cond-mat.str-el - 强关联电子系统
    cs.AI - 人工智能
    cs.AR - 硬件体系结构
    cs.CG - 计算几何学
    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.GR - 计算机图形学
    cs.HC - 人机接口
    cs.IR - 信息检索
    cs.IT - 信息论
    cs.LG - 自动学习
    cs.NE - 神经与进化计算
    cs.RO - 机器人学
    cs.SD - 声音处理
    cs.SI - 社交网络与信息网络
    econ.EM - 计量经济学
    econ.GN - 一般经济学
    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
    hep-ex - 高能物理实验
    math.OC - 优化与控制
    math.ST - 统计理论
    physics.soc-ph - 物理学与社会
    q-bio.BM - 生物分子
    q-bio.NC - 神经元与认知
    q-bio.QM - 定量方法
    q-fin.PM - 投资组合管理
    stat.AP - 应用统计
    stat.ME - 统计方法论
    stat.ML - (统计)机器学习

    • [cond-mat.str-el]Ab-initio study of interacting fermions at finite temperature with neural canonical transformation
    • [cs.AI]AI and Ethics — Operationalising Responsible AI
    • [cs.AI]Actively Learning Concepts and Conjunctive Queries under ELr-Ontologies
    • [cs.AI]Deep Reinforcement Learning for Optimal Stopping with Application in Financial Engineering
    • [cs.AI]Markdowns in E-Commerce Fresh Retail: A Counterfactual Prediction and Multi-Period Optimization Approach
    • [cs.AI]MedSensor: Medication Adherence Monitoring Using Neural Networks on Smartwatch Accelerometer Sensor Data
    • [cs.AI]More Similar Values, More Trust? — the Effect of Value Similarity on Trust in Human-Agent Interaction
    • [cs.AI]Online Selection of Diverse Committees
    • [cs.AI]Program Synthesis as Dependency Quantified Formula Modulo Theory
    • [cs.AI]Provable Guarantees on the Robustness of Decision Rules to Causal Interventions
    • [cs.AR]Block Convolution: Towards Memory-Efficient Inference of Large-Scale CNNs on FPGA
    • [cs.AR]RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance
    • [cs.CG]Obstructing Classification via Projection
    • [cs.CL]A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated Learning
    • [cs.CL]A Sequence-to-Set Network for Nested Named Entity Recognition
    • [cs.CL]An Automated Method to Enrich Consumer Health Vocabularies Using GloVe Word Embeddings and An Auxiliary Lexical Resource
    • [cs.CL]Answering Product-Questions by Utilizing Questions from Other Contextually Similar Products
    • [cs.CL]Combining GCN and Transformer for Chinese Grammatical Error Detection
    • [cs.CL]Detection of Emotions in Hindi-English Code Mixed Text Data
    • [cs.CL]Do Models Learn the Directionality of Relations? A New Evaluation Task: Relation Direction Recognition
    • [cs.CL]Effective Attention Sheds Light On Interpretability
    • [cs.CL]Essay-BR: a Brazilian Corpus of Essays
    • [cs.CL]Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
    • [cs.CL]Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixing
    • [cs.CL]Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies
    • [cs.CL]Investigating Math Word Problems using Pretrained Multilingual Language Models
    • [cs.CL]LCP-RIT at SemEval-2021 Task 1: Exploring Linguistic Features for Lexical Complexity Prediction
    • [cs.CL]Laughing Heads: Can Transformers Detect What Makes a Sentence Funny?
    • [cs.CL]Learning Language Specific Sub-network for Multilingual Machine Translation
    • [cs.CL]Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence
    • [cs.CL]Methods for Detoxification of Texts for the Russian Language
    • [cs.CL]OpenMEVA: A Benchmark for Evaluating Open-ended Story Generation Metrics
    • [cs.CL]Partner Matters! An Empirical Study on Fusing Personas for Personalized Response Selection in Retrieval-Based Chatbots
    • [cs.CL]QuatDE: Dynamic Quaternion Embedding for Knowledge Graph Completion
    • [cs.CL]Representation Learning in Sequence to Sequence Tasks: Multi-filter Gaussian Mixture Autoencoder
    • [cs.CL]Representation Learning in Sequence to Sequence Tasks: Multi-filter Gaussian Mixture Autoencoder
    • [cs.CL]Retrieval-Augmented Transformer-XL for Close-Domain Dialog Generation
    • [cs.CL]Sentence Extraction-Based Machine Reading Comprehension for Vietnamese
    • [cs.CL]Stylized Story Generation with Style-Guided Planning
    • [cs.CL]TableZa — A classical Computer Vision approach to Tabular Extraction
    • [cs.CR]Analyzing Machine Learning Approaches for Online Malware Detection in Cloud
    • [cs.CR]DID-eFed: Facilitating Federated Learning as a Service with Decentralized Identities
    • [cs.CR]Machine learning on knowledge graphs for context-aware security monitoring
    • [cs.CR]Private Hierarchical Clustering in Federated Networks
    • [cs.CV]A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep Learning
    • [cs.CV]A Novel lightweight Convolutional Neural Network, ExquisiteNetV2
    • [cs.CV]An Orthogonal Classifier for Improving the Adversarial Robustness of Neural Networks
    • [cs.CV]Analyzing the effectiveness of image augmentations for face recognition from limited data
    • [cs.CV]BatchQuant: Quantized-for-all Architecture Search with Robust Quantizer
    • [cs.CV]Correlated Adversarial Joint Discrepancy Adaptation Network
    • [cs.CV]Deep Learning Radio Frequency Signal Classification with Hybrid Images
    • [cs.CV]Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation
    • [cs.CV]Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?
    • [cs.CV]Efficient Transfer Learning via Joint Adaptation of Network Architecture and Weight
    • [cs.CV]Font Style that Fits an Image — Font Generation Based on Image Context
    • [cs.CV]Generalizable Person Re-identification with Relevance-aware Mixture of Experts
    • [cs.CV]High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network
    • [cs.CV]Large-scale Localization Datasets in Crowded Indoor Spaces
    • [cs.CV]Learn Fine-grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images
    • [cs.CV]Learning optimally separated class-specific subspace representations using convolutional autoencoder
    • [cs.CV]Light-weight Document Image Cleanup using Perceptual Loss
    • [cs.CV]Local Aggressive Adversarial Attacks on 3D Point Cloud
    • [cs.CV]Localization and Tracking of User-Defined Points on Deformable Objects for Robotic Manipulation
    • [cs.CV]Multi-Person Extreme Motion Prediction with Cross-Interaction Attention
    • [cs.CV]Multimodal Deep Learning Framework for Image Popularity Prediction on Social Media
    • [cs.CV]Multiple Meta-model Quantifying for Medical Visual Question Answering
    • [cs.CV]Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction
    • [cs.CV]PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency
    • [cs.CV]Pathdreamer: A World Model for Indoor Navigation
    • [cs.CV]Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation
    • [cs.CV]Recursive-NeRF: An Efficient and Dynamically Growing NeRF
    • [cs.CV]Self-Supervised Learning for Fine-Grained Visual Categorization
    • [cs.CV]XCycles Backprojection Acoustic Super-Resolution
    • [cs.CY]A Generalized Framework for Measuring Pedestrian Accessibility around the World Using Open Data
    • [cs.CY]Confronting Structural Inequities in AI for Education
    • [cs.CY]Copyright in Generative Deep Learning
    • [cs.CY]IT ambidexterity and patient agility: the mediating role of digital dynamic capability
    • [cs.CY]Measuring the technological pedagogical content knowledge (TPACK) of in-service teachers of computer science who teach algorithms and programming in upper secondary education
    • [cs.CY]The State of AI Ethics Report (January 2021)
    • [cs.CY]The State of AI Ethics Report (Volume 4)
    • [cs.DB]Revisiting Data Compression in Column-Stores
    • [cs.DC]Can We Break Symmetry with o(m) Communication?
    • [cs.DC]Federated Singular Vector Decomposition
    • [cs.DC]High performance and energy efficient inference for deep learning on ARM processors
    • [cs.DC]OpenGraphGym-MG: Using Reinforcement Learning to Solve Large Graph Optimization Problems on MultiGPU Systems
    • [cs.DC]TRIM: A Design Space Exploration Model for Deep Ne
    1000
    ural Networks Inference and Training Accelerators
    • [cs.GR]Guided Facial Skin Color Correction
    • [cs.HC]Assessing the Learning Behavioral Intention of Commuters in Mobility Practices
    • [cs.HC]Digital competency of educators in the virtual learning environment: a structural equation modeling analysis
    • [cs.HC]Three prophylactic interventions to counter fake news on social media
    • [cs.IR]An Overview of Computer Supported Query Formulation
    • [cs.IR]Combating Ambiguity for Hash-code Learning in Medical Instance Retrieval
    • [cs.IR]Extracting Variable-Depth Logical Document Hierarchy from Long Documents: Method, Evaluation, and Application
    • [cs.IR]Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction
    • [cs.IR]On Interpretation and Measurement of Soft Attributes for Recommendation
