving Bayesian Network Structure Learning in the Presence of Measurement Error
Yang Liu, Anthony C. Constantinou, ZhiGao Guo
http://arxiv.org/abs/2011.09776v1
• [cs.AI]Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?
Christian Schroeder de Witt, Tarun Gupta, Denys Makoviichuk, Viktor Makoviychuk, Philip H. S. Torr, Mingfei Sun, Shimon Whiteson
http://arxiv.org/abs/2011.09533v1
• [cs.AI]Iterative Planning with Plan-Space Explanations: A Tool and User Study
Rebecca Eifler, Jörg Hoffmann
http://arxiv.org/abs/2011.09705v1
• [cs.AI]Lifelong Knowledge Learning in Rule-based Dialogue Systems
Bing Liu, Chuhe Mei
http://arxiv.org/abs/2011.09811v1
• [cs.AI]Multi-Modal Subjective Context Modelling and Recognition
Qiang Shen, Stefano Teso, Wanyi Zhang, Hao Xu, Fausto Giunchiglia
http://arxiv.org/abs/2011.09671v1
• [cs.AI]On the Relationship Between KR Approaches for Explainable Planning
Stylianos Loukas Vasileiou, William Yeoh, Tran Cao Son
http://arxiv.org/abs/2011.09006v2
• [cs.AI]RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions
Karthik Valmeekam, Sarath Sreedharan, Sailik Sengupta, Subbarao Kambhampati
http://arxiv.org/abs/2011.09644v1
• [cs.CL]A Sequence-to-Sequence Approach to Dialogue State Tracking
Yue Feng, Yang Wang, Hang Li
http://arxiv.org/abs/2011.09553v1
• [cs.CL]An Integrated Approach for Improving Brand Consistency of Web Content: Modeling, Analysis and Recommendation
Soumyadeep Roy, Shamik Sural, Niyati Chhaya, Anandhavelu Natarajan, Niloy Ganguly
http://arxiv.org/abs/2011.09754v1
• [cs.CL]Are Pre-trained Language Models Knowledgeable to Ground Open Domain Dialogues?
Yufan Zhao, Wei Wu, Can Xu
http://arxiv.org/abs/2011.09708v1
• [cs.CL]Do We Need Online NLU Tools?
Petr Lorenc, Petr Marek, Jan Pichl, Jakub Konrád, Jan Šedivý
http://arxiv.org/abs/2011.09825v1
• [cs.CL]Entity Recognition and Relation Extraction from Scientific and Technical Texts in Russian
Elena Bruches, Alexey Pauls, Tatiana Batura, Vladimir Isachenko
http://arxiv.org/abs/2011.09817v1
• [cs.CL]Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP
John Chen, Ian Berlot-Atwell, Safwan Hossain, Xindi Wang, Frank Rudzicz
http://arxiv.org/abs/2011.09625v1
• [cs.CL]Fact-level Extractive Summarization with Hierarchical Graph Mask on BERT
Ruifeng Yuan, Zili Wang, Wenjie Li
http://arxiv.org/abs/2011.09739v1
• [cs.CL]Persuasive Dialogue Understanding: the Baselines and Negative Results
Hui Chen, Deepanway Ghosal, Navonil Majumder, Amir Hussain, Soujanya Poria
http://arxiv.org/abs/2011.09954v1
• [cs.CL]Predicting metrical patterns in Spanish poetry with language models
Javier de la Rosa, Salvador Ros, Elena González-Blanco
http://arxiv.org/abs/2011.09567v1
• [cs.CL]Relation Extraction with Contextualized Relation Embedding (CRE)
Xiaoyu Chen, Rohan Badlani
http://arxiv.org/abs/2011.09658v1
• [cs.CL]SentiLSTM: A Deep Learning Approach for Sentiment Analysis of Restaurant Reviews
Eftekhar Hossain, Omar Sharif, Mohammed Moshiul Hoque, Iqbal H. Sarker
http://arxiv.org/abs/2011.09684v1
• [cs.CR]Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff
Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
http://arxiv.org/abs/2011.09527v1
• [cs.CV]Abnormal Event Detection in Urban Surveillance Videos Using GAN and Transfer Learning
Ali Atghaei, Soroush Ziaeinejad, Mohammad Rahmati
http://arxiv.org/abs/2011.09619v1
• [cs.CV]Adversarial Threats to DeepFake Detection: A Practical Perspective
Paarth Neekhara, Brian Dolhansky, Joanna Bitton, Cristian Canton Ferrer
http://arxiv.org/abs/2011.09957v1
• [cs.CV]An Efficient and Scalable Deep Learning Approach for Road Damage Detection
Sadra Naddaf-sh, M-Mahdi Naddaf-sh, Amir R. Kashani, Hassan Zargarzadeh
http://arxiv.org/abs/2011.09577v1
• [cs.CV]Attention-Based Transformers for Instance Segmentation of Cells in Microstructures
Tim Prangemeier, Christoph Reich, Heinz Koeppl
http://arxiv.org/abs/2011.09763v1
• [cs.CV]Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation
Soopil Kim, Sion An, Philip Chikontwe, Sang Hyun Park
http://arxiv.org/abs/2011.09608v1
