astro-ph.GA - 星系天体物理学
astro-ph.IM - 仪器仪表和天体物理学方法 cond-mat.mtrl-sci - 材料科学 cs.AI - 人工智能 cs.AR - 硬件体系结构 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.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.NE - 神经与进化计算 cs.NI - 网络和互联网体系结构 cs.RO - 机器人学 cs.SD - 声音处理 cs.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 eess.SY - 系统和控制 math.OC - 优化与控制 math.PR - 概率 math.ST - 统计理论 physics.data-an - 数据分析、 统计和概率 q-bio.QM - 定量方法 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [astro-ph.GA]StarcNet: Machine Learning for Star Cluster Identification
• [astro-ph.IM]SRoll3: A neural network approach to reduce large-scale systematic effects in the Planck High Frequency Instrument maps
• [cond-mat.mtrl-sci]Computational discovery of new 2D materials using deep learning generative models
• [cs.AI]Applying Deutsch’s concept of good explanations to artificial intelligence and neuroscience — an initial exploration
• [cs.AI]Computational principles of intelligence: learning and reasoning with neural networks
• [cs.AI]Helping Reduce Environmental Impact of Aviation with Machine Learning
• [cs.AI]On Exploiting Hitting Sets for Model Reconciliation
• [cs.AI]Predicting Events In MOBA Games: Dataset, Attribution, and Evaluation
• [cs.AI]XAI-P-T: A Brief Review of Explainable Artificial Intelligence from Practice to Theory
• [cs.AR]SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning
• [cs.CL]Assessing COVID-19 Impacts on College Students via Automated Processing of Free-form Text
• [cs.CL]BERT Goes Shopping: Comparing Distributional Models for Product Representations
• [cs.CL]Benchmarking Automatic Detection of Psycholinguistic Characteristics for Better Human-Computer Interaction
• [cs.CL]Continual Lifelong Learning in Natural Language Processing: A Survey
• [cs.CL]Do You Do Yoga? Understanding Twitter Users’ Types and Motivations using Social and Textual Information
• [cs.CL]Exploring Thematic Coherence in Fake News
• [cs.CL]Hate Speech detection in the Bengali language: A dataset and its baseline evaluation
• [cs.CL]InSRL: A Multi-view Learning Framework Fusing Multiple Information Sources for Distantly-supervised Relation Extraction
• [cs.CL]Interactive Question Clarification in Dialogue via Reinforcement Learning
• [cs.CL]Literature Retrieval for Precision Medicine with Neural Matching and Faceted Summarization
• [cs.CL]MELINDA: A Multimodal Dataset for Biomedical Experiment Method Classification
• [cs.CL]MIX : a Multi-task Learning Approach to Solve Open-Domain Question Answering
• [cs.CL]ReferentialGym: A Nomenclature and Framework for Language Emergence & Grounding in (Visual) Referential Games
• [cs.CL]Ultra-Fast, Low-Storage, Highly Effective Coarse-grained Selection in Retrieval-based Chatbot by Using Deep Semantic Hashing
• [cs.CL]Unsupervised Learning of Discourse Structures using a Tree Autoencoder
• [cs.CL]cif-based collaborative decoding for end-to-end contextual speech recognition
• [cs.CR]Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning—Based Malware Detection
• [cs.CR]KHOVID: Interoperable Privacy Preserving Digital Contact Tracing
• [cs.CR]Machine Learning for Detecting Data Exfiltration
• [cs.CV]$\mathbb{X}$Resolution Correspondence Networks
• [cs.CV]A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks
• [cs.CV]A fully pipelined FPGA accelerator for scale invariant feature transform keypoint descriptor matching,
• [cs.CV]AutoCaption: Image Captioning with Neural Architecture Search
• [cs.CV]CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models
• [cs.CV]Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup
• [cs.CV]Detection and Prediction of Nutrient Deficiency Stress using Longitudinal Aerial Imagery
• [cs.CV]Efficient CNN-LSTM based Image Captioning using Neural Network Compression
• [cs.CV]Efficient Golf Ball Detection and Tracking Based on Convolutional Neural Networks and Kalman Filter
• [cs.CV]Embodied Visual Active Learning for Semantic Segmentation
• [cs.CV]End-to-End Human Pose and Mesh Reconstruction with Transformers
• [cs.CV]End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box
• [cs.CV]Event Camera Calibration of Per-pixel Biased Contrast Threshold
• [cs.CV]Exploiting Learnable Joint Groups for Hand Pose Estimation
• [cs.CV]Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification
• [cs.CV]FG-Net: Fast Large-Scale LiDAR Point CloudsUnderstanding Network Leveraging CorrelatedFeature Mining and Geometric-Aware Modelling
• [cs.CV]Firearm Detection via Convolutional Neural Networks: Comparing a Semantic Segmentation Model Against End-to-End Solutions
• [cs.CV]Human Mesh Recovery from Multiple Shots
• [cs.CV]ISD: Self-Supervised Learning by Iterative Similarity Distillation
• [cs.CV]Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition
• [cs.CV]Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Image
• [cs.CV]Interpretable Image Clustering via Diffeomorphism-Aware K-Means
• [cs.CV]Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation
• [cs.CV]LIGHTEN: Learning Interactions with Graph and Hierarchical TEmporal Networks for HOI in videos
• [cs.CV]Learning to Recognize Patch-Wise Consistency for Deepfake Detection
• [cs.CV]Learning to Recover 3D Scene Shape from a Single Image
• [cs.CV]Learning to Share: A Multitasking Genetic Programming Approach to Image Feature Learning
• [cs.CV]Multi-Modal Depth Estimation Using Convolutional Neural Networks
• [cs.CV]Multi-shot Temporal Event Localization: a Benchmark
• [cs.CV]Neural Pruning via Growing Regularization
• [cs.CV]Neural Radiance Flow for 4D View Synthesis and Video Processing
• [cs.CV]PCT: Point Cloud Transformer
• [cs.CV]PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection
• [cs.CV]Polyblur: Removing mild blur by polynomial reblurring
• [cs.CV]Projected Distribution Loss for Image Enhancement
• [cs.CV]RainNet: A Large-Scale Dataset for Spatial Precipitation Downscaling
• [cs.CV]Reconstructing Hand-Object Interactions in the Wild
• [cs.CV]Roof-GAN: Learning to Generate Roof Geometry and Relations for Residential Houses
• [cs.CV]S3CNet: A Sparse Semantic Scene Completion Network for LiDAR Point Clouds
• [cs.CV]SceneFormer: Indoor Scene Generation with Transformers
• [cs.CV]Self-Supervised Sketch-to-Image Synthesis
• [cs.CV]Semi-Global Shape-aware Network
• [cs.CV]Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation
• [cs.CV]Sparse Signal Models for Data Augmentation in Deep Learning ATR
• [cs.CV]Taming Transformers for High-Resolution Image Synthesis
• [cs.CV]Temporal LiDAR Frame Prediction for Autonomous Driving
• [cs.CV]Trajectory saliency detection using consistency-oriented latent codes from a recurrent auto-encoder
• [cs.CV]Transformer Interpretability Beyond Attention Visualization
• [cs.CV]Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation
• [cs.CV]Unsupervised Learning of Local Discriminative Representation for Medical Images
• [cs.CV]Weakly-Supervised Action Localization and Action Recognition using Global-Local Attention of 3D CNN
• [cs.CV]Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image
• [cs.CV]Zoom-to-Inpaint: Image Inpainting with High Frequency Details
• [cs.CV]uBAM: Unsupervised Behavior Analysis and Magnification using Deep Learning
• [cs.CY]Infrastructure for Artificial Intelligence, Quantum and High Performance Computing
• [cs.CY]PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols
• [cs.CY]Pandemic Informatics: Preparation, Robustness, and Resilience
• [cs.CY]Realizing the Promise of Automated Exposure Notification (AEN) Technology to Control the Spread of COVID-19: Recommendations for Smartphone App Deployment, Use, and Iterative Assessment
• [cs.DB]Clique: Spatiotemporal Object Re-identification at the City Scale
• [cs.DC]DAG-based Scheduling with Resource Sharing for Multi-task Applications in a Polyglot GPU Runtime
• [cs.DC]Distributed Global Optimization (DGO)
• [cs.DC]Solving large permutation flow-shop scheduling problems on GPU-accelerated supercomputers
• [cs.DC]Towards Smart e-Infrastructures, A Community Driven Approach Based on Real Datasets
• [cs.DS]Enhancing Balanced Graph Edge Partition with Effective Local Search
• [cs.GT]Game-theoretic Models of Moral and Other-Regarding Agents
• [cs.HC]An Integrated Platform for Collaborative Data Analytics
• [cs.IR]A White Box Analysis of ColBERT
• [cs.IR]Adaptive Multi-Agent E-Learning Recommender Systems
• [cs.IR]Causality-Aware Neighborhood Methods for Recommender Systems
• [cs.IR]Checking Fact Worthiness using Sentence Embeddings
• [cs.IT]Advanced NOMA Assisted Semi-Grant-Free Transmission Schemes for Randomly Distributed Users
• [cs.IT]Age of Information Minimization for Heterogenous Transmissions
• [cs.IT]Fast List Decoders for Polarization-Adjusted Convolutional (PAC) Codes
• [cs.IT]Minimizing Age of Information via Scheduling over Heterogeneous Channels
• [cs.IT]Parity Check Codes for Second Order Diversity
• [cs.IT]Trellis Code Error Exponent From Results for Asynchronous Multiple Access Channels
• [cs.LG]A Contrast Synthesized Thalamic Nuclei Segmentation Scheme using Convolutional Neural Networks
• [cs.LG]A Fast Algorithm for Heart Disease Prediction using Bayesian Network Model
• [cs.LG]A Generalization of Transformer Networks to Graphs
• [cs.LG]Are we Forgetting about Compositional Optimisers in Bayesian Optimisation?