    • [cs.IR]POINTREC: A Test Collection for Narrative-driven Point of Interest Recommendation
    • [cs.IR]Where are we in embedding spaces? A Comprehensive Analysis on Network Embedding Approaches for Recommender Systems
    • [cs.IT]An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs
    • [cs.IT]Enhancing Security of TAS/MRC Based Mixed RF-UOWC System with Induced Underwater Turbulence Effect
    • [cs.IT]Model-based and Data-driven Approaches for Downlink Massive MIMO Channel Estimation
    • [cs.IT]On the Secrecy Capacity of 2-user Gaussian Z-Interference Channel with Shared Key
    • [cs.IT]Staircase codes with non-systematic polar codes
    • [cs.IT]Unsupervised Learning of Adaptive Codebooks for Deep Feedback Encoding in FDD Systems
    • [cs.IT]User-centric Handover in mmWave Cell-Free Massive MIMO with User Mobility
    • [cs.LG]Accelerating Gossip SGD with Periodic Global Averaging
    • [cs.LG]Boosting Variational Inference With Locally Adaptive Step-Sizes
    • [cs.LG]Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation
    • [cs.LG]Compositional Processing Emerges in Neural Networks Solving Math Problems
    • [cs.LG]Diffusion Approximations for Thompson Sampling
    • [cs.LG]DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality
    • [cs.LG]E(n) Equivariant Normalizing Flows for Molecule Generation in 3D
    • [cs.LG]Errors-in-Variables for deep learning: rethinking aleatoric uncertainty
    • [cs.LG]Fast and Slow Learning of Recurrent Independent Mechanisms
    • [cs.LG]Free Energy Node Embedding via Generalized Skip-gram with Negative Sampling
    • [cs.LG]Gym-ANM: Open-source software to leverage reinforcement learning for power system management in research and education
    • [cs.LG]Image to Image Translation : Generating maps from satellite images
    • [cs.LG]Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning
    • [cs.LG]Incentivized Bandit Learning with Self-Reinforcing User Preferences
    • [cs.LG]Latent Gaussian Model Boosting
    • [cs.LG]Learning and Information in Stochastic Networks and Queues
    • [cs.LG]Masked Contrastive Learning for Anomaly Detection
    • [cs.LG]Meta-Reinforcement Learning by Tracking Task Non-stationarity
    • [cs.LG]Periodic Freight Demand Forecasting for Large-scale Tactical Planning
    • [cs.LG]Physical Constraint Embedded Neural Networks for inference and noise regulation
    • [cs.LG]Predicting Flight Delay with Spatio-Temporal Trajectory Convolutional Network and Airport Situational Awareness Map
    • [cs.LG]Prototype Guided Federated Learning of Visual Feature Representations
    • [cs.LG]Reinforcement Learning Assisted Oxygen Therapy for COVID-19 Patients Under Intensive Care
    • [cs.LG]Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning
    • [cs.LG]Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead
    • [cs.LG]Sparsity Prior Regularized Q-learning for Sparse Action Tasks
    • [cs.LG]Tool- and Domain-Agnostic Parameterization of Style Transfer Effects Leveraging Pretrained Perceptual Metrics
    • [cs.LG]Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms
    • [cs.LG]Variability of Artificial Neural Networks
    • [cs.LG]When Deep Classifiers Agree: Analyzing Correlations between Learning Order and Image Statistics
    • [cs.LG]rx-anon — A Novel Approach on the De-Identification of Heterogeneous Data based on a Modified Mondrian Algorithm
    • [cs.NE]Sparse Spiking Gradient Descent
    • [cs.RO]Active Visual SLAM with independently rotating camera
    • [cs.RO]Coverage Path Planning for Spraying Drones
    • [cs.RO]Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments
    • [cs.RO]Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data
    • [cs.RO]Projector-Guided Non-Holonomic Mobile 3D Printing
    • [cs.RO]Teaching Continuity in Robotics Labs in the Age of Covid and Beyond
    • [cs.RO]VSGM — Enhance robot task understanding ability through visual semantic graph
    • [cs.SD]Attack on practical speaker verification system using universal adversarial perturbations
    • [cs.SD]Music Generation using Deep Learning
    • [cs.SD]Unsupervised Discriminative Learning of Sounds for Audio Event Classification
    • [cs.SI]Educators, Solicitors, Flamers, Motivators, Sympathizers: Characterizing Roles in Online Extremist Movements
    • [cs.SI]Forecasting managerial turnover through e-mail based social network analysis
    • [cs.SI]Interventions with Inversity in Unknown Networks Can Help Regulate Contagion
    • [cs.SI]Robustness and stability of enterprise intranet social networks: The impact of moderators
    • [cs.SI]The Complex Community Structure of the Bitcoin Address Correspondence Network
    • [econ.EM]The Minimax Estimator of the Average Treatment Effect, among Linear Combinations of Conditional Average Treatment Effects Estimators
    • [econ.GN]Using four different online media sources to forecast the crude oil price
    • [eess.AS]Disentanglement Learning for Variational Autoencoders Applied to Audio-Visual Speech Enhancement
    • [eess.IV]Adaptive Hypergraph Convolutional Network for No-Reference 360-degree Image Quality Assessment
    • [eess.IV]Joint Calibrationless Reconstruction and Segmentation of Parallel MRI
    • [eess.IV]Multi-Contrast MRI Super-Resolution via a Multi-Stage Integration Network
    • [eess.IV]TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation
    • [eess.SP]Foundations of MIMO Radar Detection Aided by Reconfigurable Intelligent Surfaces
    • [eess.SY]Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimization
    • [hep-ex]Physics Validation of Novel Convolutional 2D Architectures for Speeding Up High Energy Physics Simulations
    • [math.OC]A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows
    • [math.OC]Distributionally Constrained Black-Box Stochastic Gradient Estimation and Optimization
    • [math.ST]A Note on High-Dimensional Confidence Regions
    • [math.ST]Local estimators and Bayesian inverse problems with non-unique solutions
    • [math.ST]Multiply Robust Causal Mediation Analysis with Continuous Treatments
    • [math.ST]Testing partial conjunction hypotheses under dependency, with applications to meta-analysis
    • [math.ST]The convergence speed of MLE to the information projection of an exponential family — a criteria for the model dimension and the sample size — with complete proof
    • [physics.soc-ph]A Phase Transition in Large Network Games
    • [physics.soc-ph]The effect of algorithmic bias and network structure on coexistence, consensus, and polarization of opinions
    • [q-bio.BM]Conformational variability of loops in the SARS-CoV-2 spike protein
    • [q-bio.NC]Complementary Structure-Learning Neural Networks for Relational Reasoning
    • [q-bio.QM]Detection of Multidecadal Changes in Vegetation Dynamics and Association with Intra-annual Climate Variability in the Columbia River Basin
    • [q-fin.PM]Robo-Advising: Enhancing Investment with Inverse Optimization and Deep Reinforcement Learning
    • [stat.AP]Changes in Crime Rates During the COVID-19 Pandemic
    • [stat.AP]Modelling short-term precipitation extremes with the blended generalised extreme value distribution
    • [stat.AP]Pooled testing and its applications in the COVID-19 pandemic
    • [stat.AP]Statistical Learning for Best Practices in Tattoo Removal
    • [stat.ME]A unified framework on defining depth for point process using function smoothing
    • [stat.ME]Conformal histogram regression
    • [stat.ME]Flexible Specification Testing in Semi-Parametric Quantile Regression Models
    • [stat.ME]High-dimensional Change-point Detection Using Generalized Homogeneity Metrics
    • [stat.ME]Improving Adaptive Seamless Designs through Bayesian optimization
    • [stat.ME]Markov-Restricted Analysis of Randomized Trials with Non-Monotone Missing Binary Outcomes: Sensitivity Analysis and Identification Results
    • [stat.ME]Maximum profile binomial likelihood estimation for the semiparametric Box—Cox power transformation model
    • [stat.ME]Measuring performance for end-of-life care
    • [stat.ME]New classes of tests for the Weibull distribution using Stein’s method in the presence of random right censoring
    • [stat.ME]Point estimation for adaptive trial designs
    • [stat.ME]Standard Curves for Empirical Likelihood Ratio Tests of Means
    • [stat.ML]Calibrating sufficiently
    • [stat.ML]From parcel to continental scale — A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations
    • [stat.ML]Localization, Convexity, and Star Aggregation
    • [stat.ML]Mill.jl and JsonGrinder.jl: automated differentiable feature extraction for learning from raw JSON data
    • [stat.ML]Statistical Optimality and Computational Efficiency of Nyström Kernel PCA