• [cs.CV]Contextual Fusion For Adversarial Robustness
Aiswarya Akumalla, Seth Haney, Maksim Bazhenov
http://arxiv.org/abs/2011.09526v1
• [cs.CV]Creative Sketch Generation
Songwei Ge, Vedanuj Goswami, C. Lawrence Zitnick, Devi Parikh
http://arxiv.org/abs/2011.10039v1
• [cs.CV]Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR Segmentation
Xinge Zhu, Hui Zhou, Tai Wang, Fangzhou Hong, Yuexin Ma, Wei Li, Hongsheng Li, Dahua Lin
http://arxiv.org/abs/2011.10033v1
• [cs.CV]DCT-Mask: Discrete Cosine Transform Mask Representation for Instance Segmentation
Xing Shen, Jirui Yang, Chunbo Wei, Bing Deng, Jianqiang Huang, Xiansheng Hua, Xiaoliang Cheng, Kewei Liang
http://arxiv.org/abs/2011.09876v1
• [cs.CV]Deep Multi-view Depth Estimation with Predicted Uncertainty
Tong Ke, Tien Do, Khiem Vuong, Kourosh Sartipi, Stergios I. Roumeliotis
http://arxiv.org/abs/2011.09594v1
• [cs.CV]DeepMorph: A System for Hiding Bitstrings in Morphable Vector Drawings
Søren Rasmussen, Karsten Østergaard Noe, Oliver Gyldenberg Hjermitslev, Henrik Pedersen
http://arxiv.org/abs/2011.09783v1
• [cs.CV]Defocus Blur Detection via Salient Region Detection Prior
Ming Qian, Min Xia, Chunyi Sun, Zhiwei Wang, Liguo Weng
http://arxiv.org/abs/2011.09677v1
• [cs.CV]Dense Label Encoding for Boundary Discontinuity Free Rotation Detection
Xue Yang, Liping Hou, Yue Zhou, Wentao Wang, Junchi Yan
http://arxiv.org/abs/2011.09670v1
• [cs.CV]Differentiable Data Augmentation with Kornia
Jian Shi, Edgar Riba, Dmytro Mishkin, Francesc Moreno, Anguelos Nicolaou
http://arxiv.org/abs/2011.09832v1
• [cs.CV]Everybody Sign Now: Translating Spoken Language to Photo Realistic Sign Language Video
Ben Saunders, Necati Cihan Camgoz, Richard Bowden
http://arxiv.org/abs/2011.09846v1
• [cs.CV]Extracting and Learning Fine-Grained Labels from Chest Radiographs
Tanveer Syeda-Mahmood, Ph. D, K. C. L Wong, Ph. D, Joy T. Wu, M. D., M. P. H, Ashutosh Jadhav, Ph. D, Orest Boyko, M. D. Ph. D
http://arxiv.org/abs/2011.09517v1
• [cs.CV]Face Forgery Detection by 3D Decomposition
Xiangyu Zhu, Hao Wang, Hongyan Fei, Zhen Lei, Stan Z. Li
http://arxiv.org/abs/2011.09737v1
• [cs.CV]Foreground-Aware Relation Network for Geospatial Object Segmentation in High Spatial Resolution Remote Sensing Imagery
Zhuo Zheng, Yanfei Zhong, Junjue Wang, Ailong Ma
http://arxiv.org/abs/2011.09766v1
• [cs.CV]Geography-Aware Self-Supervised Learning
Kumar Ayush, Burak Uzkent, Chenlin Meng, Marshall Burke, David Lobell, Stefano Ermon
http://arxiv.org/abs/2011.09980v1
• [cs.CV]HMFlow: Hybrid Matching Optical Flow Network for Small and Fast-Moving Objects
Suihanjin Yu, Youmin Zhang, Chen Wang, Xiao Bai, Liang Zhang, Edwin R. Hancock
http://arxiv.org/abs/2011.09654v1
• [cs.CV]Heterogeneous Contrastive Learning: Encoding Spatial Information for Compact Visual Representations
Xinyue Huo, Lingxi Xie, Longhui Wei, Xiaopeng Zhang, Hao Li, Zijie Yang, Wengang Zhou, Houqiang Li, Qi Tian
http://arxiv.org/abs/2011.09941v1
• [cs.CV]Latent-Separated Global Prediction for Learned Image Compression
Zongyu Guo, Zhizheng Zhang, Runsen Feng, Simeng Sun, Zhibo Chen
http://arxiv.org/abs/2011.09704v1
• [cs.CV]Learning Deep Video Stabilization without Optical Flow
Muhammad Kashif Ali, Sangjoon Yu, Tae Hyun Kim
http://arxiv.org/abs/2011.09697v1
• [cs.CV]Learning to Predict the 3D Layout of a Scene
Jihao Andreas Lin, Jakob Brünker, Daniel Fährmann
http://arxiv.org/abs/2011.09977v1
• [cs.CV]Multi-Plane Program Induction with 3D Box Priors
Yikai Li, Jiayuan Mao, Xiuming Zhang, Bill Freeman, Josh Tenenbaum, Noah Snavely, Jiajun Wu
http://arxiv.org/abs/2011.10007v1
• [cs.CV]Multigrid-in-Channels Neural Network Architectures
Moshe Eliasof, Jonathan Ephrath, Lars Ruthotto, Eran Treister
http://arxiv.org/abs/2011.09128v2
• [cs.CV]Neuro-Symbolic Representations for Video Captioning: A Case for Leveraging Inductive Biases for Vision and Language
Hassan Akbari, Hamid Palangi, Jianwei Yang, Sudha Rao, Asli Celikyilmaz, Roland Fernandez, Paul Smolensky, Jianfeng Gao, Shih-Fu Chang
http://arxiv.org/abs/2011.09530v1