• [cs.LG]Characterizing the Evasion Attackability of Multi-label Classifiers
• [cs.LG]Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues
• [cs.LG]Data optimization for large batch distributed training of deep neural networks
• [cs.LG]DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation
• [cs.LG]Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations
• [cs.LG]DenseHMM: Learning Hidden Markov Models by Learning Dense Representations
• [cs.LG]Experts with Lower-Bounded Loss Feedback: A Unifying Framework
• [cs.LG]Few-shot Sequence Learning with Transformers
• [cs.LG]Generate and Verify: Semantically Meaningful Formal Analysis of Neural Network Perception Systems
• [cs.LG]Hardness of Learning Halfspaces with Massart Noise
• [cs.LG]High-Throughput Synchronous Deep RL
• [cs.LG]Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
• [cs.LG]Intrinsically Motivated Goal-Conditioned Reinforcement Learning: a Short Survey
• [cs.LG]Joint Search of Data Augmentation Policies and Network Architectures
• [cs.LG]Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations
• [cs.LG]Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
• [cs.LG]Learning to Solve AC Optimal Power Flow by Differentiating through Holomorphic Embeddings
• [cs.LG]MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning
• [cs.LG]MASKER: Masked Keyword Regularization for Reliable Text Classification
• [cs.LG]Measuring Disentanglement: A Review of Metrics
• [cs.LG]Metrical Task Systems with Online Machine Learned Advice
• [cs.LG]Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL
• [cs.LG]On Episodes, Prototypical Networks, and Few-shot Learning
• [cs.LG]On the Limitations of Denoising Strategies as Adversarial Defenses
• [cs.LG]Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs
• [cs.LG]RainBench: Towards Global Precipitation Forecasting from Satellite Imagery
• [cs.LG]Relational Boosted Bandits
• [cs.LG]Sensitive Data Detection with High-Throughput Neural Network Models for Financial Institutions
• [cs.LG]Series Saliency: Temporal Interpretation for Multivariate Time Series Forecasting
• [cs.LG]Sparsifying networks by traversing Geodesics
• [cs.LG]Stabilizing Q Learning Via Soft Mellowmax Operator
• [cs.LG]Stochastic Compositional Gradient Descent under Compositional constraints
• [cs.LG]TROJANZOO: Everything you ever wanted to know about neural backdoors (but were afraid to ask)
• [cs.LG]Task Uncertainty Loss Reduce Negative Transfer in Asymmetric Multi-task Feature Learning
• [cs.LG]The Variational Method of Moments
• [cs.LG]Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning
• [cs.LG]Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design
• [cs.LG]Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning
• [cs.NE]Deep Learning Techniques for Super-Resolution in Video Games
• [cs.NE]On the performance of deep learning for numerical optimization: an application to protein structure prediction
• [cs.NE]Optimizing the Parameters of A Physical Exercise Dose-Response Model: An Algorithmic Comparison
• [cs.NE]Tag-based Genetic Regulation for Genetic Programming
• [cs.NI]Learning-NUM: Network Utility Maximization with Unknown Utility Functions and Queueing Delay
• [cs.NI]Online Service Migration in Edge Computing with Incomplete Information: A Deep Recurrent Actor-Critic Method
• [cs.RO]Adaptation to Team Composition Changes for Heterogeneous Multi-Robot Sensor Coverage
• [cs.RO]Connectivity Maintenance for Multi-Robot Systems Under Motion and Sensing Uncertainties Using Distributed ADMM-based Trajectory Planning
• [cs.RO]Energy-Constrained Delivery of Goods with Drones Under Varying Wind Conditions
• [cs.RO]Extending the Range of Drone-based Delivery Services by Exploration
• [cs.RO]Game Theoretic Decentralized and Communication-Free Multi-Robot Navigation
• [cs.RO]Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency
• [cs.RO]MSL-RAPTOR: A 6DoF Relative Pose Tracker for Onboard Robotic Perception
• [cs.RO]Multi-FinGAN: Generative Coarse-To-Fine Sampling of Multi-Finger Grasps
• [cs.RO]Muscle-inspired flexible mechanical logic architecture for colloidal robotics
• [cs.RO]Robotics Enabling the Workforce
• [cs.RO]Simultaneous View and Feature Selection for Collaborative Multi-Robot Recognition
• [cs.RO]Team Assignment for Heterogeneous Multi-Robot Sensor Coverage through Graph Representation Learning
• [cs.RO]Trajectory Planning Under Stochastic and Bounded Sensing Uncertainties Using Reachability Analysis
• [cs.RO]ViNG: Learning Open-World Navigation with Visual Goals
• [cs.SD]Automatic source localization and spectra generation from deconvolved beamforming maps
• [cs.SD]The voice of COVID-19: Acoustic correlates of infection
• [cs.SE]The Mind Is a Powerful Place: How Showing Code Comprehensibility Metrics Influences Code Understanding
• [cs.SI]Conspiracy Machines — The Role of Social Bots during the COVID-19 Infodemic
• [cs.SI]Digital Detox — Mitigating Digital Overuse in Times of Remote Work and Social Isolation
• [cs.SI]The COVID-19 Infodemic: Twitter versus Facebook
• [cs.SI]Virtually Extended Coworking Spaces? — The Reinforcement of Social Proximity, Motivation and Knowledge Sharing Through ICT
• [eess.AS]Speech Enhancement with Zero-Shot Model Selection
• [eess.AS]The effectiveness of unsupervised subword modeling with autoregressive and cross-lingual phone-aware networks
• [eess.IV]A new semi-supervised self-training method for lung cancer prediction
• [eess.IV]Describing the Structural Phenotype of the Glaucomatous Optic Nerve Head Using Artificial Intelligence
• [eess.IV]Learned Block-based Hybrid Image Compression
• [eess.IV]Spatial Context-Aware Self-Attention Model For Multi-Organ Segmentation
• [eess.IV]Transfer Learning Through Weighted Loss Function and Group Normalization for Vessel Segmentation from Retinal Images
• [eess.SP]Reduction in the complexity of 1D 1H-NMR spectra by the use of Frequency to Information Transformation
• [eess.SY]Towards Optimal District Heating Temperature Control in China with Deep Reinforcement Learning
• [eess.SY]Uncertainty Quantification in Case of Imperfect Models: A Review
• [math.OC]Clustering with Iterated Linear Optimization
• [math.PR]Nearly optimal central limit theorem and bootstrap approximations in high dimensions
• [math.PR]On the fractional queueing model with catastrophes
• [math.ST]A geometric investigation into the tail dependence of vine copulas
• [math.ST]Asymptotic normality of wavelet covariances and of multivariate wavelet Whittle estimators
• [math.ST]Nonparametric Two-Sample Hypothesis Testing for Random Graphs with Negative and Repeated Eigenvalues
• [physics.data-an]Image-Based Jet Analysis
• [physics.data-an]Maximum Entropy competes with Maximum Likelihood
• [q-bio.QM]Distance-aware Molecule Graph Attention Network for Drug-Target Binding Affinity Prediction
• [quant-ph]Compiler Design for Distributed Quantum Computing
