astro-ph.IM - 仪器仪表和天体物理学方法
    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.DC - 分布式、并行与集群计算
    cs.DL - 数字图书馆
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.LO - 计算逻辑
    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.NA - 数值分析
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.flu-dyn - 流体动力学
    physics.med-ph - 医学物理学
    physics.soc-ph - 物理学与社会
    q-bio.GN - 基因组学
    q-bio.NC - 神经元与认知
    q-bio.PE - 人口与发展
    quant-ph - 量子物理
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [astro-ph.IM]A deep ensemble approach to X-ray polarimetry
    • [cs.AI]Big Data Testing Techniques: Taxonomy, Challenges and Future Trends
    • [cs.AI]Deep Artificial Intelligence for Fantasy Football Language Understanding
    • [cs.AI]Engagement Decision Support for Beyond Visual Range Air Combat
    • [cs.AI]Imagine Networks
    • [cs.AI]Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football Player Trades
    • [cs.AI]Optimised Playout Implementations for the Ludii General Game System
    • [cs.AI]Whistleblower protection in the digital age — why ‘anonymous’ is not enough. Towards an interdisciplinary view of ethical dilemmas
    • [cs.AR]RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms
    • [cs.CL]A Case Study and Qualitative Analysis of Simple Cross-Lingual Opinion Mining
    • [cs.CL]A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding
    • [cs.CL]A text autoencoder from transformer for fast encoding language representation
    • [cs.CL]Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models
    • [cs.CL]Athena 2.0: Contextualized Dialogue Management for an Alexa Prize SocialBot
    • [cs.CL]BERT-DRE: BERT with Deep Recursive Encoder for Natural Language Sentence Matching
    • [cs.CL]CLUES: Few-Shot Learning Evaluation in Natural Language Understanding
    • [cs.CL]Contextual Semantic Parsing for Multilingual Task-Oriented Dialogues
    • [cs.CL]CoreLM: Coreference-aware Language Model Fine-Tuning
    • [cs.CL]Medicines Question Answering System, MeQA
    • [cs.CL]On Semantic Cognition, Inductive Generalization, and Language Models
    • [cs.CL]Reducing the impact of out of vocabulary words in the translation of natural language questions into SPARQL queries
    • [cs.CL]Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel
    • [cs.CL]Unsupervised and Distributional Detection of Machine-Generated Text
    • [cs.CR]Autonomous Attack Mitigation for Industrial Control Systems
    • [cs.CR]Effect of Miner Incentive on the Confirmation Time of Bitcoin Transactions
    • [cs.CR]Universal Private Estimators
    • [cs.CV]A dataset for multi-sensor drone detection
    • [cs.CV]A high performance fingerprint liveness detection method based on quality related features
    • [cs.CV]Body Size and Depth Disambiguation in Multi-Person Reconstruction from Single Images
    • [cs.CV]Bootstrap Your Object Detector via Mixed Training
    • [cs.CV]Building Damage Mapping with Self-PositiveUnlabeled Learning
    • [cs.CV]Certainty Volume Prediction for Unsupervised Domain Adaptation
    • [cs.CV]Deep learning for identification and face, gender, expression recognition under constraints
    • [cs.CV]FEAFA+: An Extended Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation
    • [cs.CV]Facial Emotion Recognition using Deep Residual Networks in Real-World Environments
    • [cs.CV]Improving Pose Estimation through Contextual Activity Fusion
    • [cs.CV]LVIS Challenge Track Technical Report 1st Place Solution: Distribution Balanced and Boundary Refinement for Large Vocabulary Instance Segmentation
    • [cs.CV]MixSiam: A Mixture-based Approach to Self-supervised Representation Learning
    • [cs.CV]Multi-scale 2D Representation Learning for weakly-supervised moment retrieval
    • [cs.CV]On the Frequency Bias of Generative Models
    • [cs.CV]Online Continual Learning via Multiple Deep Metric Learning and Uncertainty-guided Episodic Memory Replay — 3rd Place Solution for ICCV 2021 Workshop SSLAD Track 3A Continual Object Classification
    • [cs.CV]Panoptic 3D Scene Reconstruction From a Single RGB Image
    • [cs.CV]Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution
    • [cs.CV]Stable and Compact Face Recognition via Unlabeled Data Driven Sparse Representation-Based Classification
    • [cs.CV]Tea Chrysanthemum Detection under Unstructured Environments Using the TC-YOLO Model
    • [cs.CV]Temporal Fusion Based Mutli-scale Semantic Segmentation for Detecting Concealed Baggage Threats
    • [cs.CV]TimeMatch: Unsupervised Cross-Region Adaptation by Temporal Shift Estimation
    • [cs.CV]Towards Panoptic 3D Parsing for Single Image in the Wild
    • [cs.CV]Towards Smart Monitored AM: Open Source in-Situ Layer-wise 3D Printing Image Anomaly Detection Using Histograms of Oriented Gradients and a Physics-Based Rendering Engine
    • [cs.CV]Understanding Cross Domain Presentation Attack Detection for Visible Face Recognition
    • [cs.CV]Unified 3D Mesh Recovery of Humans and Animals by Learning Animal Exercise
    • [cs.CV]Unsupervised Learning of Compositional Energy Concepts
    • [cs.CY]Slapping Cats, Bopping Heads, and Oreo Shakes: Understanding Indicators of Virality in TikTok Short Videos
    • [cs.DC]A thread-safe Term Library
    • [cs.DC]Auto Tuning of Hadoop and Spark parameters
    • [cs.DC]Earthquake detection at the edge: IoT crowdsensing network
    • [cs.DC]Failure Aware Semi-Centralized Virtual Network Embedding in Cloud Computing Fat-Tree Data Center Networks
    • [cs.DC]MUVINE: Multi-stage Virtual Network Embedding in Cloud Data Centers using Reinforcement Learning based Predictions
    • [cs.DC]SPEEDEX: A Scalable, Parallelizable, and Economically Efficient Digital EXchange
    • [cs.DC]SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors
    • [cs.DC]TOSCAdata: Modelling data pipeline applications in TOSCA
    • [cs.DL]”We won’t even challenge their lefty academic definition of racist:” Understanding the Use of e-Prints on Reddit and 4chan
    • [cs.DL]Scientists are Working Overtime and at the Weekends: Comparison of Publication Downloading from Copyrighted and Pirated Platforms
    • [cs.HC]Characterizing Human Explanation Strategies to Inform the Design of Explainable AI for Building Damage Assessment
    • [cs.HC]Defining Gaze Patterns for Process Model Literacy — Exploring Visual Routines in Process Models with Diverse Mappings
    • [cs.IR]Sequential Movie Genre Prediction using Average Transition Probability with Clustering
    • [cs.IT]A Dynamic Programming Method to Construct Polar Codes with Improved Performance
    • [cs.IT]Analog MIMO Communication for One-shot Distributed Principal Component Analysis
    • [cs.IT]Belief Propagation based Joint Detection and Decoding for Resistive Random Access Memories
    • [cs.IT]Energy Efficiency of Uplink Cell-Free Massive MIMO With Transmit Power Control in Measured Propagation Channel
    • [cs.IT]Energy-Efficient Online Data Sensing and Processing in Wireless Powered Edge Computing Systems
    • [cs.IT]Map-Assisted Power Allocation and Constellation Design for mmWave WDM with OAM in Short-Range LOS Environment
    • [cs.IT]On the Secrecy Design of STAR-RIS assisted Uplink NOMA Networks
    • [cs.IT]Optimal Discrete Constellation Inputs for Aggregated LiFi-WiFi Networks
    • [cs.IT]Performance Analysis under IRS-User Association for Distributed IRSs Assisted MISO Systems
    • [cs.IT]The Age of Information of Short-Packet Communications: Joint or Distributed Encoding?
    • [cs.LG]A Concentration Bound for LSPE(今日学术视野(2021.11.6) - 图1)
    • [cs.LG]A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection
    • [cs.LG]A Fast Parallel Tensor Decomposition with Optimal Stochastic Gradient Descent: an Application in Structural Damage Identification
    • [cs.LG]A Meta-Learned Neuron model for Continual Learning
    • [cs.LG]A Personalized Federated Learning Algorithm: an Application in Anomaly Detection
    • [cs.LG]A Unified Approach to Coreset Learning
    • [cs.LG]A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Synergy, and Drug-Drug Interaction Prediction
    • [cs.LG]AlphaD3M: Machine Learning Pipeline Synthesis
    • [cs.LG]An Interpretable Graph Generative Model with Heterophily
    • [cs.LG]Attacking Deep Reinforcement Learning-Based Traffic Signal Control Systems with Colluding Vehicles