• [cs.CV]Patient-independent Epileptic Seizure Prediction using Deep Learning Models
Theekshana Dissanayake, Tharindu Fernando, Simon Denman, Sridha Sridharan, Clinton Fookes
http://arxiv.org/abs/2011.09581v1
• [cs.CV]Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning
Zhenda Xie, Yutong Lin, Zheng Zhang, Yue Cao, Stephen Lin, Han Hu
http://arxiv.org/abs/2011.10043v1
• [cs.CV]Robustified Domain Adaptation
Jiajin Zhang, Hanqing Chao, Pingkun Yan
http://arxiv.org/abs/2011.09563v1
• [cs.CV]Scene text removal via cascaded text stroke detection and erasing
Xuewei Bian, Chaoqun Wang, Weize Quan, Juntao Ye, Xiaopeng Zhang, Dong-Ming Yan
http://arxiv.org/abs/2011.09768v1
• [cs.CV]Semantic Scene Completion using Local Deep Implicit Functions on LiDAR Data
Christoph B. Rist, David Emmerichs, Markus Enzweiler, Dariu M. Gavrila
http://arxiv.org/abs/2011.09141v2
• [cs.CV]StressNet: Detecting Stress in Thermal Videos
Satish Kumar, A S M Iftekhar, Michael Goebel, Tom Bullock, Mary H. MacLean, Michael B. Miller, Tyler Santander, Barry Giesbrecht, Scott T. Grafton, B. S. Manjunath
http://arxiv.org/abs/2011.09540v1
• [cs.CV]Style Intervention: How to Achieve Spatial Disentanglement with Style-based Generators?
Yunfan Liu, Qi Li, Zhenan Sun, Tieniu Tan
http://arxiv.org/abs/2011.09699v1
• [cs.CV]TRAT: Tracking by Attention Using Spatio-Temporal Features
Hasan Saribas, Hakan Cevikalp, Okan Köpüklü, Bedirhan Uzun
http://arxiv.org/abs/2011.09524v1
• [cs.CV]The Cube++ Illumination Estimation Dataset
Egor Ershov, Alex Savchik, Illya Semenkov, Nikola Banić, Alexander Belokopytov, Daria Senshina, Karlo Koscević, Marko Subašić, Sven Lončarić
http://arxiv.org/abs/2011.10028v1
• [cs.CV]Towards Spatio-Temporal Video Scene Text Detection via Temporal Clustering
Yuanqiang Cai, Chang Liu, Weiqiang Wang, Qixiang Ye
http://arxiv.org/abs/2011.09781v1
• [cs.CV]Unifying Instance and Panoptic Segmentation with Dynamic Rank-1 Convolutions
Hao Chen, Chunhua Shen, Zhi Tian
http://arxiv.org/abs/2011.09796v1
• [cs.CV]Unmixing Convolutional Features for Crisp Edge Detection
Linxi Huan, Xianwei Zheng, Nan Xue, Wei He, Jianya Gong, Gui-Song Xia
http://arxiv.org/abs/2011.09808v1
• [cs.CV]Watch and Learn: Mapping Language and Noisy Real-world Videos with Self-supervision
Yujie Zhong, Linhai Xie, Sen Wang, Lucia Specia, Yishu Miao
http://arxiv.org/abs/2011.09634v1
• [cs.CY]The Influences of Pre-birth Factors in Early Assessment of Child Mortality using Machine Learning Techniques
Asadullah Hill Galib, Nadia Nahar, B M Mainul Hossain
http://arxiv.org/abs/2011.09536v1
• [cs.CY]Using Ordinal Data to Assess Distance Learning
Matthew Norris
http://arxiv.org/abs/2011.09838v1
• [cs.DB]Checking Causal Consistency of Distributed Databases
Rachid Zennou, Ranadeep Biswas, Ahmed Bouajjani, Constantin Enea, Mohammed Erradi
http://arxiv.org/abs/2011.09753v1
• [cs.DC]heSRPT: Parallel Scheduling to Minimize Mean Slowdown
Benjamin Berg, Rein Vesilo, Mor Harchol-Balter
http://arxiv.org/abs/2011.09676v1
• [cs.DS]Approximate Bipartite Vertex Cover in the CONGEST Model
Salwa Faour, Fabian Kuhn
http://arxiv.org/abs/2011.10014v1
• [cs.DS]List-Decodable Mean Estimation in Nearly-PCA Time
Ilias Diakonikolas, Daniel M. Kane, Daniel Kongsgaard, Jerry Li, Kevin Tian
http://arxiv.org/abs/2011.09973v1
• [cs.DS]Online Paging with a Vanishing Regret
Yuval Emek, Shay Kutten, Yangguang Shi
http://arxiv.org/abs/2011.09439v2
• [cs.DS]Redistricting Algorithms
Amariah Becker, Justin Solomon
http://arxiv.org/abs/2011.09504v1
• [cs.HC]Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface
Javier Fumanal-Idocin, Zdenko Takáč, Javier Fernández Jose Antonio Sanz, Harkaitz Goyena, Ching-Teng Lin, Yu-Kai Wang, Humberto Bustince
http://arxiv.org/abs/2011.09831v1
• [cs.IR]From Protocol to Screening: A Hybrid Learning Approach for Technology-Assisted Systematic Literature Reviews
Athanasios Lagopoulos, Grigorios Tsoumakas
http://arxiv.org/abs/2011.09752v1
• [cs.IR]Non-Linear Multiple Field Interactions Neural Document Ranking
Kentaro Takiguchi, Niall Twomey, Luis M. Vaquero