• [quant-ph]On the experimental feasibility of quantum state reconstruction via machine learning
• [quant-ph]Variational Quantum Algorithms
• [stat.AP]Detection of data drift and outliers affecting machine learning model performance over time
• [stat.AP]Network Hawkes Process Models for Exploring Latent Hierarchy in Social Animal Interactions
• [stat.AP]Richness estimation with species identity error
• [stat.AP]Selection of multiple donor gauges via Graphical Lasso for estimation of daily streamflow time series
• [stat.CO]A fresh take on ‘Barker dynamics’ for MCMC
• [stat.CO]High-resolution Probabilistic Precipitation Prediction for use in Climate Simulations
• [stat.ME]Bayesian semiparametric modelling of covariance matrices for multivariate longitudinal data
• [stat.ME]Differential privacy and noisy confidentiality concepts for European population statistics
• [stat.ME]Fast estimation of a convolution type model for the intensity of spatial point processes
• [stat.ME]No-harm calibration for generalized Oaxaca-Blinder estimators
• [stat.ME]Non-parametric estimation of Expectation and Variance of event count and of incidence rate in a recurrent process — where intensity of event-occurrence changes with the occurrence of each higher order event
• [stat.ME]The Causal Learning of Retail Delinquency
• [stat.ME]l1-norm quantile regression screening rule via the dual circumscribed sphere
• [stat.ML]Balancing Geometry and Density: Path Distances on High-Dimensional Data
• [stat.ML]Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection
• [stat.ML]Estimating mixed-memberships using the Symmetric Laplacian Inverse Matrix
• [stat.ML]Optimal transport for vector Gaussian mixture models
• [stat.ML]Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets
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• [astro-ph.GA]StarcNet: Machine Learning for Star Cluster Identification
Gustavo Perez, Matteo Messa, Daniela Calzetti, Subhransu Maji, Dooseok Jung, Angela Adamo, Mattia Siressi
http://arxiv.org/abs/2012.09327v1
• [astro-ph.IM]SRoll3: A neural network approach to reduce large-scale systematic effects in the Planck High Frequency Instrument maps
Manuel López-Radcenco, Jean-Marc Delouis, Laurent Vibert
http://arxiv.org/abs/2012.09702v1
• [cond-mat.mtrl-sci]Computational discovery of new 2D materials using deep learning generative models
Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Jianjun Hu
http://arxiv.org/abs/2012.09314v1
• [cs.AI]Applying Deutsch’s concept of good explanations to artificial intelligence and neuroscience — an initial exploration
Daniel C. Elton
http://arxiv.org/abs/2012.09318v1
• [cs.AI]Computational principles of intelligence: learning and reasoning with neural networks
Abel Torres Montoya
http://arxiv.org/abs/2012.09477v1
• [cs.AI]Helping Reduce Environmental Impact of Aviation with Machine Learning
Ashish Kapoor
http://arxiv.org/abs/2012.09433v1
• [cs.AI]On Exploiting Hitting Sets for Model Reconciliation
Stylianos Loukas Vasileiou, Alessandro Previti, William Yeoh
http://arxiv.org/abs/2012.09274v1
• [cs.AI]Predicting Events In MOBA Games: Dataset, Attribution, and Evaluation
Zelong Yang, Yan Wang, Piji Li, Shaobin Lin, Shuming Shi, Shao-Lun Huang
http://arxiv.org/abs/2012.09424v1
• [cs.AI]XAI-P-T: A Brief Review of Explainable Artificial Intelligence from Practice to Theory
Nazanin Fouladgar, Kary Främling
http://arxiv.org/abs/2012.09636v1
• [cs.AR]SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning
Hanrui Wang, Zhekai Zhang, Song Han
http://arxiv.org/abs/2012.09852v1
• [cs.CL]Assessing COVID-19 Impacts on College Students via Automated Processing of Free-form Text
Ravi Sharma, Sri Divya Pagadala, Pratool Bharti, Sriram Chellappan, Trine Schmidt, Raj Goyal
http://arxiv.org/abs/2012.09369v1
• [cs.CL]BERT Goes Shopping: Comparing Distributional Models for Product Representations
Federico Bianchi, Bingqing Yu, Jacopo Tagliabue
http://arxiv.org/abs/2012.09807v1
• [cs.CL]Benchmarking Automatic Detection of Psycholinguistic Characteristics for Better Human-Computer Interaction
Sanja Stajner, Seren Yenikent, Marc Franco-Salvador
http://arxiv.org/abs/2012.09692v1
• [cs.CL]Continual Lifelong Learning in Natural Language Processing: A Survey
Magdalena Biesialska, Katarzyna Biesialska, Marta R. Costa-jussà
http://arxiv.org/abs/2012.09823v1
• [cs.CL]Do You Do Yoga? Understanding Twitter Users’ Types and Motivations using Social and Textual Information
Tunazzina Islam, Dan Goldwasser
http://arxiv.org/abs/2012.09332v1
• [cs.CL]Exploring Thematic Coherence in Fake News
Martins Samuel Dogo, Deepak P, Anna Jurek-Loughrey
http://arxiv.org/abs/2012.09118v2
• [cs.CL]Hate Speech detection in the Bengali language: A dataset and its baseline evaluation
Nauros Romim, Mosahed Ahmed, Hriteshwar Talukder, Md Saiful Islam
http://arxiv.org/abs/2012.09686v1
• [cs.CL]InSRL: A Multi-view Learning Framework Fusing Multiple Information Sources for Distantly-supervised Relation Extraction
Zhendong Chu, Haiyun Jiang, Yanghua Xiao, Wei Wang
http://arxiv.org/abs/2012.09370v1
• [cs.CL]Interactive Question Clarification in Dialogue via Reinforcement Learning
Xiang Hu, Zujie Wen, Yafang Wang, Xiaolong Li, Gerard de Melo
http://arxiv.org/abs/2012.09411v1
• [cs.CL]Literature Retrieval for Precision Medicine with Neural Matching and Faceted Summarization
Jiho Noh, Ramakanth Kavuluru
http://arxiv.org/abs/2012.09355v1
• [cs.CL]MELINDA: A Multimodal Dataset for Biomedical Experiment Method Classification
Te-Lin Wu, Shikhar Singh, Sayan Paul, Gully Burns, Nanyun Peng
http://arxiv.org/abs/2012.09216v1
• [cs.CL]MIX : a Multi-task Learning Approach to Solve Open-Domain Question Answering
Sofian Chaybouti, Achraf Saghe, Aymen Shabou
http://arxiv.org/abs/2012.09766v1
• [cs.CL]ReferentialGym: A Nomenclature and Framework for Language Emergence & Grounding in (Visual) Referential Games
Kevin Denamganaï, James Alfred Walker
http://arxiv.org/abs/2012.09486v1
• [cs.CL]Ultra-Fast, Low-Storage, Highly Effective Coarse-grained Selection in Retrieval-based Chatbot by Using Deep Semantic Hashing
Tian Lan, Xian-Ling Mao, Xiao-yan Gao, He-Yan Huang
http://arxiv.org/abs/2012.09647v1
• [cs.CL]Unsupervised Learning of Discourse Structures using a Tree Autoencoder
Patrick Huber, Giuseppe Carenini
http://arxiv.org/abs/2012.09446v1
• [cs.CL]cif-based collaborative decoding for end-to-end contextual speech recognition
Minglun Han, Linhao Dong, Shiyu Zhou, Bo Xu
http://arxiv.org/abs/2012.09466v1
• [cs.CR]Beyond the Hype: A Real-World Evaluation of the Impact and Cost of Machine Learning—Based Malware Detection
Robert A. Bridges, Sean Oesch, Miki E. Verma, Michael D. Iannacone, Kelly M. T. Huffer, Brian Jewell, Jeff A. Nichols, Brian Weber, Justin M. Beaver, Jared M. Smith, Daniel Scofield, Craig Miles, Thomas Plummer, Mark Daniell, Anne M. Tall
http://arxiv.org/abs/2012.09214v1
• [cs.CR]KHOVID: Interoperable Privacy Preserving Digital Contact Tracing