    • [cs.LG]B-Pref: Benchmarking Preference-Based Reinforcement Learning
    • [cs.LG]Balanced Q-learning: Combining the Influence of Optimistic and Pessimistic Targets
    • [cs.LG]Benchmarking Multimodal AutoML for Tabular Data with Text Fields
    • [cs.LG]Communication-Efficient Separable Neural Network for Distributed Inference on Edge Devices
    • [cs.LG]Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers
    • [cs.LG]Convolutional generative adversarial imputation networks for spatio-temporal missing data in storm surge simulations
    • [cs.LG]Data-Driven Market Segmentation in Hospitality Using Unsupervised Machine Learning
    • [cs.LG]Deep Learning Methods for Daily Wildfire Danger Forecasting
    • [cs.LG]Evaluation of Tree Based Regression over Multiple Linear Regression for Non-normally Distributed Data in Battery Performance
    • [cs.LG]Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping
    • [cs.LG]Flood forecasting with machine learning models in an operational framework
    • [cs.LG]From Strings to Data Science: a Practical Framework for Automated String Handling
    • [cs.LG]Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch
    • [cs.LG]Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
    • [cs.LG]Identifying nonlinear dynamical systems from multi-modal time series data
    • [cs.LG]Introduction to Coresets: Approximated Mean
    • [cs.LG]Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies
    • [cs.LG]Label Ranking through Nonparametric Regression
    • [cs.LG]LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso
    • [cs.LG]Leveraging Time Irreversibility with Order-Contrastive Pre-training
    • [cs.LG]Model-Free Risk-Sensitive Reinforcement Learning
    • [cs.LG]Modeling Techniques for Machine Learning Fairness: A Survey
    • [cs.LG]Multi-task Learning of Order-Consistent Causal Graphs
    • [cs.LG]OpenFWI: Benchmark Seismic Datasets for Machine Learning-Based Full Waveform Inversion
    • [cs.LG]Parameterized Knowledge Transfer for Personalized Federated Learning
    • [cs.LG]Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples
    • [cs.LG]RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning
    • [cs.LG]Real-time Wireless Transmitter Authorization: Adapting to Dynamic Authorized Sets with Information Retrieval
    • [cs.LG]Recurrent Neural Network Training with Convex Loss and Regularization Functions by Extended Kalman Filtering
    • [cs.LG]Representation Edit Distance as a Measure of Novelty
    • [cs.LG]Scanflow: A multi-graph framework for Machine Learning workflow management, supervision, and debugging
    • [cs.LG]Shift Happens: Adjusting Classifiers
    • [cs.LG]Testing using Privileged Information by Adapting Features with Statistical Dependence
    • [cs.LG]Towards an Understanding of Default Policies in Multitask Policy Optimization
    • [cs.LG]Unsupervised Change Detection of Extreme Events Using ML On-Board
    • [cs.LG]Variational Inference with Holder Bounds
    • [cs.LG]WaveFake: A Data Set to Facilitate Audio Deepfake Detection
    • [cs.LG]When Neural Networks Using Different Sensors Create Similar Features
    • [cs.LO]Logically Sound Arguments for the Effectiveness of ML Safety Measures
    • [cs.RO]A System for General In-Hand Object Re-Orientation
    • [cs.RO]Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning
    • [cs.RO]Deep Direct Visual Servoing of Tendon-Driven Continuum Robots
    • [cs.RO]Extended Abstract Version: CNN-based Human Detection System for UAVs in Search and Rescue
    • [cs.RO]Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning
    • [cs.RO]Learning suction graspability considering grasp quality and robot reachability for bin-picking
    • [cs.RO]Speed Maps: An Application to Guide Robots in Human Environments
    • [cs.RO]Stein Variational Probabilistic Roadmaps
    • [cs.RO]Using Graph-Theoretic Machine Learning to Predict Human Driver Behavior
    • [cs.SD]InQSS: a speech intelligibility assessment model using a multi-task learning network
    • [cs.SD]MT3: Multi-Task Multitrack Music Transcription
    • [cs.SE]GraphSearchNet: Enhancing GNNs via Capturing Global Dependency for Semantic Code Search
    • [cs.SI]Cost-effective Network Disintegration through Targeted Enumeration
    • [cs.SI]Engaging Politically Diverse Audiences on Social Media
    • [cs.SI]Shifting Polarization and Twitter News Influencers between two U.S. Presidential Elections
    • [eess.AS]Voice Conversion Can Improve ASR in Very Low-Resource Settings
    • [eess.IV]Automatic ultrasound vessel segmentation with deep spatiotemporal context learning
    • [eess.IV]Breast Cancer Classification Using: Pixel Interpolation
    • [eess.IV]Partial supervision for the FeTA challenge 2021
    • [eess.IV]Resampling and super-resolution of hexagonally sampled images using deep learning
    • [eess.IV]Skin Cancer Classification using Inception Network and Transfer Learning
    • [eess.IV]The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties
    • [eess.IV]Towards dynamic multi-modal phenotyping using chest radiographs and physiological data
    • [eess.IV]WORD: Revisiting Organs Segmentation in the Whole Abdominal Region
    • [eess.SP]Roadmap on Signal Processing for Next Generation Measurement Systems
    • [math.NA]Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs
    • [math.OC]A Riemannian Accelerated Proximal Extragradient Framework and its Implications
    • [math.OC]A control method for solving high-dimensional Hamiltonian systems through deep neural networks
    • [math.OC]Optimal Recovery from Inaccurate Data in Hilbert Spaces: Regularize, but what of the Parameter?
    • [math.OC]Quasi-Newton Methods for Saddle Point Problems
    • [math.ST]Differential Privacy Over Riemannian Manifolds
    • [math.ST]Finding the Optimal Dynamic Treatment Regime Using Smooth Fisher Consistent Surrogate Loss
    • [math.ST]On Johnson’s “sufficientness” postulates for features-sampling models
    • [math.ST]Proximal Causal Inference with Hidden Mediators: Front-Door and Related Mediation Problems
    • [physics.flu-dyn]Symmetry-Aware Autoencoders: s-PCA and s-nlPCA
    • [physics.med-ph]A semi-automatic ultrasound image analysis system for the grading diagnosis of COVID-19 pneumonia
    • [physics.soc-ph]Efficacy the of Confinement Policies on the COVID-19 Spread Dynamics in the Early Period of the Pandemic
    • [q-bio.GN]An Information-Theoretic Framework for Identifying Age-Related Genes Using Human Dermal Fibroblast Transcriptome Data
    • [q-bio.GN]Human Age Estimation from Gene Expression Data using Artificial Neural Networks
    • [q-bio.NC]Sensory attenuation develops as a result of sensorimotor experience
    • [q-bio.PE]Effective Resistance for Pandemics: Mobility Network Sparsification for High-Fidelity Epidemic Simulation
    • [quant-ph]Fundamental limitations on device-independent quantum conference key agreement
    • [quant-ph]Graph neural network initialisation of quantum approximate optimisation
    • [quant-ph]Quantum tangent kernel
    • [quant-ph]Weighted Quantum Channel Compiling through Proximal Policy Optimization
    • [stat.AP]Effects of Mixed Distribution Statistical Flood Frequency Models on Dam Safety Assessments: A Case Study of the Pueblo Dam, USA
    • [stat.AP]Estimating SARS-CoV-2 Seroprevalence
    • [stat.AP]Joint Species Distribution Modeling with species competition and non-stationary spatial random effects
    • [stat.AP]Robust Online Detection in Serially Correlated Directed Network
    • [stat.AP]The Psychological Gains from COVID-19 Vaccination: Who Benefits the Most?
    • [stat.ME]Covariance Structure Estimation with Laplace Approximation
    • [stat.ME]Extended Principal Component Analysis
    • [stat.ME]Mixed Models and Shrinkage Estimation for Balanced and Unbalanced Designs
    • [stat.ME]Nonparametric Simulation Extrapolation for Measurement Error Models
    • [stat.ME]Online Estimation for Functional Data
    • [stat.ML]Adversarial Attacks on Graph Classification via Bayesian Optimisation
    • [stat.ML]Causal inference with imperfect instrumental variables
    • [stat.ML]Conformal prediction for text infilling and part-of-speech prediction
    • [stat.ML]Ex今日学术视野(2021.11.6) - 图2MCMC: Sampling through Exploration Exploitation
    • [stat.ML]Perturb-and-max-product: Sampling and learning in discrete energy-based models