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

    • [cond-mat.str-el]Ab-initio study of interacting fermions at finite temperature with neural canonical transformation
    Hao Xie, Linfeng Zhang, Lei Wang
    http://arxiv.org/abs/2105.08644v1

    • [cs.AI]AI and Ethics — Operationalising Responsible AI
    Liming Zhu, Xiwei Xu, Qinghua Lu, Guido Governatori, Jon Whittle
    http://arxiv.org/abs/2105.08867v1

    • [cs.AI]Actively Learning Concepts and Conjunctive Queries under ELr-Ontologies
    Maurice Funk, Jean Christoph Jung, Carsten Lutz
    http://arxiv.org/abs/2105.08326v2

    • [cs.AI]Deep Reinforcement Learning for Optimal Stopping with Application in Financial Engineering
    Abderrahim Fathan, Erick Delage
    http://arxiv.org/abs/2105.08877v1

    • [cs.AI]Markdowns in E-Commerce Fresh Retail: A Counterfactual Prediction and Multi-Period Optimization Approach
    Junhao Hua, Ling Yan, Huan Xu, Cheng Yang
    http://arxiv.org/abs/2105.08313v2

    • [cs.AI]MedSensor: Medication Adherence Monitoring Using Neural Networks on Smartwatch Accelerometer Sensor Data
    Chrisogonas Odhiambo, Pamela Wright, Cindy Corbett, Homayoun Valafar
    http://arxiv.org/abs/2105.08907v1

    • [cs.AI]More Similar Values, More Trust? — the Effect of Value Similarity on Trust in Human-Agent Interaction
    Siddharth Mehrotra, Catholijn M. Jonker, Myrthe L. Tielman
    http://arxiv.org/abs/2105.09222v1

    • [cs.AI]Online Selection of Diverse Committees
    Virginie Do, Jamal Atif, Jérôme Lang, Nicolas Usunier
    http://arxiv.org/abs/2105.09295v1

    • [cs.AI]Program Synthesis as Dependency Quantified Formula Modulo Theory
    Priyanka Golia, Subhajit Roy, Kuldeep S. Meel
    http://arxiv.org/abs/2105.09221v1

    • [cs.AI]Provable Guarantees on the Robustness of Decision Rules to Causal Interventions
    Benjie Wang, Clare Lyle, Marta Kwiatkowska
    http://arxiv.org/abs/2105.09108v1

    • [cs.AR]Block Convolution: Towards Memory-Efficient Inference of Large-Scale CNNs on FPGA
    Gang Li, Zejian Liu, Fanrong Li, Jian Cheng
    http://arxiv.org/abs/2105.08937v1

    • [cs.AR]RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance
    Udit Gupta, Samuel Hsia, Jeff, Zhang, Mark Wilkening, Javin Pombra, Hsien-Hsin S. Lee, Gu-Yeon Wei, Carole-Jean Wu, David Brooks
    http://arxiv.org/abs/2105.08820v1

    • [cs.CG]Obstructing Classification via Projection
    Pantea Haghighatkhah, Wouter Meulemans, Bettina Speckman, Jérôme Urhausen, Kevin Verbeek
    http://arxiv.org/abs/2105.09047v1

    • [cs.CL]A Privacy-Preserving Approach to Extraction of Personal Information through Automatic Annotation and Federated Learning
    Rajitha Hathurusinghe, Isar Nejadgholi, Miodrag Bolic
    http://arxiv.org/abs/2105.09198v1

    • [cs.CL]A Sequence-to-Set Network for Nested Named Entity Recognition
    Zeqi Tan, Yongliang Shen, Shuai Zhang, Weiming Lu, Yueting Zhuang
    http://arxiv.org/abs/2105.08901v1

    • [cs.CL]An Automated Method to Enrich Consumer Health Vocabularies Using GloVe Word Embeddings and An Auxiliary Lexical Resource
    Mohammed Ibrahim, Susan Gauch, Omar Salman, Mohammed Alqahatani
    http://arxiv.org/abs/2105.08812v1

    • [cs.CL]Answering Product-Questions by Utilizing Questions from Other Contextually Similar Products
    Ohad Rozen, David Carmel, Avihai Mejer, Vitaly Mirkis, Yftah Ziser
    http://arxiv.org/abs/2105.08956v1

    • [cs.CL]Combining GCN and Transformer for Chinese Grammatical Error Detection
    Jinhong Zhang
    http://arxiv.org/abs/2105.09085v1

    • [cs.CL]Detection of Emotions in Hindi-English Code Mixed Text Data
    Divyansh Singh
    http://arxiv.org/abs/2105.09226v1

    • [cs.CL]Do Models Learn the Directionality of Relations? A New Evaluation Task: Relation Direction Recognition
    Shengfei Lyu, Xingyu Wu, Jinlong Li, Qiuju Chen, Huanhuan Chen
    http://arxiv.org/abs/2105.09045v1

    • [cs.CL]Effective Attention Sheds Light On Interpretability
    Kaiser Sun, Ana Marasović
    http://arxiv.org/abs/2105.08855v1

    • [cs.CL]Essay-BR: a Brazilian Corpus of Essays
    Jeziel C. Marinho, Rafael T. Anchieta, Raimundo S. Moura
    http://arxiv.org/abs/2105.09081v1

    • [cs.CL]Explainable Tsetlin Machine framework for fake news detection with credibility score assessment
    Bimal Bhattarai, Ole-Christoffer Granmo, Lei Jiao
    http://arxiv.org/abs/2105.09114v1

    • [cs.CL]Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixing
    Ganesh Jawahar, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
    http://arxiv.org/abs/2105.08807v1

    • [cs.CL]Improving Adverse Drug Event Extraction with SpanBERT on Different Text Typologies
    Beatrice Portelli, Daniele Passabì, Edoardo Lenzi, Giuseppe Serra, Enrico Santus, Emmanuele Chersoni
    http://arxiv.org/abs/2105.08882v1

    • [cs.CL]Investigating Math Word Problems using Pretrained Multilingual Language Models
    Minghuan Tan, Lei Wang, Lingxiao Jiang, Jing Jiang
    http://arxiv.org/abs/2105.08928v1

    • [cs.CL]LCP-RIT at SemEval-2021 Task 1: Exploring Linguistic Features for Lexical Complexity Prediction
    Abhinandan Desai, Kai North, Marcos Zampieri, Christopher M. Homan
    http://arxiv.org/abs/2105.08780v1