Xiang Cheng, Hanchao Yang, Archanaa S Krishnan, Patrick Schaumont, Yaling Yang
http://arxiv.org/abs/2012.09375v1
• [cs.CR]Machine Learning for Detecting Data Exfiltration
Bushra Sabir, Faheem Ullah, M. Ali Babar, Raj Gaire
http://arxiv.org/abs/2012.09344v1
• [cs.CV]$\mathbb{X}$Resolution Correspondence Networks
Georgi Tinchev, Shuda Li, Kai Han, David Mitchell, Rigas Kouskouridas
http://arxiv.org/abs/2012.09842v1
• [cs.CV]A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks
Qingsong Yao, Zecheng He, Yi Lin, Kai Ma, Yefeng Zheng, S. Kevin Zhou
http://arxiv.org/abs/2012.09501v1
• [cs.CV]A fully pipelined FPGA accelerator for scale invariant feature transform keypoint descriptor matching,
Luka Daoud, Muhammad Kamran Latif, H S. Jacinto, Nader Rafla
http://arxiv.org/abs/2012.09666v1
• [cs.CV]AutoCaption: Image Captioning with Neural Architecture Search
Xinxin Zhu, Weining Wang, Longteng Guo, Jing Liu
http://arxiv.org/abs/2012.09742v1
• [cs.CV]CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models
Quan Quan, Qiyuan Wang, Liu Li, Yuanqi Du, S. Kevin Zhou
http://arxiv.org/abs/2012.09491v1
• [cs.CV]Computation-Efficient Knowledge Distillation via Uncertainty-Aware Mixup
Guodong Xu, Ziwei Liu, Chen Change Loy
http://arxiv.org/abs/2012.09413v1
• [cs.CV]Detection and Prediction of Nutrient Deficiency Stress using Longitudinal Aerial Imagery
Saba Dadsetan, Gisele Rose, Naira Hovakimyan, Jennifer Hobbs
http://arxiv.org/abs/2012.09654v1
• [cs.CV]Efficient CNN-LSTM based Image Captioning using Neural Network Compression
Harshit Rampal, Aman Mohanty
http://arxiv.org/abs/2012.09708v1
• [cs.CV]Efficient Golf Ball Detection and Tracking Based on Convolutional Neural Networks and Kalman Filter
Tianxiao Zhang, Xiaohan Zhang, Yiju Yang, Zongbo Wang, Guanghui Wang
http://arxiv.org/abs/2012.09393v1
• [cs.CV]Embodied Visual Active Learning for Semantic Segmentation
David Nilsson, Aleksis Pirinen, Erik Gärtner, Cristian Sminchisescu
http://arxiv.org/abs/2012.09503v1
• [cs.CV]End-to-End Human Pose and Mesh Reconstruction with Transformers
Kevin Lin, Lijuan Wang, Zicheng Liu
http://arxiv.org/abs/2012.09760v1
• [cs.CV]End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box
Vladislav Belyaev, Aleksandra Malysheva, Aleksei Shpilman
http://arxiv.org/abs/2012.09771v1
• [cs.CV]Event Camera Calibration of Per-pixel Biased Contrast Threshold
Ziwei Wang, Yonhon Ng, Pieter van Goor, Robert Mahony
http://arxiv.org/abs/2012.09378v1
• [cs.CV]Exploiting Learnable Joint Groups for Hand Pose Estimation
Moran Li, Yuan Gao, Nong Sang
http://arxiv.org/abs/2012.09496v1
• [cs.CV]Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification
Kecheng Zheng, Cuiling Lan, Wenjun Zeng, Zhizheng Zhang, Zheng-Jun Zha
http://arxiv.org/abs/2012.08733v2
• [cs.CV]FG-Net: Fast Large-Scale LiDAR Point CloudsUnderstanding Network Leveraging CorrelatedFeature Mining and Geometric-Aware Modelling
Kangcheng Liu, Zhi Gao, Feng Lin, Ben M. Chen
http://arxiv.org/abs/2012.09439v1
• [cs.CV]Firearm Detection via Convolutional Neural Networks: Comparing a Semantic Segmentation Model Against End-to-End Solutions
Alexander Egiazarov, Fabio Massimo Zennaro, Vasileios Mavroeidis
http://arxiv.org/abs/2012.09662v1
• [cs.CV]Human Mesh Recovery from Multiple Shots
Georgios Pavlakos, Jitendra Malik, Angjoo Kanazawa
http://arxiv.org/abs/2012.09843v1
• [cs.CV]ISD: Self-Supervised Learning by Iterative Similarity Distillation
Ajinkya Tejankar, Soroush Abbasi Koohpayegani, Vipin Pillai, Paolo Favaro, Hamed Pirsiavash
http://arxiv.org/abs/2012.09259v1
• [cs.CV]Incremental Learning from Low-labelled Stream Data in Open-Set Video Face Recognition
Eric Lopez-Lopez, Carlos V. Regueiro, Xose M. Pardo
http://arxiv.org/abs/2012.09571v1
• [cs.CV]Infinite Nature: Perpetual View Generation of Natural Scenes from a Single Image
Andrew Liu, Richard Tucker, Varun Jampani, Ameesh Makadia, Noah Snavely, Angjoo Kanazawa
http://arxiv.org/abs/2012.09855v1
• [cs.CV]Interpretable Image Clustering via Diffeomorphism-Aware K-Means
Romain Cosentino, Randall Balestriero, Yanis Bahroun, Anirvan Sengupta, Richard Baraniuk, Behnaam Aazhang
http://arxiv.org/abs/2012.09743v1
• [cs.CV]Invariant Teacher and Equivariant Student for Unsupervised 3D Human Pose Estimation
Chenxin Xu, Siheng Chen, Maosen Li, Ya Zhang
http://arxiv.org/abs/2012.09398v1
• [cs.CV]LIGHTEN: Learning Interactions with Graph and Hierarchical TEmporal Networks for HOI in videos
Sai Praneeth Reddy Sunkesula, Rishabh Dabral, Ganesh Ramakrishnan
http://arxiv.org/abs/2012.09402v1
• [cs.CV]Learning to Recognize Patch-Wise Consistency for Deepfake Detection
Tianchen Zhao, Xiang Xu, Mingze Xu, Hui Ding, Yuanjun Xiong, Wei Xia
http://arxiv.org/abs/2012.09311v1
• [cs.CV]Learning to Recover 3D Scene Shape from a Single Image
Wei Yin, Jianming Zhang, Oliver Wang, Simon Niklaus, Long Mai, Simon Chen, Chunhua Shen
http://arxiv.org/abs/2012.09365v1
• [cs.CV]Learning to Share: A Multitasking Genetic Programming Approach to Image Feature Learning
Ying Bi, Bing Xue, Mengjie Zhang
http://arxiv.org/abs/2012.09444v1
• [cs.CV]Multi-Modal Depth Estimation Using Convolutional Neural Networks
Sadique Adnan Siddiqui, Axel Vierling, Karsten Berns
http://arxiv.org/abs/2012.09667v1
• [cs.CV]Multi-shot Temporal Event Localization: a Benchmark
Xiaolong Liu, Yao Hu, Song Bai, Fei Ding, Xiang Bai, Philip H. S. Torr
http://arxiv.org/abs/2012.09434v1
• [cs.CV]Neural Pruning via Growing Regularization
Huan Wang, Can Qin, Yulun Zhang, Yun Fu
http://arxiv.org/abs/2012.09243v1
• [cs.CV]Neural Radiance Flow for 4D View Synthesis and Video Processing
Yilun Du, Yinan Zhang, Hong-Xing Yu, Joshua B. Tenenbaum, Jiajun Wu
http://arxiv.org/abs/2012.09790v1
• [cs.CV]PCT: Point Cloud Transformer
Meng-Hao Guo, Jun-Xiong Cai, Zheng-Ning Liu, Tai-Jiang Mu, Ralph R. Martin, Shi-Min Hu
http://arxiv.org/abs/2012.09688v1
• [cs.CV]PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection
Xia Chen, Jianren Wang, David Held, Martial Hebert
http://arxiv.org/abs/2012.09418v1
• [cs.CV]Polyblur: Removing mild blur by polynomial reblurring
Mauricio Delbracio, Ignacio Garcia-Dorado, Sungjoon Choi, Damien Kelly, Peyman Milanfar
http://arxiv.org/abs/2012.09322v1
• [cs.CV]Projected Distribution Loss for Image Enhancement
Mauricio Delbracio, Hossein Talebi, Peyman Milanfar
http://arxiv.org/abs/2012.09289v1
• [cs.CV]RainNet: A Large-Scale Dataset for Spatial Precipitation Downscaling
Xuanhong Chen, Kairui Feng, Naiyuan Liu, Naiyuan Liu, Zhengyan Tong, Bingbing Ni, Ziang Liu, Ning Lin
http://arxiv.org/abs/2012.09700v1
• [cs.CV]Reconstructing Hand-Object Interactions in the Wild
Zhe Cao, Ilija Radosavovic, Angjoo Kanazawa, Jitendra Malik
http://arxiv.org/abs/2012.09856v1
• [cs.CV]Roof-GAN: Learning to Generate Roof Geometry and Relations for Residential Houses
Yiming Qian, Hao Zhang, Yasutaka Furukawa
http://arxiv.org/abs/2012.09340v1
• [cs.CV]S3CNet: A Sparse Semantic Scene Completion Network for LiDAR Point Clouds