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

    • [astro-ph.IM]A deep ensemble approach to X-ray polarimetry
    A. L. Peirson, R. W. Romani
    http://arxiv.org/abs/2111.03047v1

    • [cs.AI]Big Data Testing Techniques: Taxonomy, Challenges and Future Trends
    Iram Arshad, Saeed Hamood Alsamhi
    http://arxiv.org/abs/2111.02853v1

    • [cs.AI]Deep Artificial Intelligence for Fantasy Football Language Understanding
    Aaron Baughman, Micah Forester, Jeff Powell, Eduardo Morales, Shaun McPartlin, Daniel Bohm
    http://arxiv.org/abs/2111.02874v1

    • [cs.AI]Engagement Decision Support for Beyond Visual Range Air Combat
    Joao P. A. Dantas, Andre N. Costa, Diego Geraldo, Marcos R. O. A. Maximo, Takashi Yoneyama
    http://arxiv.org/abs/2111.03059v1

    • [cs.AI]Imagine Networks
    Seokjun Kim, Jaeeun Jang, Hyeoncheol Kim
    http://arxiv.org/abs/2111.03048v1

    • [cs.AI]Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football Player Trades
    Aaron Baughman, Daniel Bohm, Micah Forster, Eduardo Morales, Jeff Powell, Shaun McPartlin, Raja Hebbar, Kavitha Yogaraj
    http://arxiv.org/abs/2111.02859v1

    • [cs.AI]Optimised Playout Implementations for the Ludii General Game System
    Dennis J. N. J. Soemers, Éric Piette, Matthew Stephenson, Cameron Browne
    http://arxiv.org/abs/2111.02839v1

    • [cs.AI]Whistleblower protection in the digital age — why ‘anonymous’ is not enough. Towards an interdisciplinary view of ethical dilemmas
    Bettina Berendt, Stefan Schiffner
    http://arxiv.org/abs/2111.02825v1

    • [cs.AR]RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms
    Yongan Zhang, Anton Banta, Yonggan Fu, Mathews M. John, Allison Post, Mehdi Razavi, Joseph Cavallaro, Behnaam Aazhang, Yingyan Lin
    http://arxiv.org/abs/2111.02569v1

    • [cs.CL]A Case Study and Qualitative Analysis of Simple Cross-Lingual Opinion Mining
    Gerhard Hagerer, Wing Sheung Leung, Qiaoxi Liu, Hannah Danner, Georg Groh
    http://arxiv.org/abs/2111.02259v2

    • [cs.CL]A Fine-tuned Wav2vec 2.0/HuBERT Benchmark For Speech Emotion Recognition, Speaker Verification and Spoken Language Understanding
    Yingzhi Wang, Abdelmoumene Boumadane, Abdelwahab Heba
    http://arxiv.org/abs/2111.02735v1

    • [cs.CL]A text autoencoder from transformer for fast encoding language representation
    Tan Huang
    http://arxiv.org/abs/2111.02844v1

    • [cs.CL]Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models
    Boxin Wang, Chejian Xu, Shuohang Wang, Zhe Gan, Yu Cheng, Jianfeng Gao, Ahmed Hassan Awadallah, Bo Li
    http://arxiv.org/abs/2111.02840v1

    • [cs.CL]Athena 2.0: Contextualized Dialogue Management for an Alexa Prize SocialBot
    Juraj Juraska, Kevin K. Bowden, Lena Reed, Vrindavan Harrison, Wen Cui, Omkar Patil, Rishi Rajasekaran, Angela Ramirez, Cecilia Li, Eduardo Zamora, Phillip Lee, Jeshwanth Bheemanpally, Rohan Pandey, Adwait Ratnaparkhi, Marilyn Walker
    http://arxiv.org/abs/2111.02519v1

    • [cs.CL]BERT-DRE: BERT with Deep Recursive Encoder for Natural Language Sentence Matching
    Ehsan Tavan, Ali Rahmati, Maryam Najafi, Saeed Bibak, Zahed Rahmati
    http://arxiv.org/abs/2111.02188v2

    • [cs.CL]CLUES: Few-Shot Learning Evaluation in Natural Language Understanding
    Subhabrata Mukherjee, Xiaodong Liu, Guoqing Zheng, Saghar Hosseini, Hao Cheng, Greg Yang, Christopher Meek, Ahmed Hassan Awadallah, Jianfeng Gao
    http://arxiv.org/abs/2111.02570v1

    • [cs.CL]Contextual Semantic Parsing for Multilingual Task-Oriented Dialogues
    Mehrad Moradshahi, Victoria Tsai, Giovanni Campagna, Monica S. Lam
    http://arxiv.org/abs/2111.02574v1

    • [cs.CL]CoreLM: Coreference-aware Language Model Fine-Tuning
    Nikolaos Stylianou, Ioannis Vlahavas
    http://arxiv.org/abs/2111.02687v1

    • [cs.CL]Medicines Question Answering System, MeQA
    Jesús Santamaría
    http://arxiv.org/abs/2111.02760v1

    • [cs.CL]On Semantic Cognition, Inductive Generalization, and Language Models
    Kanishka Misra
    http://arxiv.org/abs/2111.02603v1

    • [cs.CL]Reducing the impact of out of vocabulary words in the translation of natural language questions into SPARQL queries
    Manuel A. Borroto Santana, Francesco Ricca, Bernardo Cuteri
    http://arxiv.org/abs/2111.03000v1

    • [cs.CL]Towards Learning to Speak and Hear Through Multi-Agent Communication over a Continuous Acoustic Channel
    Kevin Eloff, Arnu Pretorius, Okko Räsänen, Herman A. Engelbrecht, Herman Kamper
    http://arxiv.org/abs/2111.02827v1

    • [cs.CL]Unsupervised and Distributional Detection of Machine-Generated Text
    Matthias Gallé, Jos Rozen, Germán Kruszewski, Hady Elsahar
    http://arxiv.org/abs/2111.02878v1

    • [cs.CR]Autonomous Attack Mitigation for Industrial Control Systems
    John Mern, Kyle Hatch, Ryan Silva, Cameron Hickert, Tamim Sookoor, Mykel J. Kochenderfer
    http://arxiv.org/abs/2111.02445v1

    • [cs.CR]Effect of Miner Incentive on the Confirmation Time of Bitcoin Transactions
    Befekadu G. Gebraselase, Bjarne E. Helvik, Yuming Jiang
    http://arxiv.org/abs/2111.02725v1

    • [cs.CR]Universal Private Estimators
    Wei Dong, Ke Yi
    http://arxiv.org/abs/2111.02598v1

    • [cs.CV]A dataset for multi-sensor drone detection
    Fredrik Svanström, Fernando Alonso-Fernandez, Cristofer Englund
    http://arxiv.org/abs/2111.01888v1

    • [cs.CV]A high performance fingerprint liveness detection method based on quality related features
    Javier Galbally, Fernando Alonso-Fernandez, Julian Fierrez, Javier Ortega-Garcia
    http://arxiv.org/abs/2111.01898v1