    • [cs.CL]Laughing Heads: Can Transformers Detect What Makes a Sentence Funny?
    Maxime Peyrard, Beatriz Borges, Kristina Gligorić, Robert West
    http://arxiv.org/abs/2105.09142v1

    • [cs.CL]Learning Language Specific Sub-network for Multilingual Machine Translation
    Zehui Lin, Liwei Wu, Mingxuan Wang, Lei Li
    http://arxiv.org/abs/2105.09259v1

    • [cs.CL]Long Text Generation by Modeling Sentence-Level and Discourse-Level Coherence
    Jian Guan, Xiaoxi Mao, Changjie Fan, Zitao Liu, Wenbiao Ding, Minlie Huang
    http://arxiv.org/abs/2105.08963v1

    • [cs.CL]Methods for Detoxification of Texts for the Russian Language
    Daryna Dementieva, Daniil Moskovskiy, Varvara Logacheva, David Dale, Olga Kozlova, Nikita Semenov, Alexander Panchenko
    http://arxiv.org/abs/2105.09052v1

    • [cs.CL]OpenMEVA: A Benchmark for Evaluating Open-ended Story Generation Metrics
    Jian Guan, Zhexin Zhang, Zhuoer Feng, Zitao Liu, Wenbiao Ding, Xiaoxi Mao, Changjie Fan, Minlie Huang
    http://arxiv.org/abs/2105.08920v1

    • [cs.CL]Partner Matters! An Empirical Study on Fusing Personas for Personalized Response Selection in Retrieval-Based Chatbots
    Jia-Chen Gu, Hui Liu, Zhen-Hua Ling, Quan Liu, Zhigang Chen, Xiaodan Zhu
    http://arxiv.org/abs/2105.09050v1

    • [cs.CL]QuatDE: Dynamic Quaternion Embedding for Knowledge Graph Completion
    Haipeng Gao, Kun Yang, Yuxue Yang, Rufai Yusuf Zakari, Jim Wilson Owusu, Ke Qin
    http://arxiv.org/abs/2105.09002v1

    • [cs.CL]Representation Learning in Sequence to Sequence Tasks: Multi-filter Gaussian Mixture Autoencoder
    Yunhao Yang, Zhaokun Xue
    http://arxiv.org/abs/2105.08840v1

    • [cs.CL]Representation Learning in Sequence to Sequence Tasks: Multi-filter Gaussian Mixture Autoencoder
    Yunhao Yang, Zhaokun Xue
    http://arxiv.org/abs/3000
    s/2105.08840v1
    s/2105.08840v1)

    • [cs.CL]Retrieval-Augmented Transformer-XL for Close-Domain Dialog Generation
    Giovanni Bonetta, Rossella Cancelliere, Ding Liu, Paul Vozila
    http://arxiv.org/abs/2105.09235v1

    • [cs.CL]Sentence Extraction-Based Machine Reading Comprehension for Vietnamese
    Phong Nguyen-Thuan Do, Nhat Duy Nguyen, Tin Van Huynh, Kiet Van Nguyen, Anh Gia-Tuan Nguyen, Ngan Luu-Thuy Nguyen
    http://arxiv.org/abs/2105.09043v1

    • [cs.CL]Stylized Story Generation with Style-Guided Planning
    Xiangzhe Kong, Jialiang Huang, Ziquan Tung, Jian Guan, Minlie Huang
    http://arxiv.org/abs/2105.08625v2

    • [cs.CL]TableZa — A classical Computer Vision approach to Tabular Extraction
    Saumya Banthia, Anantha Sharma, Ravi Mangipudi
    http://arxiv.org/abs/2105.09137v1

    • [cs.CR]Analyzing Machine Learning Approaches for Online Malware Detection in Cloud
    Jeffrey C Kimmell, Mahmoud Abdelsalam, Maanak Gupta
    http://arxiv.org/abs/2105.09268v1

    • [cs.CR]DID-eFed: Facilitating Federated Learning as a Service with Decentralized Identities
    Jiahui Geng, Neel Kanwal, Martin Gilje Jaatun, Chunming Rong
    http://arxiv.org/abs/2105.08671v2

    • [cs.CR]Machine learning on knowledge graphs for context-aware security monitoring
    Josep Soler Garrido, Dominik Dold, Johannes Frank
    http://arxiv.org/abs/2105.08741v1

    • [cs.CR]Private Hierarchical Clustering in Federated Networks
    Aashish Kolluri, Teodora Baluta, Prateek Saxena
    http://arxiv.org/abs/2105.09057v1

    • [cs.CV]A Lightweight Privacy-Preserving Scheme Using Label-based Pixel Block Mixing for Image Classification in Deep Learning
    Yuexin Xiang, Tiantian Li, Wei Ren, Tianqing Zhu, Kim-Kwang Raymond Choo
    http://arxiv.org/abs/2105.08876v1

    • [cs.CV]A Novel lightweight Convolutional Neural Network, ExquisiteNetV2
    Shyh Yaw Jou, Chung Yen Su
    http://arxiv.org/abs/2105.09008v1

    • [cs.CV]An Orthogonal Classifier for Improving the Adversarial Robustness of Neural Networks
    Cong Xu, Xiang Li, Min Yang
    http://arxiv.org/abs/2105.09109v1

    • [cs.CV]Analyzing the effectiveness of image augmentations for face recognition from limited data
    Aleksei Zhuchkov
    http://arxiv.org/abs/2105.08796v1

    • [cs.CV]BatchQuant: Quantized-for-all Architecture Search with Robust Quantizer
    Haoping Bai, Meng Cao, Ping Huang, Jiulong Shan
    http://arxiv.org/abs/2105.08952v1

    • [cs.CV]Correlated Adversarial Joint Discrepancy Adaptation Network
    Youshan Zhang, Brian D. Davison
    http://arxiv.org/abs/2105.08808v1

    • [cs.CV]Deep Learning Radio Frequency Signal Classification with Hybrid Images
    Hilal Elyousseph, Majid L Altamimi
    http://arxiv.org/abs/2105.09063v1

    • [cs.CV]Differentiable SLAM-net: Learning Particle SLAM for Visual Navigation
    Peter Karkus, Shaojun Cai, David Hsu
    http://arxiv.org/abs/2105.07593v2

    • [cs.CV]Do We Really Need to Learn Representations from In-domain Data for Outlier Detection?
    Zhisheng Xiao, Qing Yan, Yali Amit
    http://arxiv.org/abs/2105.09270v1

    • [cs.CV]Efficient Transfer Learning via Joint Adaptation of Network Architecture and Weight
    Ming Sun, Haoxuan Dou, Junjie Yan
    http://arxiv.org/abs/2105.08994v1

    • [cs.CV]Font Style that Fits an Image — Font Generation Based on Image Context
    Taiga Miyazono, Brian Kenji Iwana, Daichi Haraguchi, Seiichi Uchida
    http://arxiv.org/abs/2105.08879v1

    • [cs.CV]Generalizable Person Re-identification with Relevance-aware Mixture of Experts
    Yongxing Dai, Xiaotong Li, Jun Liu, Zekun Tong, Ling-Yu Duan
    http://arxiv.org/abs/2105.09156v1

    • [cs.CV]High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network
    Jie Liang, Hui Zeng, Lei Zhang
    http://arxiv.org/abs/2105.09188v1

    • [cs.CV]Large-scale Localization Datasets in Crowded Indoor Spaces
    Donghwan Lee, Soohyun Ryu, Suyong Yeon, Yonghan Lee, Deokhwa Kim, Cheolho Han, Yohann Cabon, Philippe Weinzaepfel, Nicolas Guérin, Gabriela Csurka, Martin Humenberger
    http://arxiv.org/abs/2105.08941v1

    • [cs.CV]Learn Fine-grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images
    Guang-Quan Zhou, Juzheng Miao, Xin Yang, Rui Li, En-Ze Huo, Wenlong Shi, Yuhao Huang, Jikuan Qian, Chaoyu Chen, Dong Ni
    http://arxiv.org/abs/2105.09124v1