http://arxiv.org/abs/2011.09580v1
• [cs.IT]Approximate Weighted $CR$ Coded Matrix Multiplication
Neophytos Charalambides, Mert Pilanci, Alfred Hero
http://arxiv.org/abs/2011.09709v1
• [cs.IT]Energy Efficiency and Spectral Efficiency Tradeoff in RIS-Aided Multiuser MIMO Uplink Transmission
Li You, Jiayuan Xiong, Derrick Wing Kwan Ng, Chau Yuen, Wenjin Wang, Xiqi Gao
http://arxiv.org/abs/2011.09724v1
• [cs.IT]Error Exponents in the Bee Identification Problem
Ran Tamir, Neri Merhav
http://arxiv.org/abs/2011.09799v1
• [cs.IT]Hardware Implementation of Fano Decoder for PAC Codes
Amir Mozammel
http://arxiv.org/abs/2011.09819v1
• [cs.IT]Hidden chaos factors inducing random walks as a factor restricting hospital operative efficiency
A. J. Rodríguez-Hernández, Carlos Sevcik
http://arxiv.org/abs/2011.09514v1
• [cs.IT]Reconfigurable Intelligent Surface Optimal Placement in Millimeter-Wave Networks
Konstantinos Ntontin, Alexandros-Apostolos A. Boulogeorgos, Dimitrios Selimis, Fotis Lazarakis, Angeliki Alexiou, Symeon Chatzinotas
http://arxiv.org/abs/2011.09949v1
• [cs.IT]Reconfigurable Intelligent Surface-Assisted Uplink Sparse Code Multiple Access
Ibrahim Al-Nahhal, Octavia A. Dobre, Ertugrul Basar
http://arxiv.org/abs/2011.09647v1
• [cs.LG]A Cognitive Approach based on the Actionable Knowledge Graph for supporting Maintenance Operations
Giuseppe Fenza, Mariacristina Gallo, Vincenzo Loia, Domenico Marino, Francesco Orciuoli
http://arxiv.org/abs/2011.09554v1
• [cs.LG]A Stable High-order Tuner for General Convex Functions
José M. Moreu, Anuradha M. Annaswamy
http://arxiv.org/abs/2011.09996v1
• [cs.LG]A Temporal Convolution Network Approach to State-of-Charge Estimation in Li-ion Batteries
Aniruddh Herle, Janamejaya Channegowda, Dinakar Prabhu
http://arxiv.org/abs/2011.09775v1
• [cs.LG]Adversarial Examples for $k$-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams
Chawin Sitawarin, Evgenios M. Kornaropoulos, Dawn Song, David Wagner
http://arxiv.org/abs/2011.09719v1
• [cs.LG]An Experimental Study of Semantic Continuity for Deep Learning Models
Shangxi Wu, Jitao Sang, Xian Zhao, Lizhang Chen
http://arxiv.org/abs/2011.09789v1
• [cs.LG]Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification
Youngseog Chung, Willie Neiswanger, Ian Char, Jeff Schneider
http://arxiv.org/abs/2011.09588v1
• [cs.LG]Budgeted Online Selection of Candidate IoT Clients to Participate in Federated Learning
Ihab Mohammed, Shadha Tabatabai, Ala Al-Fuqaha, Faissal El Bouanani, Junaid Qadir, Basheer Qolomany, Mohsen Guizani
http://arxiv.org/abs/2011.09849v1
• [cs.LG]Challenges in Deploying Machine Learning: a Survey of Case Studies
Andrei Paleyes, Raoul-Gabriel Urma, Neil D. Lawrence
http://arxiv.org/abs/2011.09926v1
• [cs.LG]Data Representing Ground-Truth Explanations to Evaluate XAI Methods
Shideh Shams Amiri, Rosina O. Weber, Prateek Goel, Owen Brooks, Archer Gandley, Brian Kitchell, Aaron Zehm
http://arxiv.org/abs/2011.09892v1
• [cs.LG]Deep Reinforcement Learning for Stochastic Computation Offloading in Digital Twin Networks
Yueyue Dai, Ke Zhang, Sabita Maharjan, Yan Zhang
http://arxiv.org/abs/2011.08430v2
• [cs.LG]DeepRepair: Style-Guided Repairing for DNNs in the Real-world Operational Environment
Bing Yu, Hua Qi, Qing Guo, Felix Juefei-Xu, Xiaofei Xie, Lei Ma, Jianjun Zhao
http://arxiv.org/abs/2011.09884v1
• [cs.LG]DiffusionNet: Accelerating the solution of Time-Dependent partial differential equations using deep learning
Mahmoud Asem
http://arxiv.org/abs/2011.10015v1
• [cs.LG]Effective, Efficient and Robust Neural Architecture Search
Zhixiong Yue, Baijiong Lin, Xiaonan Huang, Yu Zhang
http://arxiv.org/abs/2011.09820v1
• [cs.LG]End-To-End Dilated Variational Autoencoder with Bottleneck Discriminative Loss for Sound Morphing — A Preliminary Study
Matteo Lionello, Hendrik Purwins
http://arxiv.org/abs/2011.09744v1
• [cs.LG]Energy Aware Deep Reinforcement Learning Scheduling for Sensors Correlated in Time and Space
Jernej Hribar, Andrei Marinescu, Alessandro Chiumento, Luiz A. DaSilva
http://arxiv.org/abs/2011.09747v1