    • [cs.CV]Body Size and Depth Disambiguation in Multi-Person Reconstruction from Single Images
    Nicolas Ugrinovic, Adria Ruiz, Antonio Agudo, Alberto Sanfeliu, Francesc Moreno-Noguer
    http://arxiv.org/abs/2111.01884v1

    • [cs.CV]Bootstrap Your Object Detector via Mixed Training
    Mengde Xu, Zheng Zhang, Fangyun Wei, Yutong Lin, Yue Cao, Stephen Lin, Han Hu, Xiang Bai
    http://arxiv.org/abs/2111.03056v1

    • [cs.CV]Building Damage Mapping with Self-PositiveUnlabeled Learning
    Junshi Xia, Naoto Yokoya, Bruno Adriano
    http://arxiv.org/abs/2111.02586v1

    • [cs.CV]Certainty Volume Prediction for Unsupervised Domain Adaptation
    Tobias Ringwald, Rainer Stiefelhagen
    http://arxiv.org/abs/2111.02901v1

    • [cs.CV]Deep learning for identification and face, gender, expression recognition under constraints
    Ahmad B. Hassanat, Abeer Albustanji, Ahmad S. Tarawneh, Malek Alrashidi, Hani Alharbi, Mohammed Alanazi, Mansoor Alghamdi, Ibrahim S Alkhazi, V. B. Surya Prasath
    http://arxiv.org/abs/2111.01930v1

    • [cs.CV]FEAFA+: An Extended Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation
    Wei Gan, Jian Xue, Ke Lu, Yanfu Yan, Pengcheng Gao, Jiayi Lyu
    http://arxiv.org/abs/2111.02751v1

    • [cs.CV]Facial Emotion Recognition using Deep Residual Networks in Real-World Environments
    Panagiotis Tzirakis, Dénes Boros, Elnar Hajiyev, Björn W. Schuller
    http://arxiv.org/abs/2111.02717v1

    • [cs.CV]Improving Pose Estimation through Contextual Activity Fusion
    David Poulton, Richard Klein
    http://arxiv.org/abs/2111.02500v1

    • [cs.CV]LVIS Challenge Track Technical Report 1st Place Solution: Distribution Balanced and Boundary Refinement for Large Vocabulary Instance Segmentation
    WeiFu Fu, CongChong Nie, Ting Sun, Jun Liu, TianLiang Zhang, Yong Liu
    http://arxiv.org/abs/2111.02668v1

    • [cs.CV]MixSiam: A Mixture-based Approach to Self-supervised Representation Learning
    Xiaoyang Guo, Tianhao Zhao, Yutian Lin, Bo Du
    http://arxiv.org/abs/2111.02679v1

    • [cs.CV]Multi-scale 2D Representation Learning for weakly-supervised moment retrieval
    Ding Li, Rui Wu, Yongqiang Tang, Zhizhong Zhang, Wensheng Zhang
    http://arxiv.org/abs/2111.02741v1

    • [cs.CV]On the Frequency Bias of Generative Models
    Katja Schwarz, Yiyi Liao, Andreas Geiger
    http://arxiv.org/abs/2111.02447v1

    • [cs.CV]Online Continual Learning via Multiple Deep Metric Learning and Uncertainty-guided Episodic Memory Replay — 3rd Place Solution for ICCV 2021 Workshop SSLAD Track 3A Continual Object Classification
    Muhammad Rifki Kurniawan, Xing Wei, Yihong Gong
    http://arxiv.org/abs/2111.02757v1

    • [cs.CV]Panoptic 3D Scene Reconstruction From a Single RGB Image
    Manuel Dahnert, Ji Hou, Matthias Nießner, Angela Dai
    http://arxiv.org/abs/2111.02444v1

    • [cs.CV]Sequence-to-Sequence Modeling for Action Identification at High Temporal Resolution
    Aakash Kaku, Kangning Liu, Avinash Parnandi, Haresh Rengaraj Rajamohan, Kannan Venkataramanan, Anita Venkatesan, Audre Wirtanen, Natasha Pandit, Heidi Schambra, Carlos Fernandez-Granda
    http://arxiv.org/abs/2111.02521v1

    • [cs.CV]Stable and Compact Face Recognition via Unlabeled Data Driven Sparse Representation-Based Classification
    Xiaohui Yang, Zheng Wang, Huan Wu, Licheng Jiao, Yiming Xu, Haolin Chen
    http://arxiv.org/abs/2111.02847v1

    • [cs.CV]Tea Chrysanthemum Detection under Unstructured Environments Using the TC-YOLO Model
    Chao Qi, Junfeng Gao, Simon Pearson, Helen Harman, Kunjie Chen, Lei Shu
    http://arxiv.org/abs/2111.02724v1

    • [cs.CV]Temporal Fusion Based Mutli-scale Semantic Segmentation for Detecting Concealed Baggage Threats
    Muhammed Shafay, Taimur Hassan, Ernesto Damiani, Naoufel Werghi
    http://arxiv.org/abs/2111.02651v1

    • [cs.CV]TimeMatch: Unsupervised Cross-Region Adaptation by Temporal Shift Estimation
    Joachim Nyborg, Charlotte Pelletier, Sébastien Lefèvre, Ira Assent
    http://arxiv.org/abs/2111.02682v1

    • [cs.CV]Towards Panoptic 3D Parsing for Single Image in the Wild
    Sainan Liu, Vincent Nguyen, Yuan Gao, Subarna Tripathi, Zhuowen Tu
    http://arxiv.org/abs/2111.03039v1

    • [cs.CV]Towards Smart Monitored AM: Open Source in-Situ Layer-wise 3D Printing Image Anomaly Detection Using Histograms of Oriented Gradients and a Physics-Based Rendering Engine
    Aliaksei Petsiuk, Joshua M. Pearce
    http://arxiv.org/abs/2111.02703v1

    • [cs.CV]Understanding Cross Domain Presentation Attack Detection for Visible Face Recognition
    Jennifer Hamblin, Kshitij Nikhal, Benjamin S. Riggan
    http://arxiv.org/abs/2111.02548v1

    • [cs.CV]Unified 3D Mesh Recovery of Humans and Animals by Learning Animal Exercise
    Kim Youwang, Kim Ji-Yeon, Kyungdon Joo, Tae-Hyun Oh
    http://arxiv.org/abs/2111.02450v1

    • [cs.CV]Unsupervised Learning of Compositional Energy Concepts
    Yilun Du, Shuang Li, Yash Sharma, Joshua B. Tenenbaum, Igor Mordatch
    http://arxiv.org/abs/2111.03042v1

    • [cs.CY]Slapping Cats, Bopping Heads, and Oreo Shakes: Understanding Indicators of Virality in TikTok Short Videos
    Chen Ling, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini
    http://arxiv.org/abs/2111.02452v1

    • [cs.DC]A thread-safe Term Library
    J. F. Groote, M. Laveaux, P. H. M. van Spaendonck
    http://arxiv.org/abs/2111.02706v1

    • [cs.DC]Auto Tuning of Hadoop and Spark parameters
    Tanuja Patanshetti, Ashish Anil Pawar, Disha Patel, Sanket Thakare
    http://arxiv.org/abs/2111.02604v1

    • [cs.DC]Earthquake detection at the edge: IoT crowdsensing network
    Enrico Bassetti, Emanuele Panizzi
    http://arxiv.org/abs/2111.02869v1

    • [cs.DC]Failure Aware Semi-Centralized Virtual Network Embedding in Cloud Computing Fat-Tree Data Center Networks
    Chinmaya Kumar Dehury, Prasan Kumar Sahoo
    http://arxiv.org/abs/2111.02727v1

    • [cs.DC]MUVINE: Multi-stage Virtual Network Embedding in Cloud Data Centers using Reinforcement Learning based Predictions
    Hiren Kumar Thakkar, Chinmaya Kumar Dehury, Prasan Kumar Sahoo
    http://arxiv.org/abs/2111.02737v1

    • [cs.DC]SPEEDEX: A Scalable, Parallelizable, and Economically Efficient Digital EXchange
    Geoffrey Ramseyer, Ashish Goel, David Mazières
    http://arxiv.org/abs/2111.02719v1