    • [cs.CV]Learning optimally separated class-specific subspace representations using convolutional autoencoder
    Krishan Sharma, Shikha Gupta, Renu Rameshan
    http://arxiv.org/abs/2105.08865v1

    • [cs.CV]Light-weight Document Image Cleanup using Perceptual Loss
    Soumyadeep Dey, Pratik Jawanpuria
    http://arxiv.org/abs/2105.09076v1

    • [cs.CV]Local Aggressive Adversarial Attacks on 3D Point Cloud
    Yiming Sun, Feng Chen, Zhiyu Chen, Mingjie Wang, Ruonan Li
    http://arxiv.org/abs/2105.09090v1

    • [cs.CV]Localization and Tracking of User-Defined Points on Deformable Objects for Robotic Manipulation
    Sven Dittus, Benjamin Alt, Andreas Hermann, Darko Katic, Rainer Jäkel, Jürgen Fleischer
    http://arxiv.org/abs/2105.09067v1

    • [cs.CV]Multi-Person Extreme Motion Prediction with Cross-Interaction Attention
    Wen Guo, Xiaoyu Bie, Xavier Alameda-Pineda, Francesc Moreno
    http://arxiv.org/abs/2105.08825v1

    • [cs.CV]Multimodal Deep Learning Framework for Image Popularity Prediction on Social Media
    Fatma S. Abousaleh, Wen-Huang Cheng, Neng-Hao Yu, Yu Tsao
    http://arxiv.org/abs/2105.08809v1

    • [cs.CV]Multiple Meta-model Quantifying for Medical Visual Question Answering
    Tuong Do, Binh X. Nguyen, Erman Tjiputra, Minh Tran, Quang D. Tran, Anh Nguyen
    http://arxiv.org/abs/2105.08913v1

    • [cs.CV]Non-contact Pain Recognition from Video Sequences with Remote Physiological Measurements Prediction
    Ruijing Yang, Ziyu Guan, Zitong Yu, Guoying Zhao, Xiaoyi Feng, Jinye Peng
    http://arxiv.org/abs/2105.08822v1

    • [cs.CV]PPR10K: A Large-Scale Portrait Photo Retouching Dataset with Human-Region Mask and Group-Level Consistency
    Jie Liang, Hui Zeng, Miaomiao Cui, Xuansong Xie, Lei Zhang
    http://arxiv.org/abs/2105.09180v1

    • [cs.CV]Pathdreamer: A World Model for Indoor Navigation
    Jing Yu Koh, Honglak Lee, Yinfei Yang, Jason Baldridge, Peter Anderson
    http://arxiv.org/abs/2105.08756v1

    • [cs.CV]Railroad is not a Train: Saliency as Pseudo-pixel Supervision for Weakly Supervised Semantic Segmentation
    Seungho Lee, Minhyun Lee, Jongwuk Lee, Hyunjung Shim
    http://arxiv.org/abs/2105.08965v1

    • [cs.CV]Recursive-NeRF: An Efficient and Dynamically Growing NeRF
    Guo-Wei Yang, Wen-Yang Zhou, Hao-Yang Peng, Dun Liang, Tai-Jiang Mu, Shi-Min Hu
    http://arxiv.org/abs/2105.09103v1

    • [cs.CV]Self-Supervised Learning for Fine-Grained Visual Categorization
    Muhammad Maaz, Hanoona Abdul Rasheed, Dhanalaxmi Gaddam
    http://arxiv.org/abs/2105.08788v1

    • [cs.CV]XCycles Backprojection Acoustic Super-Resolution
    Feras Almasri, Jurgen Vandendriessche, Laurent Segers, Bruno da Silva, An Braeken, Kris Steenhaut, Abdellah Touhafi, Olivier Debeir
    http://arxiv.org/abs/2105.09128v1

    • [cs.CY]A Generalized Framework for Measuring Pedestrian Accessibility around the World Using Open Data
    Shiqin Liu, Carl Higgs, Jonathan Arundel, Geoff Boeing, Nicholas Cerdera, David Moctezuma, Ester Cerin, Deepti Adlakha, Melanie Lowe, Billie Giles-Corti
    http://arxiv.org/abs/2105.08814v1

    • [cs.CY]Confronting Structural Inequities in AI for Education
    Michael Madaio, Su Lin Blodgett, Elijah Mayfield, Ezekiel Dixon-Román
    http://arxiv.org/abs/2105.08847v1

    • [cs.CY]Copyright in Generative Deep Learning
    Giorgio Franceschelli, Mirco Musolesi
    http://arxiv.org/abs/2105.09266v1

    • [cs.CY]IT ambidexterity and patient agility: the mediating role of digital dynamic capability
    Rogier van de Wetering
    http://arxiv.org/abs/2105.09013v1

    • [cs.CY]Measuring the technological pedagogical content knowledge (TPACK) of in-service teachers of computer science who teach algorithms and programming in upper secondary education
    Spyridon Doukakis, Alexandra Psaltidou, Athena Stavraki, Nikos Adamopoulos, Panagiotis Tsiotakis, Stathis Stergou
    http://arxiv.org/abs/2105.09252v1

    • [cs.CY]The State of AI Ethics Report (January 2021)
    Abhishek Gupta, Alexandrine Royer, Connor Wright, Falaah Arif Khan, Victoria Heath, Erick Galinkin, Ryan Khurana, Marianna Bergamaschi Ganapini, Muriam Fancy, Masa Sweidan, Mo Akif, Renjie Butalid
    http://arxiv.org/abs/2105.09059v1

    • [cs.CY]The State of AI Ethics Report (Volume 4)
    Abhishek Gupta, Alexandrine Royer, Connor Wright, Victoria Heath, Muriam Fancy, Marianna Bergamaschi Ganapini, Shannon Egan, Masa Sweidan, Mo Akif, Renjie Butalid
    http://arxiv.org/abs/2105.09060v1

    • [cs.DB]Revisiting Data Compression in Column-Stores
    Alexander Slesarev, Evgeniy Klyuchikov, Kirill Smirnov, George Chernishev
    http://arxiv.org/abs/2105.09058v1

    • [cs.DC]Can We Break Symmetry with o(m) Communication?
    Shreyas Pai, Gopal Pandurangan, Sriram V. Pemmaraju, Peter Robinson
    http://arxiv.org/abs/2105.08917v1

    • [cs.DC]Federated Singular Vector Decomposition
    Di Chai, Leye Wang, Lianzhi Fu, Junxue Zhang, Kai Chen, Qiang Yang
    http://arxiv.org/abs/2105.08925v1

    • [cs.DC]High performance and energy efficient inference for deep learning on ARM processors
    Adrián Castelló, Sergio Barrachina, Manuel F. Dolz, Enrique S. Quintana-Ortí, Pau San Juan
    http://arxiv.org/abs/2105.09187v1

    • [cs.DC]OpenGraphGym-MG: Using Reinforcement Learning to Solve Large Graph Optimization Problems on MultiGPU Systems
    Weijian Zheng, Dali Wang, Fengguang Song
    http://arxiv.org/abs/2105.08764v1

    • [cs.DC]TRIM: A Design Space Exploration Model for Deep Ne
    1000
    ural Networks Inference and Training Accelerators
    Yangjie Qi, Shuo Zhang, Tarek M. Taha
    http://arxiv.org/abs/2105.08239v2

    • [cs.GR]Guided Facial Skin Color Correction
    Keiichiro Shirai, Tatsuya Baba, Shunsuke Ono, Masahiro Okuda, Yusuke Tatesumi, Paul Perrotin
    http://arxiv.org/abs/2105.09034v1

    • [cs.HC]Assessing the Learning Behavioral Intention of Commuters in Mobility Practices
    Waqas Ahmed, Habiba Akter, Sheikh M. Hizam, Ilham Sentosa, Syeliya Md. Zaini
    http://arxiv.org/abs/2105.08915v1

    • [cs.HC]Digital competency of educators in the virtual learning environment: a structural equation modeling analysis
    S. M. Hizam, H. Akter, I. Sentosa, W. Ahmed
    http://arxiv.org/abs/2105.08927v1