• [cs.LG]Estimation of Shortest Path Covariance Matrices
Raj Kumar Maity, Cameron Musco
http://arxiv.org/abs/2011.09986v1
• [cs.LG]FedEval: A Benchmark System with a Comprehensive Evaluation Model for Federated Learning
Di Chai, Leye Wang, Kai Chen, Qiang Yang
http://arxiv.org/abs/2011.09655v1
• [cs.LG]Finding the Homology of Decision Boundaries with Active Learning
Weizhi Li, Gautam Dasarathy, Karthikeyan Natesan Ramamurthy, Visar Berisha
http://arxiv.org/abs/2011.09645v1
• [cs.LG]Fully Gap-Dependent Bounds for Multinomial Logit Bandit
Jiaqi Yang
http://arxiv.org/abs/2011.09998v1
• [cs.LG]GRAPHSPY: Fused Program Semantic-Level Embedding via Graph Neural Networks for Dead Store Detection
Yixin Guo, Pengcheng Li, Yingwei Luo, Xiaolin Wang, Zhenlin Wang
http://arxiv.org/abs/2011.09501v1
• [cs.LG]High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records
Alex Taylor, Ross Kleiman, Scott Hebbring, Peggy Peissig, David Page
http://arxiv.org/abs/2011.09497v1
• [cs.LG]Impact of Accuracy on Model Interpretations
Brian Liu, Madeleine Udell
http://arxiv.org/abs/2011.09903v1
• [cs.LG]Improved rates for identification of partially observed linear dynamical systems
Holden Lee
http://arxiv.org/abs/2011.10006v1
• [cs.LG]Inverse Constrained Reinforcement Learning
Usman Anwar, Shehryar Malik, Alireza Aghasi, Ali Ahmed
http://arxiv.org/abs/2011.09999v1
• [cs.LG]Inverse Reinforcement Learning via Matching of Optimality Profiles
Luis Haug, Ivan Ovinnikov, Eugene Bykovets
http://arxiv.org/abs/2011.09264v2
• [cs.LG]KD3A: Unsupervised Multi-Source Decentralized Domain Adaptation via Knowledge Distillation
Hao-Zhe Feng, Zhaoyang You, Minghao Chen, Tianye Zhang, Minfeng Zhu, Fei Wu, Chao Wu, Wei Chen
http://arxiv.org/abs/2011.09757v1
• [cs.LG]Learning Recurrent Neural Net Models of Nonlinear Systems
Joshua Hanson, Maxim Raginsky, Eduardo Sontag
http://arxiv.org/abs/2011.09573v1
• [cs.LG]Learning in School: Multi-teacher Knowledge Inversion for Data-Free Quantization
Yuhang Li, Feng Zhu, Ruihao Gong, Mingzhu Shen, Fengwei Yu, Shaoqing Lu, Shi Gu
http://arxiv.org/abs/2011.09899v1
• [cs.LG]MG-GCN: Fast and Effective Learning with Mix-grained Aggregators for Training Large Graph Convolutional Networks
Tao Huang, Yihan Zhang, Jiajing Wu, Junyuan Fang, Zibin Zheng
http://arxiv.org/abs/2011.09900v1
• [cs.LG]MOFA: Modular Factorial Design for Hyperparameter Optimization
Bo Xiong, Yimin Huang, Steffen Staab, Zhenguo Li
http://arxiv.org/abs/2011.09545v1
• [cs.LG]Modular Multi Target Tracking Using LSTM Networks
Rishabh Verma, R Rajesh, MS Easwaran
http://arxiv.org/abs/2011.09839v1
• [cs.LG]Multi-Task Adversarial Attack
Pengxin Guo, Yuancheng Xu, Baijiong Lin, Yu Zhang
http://arxiv.org/abs/2011.09824v1
• [cs.LG]NeVer 2.0: Learning, Verification and Repair of Deep Neural Networks
Dario Guidotti, Luca Pulina, Armando Tacchella
http://arxiv.org/abs/2011.09933v1
• [cs.LG]Node Similarity Preserving Graph Convolutional Networks
Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang
http://arxiv.org/abs/2011.09643v1
• [cs.LG]On the Dynamics of Training Attention Models
Haoye Lu, Yongyi Mao, Amiya Nayak
http://arxiv.org/abs/2011.10036v1
• [cs.LG]On tuning deep learning models: a data mining perspective
M. M. Ozturk
http://arxiv.org/abs/2011.09857v1
• [cs.LG]Online Model Selection for Reinforcement Learning with Function Approximation
Jonathan N. Lee, Aldo Pacchiano, Vidya Muthukumar, Weihao Kong, Emma Brunskill
http://arxiv.org/abs/2011.09750v1
• [cs.LG]Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
Avi Singh, Huihan Liu, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
http://arxiv.org/abs/2011.10024v1
• [cs.LG]Robustness to Missing Features using Hierarchical Clustering with Split Neural Networks
Rishab Khincha, Utkarsh Sarawgi, Wazeer Zulfikar, Pattie Maes
http://arxiv.org/abs/2011.09596v1
• [cs.LG]SOCAIRE: Forecasting and Monitoring Urban Air Quality in Madrid
Rodrigo de Medrano, Víctor de Buen Remiro, José L. Aznarte
http://arxiv.org/abs/2011.09741v1
• [cs.LG]Scalable Graph Neural Networks for Heterogeneous Graphs