    • [cs.DC]SZ3: A Modular Framework for Composing Prediction-Based Error-Bounded Lossy Compressors
    Xin Liang, Kai Zhao, Sheng Di, Sihuan Li, Robert Underwood, Ali M. Gok, Jiannan Tian, Junjing Deng, Jon C. Calhoun, Dingwen Tao, Zizhong Chen, Franck Cappello
    http://arxiv.org/abs/2111.02925v1

    • [cs.DC]TOSCAdata: Modelling data pipeline applications in TOSCA
    Chinmaya Kumar Dehury, Pelle Jakovits, Satish Narayana Srirama, Giorgos Giotis, Gaurav Garg
    http://arxiv.org/abs/2111.02524v1

    • [cs.DL]“We won’t even challenge their lefty academic definition of racist:” Understanding the Use of e-Prints on Reddit and 4chan
    Satrio Baskoro Yudhoatmojo, Emiliano De Cristofaro, Jeremy Blackburn
    http://arxiv.org/abs/2111.02455v1

    • [cs.DL]Scientists are Working Overtime and at the Weekends: Comparison of Publication Downloading from Copyrighted and Pirated Platforms
    Yu Geng, Ren-Meng Cao, Xiao-Pu Han, Wen-Can Tian, Guang-Yao Zhang, Xian-Wen Wang
    http://arxiv.org/abs/2111.02664v1

    • [cs.HC]Characterizing Human Explanation Strategies to Inform the Design of Explainable AI for Building Damage Assessment
    Donghoon Shin, Sachin Grover, Kenneth Holstein, Adam Perer
    http://arxiv.org/abs/2111.02626v1

    • [cs.HC]Defining Gaze Patterns for Process Model Literacy — Exploring Visual Routines in Process Models with Diverse Mappings
    Michael Winter, Heiko Neumann, Rüdiger Pryss, Thomas Probst, Manfred Reichert
    http://arxiv.org/abs/2111.02881v1

    • [cs.IR]Sequential Movie Genre Prediction using Average Transition Probability with Clustering
    Jihyeon Kim, Jinkyung Kim, Jaeyoung Choi
    http://arxiv.org/abs/2111.02740v1

    • [cs.IT]A Dynamic Programming Method to Construct Polar Codes with Improved Performance
    Guodong Li, Min Ye, Sihuang Hu
    http://arxiv.org/abs/2111.02851v1

    • [cs.IT]Analog MIMO Communication for One-shot Distributed Principal Component Analysis
    Xu Chen, Erik G. Larsson, Kaibin Huang
    http://arxiv.org/abs/2111.02709v1

    • [cs.IT]Belief Propagation based Joint Detection and Decoding for Resistive Random Access Memories
    Ce Sun, Kui Cai, Guanghui Song, Tony Q. S. Quek, Zesong Fei
    http://arxiv.org/abs/2111.01988v2

    • [cs.IT]Energy Efficiency of Uplink Cell-Free Massive MIMO With Transmit Power Control in Measured Propagation Channel
    Thomas Choi, Masaaki Ito, Issei Kanno, Jorge Gomez-Ponce, Colton Bullard, Takeo Ohseki, Kosuke Yamazaki, Andreas F. Molisch
    http://arxiv.org/abs/2111.02514v1

    • [cs.IT]Energy-Efficient Online Data Sensing and Processing in Wireless Powered Edge Computing Systems
    Xian Li, Suzhi Bi, Yuan Zheng, Hui Wang
    http://arxiv.org/abs/2111.02593v1

    • [cs.IT]Map-Assisted Power Allocation and Constellation Design for mmWave WDM with OAM in Short-Range LOS Environment
    Yuan Wang, Chen Gong, Zhengyuan Xu
    http://arxiv.org/abs/2111.02921v1

    • [cs.IT]On the Secrecy Design of STAR-RIS assisted Uplink NOMA Networks
    Zheng Zhang, Jian Chen, Yuanwei Liu, Qingqing Wu, Bingtao He, Long Yang
    http://arxiv.org/abs/2111.02642v1

    • [cs.IT]Optimal Discrete Constellation Inputs for Aggregated LiFi-WiFi Networks
    Shuai Ma, Fan Zhang, Songtao Lu, Hang Li, Ruixin Yang, Sihua Shao, Jiaheng Wang, Shiyin Li
    http://arxiv.org/abs/2111.02581v1

    • [cs.IT]Performance Analysis under IRS-User Association for Distributed IRSs Assisted MISO Systems
    Hibatallah Alwazani, Qurrat-Ul-Ain Nadeem, Anas Chaaban
    http://arxiv.org/abs/2111.02531v1

    • [cs.IT]The Age of Information of Short-Packet Communications: Joint or Distributed Encoding?
    Zhifeng Tang, Nan Yang, Parastoo Sadeghi, Xiangyu
    1000
    n Zhou
    http://arxiv.org/abs/2111.02638v1

    • [cs.LG]A Concentration Bound for LSPE(今日学术视野(2021.11.6) - 图3)
    Vivek S. Borkar, Siddharth Chandak, Harsh Dolhare
    http://arxiv.org/abs/2111.02644v1

    • [cs.LG]A Cyber Threat Intelligence Sharing Scheme based on Federated Learning for Network Intrusion Detection
    Mohanad Sarhan, Siamak Layeghy, Nour Moustafa, Marius Portmann
    http://arxiv.org/abs/2111.02791v1

    • [cs.LG]A Fast Parallel Tensor Decomposition with Optimal Stochastic Gradient Descent: an Application in Structural Damage Identification
    Ali Anaissi, Basem Suleiman, Seid Miad Zandavi
    http://arxiv.org/abs/2111.02632v1

    • [cs.LG]A Meta-Learned Neuron model for Continual Learning
    Rodrigue Siry
    http://arxiv.org/abs/2111.02557v1

    • [cs.LG]A Personalized Federated Learning Algorithm: an Application in Anomaly Detection
    Ali Anaissi, Basem Suleiman
    http://arxiv.org/abs/2111.02627v1

    • [cs.LG]A Unified Approach to Coreset Learning
    Alaa Maalouf, Gilad Eini, Ben Mussay, Dan Feldman, Margarita Osadchy
    http://arxiv.org/abs/2111.03044v1

    • [cs.LG]A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Synergy, and Drug-Drug Interaction Prediction
    Benedek Rozemberczki, Stephen Bonner, Andriy Nikolov, Michael Ughetto, Sebastian Nilsson, Eliseo Papa
    http://arxiv.org/abs/2111.02916v1

    • [cs.LG]AlphaD3M: Machine Learning Pipeline Synthesis
    Iddo Drori, Yamuna Krishnamurthy, Remi Rampin, Raoni de Paula Lourenco, Jorge Piazentin Ono, Kyunghyun Cho, Claudio Silva, Juliana Freire
    http://arxiv.org/abs/2111.02508v1

    • [cs.LG]An Interpretable Graph Generative Model with Heterophily
    Sudhanshu Chanpuriya, Ryan A. Rossi, Anup Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco
    http://arxiv.org/abs/2111.03030v1

    • [cs.LG]Attacking Deep Reinforcement Learning-Based Traffic Signal Control Systems with Colluding Vehicles
    Ao Qu, Yihong Tang, Wei Ma
    http://arxiv.org/abs/2111.02845v1

    • [cs.LG]B-Pref: Benchmarking Preference-Based Reinforcement Learning
    Kimin Lee, Laura Smith, Anca Dragan, Pieter Abbeel
    http://arxiv.org/abs/2111.03026v1

    • [cs.LG]Balanced Q-learning: Combining the Influence of Optimistic and Pessimistic Targets
    Thommen George Karimpanal, Hung Le, Majid Abdolshah, Santu Rana, Sunil Gupta, Truyen Tran, Svetha Venkatesh
    http://arxiv.org/abs/2111.02787v1

    • [cs.LG]Benchmarking Multimodal AutoML for Tabular Data with Text Fields
    Xingjian Shi, Jonas Mueller, Nick Erickson, Mu Li, Alexander J. Smola
    http://arxiv.org/abs/2111.02705v1