    • [cs.HC]Three prophylactic interventions to counter fake news on social media
    David A. Eccles, Tilman Dingler
    http://arxiv.org/abs/2105.08929v1

    • [cs.IR]An Overview of Computer Supported Query Formulation
    H. A. Proper
    http://arxiv.org/abs/2105.09009v1

    • [cs.IR]Combating Ambiguity for Hash-code Learning in Medical Instance Retrieval
    Jiansheng Fang, Huazhu Fu, Dan Zeng, Xiao Yan, Yuguang Yan, Jiang Liu
    http://arxiv.org/abs/2105.08872v1

    • [cs.IR]Extracting Variable-Depth Logical Document Hierarchy from Long Documents: Method, Evaluation, and Application
    Rongyu Cao, Yixuan Cao, Ganbin Zhou, Ping Luo
    http://arxiv.org/abs/2105.09297v1

    • [cs.IR]Learning Graph Meta Embeddings for Cold-Start Ads in Click-Through Rate Prediction
    Wentao Ouyang, Xiuwu Zhang, Shukui Ren, Li Li, Kun Zhang, Jinmei Luo, Zhaojie Liu, Yanlong Du
    http://arxiv.org/abs/2105.08909v1

    • [cs.IR]On Interpretation and Measurement of Soft Attributes for Recommendation
    Krisztian Balog, Filip Radlinski, Alexandros Karatzoglou
    http://arxiv.org/abs/2105.09179v1

    • [cs.IR]POINTREC: A Test Collection for Narrative-driven Point of Interest Recommendation
    Jafar Afzali, Aleksander Mark Drzewiecki, Krisztian Balog
    http://arxiv.org/abs/2105.09204v1

    • [cs.IR]Where are we in embedding spaces? A Comprehensive Analysis on Network Embedding Approaches for Recommender Systems
    Sixiao Zhang, Hongxu Chen, Xiao Ming, Lizhen Cui, Hongzhi Yin, Guandong Xu
    http://arxiv.org/abs/2105.08908v1

    • [cs.IT]An Analysis of Probabilistic Forwarding of Coded Packets on Random Geometric Graphs
    B. R. Vinay Kumar, Navin Kashyap, D. Yogeshwaran
    http://arxiv.org/abs/2105.08779v1

    • [cs.IT]Enhancing Security of TAS/MRC Based Mixed RF-UOWC System with Induced Underwater Turbulence Effect
    Md. Ibrahim, A. S. M. Badrudduza, Md. Shakhawat Hossen, Milton Kumar Kundu, Imran Shafique Ansari
    http://arxiv.org/abs/2105.09088v1

    • [cs.IT]Model-based and Data-driven Approaches for Downlink Massive MIMO Channel Estimation
    Amin Ghazanfari, Trinh Van Chien, Emil Björnson, Erik G. Larsson
    http://arxiv.org/abs/2105.09097v1

    • [cs.IT]On the Secrecy Capacity of 2-user Gaussian Z-Interference Channel with Shared Key
    Somalatha U, Parthajit Mohapatra
    http://arxiv.org/abs/2105.08975v1

    • [cs.IT]Staircase codes with non-systematic polar codes
    Carlo Condo, Valerio Bioglio, Charles Pillet, Ingmar Land
    http://arxiv.org/abs/2105.09104v1

    • [cs.IT]Unsupervised Learning of Adaptive Codebooks for Deep Feedback Encoding in FDD Systems
    Nurettin Turan, Michael Koller, Samer Bazzi, Wen Xu, Wolfgang Utschick
    http://arxiv.org/abs/2105.09125v1

    • [cs.IT]User-centric Handover in mmWave Cell-Free Massive MIMO with User Mobility
    Carmen D’Andrea, Giovanni Interdonato, Stefano Buzzi
    http://arxiv.org/abs/2105.09041v1

    • [cs.LG]Accelerating Gossip SGD with Periodic Global Averaging
    Yiming Chen, Kun Yuan, Yingya Zhang, Pan Pan, Yinghui Xu, Wotao Yin
    http://arxiv.org/abs/2105.09080v1

    • [cs.LG]Boosting Variational Inference With Locally Adaptive Step-Sizes
    Gideon Dresdner, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, Gunnar Rätsch
    http://arxiv.org/abs/2105.09240v1

    • [cs.LG]Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation
    Taehyeon Kim, Jaehoon Oh, NakYil Kim, Sangwook Cho, Se-Young Yun
    http://arxiv.org/abs/2105.08919v1

    • [cs.LG]Compositional Processing Emerges in Neural Networks Solving Math Problems
    Jacob Russin, Hamid Palangi, Eric Rosen, Nebojsa Jojic, Paul Smolensky, Jianfeng Gao
    http://arxiv.org/abs/2105.08961v1

    • [cs.LG]Diffusion Approximations for Thompson Sampling
    Lin Fan, Peter W. Glynn
    http://arxiv.org/abs/2105.09232v1

    • [cs.LG]DumbleDR: Predicting User Preferences of Dimensionality Reduction Projection Quality
    Cristina Morariu, Adrien Bibal, Rene Cutura, Benoît Frénay, Michael Sedlmair
    http://arxiv.org/abs/2105.09275v1

    • [cs.LG]E(n) Equivariant Normalizing Flows for Molecule Generation in 3D
    Victor Garcia Satorras, Emiel Hoogeboom, Fabian B. Fuchs, Ingmar Posner, Max Welling
    http://arxiv.org/abs/2105.09016v1

    • [cs.LG]Errors-in-Variables for deep learning: rethinking aleatoric uncertainty
    Jörg Martin, Clemens Elster
    http://arxiv.org/abs/2105.09095v1

    • [cs.LG]Fast and Slow Learning of Recurrent Independent Mechanisms
    Kanika Madan, Nan Rosemary Ke, Anirudh Goyal, Bernhard Schölkopf, Yoshua Bengio
    http://arxiv.org/abs/2105.08710v2

    • [cs.LG]Free Energy Node Embedding via Generalized Skip-gram with Negative Sampling
    Yu Zhu, Ananthram Swami, Santiago Segarra
    http://arxiv.org/abs/2105.09182v1

    • [cs.LG]Gym-ANM: Open-source software to leverage reinforcement learning for power system management in research and education
    Robin Henry, Damien Ernst
    http://arxiv.org/abs/2105.08846v1

    • [cs.LG]Image to Image Translation : Generating maps from satellite images
    Vaishali Ingale, Rishabh Singh, Pragati Patwal
    http://arxiv.org/abs/2105.09253v1

    • [cs.LG]Improved Exploring Starts by Kernel Density Estimation-Based State-Space Coverage Acceleration in Reinforcement Learning
    Maximilian Schenke, Oliver Wallscheid
    http://arxiv.org/abs/2105.08990v1

    • [cs.LG]Incentivized Bandit Learning with Self-Reinforcing User Preferences
    Tianchen Zhou, Jia Liu, Chaosheng Dong, Jingyuan Deng
    http://arxiv.org/abs/2105.08869v1

    • [cs.LG]Latent Gaussian Model Boosting
    Fabio Sigrist
    http://arxiv.org/abs/2105.08966v1

    • [cs.LG]Learning and Information in Stochastic Networks and Queues
    Neil Walton, Kuang Xu
    http://arxiv.org/abs/2105.08769v1

    • [cs.LG]Masked Contrastive Learning for Anomaly Detection
    Hyunsoo Cho, Jinseok Seol, Sang-goo Lee
    http://arxiv.org/abs/2105.08793v1

    • [cs.LG]Meta-Reinforcement Learning by Tracking Task Non-stationarity
    Riccardo Poiani, Andrea Tirinzoni, Marcello Restelli
    http://arxiv.org/abs/2105.08834v1

    • [cs.LG]Periodic Freight Demand Forecasting for Large-scale Tactical Planning
    Greta Laage, Emma Frejinger, Gilles Savard
    http://arxiv.org/abs/2105.09136v1

    • [cs.LG]Physical Constraint Embedded Neural Networks for inference and noise regulation
    Gregory Barber, Mulugeta A. Haile, Tzikang Chen
    http://arxiv.org/abs/2105.09146v1