Lingfan Yu, Jiajun Shen, Jinyang Li, Adam Lerer
http://arxiv.org/abs/2011.09679v1
• [cs.LG]Self-Gradient Networks
Hossein Aboutalebi, Mohammad Javad Shafiee Alexander Wong
http://arxiv.org/abs/2011.09364v2
• [cs.LG]Similarity-based Distance for Categorical Clustering using Space Structure
Utkarsh Nath, Shikha Asrani, Rahul Katarya
http://arxiv.org/abs/2011.09887v1
• [cs.LG]Using Text to Teach Image Retrieval
Haoyu Dong, Ze Wang, Qiang Qiu, Guillermo Sapiro
http://arxiv.org/abs/2011.09928v1
• [cs.LG]Vector Embeddings with Subvector Permutation Invariance using a Triplet Enhanced Autoencoder
Mark Alan Matties
http://arxiv.org/abs/2011.09550v1
• [cs.LG]Wasserstein Learning of Determinantal Point Processes
Lucas Anquetil, Mike Gartrell, Alain Rakotomamonjy, Ugo Tanielian, Clément Calauzènes
http://arxiv.org/abs/2011.09712v1
• [cs.NE]Neural network algorithm and its application in reactive distillation
Huihui Wang, Ruyang Mo
http://arxiv.org/abs/2011.09969v1
• [cs.NE]Proposing method to Increase the detection accuracy of stomach cancer based on colour and lint features of tongue using CNN and SVM
Elham Gholami, Seyed Reza Kamel Tabbakh, Maryam Kheirabadi
http://arxiv.org/abs/2011.09962v1
• [cs.NE]Randomized Self Organizing Map
Nicolas P. Rougier, Georgios Is. Detorakis
http://arxiv.org/abs/2011.09534v1
• [cs.NE]Temporal Surrogate Back-propagation for Spiking Neural Networks
Yukun Yang
http://arxiv.org/abs/2011.09964v1
• [cs.NE]Towards Metaheuristics “In the Large”
Jerry Swan, Steven Adraensen, Alexander E. I. Brownlee, Colin G. Johnson, Ahmed Kheiri, Faustyna Krawiec, J. J. Merelo, Leandro L. Minku, Ender Özcan, Gisele L. Pappa, Pablo García-Sánchez, Kenneth Sörensen, Stefan Voß, Markus Wagner, David R. White
http://arxiv.org/abs/2011.09821v1
• [cs.NE]Transfer learning of chaotic systems
Yali Guo, Han Zhang, Liang Wang, Huawei Fan, Xingang Wang
http://arxiv.org/abs/2011.09970v1
• [cs.RO]ACRONYM: A Large-Scale Grasp Dataset Based on Simulation
Clemens Eppner, Arsalan Mousavian, Dieter Fox
http://arxiv.org/abs/2011.09584v1
• [cs.RO]Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics
Corrado Pezzato, Carlos Hernandez, Martijn Wisse
http://arxiv.org/abs/2011.09756v1
• [cs.RO]Decentralized Task and Path Planning for Multi-Robot Systems
Yuxiao Chen, Ugo Rosolia, Aaron D. Ames
http://arxiv.org/abs/2011.10034v1
• [cs.RO]SAFARI: Safe and Active Robot Imitation Learning with Imagination
Norman Di Palo, Edward Johns
http://arxiv.org/abs/2011.09586v1
• [cs.RO]Seeing Through your Skin: Recognizing Objects with a Novel Visuotactile Sensor
Francois Robert Hogan, Michael Jenkin, Sahand Rezaei-Shoshtari, Yogesh Girdhar, David Meger, Gregory Dudek
http://arxiv.org/abs/2011.09552v1
• [cs.RO]Solving Footstep Planning as a Feasibility Problem using L1-norm Minimization
Daeun Song, Pierre Fernbach, Thomas Flayols, Andrea Del Prete, Nicolas Mansard, Steve Tonneau, Young J. Kim
http://arxiv.org/abs/2011.09772v1
• [cs.RO]The Robot Household Marathon Experiment
Gayane Kazhoyan, Simon Stelter, Franklin Kenghagho Kenfack, Sebastian Koralewski, Michael Beetz
http://arxiv.org/abs/2011.09792v1
• [cs.RO]Visual Diver Face Recognition for Underwater Human-Robot Interaction
Jungseok Hong, Sadman Sakib Enan, Christopher Morse, Junaed Sattar
http://arxiv.org/abs/2011.09556v1
• [cs.SD]Deep Residual Local Feature Learning for Speech Emotion Recognition
Sattaya Singkul, Thakorn Chatchaisathaporn, Boontawee Suntisrivaraporn, Kuntpong Woraratpanya
http://arxiv.org/abs/2011.09767v1
• [cs.SE]ReAssert: Deep Learning for Assert Generation
Robert White, Jens Krinke
http://arxiv.org/abs/2011.09784v1
• [cs.SI]A Deterministic Hitting-Time Moment Approach to Seed-set Expansion over a Graph
Alexander H. Foss, Richard B. Lehoucq, W. Zachary Stuart, J. Derek Tucker, Jonathan W. Berry
http://arxiv.org/abs/2011.09544v1
• [cs.SI]A Distributed Privacy-Preserving Learning Dynamics in General Social Networks
Youming Tao, Shuzhen Chen, Feng Li, Dongxiao Yu, Jiguo Yu, Hao Sheng
http://arxiv.org/abs/2011.09845v1