    • [cs.LG]Communication-Efficient Separable Neural Network for Distributed Inference on Edge Devices
    Jun-Liang Lin, Sheng-De Wang
    http://arxiv.org/abs/2111.02489v1

    • [cs.LG]Consistent Estimation for PCA and Sparse Regression with Oblivious Outliers
    Tommaso d’Orsi, Chih-Hung Liu, Rajai Nasser, Gleb Novikov, David Steurer, Stefan Tiegel
    http://arxiv.org/abs/2111.02966v1

    • [cs.LG]Convolutional generative adversarial imputation networks for spatio-temporal missing data in storm surge simulations
    Ehsan Adeli, Jize Zhang, Alexandros A. Taflanidis
    http://arxiv.org/abs/2111.02823v1

    • [cs.LG]Data-Driven Market Segmentation in Hospitality Using Unsupervised Machine Learning
    Rik van Leeuwen, Ger Koole
    http://arxiv.org/abs/2111.02848v1

    • [cs.LG]Deep Learning Methods for Daily Wildfire Danger Forecasting
    Ioannis Prapas, Spyros Kondylatos, Ioannis Papoutsis, Gustau Camps-Valls, Michele Ronco, Miguel-Ángel Fernández-Torres, Maria Piles Guillem, Nuno Carvalhais
    http://arxiv.org/abs/2111.02736v1

    • [cs.LG]Evaluation of Tree Based Regression over Multiple Linear Regression for Non-normally Distributed Data in Battery Performance
    Shovan Chowdhury, Yuxiao Lin, Boryann Liaw, Leslie Kerby
    http://arxiv.org/abs/2111.02513v1

    • [cs.LG]Finite-Time Consensus Learning for Decentralized Optimization with Nonlinear Gossiping
    Junya Chen, Sijia Wang, Lawrence Carin, Chenyang Tao
    http://arxiv.org/abs/2111.02949v1

    • [cs.LG]Flood forecasting with machine learning models in an operational framework
    Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, Yossi Matias
    http://arxiv.org/abs/2111.02780v1

    • [cs.LG]From Strings to Data Science: a Practical Framework for Automated String Handling
    John W. van Lith, Joaquin Vanschoren
    http://arxiv.org/abs/2111.01868v2

    • [cs.LG]Global Optimality and Finite Sample Analysis of Softmax Off-Policy Actor Critic under State Distribution Mismatch
    Shangtong Zhang, Remi Tachet, Romain Laroche
    http://arxiv.org/abs/2111.02997v1

    • [cs.LG]Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
    Greg Ver Steeg, Aram Galstyan
    http://arxiv.org/abs/2111.02434v1

    • [cs.LG]Identifying nonlinear dynamical systems from multi-modal time series data
    Philine Lou Bommer, Daniel Kramer, Carlo Tombolini, Georgia Koppe, Daniel Durstewitz
    http://arxiv.org/abs/2111.02922v1

    • [cs.LG]Introduction to Coresets: Approximated Mean
    Alaa Maalouf, Ibrahim Jubran, Dan Feldman
    http://arxiv.org/abs/2111.03046v1

    • [cs.LG]Is Bang-Bang Control All You Need? Solving Continuous Control with Bernoulli Policies
    Tim Seyde, Igor Gilitschenski, Wilko Schwa
    f48
    rting, Bartolomeo Stellato, Martin Riedmiller, Markus Wulfmeier, Daniela Rus
    http://arxiv.org/abs/2111.02552v1

    • [cs.LG]Label Ranking through Nonparametric Regression
    Dimitris Fotakis, Alkis Kalavasis, Eleni Psaroudaki
    http://arxiv.org/abs/2111.02749v1

    • [cs.LG]LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso
    Kenan Šehić, Alexandre Gramfort, Joseph Salmon, Luigi Nardi
    http://arxiv.org/abs/2111.02790v1

    • [cs.LG]Leveraging Time Irreversibility with Order-Contrastive Pre-training
    Monica Agrawal, Hunter Lang, Michael Offin, Lior Gazit, David Sontag
    http://arxiv.org/abs/2111.02599v1

    • [cs.LG]Model-Free Risk-Sensitive Reinforcement Learning
    Grégoire Delétang, Jordi Grau-Moya, Markus Kunesch, Tim Genewein, Rob Brekelmans, Shane Legg, Pedro A. Ortega
    http://arxiv.org/abs/2111.02907v1

    • [cs.LG]Modeling Techniques for Machine Learning Fairness: A Survey
    Mingyang Wan, Daochen Zha, Ninghao Liu, Na Zou
    http://arxiv.org/abs/2111.03015v1

    • [cs.LG]Multi-task Learning of Order-Consistent Causal Graphs
    Xinshi Chen, Haoran Sun, Caleb Ellington, Eric Xing, Le Song
    http://arxiv.org/abs/2111.02545v1

    • [cs.LG]OpenFWI: Benchmark Seismic Datasets for Machine Learning-Based Full Waveform Inversion
    Chengyuan Deng, Yinan Feng, Shihang Feng, Peng Jin, Xitong Zhang, Qili Zeng, Youzuo Lin
    http://arxiv.org/abs/2111.02926v1

    • [cs.LG]Parameterized Knowledge Transfer for Personalized Federated Learning
    Jie Zhang, Song Guo, Xiaosong Ma, Haozhao Wang, Wencao Xu, Feijie Wu
    http://arxiv.org/abs/2111.02862v1

    • [cs.LG]Qimera: Data-free Quantization with Synthetic Boundary Supporting Samples
    Kanghyun Choi, Deokki Hong, Noseong Park, Youngsok Kim, Jinho Lee
    http://arxiv.org/abs/2111.02625v1

    • [cs.LG]RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning
    Sabela Ramos, Sertan Girgin, Léonard Hussenot, Damien Vincent, Hanna Yakubovich, Daniel Toyama, Anita Gergely, Piotr Stanczyk, Raphael Marinier, Jeremiah Harmsen, Olivier Pietquin, Nikola Momchev
    http://arxiv.org/abs/2111.02767v1

    • [cs.LG]Real-time Wireless Transmitter Authorization: Adapting to Dynamic Authorized Sets with Information Retrieval
    Samurdhi Karunaratne, Samer Hanna, Danijela Cabric
    http://arxiv.org/abs/2111.02584v1

    • [cs.LG]Recurrent Neural Network Training with Convex Loss and Regularization Functions by Extended Kalman Filtering
    Alberto Bemporad
    http://arxiv.org/abs/2111.02673v1

    • [cs.LG]Representation Edit Distance as a Measure of Novelty
    Joshua Alspector
    http://arxiv.org/abs/2111.02770v1

    • [cs.LG]Scanflow: A multi-graph framework for Machine Learning workflow management, supervision, and debugging
    Gusseppe Bravo-Rocca, Peini Liu, Jordi Guitart, Ajay Dholakia, David Ellison, Jeffrey Falkanger, Miroslav Hodak
    http://arxiv.org/abs/2111.03003v1

    • [cs.LG]Shift Happens: Adjusting Classifiers
    Theodore James Thibault Heiser, Mari-Liis Allikivi, Meelis Kull
    http://arxiv.org/abs/2111.02529v1

    • [cs.LG]Testing using Privileged Information by Adapting Features with Statistical Dependence
    Kwang In Kim, James Tompkin
    http://arxiv.org/abs/2111.02865v1

    • [cs.LG]Towards an Understanding of Default Policies in Multitask Policy Optimization
    Ted Moskovitz, Michael Arbel, Jack Parker-Holder, Aldo Pacchiano
    http://arxiv.org/abs/2111.02994v1

    • [cs.LG]Unsupervised Change Detection of Extreme Events Using ML On-Board
    Vít Růžička, Anna Vaughan, Daniele De Martini, James Fulton, Valentina Salvatelli, Chris Bridges, Gonzalo Mateo-Garcia, Valentina Zantedeschi
    http://arxiv.org/abs/2111.02995v1