Ran Cheng, Christopher Agia, Yuan Ren, Xinhai Li, Liu Bingbing
http://arxiv.org/abs/2012.09242v1
• [cs.CV]SceneFormer: Indoor Scene Generation with Transformers
Xinpeng Wang, Chandan Yeshwanth, Matthias Nießner
http://arxiv.org/abs/2012.09793v1
• [cs.CV]Self-Supervised Sketch-to-Image Synthesis
Bingchen Liu, Yizhe Zhu, Kunpeng Song, Ahmed Elgammal
http://arxiv.org/abs/2012.09290v1
• [cs.CV]Semi-Global Shape-aware Network
Pengju Zhang, Yihong Wu, Jiagang Zhu
http://arxiv.org/abs/2012.09372v1
• [cs.CV]Shape My Face: Registering 3D Face Scans by Surface-to-Surface Translation
Mehdi Bahri, Eimear O’ Sullivan, Shunwang Gong, Feng Liu, Xiaoming Liu, Michael M. Bronstein, Stefanos Zafeiriou
http://arxiv.org/abs/2012.09235v1
• [cs.CV]Sparse Signal Models for Data Augmentation in Deep Learning ATR
Tushar Agarwal, Nithin Sugavanam, Emre Ertin
http://arxiv.org/abs/2012.09284v1
• [cs.CV]Taming Transformers for High-Resolution Image Synthesis
Patrick Esser, Robin Rombach, Björn Ommer
http://arxiv.org/abs/2012.09841v1
• [cs.CV]Temporal LiDAR Frame Prediction for Autonomous Driving
David Deng, Avideh Zakhor
http://arxiv.org/abs/2012.09409v1
• [cs.CV]Trajectory saliency detection using consistency-oriented latent codes from a recurrent auto-encoder
L. Maczyta, P. Bouthemy, O. Le Meur
http://arxiv.org/abs/2012.09573v1
• [cs.CV]Transformer Interpretability Beyond Attention Visualization
Hila Chefer, Shir Gur, Lior Wolf
http://arxiv.org/abs/2012.09838v1
• [cs.CV]Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation
Hongxiao Wang, Hao Zheng, Jianxu Chen, Lin Yang, Yizhe Zhang, Danny Z. Chen
http://arxiv.org/abs/2012.09373v1
• [cs.CV]Unsupervised Learning of Local Discriminative Representation for Medical Images
Huai Chen, Jieyu Li, Renzhen Wang, Yijie Huang, Fanrui Meng, Deyu Meng, Qing Peng, Lisheng Wang
http://arxiv.org/abs/2012.09333v1
• [cs.CV]Weakly-Supervised Action Localization and Action Recognition using Global-Local Attention of 3D CNN
Novanto Yudistira, Muthu Subash Kavitha, Takio Kurita
http://arxiv.org/abs/2012.09542v1
• [cs.CV]Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image
Ronghang Hu, Deepak Pathak
http://arxiv.org/abs/2012.09854v1
• [cs.CV]Zoom-to-Inpaint: Image Inpainting with High Frequency Details
Soo Ye Kim, Kfir Aberman, Nori Kanazawa, Rahul Garg, Neal Wadhwa, Huiwen Chang, Nikhil Karnad, Munchurl Kim, Orly Liba
http://arxiv.org/abs/2012.09401v1
• [cs.CV]uBAM: Unsupervised Behavior Analysis and Magnification using Deep Learning
Biagio Brattoli, Uta Buechler, Michael Dorkenwald, Philipp Reiser, Linard Filli, Fritjof Helmchen, Anna-Sophia Wahl, Bjoern Ommer
http://arxiv.org/abs/2012.09237v1
• [cs.CY]Infrastructure for Artificial Intelligence, Quantum and High Performance Computing
William Gropp, Sujata Banerjee, Ian Foster
http://arxiv.org/abs/2012.09303v1
• [cs.CY]PURE: A Framework for Analyzing Proximity-based Contact Tracing Protocols
Fabrizio Cicala, Weicheng Wang, Tianhao Wang, Ninghui Li, Elisa Bertino, Faming Liang, Yang Yang
http://arxiv.org/abs/2012.09520v1
• [cs.CY]Pandemic Informatics: Preparation, Robustness, and Resilience
Elizabeth Bradley, Madhav Marathe, Melanie Moses, William D Gropp, Daniel Lopresti
http://arxiv.org/abs/2012.09300v1
• [cs.CY]Realizing the Promise of Automated Exposure Notification (AEN) Technology to Control the Spread of COVID-19: Recommendations for Smartphone App Deployment, Use, and Iterative Assessment
Jesslyn Alekseyev, Erica Dixon, Vilhelm L Andersen Woltz, Danny Weitzner
http://arxiv.org/abs/2012.09232v1
• [cs.DB]Clique: Spatiotemporal Object Re-identification at the City Scale
Tiantu Xu, Kaiwen Shen, Yang Fu, Humphrey Shi, Felix Xiaozhu Lin
http://arxiv.org/abs/2012.09329v1
• [cs.DC]DAG-based Scheduling with Resource Sharing for Multi-task Applications in a Polyglot GPU Runtime
Alberto Parravicini, Arnaud Delamare, Marco Arnaboldi, Marco D. Santambrogio
http://arxiv.org/abs/2012.09646v1
• [cs.DC]Distributed Global Optimization (DGO)
Homayoun Valafar, Okan K. Ersoy, Faramarz Valafar
http://arxiv.org/abs/2012.09252v1
• [cs.DC]Solving large permutation flow-shop scheduling problems on GPU-accelerated supercomputers
Jan Gmys
http://arxiv.org/abs/2012.09511v1
• [cs.DC]Towards Smart e-Infrastructures, A Community Driven Approach Based on Real Datasets
Prashant Singh, Mona Mohamed Elamin, Salman Toor
http://arxiv.org/abs/2012.09579v1
• [cs.DS]Enhancing Balanced Graph Edge Partition with Effective Local Search
Zhenyu Guo, Mingyu Xiao, Yi Zhou, Dongxiang Zhang, Kian-Lee Tan
http://arxiv.org/abs/2012.09451v1
• [cs.GT]Game-theoretic Models of Moral and Other-Regarding Agents
Gabriel Istrate
http://arxiv.org/abs/2012.09759v1
• [cs.HC]An Integrated Platform for Collaborative Data Analytics
Sean Oesch, Rob Gillen, Tom Karnowski
http://arxiv.org/abs/2012.09244v1
• [cs.IR]A White Box Analysis of ColBERT
Thibault Formal, Benjamin Piwowarski, Stéphane Clinchant
http://arxiv.org/abs/2012.09650v1
• [cs.IR]Adaptive Multi-Agent E-Learning Recommender Systems
Nethra Viswanathan
http://arxiv.org/abs/2012.09342v1
• [cs.IR]Causality-Aware Neighborhood Methods for Recommender Systems
Masahiro Sato, Sho Takemori, Janmajay Singh, Qian Zhang
http://arxiv.org/abs/2012.09442v1
• [cs.IR]Checking Fact Worthiness using Sentence Embeddings
Sidharth Singla
http://arxiv.org/abs/2012.09263v1
• [cs.IT]Advanced NOMA Assisted Semi-Grant-Free Transmission Schemes for Randomly Distributed Users
Huabing Lu, Xianzhong Xie, Zhaoyuan Shi, Hongjiang Lei, Helin Yang, Jun Cai
http://arxiv.org/abs/2012.09423v1
• [cs.IT]Age of Information Minimization for Heterogenous Transmissions
Guidan Yao, Ahmed M. Bedewy, Ness B. Shroff
http://arxiv.org/abs/2012.09351v1
• [cs.IT]Fast List Decoders for Polarization-Adjusted Convolutional (PAC) Codes
Hongfei Zhu, Zhiwei Cao, Yuping Zhao, Dou Li, Yanjun Yang, Yiru Wang, Zongren Guo
http://arxiv.org/abs/2012.09425v1
• [cs.IT]Minimizing Age of Information via Scheduling over Heterogeneous Channels
Jiayu Pan, Ahmed M. Bedewy, Yin Sun, Ness B. Shroff
http://arxiv.org/abs/2012.09403v1
• [cs.IT]Parity Check Codes for Second Order Diversity
Aaqib A. Patel, Abdul Mateen Ahmed, Mohammed Zafar Ali Khan
http://arxiv.org/abs/2012.09497v1
• [cs.IT]Trellis Code Error Exponent From Results for Asynchronous Multiple Access Channels
Lóránt Farkas
http://arxiv.org/abs/2012.09705v1
• [cs.LG]A Contrast Synthesized Thalamic Nuclei Segmentation Scheme using Convolutional Neural Networks
Lavanya Umapathy, Mahesh Bharath Keerthivasan, Natalie M. Zahr, Ali Bilgin, Manojkumar Saranathan
http://arxiv.org/abs/2012.09386v1
• [cs.LG]A Fast Algorithm for Heart Disease Prediction using Bayesian Network Model
Mistura Muibideen, Rajesh Prasad
http://arxiv.org/abs/2012.09429v1
• [cs.LG]A Generalization of Transformer Networks to Graphs
Vijay Prakash Dwivedi, Xavier Bresson
http://arxiv.org/abs/2012.09699v1
• [cs.LG]Are we Forgetting about Compositional Optimisers in Bayesian Optimisation?