• [cs.SI]A First Look at COVID-19 Messages on WhatsApp in Pakistan
R. Tallal Javed, Mirza Elaaf Shuja, Muhammad Usama, Junaid Qadir, Waleed Iqbal, Gareth Tyson, Ignacio Castro, Kiran Garimella
http://arxiv.org/abs/2011.09145v2
• [cs.SI]Contextual Stochastic Block Model: Sharp Thresholds and Contiguity
Chen Lu, Subhabrata Sen
http://arxiv.org/abs/2011.09841v1
• [cs.SI]Evolution of the political opinion landscape during electoral periods
Tomás Mussi Reyero, Mariano G. Beiró, J. Ignacio Alvarez-Hamelin, Laura Hernández, Dimitris Kotzinos
http://arxiv.org/abs/2011.09538v1
• [cs.SI]Time-Series Snapshot Network as A New Model for Role Recommendation in OSS
Jinyin Chen, Yunyi Xie, Jian Zhang, Xincheng Shu, Qi Xuan
http://arxiv.org/abs/2011.09883v1
• [cs.SI]Towards mmWave V2X in 5G and Beyond to Support Automated Driving
Kei Sakaguchi, Ryuichi Fukatsu, Tao Yu, Eisuke Fukuda, Kim Mahler, Robert Heath, Takeo Fujii, Kazuaki Takahashi, Alexey Khoryaev, Satoshi Nagata, Takayuki Shimizu
http://arxiv.org/abs/2011.09590v1
• [eess.AS]Multi-stage Speaker Extraction with Utterance and Frame-Level Reference Signals
Meng Ge, Chenglin Xu, Longbiao Wang, Eng Siong Chng, Jianwu Dang, Haizhou Li
http://arxiv.org/abs/2011.09624v1
• [eess.AS]TaL: a synchronised multi-speaker corpus of ultrasound tongue imaging, audio, and lip videos
Manuel Sam Ribeiro, Jennifer Sanger, Jing-Xuan Zhang, Aciel Eshky, Alan Wrench, Korin Richmond, Steve Renals
http://arxiv.org/abs/2011.09804v1
• [eess.AS]Universal MelGAN: A Robust Neural Vocoder for High-Fidelity Waveform Generation in Multiple Domains
Won Jang, Dan Lim, Jaesam Yoon
http://arxiv.org/abs/2011.09631v1
• [eess.IV]A Preliminary Comparison Between Compressive Sampling and Anisotropic Mesh-based Image Representation
Xianping Li, Teresa Wu
http://arxiv.org/abs/2011.09944v1
• [eess.IV]All-in-Focus Iris Camera With a Great Capture Volume
Kunbo Zhang, Zhenteng Shen, Yunlong Wang, Zhenan Sun
http://arxiv.org/abs/2011.09908v1
• [eess.IV]Deep LF-Net: Semantic Lung Segmentation from Indian Chest Radiographs Including Severely Unhealthy Images
Anushikha Singh, Brejesh Lall, B. K. Panigrahi, Anjali Agrawal, Anurag Agrawal, DJ Christopher, Balamugesh Thangakunam
http://arxiv.org/abs/2011.09695v1
• [eess.IV]Deep Learning for Automated Screening of Tuberculosis from Indian Chest X-rays: Analysis and Update
Anushikha Singh, Brejesh Lall, B. K. Panigrahi, Anjali Agrawal, Anurag Agrawal, Balamugesh Thangakunam, DJ Christopher
http://arxiv.org/abs/2011.09778v1
• [eess.IV]Recursive Deep Prior Video: a Super Resolution algorithm for Time-Lapse Microscopy of organ-on-chip experiments
Pasquale Cascarano, Maria Colomba Comes, Arianna Mencattini, Maria Carla Parrini, Elena Loli Piccolomini, Eugenio Martinelli
http://arxiv.org/abs/2011.09855v1
• [eess.IV]Spectral Response Function Guided Deep Optimization-driven Network for Spectral Super-resolution
Jiang He, Jie Li, Qiangqiang Yuan, Huanfeng Shen, Liangpei Zhang
http://arxiv.org/abs/2011.09701v1
• [eess.SP]Novel Classification of Ischemic Heart Disease Using Artificial Neural Network
Giulia Silveri, Marco Merlo, Luca Restivo, Gianfranco Sinagra, Agostino Accardo
http://arxiv.org/abs/2011.09801v1
• [math.HO]Finding Your Way: Shortest Paths on Networks
Teresa Rexin, Mason A. Porter
http://arxiv.org/abs/2011.09632v1
• [math.NA]GL-Coarsener: A Graph representation learning framework to construct coarse grid hierarchy for AMG solvers
Reza Namazi, Arsham Zolanvari, Mahdi Sani, Seyed Amir Ali Ghafourian Ghahramani
http://arxiv.org/abs/2011.09994v1
• [math.OC]Data-Driven Robust Optimization using Unsupervised Deep Learning
Marc Goerigk, Jannis Kurtz
http://arxiv.org/abs/2011.09769v1
• [math.OC]On Uninformative Optimal Policies in Adaptive LQR with Unknown B-Matrix
Ingvar Ziemann, Henrik Sandberg
http://arxiv.org/abs/2011.09288v2
• [math.ST]In- and Equivariance for Optimal Designs in Generalized Linear Models: The Gamma Model
Osama Idais, Rainer Schwabe
http://arxiv.org/abs/2011.09745v1
• [math.ST]On the asymptotic rate of convergence of Stochastic Newton algorithms and their Weighted Averaged versions