    • [cs.LG]Variational Inference with Holder Bounds
    Junya Chen, Danni Lu, Zidi Xiu, Ke Bai, Lawrence Carin, Chenyang Tao
    http://arxiv.org/abs/2111.02947v1

    • [cs.LG]WaveFake: A Data Set to Facilitate Audio Deepfake Detection
    Joel Frank, Lea Schönherr
    http://arxiv.org/abs/2111.02813v1

    • [cs.LG]When Neural Networks Using Different Sensors Create Similar Features
    Hugues Moreau, Andréa Vassilev, Liming Chen
    http://arxiv.org/abs/2111.02732v1

    • [cs.LO]Logically Sound Arguments for the Effectiveness of ML Safety Measures
    Chih-Hong Cheng, Tobias Schuster, Simon Burton
    http://arxiv.org/abs/2111.02649v1

    • [cs.RO]A System for General In-Hand Object Re-Orientation
    Tao Chen, Jie Xu, Pulkit Agrawal
    http://arxiv.org/abs/2111.03043v1

    • [cs.RO]Causal versus Marginal Shapley Values for Robotic Lever Manipulation Controlled using Deep Reinforcement Learning
    Sindre Benjamin Remman, Inga Strümke, Anastasios M. Lekkas
    http://arxiv.org/abs/2111.02936v1

    • [cs.RO]Deep Direct Visual Servoing of Tendon-Driven Continuum Robots
    Ibrahim Abdulhafiz, Ali A. Nazari, Taha Abbasi-Hashemi, Amir Jalali, Kourosh Zareinia, Sajad Saeedi, Farrokh Janabi-Sharifi
    http://arxiv.org/abs/2111.02580v1

    • [cs.RO]Extended Abstract Version: CNN-based Human Detection System for UAVs in Search and Rescue
    Nikite Mesvan
    http://arxiv.org/abs/2111.02870v1

    • [cs.RO]Generalization in Dexterous Manipulation via Geometry-Aware Multi-Task Learning
    Wenlong Huang, Igor Mordatch, Pieter Abbeel, Deepak Pathak
    http://arxiv.org/abs/2111.03062v1

    • [cs.RO]Learning suction graspability considering grasp quality and robot reachability for bin-picking
    Ping Jiang, Junji Oaki, Yoshiyuki Ishihara, Junichiro Ooga, Haifeng Han, Atsushi Sugahara, Seiji Tokura, Haruna Eto, Kazuma Komoda, Akihito Ogawa
    http://arxiv.org/abs/2111.02571v1

    • [cs.RO]Speed Maps: An Application to Guide Robots in Human Environments
    Akansel Cosgun
    http://arxiv.org/abs/2111.02659v1

    • [cs.RO]Stein Variational Probabilistic Roadmaps
    Alexander Lambert, Brian Hou, Rosario Scalise, Siddhartha S. Srinivasa, Byron Boots
    http://arxiv.org/abs/2111.02972v1

    • [cs.RO]Using Graph-Theoretic Machine Learning to Predict Human Driver Behavior
    Rohan Chandra, Aniket Bera, Dinesh Manocha
    http://arxiv.org/abs/2111.02964v1

    • [cs.SD]InQSS: a speech intelligibility assessment model using a multi-task learning network
    Yu-Wen Chen, Yu Tsao
    http://arxiv.org/abs/2111.02585v1

    • [cs.SD]MT3: Multi-Task Multitrack Music Transcription
    Josh Gardner, Ian Simon, Ethan Manilow, Curtis Hawthorne, Jesse Engel
    http://arxiv.org/abs/2111.03017v1

    • [cs.SE]GraphSearchNet: Enhancing GNNs via Capturing Global Dependency for Semantic Code Search
    Shangqing Liu, Xiaofei Xie, Lei Ma, Jingkai Siow, Yang Liu
    http://arxiv.org/abs/2111.02671v1

    • [cs.SI]Cost-effective Network Disintegration through Targeted Enumeration
    Zhi-Gang Wang, Ye Deng, Zeng-Ru Di, Jun Wu
    http://arxiv.org/abs/2111.02655v1

    • [cs.SI]Engaging Politically Diverse Audiences on Social Media
    Martin Saveski, Doug Beeferman, David McClure, Deb Roy
    http://arxiv.org/abs/2111.02646v1

    • [cs.SI]Shifting Polarization and Twitter News Influencers between two U.S. Presidential Elections
    James Flamino, Alessandro Galezzi, Stuart Feldman, Michael W. Macy, Brendan Cross, Zhenkun Zhou, Matteo Serafino, Alexandre Bovet, Hernan A. Makse, Boleslaw K. Szymanski
    http://arxiv.org/abs/2111.02505v1

    • [eess.AS]Voice Conversion Can Improve ASR in Very Low-Resource Settings
    Matthew Baas, Herman Kamper
    http://arxiv.org/abs/2111.02674v1

    • [eess.IV]Automatic ultrasound vessel segmentation with deep spatiotemporal context learning
    Baichuan Jiang, Alvin Chen, Shyam Bharat, Mingxin Zheng
    http://arxiv.org/abs/2111.02461v1

    • [eess.IV]Breast Cancer Classification Using: Pixel Interpolation
    Osama Rezq Shahin, Hamdy Mohammed Kelash, Gamal Mahrous Attiya, Osama Slah Farg Allah
    http://arxiv.org/abs/2111.02409v1

    • [eess.IV]Partial supervision for the FeTA challenge 2021
    Lucas Fidon, Michael Aertsen, Suprosanna Shit, Philippe Demaerel, Sébastien Ourselin, Jan Deprest, Tom Vercauteren
    http://arxiv.org/abs/2111.02408v1

    • [eess.IV]Resampling and super-resolution of hexagonally sampled images using deep learning
    Dylan Flaute, Russell C. Hardie, Hamed Elwarfalli
    http://arxiv.org/abs/2111.02520v1

    • [eess.IV]Skin Cancer Classification using Inception Network and Transfer Learning
    Priscilla Benedetti, Damiano Perri, Marco Simonetti, Osvaldo Gervasi, Gianluca Reali, Mauro Femminella
    http://arxiv.org/abs/2111.02402v1

    • [eess.IV]The role of MRI physics in brain segmentation CNNs: achieving acquisition invariance and instructive uncertainties
    Pedro Borges, Richard Shaw, Thomas Varsavsky, Kerstin Klaser, David Thomas, Ivana Drobnjak, Sebastien Ourselin, M Jorge Cardoso
    http://arxiv.org/abs/2111.02771v1

    • [eess.IV]Towards dynamic multi-modal phenotyping using chest radiographs and physiological data
    Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout
    http://arxiv.org/abs/2111.02710v1

    • [eess.IV]WORD: Revisiting Organs Segmentation in the Whole Abdominal Region
    Xiangde Luo, Wenjun Liao, Jianghong Xiao, Tao Song, Xiaofan Zhang, Kang Li, Guotai Wang, Shaoting Zhang
    http://arxiv.org/abs/2111.02403v1

    • [eess.SP]Roadmap on Signal Processing for Next Generation Measurement Systems
    D. K. Iakovidis, M. Ooi, Y. C. Kuang, S. Damidenko, A. Shestakov, V. Sinistin, M. Henry, A. Sciacchitano, A. Discetti, S. Donati, M. Norgia, A. Menychtas, I. Maglogiannis, S. C. Wriessnegger, L. A. Barradas Chacon, G. Dimas, D. Filos, A. H. Aletras, J. Töger, F. Dong, S. Ren, A. Uhl, J. Paziewski, J. Geng, F. Fioranelli, R. M. Narayanan, C. Fernandez, C. Stiller, K. Malamousi, S. Kamnis, K. Delibasis, D. Wang, J. Zhang, R. X. Gao
    http://arxiv.org/abs/2111.02493v1

    • [math.NA]Accelerated replica exchange stochastic gradient Langevin diffusion enhanced Bayesian DeepONet for solving noisy parametric PDEs
    Guang Lin, Christian Moya, Zecheng Zhang
    http://arxiv.org/abs/2111.02484v1