Antoine Grosnit, Alexander I. Cowen-Rivers, Rasul Tutunov, Ryan-Rhys Griffiths, Jun Wang, Haitham Bou-Ammar
http://arxiv.org/abs/2012.08240v2
• [cs.LG]Characterizing the Evasion Attackability of Multi-label Classifiers
Zhuo Yang, Yufei Han, Xiangliang Zhang
http://arxiv.org/abs/2012.09427v1
• [cs.LG]Combating Mode Collapse in GAN training: An Empirical Analysis using Hessian Eigenvalues
Ricard Durall, Avraam Chatzimichailidis, Peter Labus, Janis Keuper
http://arxiv.org/abs/2012.09673v1
• [cs.LG]Data optimization for large batch distributed training of deep neural networks
Shubhankar Gahlot, Junqi Yin, Mallikarjun, Shankar
http://arxiv.org/abs/2012.09272v1
• [cs.LG]DecAug: Out-of-Distribution Generalization via Decomposed Feature Representation and Semantic Augmentation
Haoyue Bai, Rui Sun, Lanqing Hong, Fengwei Zhou, Nanyang Ye, Han-Jia Ye, S. -H. Gary Chan, Zhenguo Li
http://arxiv.org/abs/2012.09382v1
• [cs.LG]Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations
Cynthia Shen, Mario Krenn, Sagi Eppel, Alan Aspuru-Guzik
http://arxiv.org/abs/2012.09712v1
• [cs.LG]DenseHMM: Learning Hidden Markov Models by Learning Dense Representations
Joachim Sicking, Maximilian Pintz, Maram Akila, Tim Wirtz
http://arxiv.org/abs/2012.09783v1
• [cs.LG]Experts with Lower-Bounded Loss Feedback: A Unifying Framework
Eyal Gofer, Guy Gilboa
http://arxiv.org/abs/2012.09537v1
• [cs.LG]Few-shot Sequence Learning with Transformers
Lajanugen Logeswaran, Ann Lee, Myle Ott, Honglak Lee, Marc’Aurelio Ranzato, Arthur Szlam
http://arxiv.org/abs/2012.09543v1
• [cs.LG]Generate and Verify: Semantically Meaningful Formal Analysis of Neural Network Perception Systems
Chris R. Serrano, Pape M. Sylla, Michael A. Warren
http://arxiv.org/abs/2012.09313v1
• [cs.LG]Hardness of Learning Halfspaces with Massart Noise
Ilias Diakonikolas, Daniel M. Kane
http://arxiv.org/abs/2012.09720v1
• [cs.LG]High-Throughput Synchronous Deep RL
Iou-Jen Liu, Raymond A. Yeh, Alexander G. Schwing
http://arxiv.org/abs/2012.09849v1
• [cs.LG]Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Haoyi Zhou, Shanghang Zhang, Jieqi Peng, Shuai Zhang, Jianxin Li, Hui Xiong, Wancai Zhang
http://arxiv.org/abs/2012.07436v2
• [cs.LG]Intrinsically Motivated Goal-Conditioned Reinforcement Learning: a Short Survey
Cédric Colas, Tristan Karch, Olivier Sigaud, Pierre-Yves Oudeyer
http://arxiv.org/abs/2012.09830v1
• [cs.LG]Joint Search of Data Augmentation Policies and Network Architectures
Taiga Kashima, Yoshihiro Yamada, Shunta Saito
http://arxiv.org/abs/2012.09407v1
• [cs.LG]Latent-CF: A Simple Baseline for Reverse Counterfactual Explanations
Rachana Balasubramanian, Samuel Sharpe, Brian Barr, Jason Wittenbach, C. Bayan Bruss
http://arxiv.org/abs/2012.09301v1
• [cs.LG]Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning
Matthieu Zimmer, Umer Siddique, Paul Weng
http://arxiv.org/abs/2012.09421v1
• [cs.LG]Learning to Solve AC Optimal Power Flow by Differentiating through Holomorphic Embeddings
Henning Lange, Bingqing Chen, Mario Berges, Soummya Kar
http://arxiv.org/abs/2012.09622v1
• [cs.LG]MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning
Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
http://arxiv.org/abs/2012.09762v1
• [cs.LG]MASKER: Masked Keyword Regularization for Reliable Text Classification
Seung Jun Moon, Sangwoo Mo, Kimin Lee, Jaeho Lee, Jinwoo Shin
http://arxiv.org/abs/2012.09392v1
• [cs.LG]Measuring Disentanglement: A Review of Metrics
Julian Zaidi, Jonathan Boilard, Ghyslain Gagnon, Marc-André Carbonneau
http://arxiv.org/abs/2012.09276v1
• [cs.LG]Metrical Task Systems with Online Machine Learned Advice
Kevin Rao
http://arxiv.org/abs/2012.09394v1
• [cs.LG]Model-free and Bayesian Ensembling Model-based Deep Reinforcement Learning for Particle Accelerator Control Demonstrated on the FERMI FEL
Simon Hirlaender, Niky Bruchon
http://arxiv.org/abs/2012.09737v1
• [cs.LG]On Episodes, Prototypical Networks, and Few-shot Learning
Steinar Laenen, Luca Bertinetto
http://arxiv.org/abs/2012.09831v1
• [cs.LG]On the Limitations of Denoising Strategies as Adversarial Defenses
Zhonghan Niu, Zhaoxi Chen, Linyi Li, Yubin Yang, Bo Li, Jinfeng Yi
http://arxiv.org/abs/2012.09384v1
• [cs.LG]Polynomial-Time Algorithms for Counting and Sampling Markov Equivalent DAGs
Marcel Wienöbst, Max Bannach, Maciej Liśkiewicz
http://arxiv.org/abs/2012.09679v1
• [cs.LG]RainBench: Towards Global Precipitation Forecasting from Satellite Imagery
Christian Schroeder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Freddie Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski
http://arxiv.org/abs/2012.09670v1
• [cs.LG]Relational Boosted Bandits
Ashutosh Kakadiya, Sriraam Natarajan, Balaraman Ravindran
http://arxiv.org/abs/2012.09220v1
• [cs.LG]Sensitive Data Detection with High-Throughput Neural Network Models for Financial Institutions
Anh Truong, Austin Walters, Jeremy Goodsitt
http://arxiv.org/abs/2012.09597v1
• [cs.LG]Series Saliency: Temporal Interpretation for Multivariate Time Series Forecasting
Qingyi Pan, Wenbo Hu, Jun Zhu
http://arxiv.org/abs/2012.09324v1
• [cs.LG]Sparsifying networks by traversing Geodesics
Guruprasad Raghavan, Matt Thomson
http://arxiv.org/abs/2012.09605v1
• [cs.LG]Stabilizing Q Learning Via Soft Mellowmax Operator
Yaozhong Gan, Zhe Zhang, Xiaoyang Tan
http://arxiv.org/abs/2012.09456v1
• [cs.LG]Stochastic Compositional Gradient Descent under Compositional constraints
Srujan Teja Thomdapu, Harshvardhan, Ketan Rajawat
http://arxiv.org/abs/2012.09400v1
• [cs.LG]TROJANZOO: Everything you ever wanted to know about neural backdoors (but were afraid to ask)
Ren Pang, Zheng Zhang, Xiangshan Gao, Zhaohan Xi, Shouling Ji, Peng Cheng, Ting Wang
http://arxiv.org/abs/2012.09302v1
• [cs.LG]Task Uncertainty Loss Reduce Negative Transfer in Asymmetric Multi-task Feature Learning
Rafael Peres da Silva, Chayaporn Suphavilai, Niranjan Nagarajan
http://arxiv.org/abs/2012.09575v1
• [cs.LG]The Variational Method of Moments
Andrew Bennett, Nathan Kallus
http://arxiv.org/abs/2012.09422v1
• [cs.LG]Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning
Zhiyuan Li, Yuping Luo, Kaifeng Lyu
http://arxiv.org/abs/2012.09839v1
• [cs.LG]Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design