Claire Boyer, Antoine Godichon-Baggioni
http://arxiv.org/abs/2011.09706v1
• [math.ST]Sharp bounds for variance of treatment effect estimators in the finite population in the presence of covariates
Ruoyu Wang, Qihua Wang, Wang Miao, Xiaohua Zhou
http://arxiv.org/abs/2011.09829v1
• [q-bio.PE]A Generalized Epidemiological Model for COVID-19 with Dynamic and Asymptomatic Population
Anirban Ghatak, Shivshanker Singh Patel, Soham Bonnerjee, Subhrajyoty Roy
http://arxiv.org/abs/2011.09686v1
• [q-bio.QM]Freecyto: Quantized Flow Cytometry Analysis for the Web
Nathan Wong, Daehwan Kim, Zachery Robinson, Connie Huang, Irina M. Conboy
http://arxiv.org/abs/2011.09770v1
• [q-fin.TR]FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance
Xiao-Yang Liu, Hongyang Yang, Qian Chen, Runjia Zhang, Liuqing Yang, Bowen Xiao, Christina Dan Wang
http://arxiv.org/abs/2011.09607v1
• [quant-ph]Classical-Quantum Differentially Private Mechanisms Beyond Classical Ones
Yuuya Yoshida
http://arxiv.org/abs/2011.09960v1
• [quant-ph]Quantum Multiple Kernel Learning
Seyed Shakib Vedaie, Moslem Noori, Jaspreet S. Oberoi, Barry C. Sanders, Ehsan Zahedinejad
http://arxiv.org/abs/2011.09694v1
• [stat.AP]Modelling fertility potential in survivors of childhood cancer: An introduction to modern statistical and computational methods
L. Yu, Z. Lu, P. C. Nathan, S. Mostoufi-Moab, Y. Yuan
http://arxiv.org/abs/2011.10020v1
• [stat.AP]Stochastic Tropical Cyclone Precipitation Field Generation
William Kleiber, Stephan Sain, Luke Madaus, Patrick Harr
http://arxiv.org/abs/2011.09918v1
• [stat.AP]The Development and Deployment of a Model for Hospital-level COVID-19 Associated Patient Demand Intervals from Consistent Estimators (DICE)
Linying Yang, Teng Zhang, Peter Glynn, David Scheinker
http://arxiv.org/abs/2011.09377v2
• [stat.AP]Variational Bayes method for ODE parameter estimation with application to time-varying SIR model for Covid-19 epidemic
Hyunjoo Yang, Jaeyong Lee
http://arxiv.org/abs/2011.09718v1
• [stat.CO]The Pearson Bayes factor: An analytic formula for computing evidential value from minimal summary statistics
Thomas J. Faulkenberry
http://arxiv.org/abs/2011.09549v1
• [stat.ME]A general theory of regression adjustment for covariate-adaptive randomization: OLS, Lasso, and beyond
Hanzhong Liu, Fuyi Tu, Wei Ma
http://arxiv.org/abs/2011.09734v1
• [stat.ME]A systematic review of causal methods enabling predictions under hypothetical interventions
Lijing Lin, Matthew Sperrin, David A. Jenkins, Glen P. Martin, Niels Peek
http://arxiv.org/abs/2011.09815v1
• [stat.ME]Clarifying causal mediation analysis for the applied researcher: Effect identification via three assumptions and five potential outcomes
Trang Quynh Nguyen, Ian Schmid, Elizabeth L. Ogburn, Elizabeth A. Stuart
http://arxiv.org/abs/2011.09537v1
• [stat.ME]Positively Correlated Samples Save Pooled Testing Costs
Yi-Jheng Lin, Che-Hao Yu, Tzu-Hsuan Liu, Cheng-Shang Chang, Wen-Tsuen Chen
http://arxiv.org/abs/2011.09794v1
• [stat.ME]Robust, multiple change-point detection for covariance matrices using data depth
Kelly Ramsay, Shoja’eddin Chenouri
http://arxiv.org/abs/2011.09558v1
• [stat.ME]Some Doubly and Multiply Robust Estimators of Controlled Direct Effects
Xiang Zhou
http://arxiv.org/abs/2011.09569v1
• [stat.ML]Application of Deep Learning-based Interpolation Methods to Nearshore Bathymetry
Yizhou Qian, Mojtaba Forghani, Jonghyun Harry Lee, Matthew Farthing, Tyler Hesser, Peter Kitanidis, Eric Darve
http://arxiv.org/abs/2011.09707v1
• [stat.ML]Categorical exploratory data analysis on goodness-of-fit issues
Sabrina Enriquez, Fushing Hsieh
http://arxiv.org/abs/2011.09682v1
• [stat.ML]Preparing Weather Data for Real-Time Building Energy Simulation
Maryam MeshkinKiya, Riccardo Paolini
http://arxiv.org/abs/2011.09733v1
• [stat.ML]Variational Bayes Neural Network: Posterior Consistency, Classification Accuracy and Computational Challenges
Shrijita Bhattacharya, Zihuan Liu, Tapabrata Maiti
http://arxiv.org/abs/2011.09592v1