    • [math.OC]A Riemannian Accelerated Proximal Extragradient Framework and its Implications
    Jikai Jin, Suvrit Sra
    http://arxiv.org/abs/2111.02763v1

    • [math.OC]A control method for solving high-dimensional Hamiltonian systems through deep neural networks
    Shaolin Ji, Shige Peng, Ying Peng, Xichuan Zhang
    http://arxiv.org/abs/2111.02636v1

    • [math.OC]Optimal Recovery from Inaccurate Data in Hilbert Spaces: Regularize, but what of the Parameter?
    Simon Foucart, Chunyang Liao
    http://arxiv.org/abs/2111.02601v1

    • [math.OC]Quasi-Newton Methods for Saddle Point Problems
    Chengchang Liu, Luo Luo
    http://arxiv.org/abs/2111.02708v1

    • [math.ST]Differential Privacy Over Riemannian Manifolds
    Matthew Reimherr, Karthik Bharath, Carlos Soto
    http://arxiv.org/abs/2111.02516v1

    • [math.ST]Finding the Optimal Dynamic Treatment Regime Using Smooth Fisher Consistent Surrogate Loss
    Nilanjana Laha, Aaron Sonabend-W, Rajarshi Mukherjee, Tianxi Cai
    http://arxiv.org/abs/2111.02826v1

    • [math.ST]On Johnson’s “sufficientness” postulates for features-sampling models
    Federico Camerlenghi, Stefano Favaro
    http://arxiv.org/abs/2111.02456v1

    • [math.ST]Proximal Causal Inference with Hidden Mediators: Front-Door and Related Mediation Problems
    AmirEmad Ghassami, Ilya Shpitser, Eric Tchetgen Tchetgen
    http://arxiv.org/abs/2111.02927v1

    • [physics.flu-dyn]Symmetry-Aware Autoencoders: s-PCA and s-nlPCA
    Simon Kneer, Taraneh Sayadi, Denis Sipp, Peter Schmid, Georgios Rigas
    http://arxiv.org/abs/2111.02893v1

    • [physics.med-ph]A semi-automatic ultrasound image analysis system for the grading diagnosis of COVID-19 pneumonia
    Yuanyuan Wang, Yao Zhang, Qiong He, Hongen Liao, Jianwen Luo
    http://arxiv.org/abs/2111.02676v1

    • [physics.soc-ph]Efficacy the of Confinement Policies on the COVID-19 Spread Dynamics in the Early Period of the Pandemic
    Mehedi Hassan, Md Enamul Haque, Mehmet Engin Tozal
    http://arxiv.org/abs/2111.03020v1

    • [q-bio.GN]An Information-Theoretic Framework for Identifying Age-Related Genes Using Human Dermal Fibroblast Transcriptome Data
    Salman Mohamadi, Donald Adjeroh
    http://arxiv.org/abs/2111.02595v1

    • [q-bio.GN]Human Age Estimation from Gene Expression Data using Artificial Neural Networks
    Salman Mohamadi, Gianfranco. Doretto, Nasser M. Nasrabadi, Donald A. Adjeroh
    http://arxiv.org/abs/2111.02692v1

    • [q-bio.NC]Sensory attenuation develops as a result of sensorimotor experience
    Hayato Idei, Wataru Ohata, Yuichi Yamashita, Tetsuya Ogata, Jun Tani
    http://arxiv.org/abs/2111.02666v1

    • [q-bio.PE]Effective Resistance for Pandemics: Mobility Network Sparsification for High-Fidelity Epidemic Simulation
    Alexander M. Mercier, Samuel V. Scarpino, Cristopher Moore
    http://arxiv.org/abs/2111.02449v1

    • [quant-ph]Fundamental limitations on device-independent quantum conference key agreement
    Karol Horodecki, Marek Winczewski, Siddhartha Das
    http://arxiv.org/abs/2111.02467v1

    • [quant-ph]Graph neural network initialisation of quantum approximate optimisation
    Nishant Jain, Brian Coyle, Elham Kashefi, Niraj Kumar
    http://arxiv.org/abs/2111.03016v1

    • [quant-ph]Quantum tangent kernel
    Norihito Shirai, Kenji Kubo, Kosuke Mitarai, Keisuke Fujii
    http://arxiv.org/abs/2111.02951v1

    • [quant-ph]Weighted Quantum Channel Compiling through Proximal Policy Optimization
    Weiyuan Gong, Si Jiang, Dong-Ling Deng
    http://arxiv.org/abs/2111.02426v1

    • [stat.AP]Effects of Mixed Distribution Statistical Flood Frequency Models on Dam Safety Assessments: A Case Study of the Pueblo Dam, USA
    K. J. Roop-Eckart, Sanjib Sharma, Mahkameh Zarekarizi, Ben Seiyon Lee, Caitlin Spence, Tess Russo, Klaus Keller
    http://arxiv.org/abs/2111.02610v1

    • [stat.AP]Estimating SARS-CoV-2 Seroprevalence
    Samuel Rosin, Bonnie E. Shook-Sa, Stephen R. Cole, Michael G. Hudgens
    http://arxiv.org/abs/2111.02910v1

    • [stat.AP]Joint Species Distribution Modeling with species competition and non-stationary spatial random effects
    Juho Kettunen, Lauri Mehtätalo, Eeva-Stiina Tuittila, Aino Korrensalo, Jarno Vanhatalo
    http://arxiv.org/abs/2111.02460v1

    • [stat.AP]Robust Online Detection in Serially Correlated Directed Network
    Miaomiao Yu, Yuhao Zhou, Fugee Tsung
    http://arxiv.org/abs/2111.02653v1

    • [stat.AP]The Psychological Gains from COVID-19 Vaccination: Who Benefits the Most?
    Manuel Bagues, Velichka Dimitrova
    http://arxiv.org/abs/2111.02197v1

    • [stat.ME]Covariance Structure Estimation with Laplace Approximation
    Bongjung Sung, Jaeyong Lee
    http://arxiv.org/abs/2111.02637v1

    • [stat.ME]Extended Principal Component Analysis
    Pablo Soto-Quiros, Anatoli Torokhti
    http://arxiv.org/abs/2111.03040v1

    • [stat.ME]Mixed Models and Shrinkage Estimation for Balanced and Unbalanced Designs
    Yihan Bao, James G. Booth
    http://arxiv.org/abs/2111.02829v1

    • [stat.ME]Nonparametric Simulation Extrapolation for Measurement Error Models
    Dylan Spicker, Michael Wallace, Grace Yi
    http://arxiv.org/abs/2111.02863v1

    • [stat.ME]Online Estimation for Functional Data
    Ying Yang, Fang Yao
    http://arxiv.org/abs/2111.02750v1

    • [stat.ML]Adversarial Attacks on Graph Classification via Bayesian Optimisation
    Xingchen Wan, Henry Kenlay, Binxin Ru, Arno Blaas, Michael A. Osborne, Xiaowen Dong
    http://arxiv.org/abs/2111.02842v1

    • [stat.ML]Causal inference with imperfect instrumental variables
    Nikolai Miklin, Mariami Gachechiladze, George Moreno, Rafael Chaves
    http://arxiv.org/abs/2111.03029v1

    • [stat.ML]Conformal prediction for text infilling and part-of-speech prediction
    Neil Dey, Jing Ding, Jack Ferrell, Carolina Kapper, Maxwell Lovig, Emiliano Planchon, Jonathan P Williams
    http://arxiv.org/abs/2111.02592v1

    • [stat.ML]Ex今日学术视野(2021.11.6) - 图4MCMC: Sampling through Exploration Exploitation
    Evgeny Lagutin, Daniil Selikhanovych, Achille Thin, Sergey Samsonov, Alexey Naumov, Denis Belomestny, Maxim Panov, Eric Moulines
    http://arxiv.org/abs/2111.02702v1

    • [stat.ML]Perturb-and-max-product: Sampling and learning in discrete energy-based models
    Miguel Lazaro-Gredilla, Antoine Dedieu, Dileep George
    http://arxiv.org/abs/2111.02458v1