Chaochao Chen, Jun Zhou, Longfei Zheng, Yan Wang, Xiaolin Zheng, Bingzhe Wu, Cen Chen, Li Wang, Jianwei Yin
http://arxiv.org/abs/2012.09364v1
• [cs.LG]Towards Understanding Ensemble, Knowledge Distillation and Self-Distillation in Deep Learning
Zeyuan Allen-Zhu, Yuanzhi Li
http://arxiv.org/abs/2012.09816v1
• [cs.NE]Deep Learning Techniques for Super-Resolution in Video Games
Alexander Watson
http://arxiv.org/abs/2012.09810v1
• [cs.NE]On the performance of deep learning for numerical optimization: an application to protein structure prediction
Hojjat Rakhshani, Lhassane Idoumghar, Soheila Ghambari, Julien Lepagnot, Mathieu Brévilliers
http://arxiv.org/abs/2012.09741v1
• [cs.NE]Optimizing the Parameters of A Physical Exercise Dose-Response Model: An Algorithmic Comparison
Mark Connor, Michael O’Neill
http://arxiv.org/abs/2012.09287v1
• [cs.NE]Tag-based Genetic Regulation for Genetic Programming
Alexander Lalejini, Matthew Andres Moreno, Charles Ofria
http://arxiv.org/abs/2012.09229v1
• [cs.NI]Learning-NUM: Network Utility Maximization with Unknown Utility Functions and Queueing Delay
Xinzhe Fu, Eytan Modiano
http://arxiv.org/abs/2012.09222v1
• [cs.NI]Online Service Migration in Edge Computing with Incomplete Information: A Deep Recurrent Actor-Critic Method
Jin Wang, Jia Hu, Geyong Min
http://arxiv.org/abs/2012.08679v2
• [cs.RO]Adaptation to Team Composition Changes for Heterogeneous Multi-Robot Sensor Coverage
Brian Reily, Terran Mott, Hao Zhang
http://arxiv.org/abs/2012.09334v1
• [cs.RO]Connectivity Maintenance for Multi-Robot Systems Under Motion and Sensing Uncertainties Using Distributed ADMM-based Trajectory Planning
Akshay Shetty, Derek Knowles, Grace Xingxin Gao
http://arxiv.org/abs/2012.09808v1
• [cs.RO]Energy-Constrained Delivery of Goods with Drones Under Varying Wind Conditions
Francesco Betti Sorbelli, Federico Corò, Sajal K. Das, Cristina M. Pinotti
http://arxiv.org/abs/2012.08602v2
• [cs.RO]Extending the Range of Drone-based Delivery Services by Exploration
Tsz-Chiu Au
http://arxiv.org/abs/2012.09367v1
• [cs.RO]Game Theoretic Decentralized and Communication-Free Multi-Robot Navigation
Brian Reily, Terran Mott, Hao Zhang
http://arxiv.org/abs/2012.09335v1
• [cs.RO]Learning Cross-Domain Correspondence for Control with Dynamics Cycle-Consistency
Qiang Zhang, Tete Xiao, Alexei A. Efros, Lerrel Pinto, Xiaolong Wang
http://arxiv.org/abs/2012.09811v1
• [cs.RO]MSL-RAPTOR: A 6DoF Relative Pose Tracker for Onboard Robotic Perception
Benjamin Ramtoula, Adam Caccavale, Giovanni Beltrame, Mac Schwager
http://arxiv.org/abs/2012.09264v1
• [cs.RO]Multi-FinGAN: Generative Coarse-To-Fine Sampling of Multi-Finger Grasps
Jens Lundell, Enric Corona, Tran Nguyen Le, Francesco Verdoja, Philippe Weinzaepfel, Gregory Rogez, Francesc Moreno-Noguer, Ville Kyrki
http://arxiv.org/abs/2012.09696v1
• [cs.RO]Muscle-inspired flexible mechanical logic architecture for colloidal robotics
Mayank Agrawal, Sharon C. Glotzer
http://arxiv.org/abs/2012.09345v1
• [cs.RO]Robotics Enabling the Workforce
Henrik Christensen, Maria Gini, Odest Chadwicke Jenkins, Holly Yanco
http://arxiv.org/abs/2012.09309v1
• [cs.RO]Simultaneous View and Feature Selection for Collaborative Multi-Robot Recognition
Brian Reily, Hao Zhang
http://arxiv.org/abs/2012.09328v1
• [cs.RO]Team Assignment for Heterogeneous Multi-Robot Sensor Coverage through Graph Representation Learning
Brian Reily, Hao Zhang
http://arxiv.org/abs/2012.09331v1
• [cs.RO]Trajectory Planning Under Stochastic and Bounded Sensing Uncertainties Using Reachability Analysis
Akshay Shetty, Grace Xingxin Gao
http://arxiv.org/abs/2012.09689v1
• [cs.RO]ViNG: Learning Open-World Navigation with Visual Goals
Dhruv Shah, Benjamin Eysenbach, Gregory Kahn, Nicholas Rhinehart, Sergey Levine
http://arxiv.org/abs/2012.09812v1
• [cs.SD]Automatic source localization and spectra generation from deconvolved beamforming maps
Armin Goudarzi, Carsten Spehr, Steffen Herbold
http://arxiv.org/abs/2012.09643v1
• [cs.SD]The voice of COVID-19: Acoustic correlates of infection
Katrin D. Bartl-Pokorny, Florian B. Pokorny, Anton Batliner, Shahin Amiriparian, Anastasia Semertzidou, Florian Eyben, Elena Kramer, Florian Schmidt, Rainer Schönweiler, Markus Wehler, Björn W. Schuller
http://arxiv.org/abs/2012.09478v1
• [cs.SE]The Mind Is a Powerful Place: How Showing Code Comprehensibility Metrics Influences Code Understanding
Marvin Wyrich, Andreas Preikschat, Daniel Graziotin, Stefan Wagner
http://arxiv.org/abs/2012.09590v1
• [cs.SI]Conspiracy Machines — The Role of Social Bots during the COVID-19 Infodemic
Julian Marx, Felix Brünker, Milad Mirbabaie, Eric Hochstrate
http://arxiv.org/abs/2012.09536v1
• [cs.SI]Digital Detox — Mitigating Digital Overuse in Times of Remote Work and Social Isolation
Milad Mirbabaie, Julian Marx, Lea-Marie Braun, Stefan Stieglitz
http://arxiv.org/abs/2012.09535v1
• [cs.SI]The COVID-19 Infodemic: Twitter versus Facebook
Kai-Cheng Yang, Francesco Pierri, Pik-Mai Hui, David Axelrod, Christopher Torres-Lugo, John Bryden, Filippo Menczer
http://arxiv.org/abs/2012.09353v1
• [cs.SI]Virtually Extended Coworking Spaces? — The Reinforcement of Social Proximity, Motivation and Knowledge Sharing Through ICT
Lennart Hofeditz, Milad Mirbabaie, Stefan Stieglitz
http://arxiv.org/abs/2012.09538v1
• [eess.AS]Speech Enhancement with Zero-Shot Model Selection
Ryandhimas E. Zezario, Chiou-Shann Fuh, Hsin-Min Wang, Yu Tsao
http://arxiv.org/abs/2012.09359v1
• [eess.AS]The effectiveness of unsupervised subword modeling with autoregressive and cross-lingual phone-aware networks
Siyuan Feng, Odette Scharenborg
http://arxiv.org/abs/2012.09544v1
• [eess.IV]A new semi-supervised self-training method for lung cancer prediction
Kelvin Shak, Mundher Al-Shabi, Andrea Liew, Boon Leong Lan, Wai Yee Chan, Kwan Hoong Ng, Maxine Tan
http://arxiv.org/abs/2012.09472v1
• [eess.IV]Describing the Structural Phenotype of the Glaucomatous Optic Nerve Head Using Artificial Intelligence
Satish K. Panda, Haris Cheong, Tin A. Tun, Sripad K. Devella, Ramaswami Krishnadas, Martin L. Buist, Shamira Perera, Ching-Yu Cheng, Tin Aung, Alexandre H. Thiéry, Michaël J. A. Girard
http://arxiv.org/abs/2012.09755v1