    • [cs.LG]Predicting Flight Delay with Spatio-Temporal Trajectory Convolutional Network and Airport Situational Awareness Map
    Wei Shao, Arian Prabowo, Sichen Zhao, Piotr Koniusz, Flora D. Salim
    http://arxiv.org/abs/2105.08969v1

    • [cs.LG]Prototype Guided Federated Learning of Visual Feature Representations
    Umberto Michieli, Mete Ozay
    http://arxiv.org/abs/2105.08982v1

    • [cs.LG]Reinforcement Learning Assisted Oxygen Therapy for COVID-19 Patients Under Intensive Care
    Hua Zheng, Jiahao Zhu, Wei Xie, Judy Zhong
    http://arxiv.org/abs/2105.08923v1

    • [cs.LG]Self-supervised Heterogeneous Graph Neural Network with Co-contrastive Learning
    Xiao Wang, Nian Liu, Hui Han, Chuan Shi
    http://arxiv.org/abs/2105.09111v1

    • [cs.LG]Single-Layer Vision Transformers for More Accurate Early Exits with Less Overhead
    Arian Bakhtiarnia, Qi Zhang, Alexandros Iosifidis
    http://arxiv.org/abs/2105.09121v1

    • [cs.LG]Sparsity Prior Regularized Q-learning for Sparse Action Tasks
    Jing-Cheng Pang, Tian Xu, Sheng-Yi Jiang, Yu-Ren Liu, Yang Yu
    http://arxiv.org/abs/2105.08666v2

    • [cs.LG]Tool- and Domain-Agnostic Parameterization of Style Transfer Effects Leveraging Pretrained Perceptual Metrics
    Hiromu Yakura, Yuki Koyama, Masataka Goto
    http://arxiv.org/abs/2105.09207v1

    • [cs.LG]Value Function is All You Need: A Unified Learning Framework for Ride Hailing Platforms
    Xiaocheng Tang, Fan Zhang, Zhiwei, Qin, Yansheng Wang, Dingyuan Shi, Bingchen Song, Yongxin Tong, Hongtu Zhu, Jieping Ye
    http://arxiv.org/abs/2105.08791v1

    • [cs.LG]Variability of Artificial Neural Networks
    Yin Zhang, Yueyao Yu
    http://arxiv.org/abs/2105.08911v1

    • [cs.LG]When Deep Classifiers Agree: Analyzing Correlations between Learning Order and Image Statistics
    Iuliia Pliushch, Martin Mundt, Nicolas Lupp, Visvanathan Ramesh
    http://arxiv.org/abs/2105.08997v1

    • [cs.LG]rx-anon — A Novel Approach on the De-Identification of Heterogeneous Data based on a Modified Mondrian Algorithm
    Fabian Singhofer, Aygul Garifullina, Mathias Kern, Ansgar Scherp
    http://arxiv.org/abs/2105.08842v1

    • [cs.NE]Sparse Spiking Gradient Descent
    Nicolas Perez-Nieves, Dan F. M. Goodman
    http://arxiv.org/abs/2105.08810v1

    • [cs.RO]Active Visual SLAM with independently rotating camera
    Elia Bonetto, Pascal Goldschmid, Michael J. Black, Aamir Ahmad
    http://arxiv.org/abs/2105.08958v1

    • [cs.RO]Coverage Path Planning for Spraying Drones
    E. Viridiana Vazquez-Carmona, J. Irving Vasquez-Gomez, Juan Carlos Herrera Lozada, Mayra Antonio Cruz
    http://arxiv.org/abs/2105.08743v1

    • [cs.RO]Fusion-DHL: WiFi, IMU, and Floorplan Fusion for Dense History of Locations in Indoor Environments
    Sachini Herath, Saghar Irandoust, Bowen Chen, Yiming Qian, Pyojin Kim, Yasutaka Furukawa
    http://arxiv.org/abs/2105.08837v1

    • [cs.RO]Moving Object Segmentation in 3D LiDAR Data: A Learning-based Approach Exploiting Sequential Data
    Xieyuanli Chen, Shijie Li, Benedikt Mersch, Louis Wiesmann, Jürgen Gall, Jens Behley, Cyrill Stachniss
    http://arxiv.org/abs/2105.08971v1

    • [cs.RO]Projector-Guided Non-Holonomic Mobile 3D Printing
    Xuchu Xu, Ziteng Wang, Chen Feng
    http://arxiv.org/abs/2105.08950v1

    • [cs.RO]Teaching Continuity in Robotics Labs in the Age of Covid and Beyond
    R. Pito Salas
    http://arxiv.org/abs/2105.08839v1

    • [cs.RO]VSGM — Enhance robot task understanding ability through visual semantic graph
    Cheng Yu Tsai, Mu-Chun Su
    http://arxiv.org/abs/2105.08959v1

    • [cs.SD]Attack on practical speaker verification system using universal adversarial perturbations
    Weiyi Zhang, Shuning Zhao, Le Liu, Jianmin Li, Xingliang Cheng, Thomas Fang Zheng, Xiaolin Hu
    http://arxiv.org/abs/2105.09022v1

    • [cs.SD]Music Generation using Deep Learning
    Vaishali Ingale, Anush Mohan, Divit Adlakha, Krishna Kumar, Mohit Gupta
    http://arxiv.org/abs/2105.09046v1

    • [cs.SD]Unsupervised Discriminative Learning of Sounds for Audio Event Classification
    Sascha Hornauer, Ke Li, Stella X. Yu, Shabnam Ghaffarzadegan, Liu Ren
    http://arxiv.org/abs/2105.09279v1

    • [cs.SI]Educators, Solicitors, Flamers, Motivators, Sympathizers: Characterizing Roles in Online Extremist Movements
    Shruti Phadke, Tanushree Mitra
    http://arxiv.org/abs/2105.08827v1

    • [cs.SI]Forecasting managerial turnover through e-mail based social network analysis
    P. A. Gloor, A. Fronzetti Colladon, F. Grippa, G. Giacomelli
    http://arxiv.org/abs/2105.09208v1

    • [cs.SI]Interventions with Inversity in Unknown Networks Can Help Regulate Contagion
    Vineet Kumar, David Krackhardt, Scott Feld
    http://arxiv.org/abs/2105.08758v1

    • [cs.SI]Robustness and stability of enterprise intranet social networks: The impact of moderators
    A. Fronzetti Colladon, F. Vagaggini
    http://arxiv.org/abs/2105.09127v1

    • [cs.SI]The Complex Community Structure of the Bitcoin Address Correspondence Network
    Jan Alexander Fischer, Andres Palechor, Daniele Dell’Aglio, Abraham Bernstein, Claudio J. Tessone
    http://arxiv.org/abs/2105.09078v1

    • [econ.EM]The Minimax Estimator of the Average Treatment Effect, among Linear Combinations of Conditional Average Treatment Effects Estimators
    Clément de Chaisemartin
    http://arxiv.org/abs/2105.08766v1

    • [econ.GN]Using four different online media sources to forecast the crude oil price
    M. Elshendy, A. Fronzetti Colladon, E. Battistoni, P. A. Gloor
    http://arxiv.org/abs/2105.09154v1

    • [eess.AS]Disentanglement Learning for Variational Autoencoders Applied to Audio-Visual Speech Enhancement
    Guillaume Carbajal, Julius Richter, Timo Gerkmann
    http://arxiv.org/abs/2105.08970v1

    • [eess.IV]Adaptive Hypergraph Convolutional Network for No-Reference 360-degree Image Quality Assessment
    Jun Fu, Chen Hou, Wei Zhou, Jiahua Xu, Zhibo Chen
    http://arxiv.org/abs/2105.09143v1

    • [eess.IV]Joint Calibrationless Reconstruction and Segmentation of Parallel MRI
    Aniket Pramanik, Xiaodong Wu, Mathews Jacob
    http://arxiv.org/abs/2105.09220v1

    • [eess.IV]Multi-Contrast MRI Super-Resolution via a Multi-Stage Integration Network
    Chun-Mei Feng, Huazhu Fu, Shuhao Yuan, Yong Xu
    http://arxiv.org/abs/2105.08949v1