• [eess.IV]Learned Block-based Hybrid Image Compression
Yaojun Wu, Xin Li, Zhizheng Zhang, Xin Jin, Zhibo Chen
http://arxiv.org/abs/2012.09550v1
• [eess.IV]Spatial Context-Aware Self-Attention Model For Multi-Organ Segmentation
Hao Tang, Xingwei Liu, Kun Han, Shanlin Sun, Narisu Bai, Xuming Chen, Huang Qian, Yong Liu, Xiaohui Xie
http://arxiv.org/abs/2012.09279v1
• [eess.IV]Transfer Learning Through Weighted Loss Function and Group Normalization for Vessel Segmentation from Retinal Images
Abdullah Sarhan, Jon Rokne, Reda Alhajj, Andrew Crichton
http://arxiv.org/abs/2012.09250v1
• [eess.SP]Reduction in the complexity of 1D 1H-NMR spectra by the use of Frequency to Information Transformation
Homayoun Valafar, Faramarz Valafar
http://arxiv.org/abs/2012.09267v1
• [eess.SY]Towards Optimal District Heating Temperature Control in China with Deep Reinforcement Learning
Adrien Le Coz, Tahar Nabil, Francois Courtot
http://arxiv.org/abs/2012.09508v1
• [eess.SY]Uncertainty Quantification in Case of Imperfect Models: A Review
Sebastian Kersting, Michael Kohler
http://arxiv.org/abs/2012.09449v1
• [math.OC]Clustering with Iterated Linear Optimization
Pedro Felzenszwalb, Caroline Klivans, Alice Paul
http://arxiv.org/abs/2012.09202v1
• [math.PR]Nearly optimal central limit theorem and bootstrap approximations in high dimensions
Victor Chernozhukov, Denis Chetverikov, Yuta Koike
http://arxiv.org/abs/2012.09513v1
• [math.PR]On the fractional queueing model with catastrophes
Matheus de Oliveira Souza, Pablo Martin Rodriguez
http://arxiv.org/abs/2012.09317v1
• [math.ST]A geometric investigation into the tail dependence of vine copulas
Emma S. Simpson, Jennifer L. Wadsworth, Jonathan A. Tawn
http://arxiv.org/abs/2012.09623v1
• [math.ST]Asymptotic normality of wavelet covariances and of multivariate wavelet Whittle estimators
Irène Gannaz
http://arxiv.org/abs/2012.09436v1
• [math.ST]Nonparametric Two-Sample Hypothesis Testing for Random Graphs with Negative and Repeated Eigenvalues
Joshua Agterberg, Minh Tang, Carey Priebe
http://arxiv.org/abs/2012.09828v1
• [physics.data-an]Image-Based Jet Analysis
Michael Kagan
http://arxiv.org/abs/2012.09719v1
• [physics.data-an]Maximum Entropy competes with Maximum Likelihood
A. E. Allahverdyan, N. H. Martirosyan
http://arxiv.org/abs/2012.09430v1
• [q-bio.QM]Distance-aware Molecule Graph Attention Network for Drug-Target Binding Affinity Prediction
Jingbo Zhou, Shuangli Li, Liang Huang, Haoyi Xiong, Fan Wang, Tong Xu, Hui Xiong, Dejing Dou
http://arxiv.org/abs/2012.09624v1
• [quant-ph]Compiler Design for Distributed Quantum Computing
Davide Ferrari, Angela Sara Cacciapuoti, Michele Amoretti, Marcello Caleffi
http://arxiv.org/abs/2012.09680v1
• [quant-ph]On the experimental feasibility of quantum state reconstruction via machine learning
Sanjaya Lohani, Thomas A. Searles, Brian T. Kirby, Ryan T. Glasser
http://arxiv.org/abs/2012.09432v1
• [quant-ph]Variational Quantum Algorithms
M. Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, Patrick J. Coles
http://arxiv.org/abs/2012.09265v1
• [stat.AP]Detection of data drift and outliers affecting machine learning model performance over time
Samuel Ackerman, Eitan Farchi, Orna Raz, Marcel Zalmanovici, Parijat Dube
http://arxiv.org/abs/2012.09258v1
• [stat.AP]Network Hawkes Process Models for Exploring Latent Hierarchy in Social Animal Interactions
Owen G. Ward, Jing Wu, Tian Zheng, Anna L. Smith, James P. Curley
http://arxiv.org/abs/2012.09598v1
• [stat.AP]Richness estimation with species identity error
Jai-Hua Yen, Chun-Huo Chiu
http://arxiv.org/abs/2012.07485v2
• [stat.AP]Selection of multiple donor gauges via Graphical Lasso for estimation of daily streamflow time series
German A. Villalba, Xu Liang, Yao Liang
http://arxiv.org/abs/2012.08652v2
• [stat.CO]A fresh take on ‘Barker dynamics’ for MCMC
Max Hird, Samuel Livingstone, Giacomo Zanella
http://arxiv.org/abs/2012.09731v1
• [stat.CO]High-resolution Probabilistic Precipitation Prediction for use in Climate Simulations
Sherman Lo, Peter Watson, Peter Dueben, Ritabrata Dutta
http://arxiv.org/abs/2012.09821v1
• [stat.ME]Bayesian semiparametric modelling of covariance matrices for multivariate longitudinal data
Georgios Papageorgiou
http://arxiv.org/abs/2012.09833v1
• [stat.ME]Differential privacy and noisy confidentiality concepts for European population statistics
Fabian Bach
http://arxiv.org/abs/2012.09775v1
• [stat.ME]Fast estimation of a convolution type model for the intensity of spatial point processes
Francisco Cuevas-Pacheco, Jean-François Coeurjolly, Marie-Hélène Descary
http://arxiv.org/abs/2012.09659v1
• [stat.ME]No-harm calibration for generalized Oaxaca-Blinder estimators
Peter L. Cohen, Colin B. Fogarty
http://arxiv.org/abs/2012.09246v1
• [stat.ME]Non-parametric estimation of Expectation and Variance of event count and of incidence rate in a recurrent process — where intensity of event-occurrence changes with the occurrence of each higher order event
Sudipta Bhattacharya
http://arxiv.org/abs/2012.09746v1
• [stat.ME]The Causal Learning of Retail Delinquency
Yiyan Huang, Cheuk Hang Leung, Xing Yan, Qi Wu, Nanbo Peng, Dongdong Wang, Zhixiang Huang
http://arxiv.org/abs/2012.09448v1
• [stat.ME]l1-norm quantile regression screening rule via the dual circumscribed sphere
Pan Shang, Lingchen Kong
http://arxiv.org/abs/2012.09395v1
• [stat.ML]Balancing Geometry and Density: Path Distances on High-Dimensional Data
Anna Little, Daniel McKenzie, James Murphy
http://arxiv.org/abs/2012.09385v1
• [stat.ML]Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection
Edward Raff, William Fleshman, Richard Zak, Hyrum S. Anderson, Bobby Filar, Mark McLean
http://arxiv.org/abs/2012.09390v1
• [stat.ML]Estimating mixed-memberships using the Symmetric Laplacian Inverse Matrix
Huan Qing, Jingli Wang
http://arxiv.org/abs/2012.09561v1
• [stat.ML]Optimal transport for vector Gaussian mixture models
Jiening Zhu, Kaiming Xu, Allen Tannenbaum
http://arxiv.org/abs/2012.09226v1
• [stat.ML]Rank-One Measurements of Low-Rank PSD Matrices Have Small Feasible Sets
T. Mitchell Roddenberry, Santiago Segarra, Anastasios Kyrillidis
http://arxiv.org/abs/2012.09768v1
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