    • [eess.IV]TarGAN: Target-Aware Generative Adversarial Networks for Multi-modality Medical Image Translation
    Junxiao Chen, Jia Wei, Rui Li
    http://arxiv.org/abs/2105.08993v1

    • [eess.SP]Foundations of MIMO Radar Detection Aided by Reconfigurable Intelligent Surfaces
    Stefano Buzzi, Emanuele Grossi, Marco Lops, Luca Venturino
    http://arxiv.org/abs/2105.09250v1

    • [eess.SY]Enforcing Policy Feasibility Constraints through Differentiable Projection for Energy Optimization
    Bingqing Chen, Priya Donti, Kyri Baker, J. Zico Kolter, Mario Berges
    http://arxiv.org/abs/2105.08881v1

    • [hep-ex]Physics Validation of Novel Convolutional 2D Architectures for Speeding Up High Energy Physics Simulations
    Florian Rehm, Sofia Vallecorsa, Kerstin Borras, Dirk Krücker
    http://arxiv.org/abs/2105.08960v1

    • [math.OC]A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows
    Pedro Cisneros-Velarde, Francesco Bullo
    http://arxiv.org/abs/2105.08832v1

    • [math.OC]Distributionally Constrained Black-Box Stochastic Gradient Estimation and Optimization
    Henry Lam, Junhui Zhang
    http://arxiv.org/abs/2105.09177v1

    • [math.ST]A Note on High-Dimensional Confidence Regions
    Sven Klaassen
    http://arxiv.org/abs/2105.09028v1

    • [math.ST]Local estimators and Bayesian inverse problems with non-unique solutions
    Jiguang Sun
    http://arxiv.org/abs/2105.09141v1

    • [math.ST]Multiply Robust Causal Mediation Analysis with Continuous Treatments
    AmirEmad Ghassami, Numair Sani, Yizhen Xu, Ilya Shpitser
    http://arxiv.org/abs/2105.09254v1

    • [math.ST]Testing partial conjunction hypotheses under dependency, with applications to meta-analysis
    Marina Bogomolov
    http://arxiv.org/abs/2105.09032v1

    • [math.ST]The convergence speed of MLE to the information projection of an exponential family — a criteria for the model dimension and the sample size — with complete proof
    Yo Sheena
    http://arxiv.org/abs/2105.08947v1

    • [physics.soc-ph]A Phase Transition in Large Network Games
    Abhishek Shende, Deepanshu Vasal, Sriram Vishwanath
    http://arxiv.org/abs/2105.08892v1

    • [physics.soc-ph]The effect of algorithmic bias and network structure on coexistence, consensus, and polarization of opinions
    Antonio F. Peralta, Matteo Neri, János Kertész, Gerardo Iñiguez
    http://arxiv.org/abs/2105.07703v2

    • [q-bio.BM]Conformational variability of loops in the SARS-CoV-2 spike protein
    Samuel W. K. Wong, Zongjun Liu
    http://arxiv.org/abs/2105.08835v1

    • [q-bio.NC]Complementary Structure-Learning Neural Networks for Relational Reasoning
    Jacob Russin, Maryam Zolfaghar, Seongmin A. Park, Erie Boorman, Randall C. O’Reilly
    http://arxiv.org/abs/2105.08944v1

    • [q-bio.QM]Detection of Multidecadal Changes in Vegetation Dynamics and Association with Intra-annual Climate Variability in the Columbia River Basin
    Andrew B Whetten, Hannah Demler
    http://arxiv.org/abs/2105.08864v1

    • [q-fin.PM]Robo-Advising: Enhancing Investment with Inverse Optimization and Deep Reinforcement Learning
    Haoran Wang, Shi Yu
    http://arxiv.org/abs/2105.09264v1

    • [stat.AP]Changes in Crime Rates During the COVID-19 Pandemic
    Mikaela Meyer, Ahmed Hassafy, Gina Lewis, Prasun Shrestha, Amelia M. Haviland, Daniel S. Nagin
    http://arxiv.org/abs/2105.08859v1

    • [stat.AP]Modelling short-term precipitation extremes with the blended generalised extreme value distribution
    Silius M. Vandeskog, Sara Martino, Daniela Castro-Camilo, Håvard Rue
    http://arxiv.org/abs/2105.09062v1

    • [stat.AP]Pooled testing and its applications in the COVID-19 pandemic
    Matthew Aldridge, David Ellis
    http://arxiv.org/abs/2105.08845v1

    • [stat.AP]Statistical Learning for Best Practices in Tattoo Removal
    Richard Yim, Jamie Haddock, Deanna Needell
    http://arxiv.org/abs/2105.09065v1

    • [stat.ME]A unified framework on defining depth for point process using function smoothing
    Zishen Xu, Chenran Wang, Wei Wu
    http://arxiv.org/abs/2105.08893v1

    • [stat.ME]Conformal histogram regression
    Matteo Sesia, Yaniv Romano
    http://arxiv.org/abs/2105.08747v1

    • [stat.ME]Flexible Specification Testing in Semi-Parametric Quantile Regression Models
    Tim Kutzker, Nadja Klein, Dominik Wied
    http://arxiv.org/abs/2105.09003v1

    • [stat.ME]High-dimensional Change-point Detection Using Generalized Homogeneity Metrics
    Shubhadeep Chakraborty, Xianyang Zhang
    http://arxiv.org/abs/2105.08976v1

    • [stat.ME]Improving Adaptive Seamless Designs through Bayesian optimization
    Jakob Richter, Tim Friede, Jörg Rahnenführer
    http://arxiv.org/abs/2105.09223v1

    • [stat.ME]Markov-Restricted Analysis of Randomized Trials with Non-Monotone Missing Binary Outcomes: Sensitivity Analysis and Identification Results
    Daniel O. Scharfstein, Jaron J. R. Lee, Aidan McDermott, Aimee Campbell, Edward Nunes, Abigail G. Matthews, Ilya Shpitser
    http://arxiv.org/abs/2105.08868v1

    • [stat.ME]Maximum profile binomial likelihood estimation for the semiparametric Box—Cox power transformation model
    Pengfei
    2b8
    Li, Tao Yu, Baojiang Chen, Jing Qin
    http://arxiv.org/abs/2105.08677v2

    • [stat.ME]Measuring performance for end-of-life care
    Sebastien Haneuse, Deborah Schrag, Francesca Dominici, Sharon-Lise Normand, Kyu Ha Lee
    http://arxiv.org/abs/2105.08776v1

    • [stat.ME]New classes of tests for the Weibull distribution using Stein’s method in the presence of random right censoring
    E Bothma, JS Allison, IJH Visagie
    http://arxiv.org/abs/2105.09019v1

    • [stat.ME]Point estimation for adaptive trial designs
    D. S. Robertson, B. Choodari-Oskooei, M. Dimairo, L. Flight, P. Pallmann, T. Jaki
    http://arxiv.org/abs/2105.08836v1

    • [stat.ME]Standard Curves for Empirical Likelihood Ratio Tests of Means
    Jost Viebrock, Thorsten Dickhaus
    http://arxiv.org/abs/2105.09031v1

    • [stat.ML]Calibrating sufficiently
    Dirk Tasche
    http://arxiv.org/abs/2105.07283v2

    • [stat.ML]From parcel to continental scale — A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations
    Raphaël, d’Andrimont, Astrid, Verhegghen, Guido, Lemoine, Pieter, Kempeneers, Michele, Meroni, Marijn, van der Velde
    http://arxiv.org/abs/2105.09261v1

    • [stat.ML]Localization, Convexity, and Star Aggregation
    Suhas Vijaykumar
    http://arxiv.org/abs/2105.08866v1

    • [stat.ML]Mill.jl and JsonGrinder.jl: automated differentiable feature extraction for learning from raw JSON data
    Simon Mandlik, Matej Racinsky, Viliam Lisy, Tomas Pevny
    http://arxiv.org/abs/2105.09107v1

    • [stat.ML]Statistical Optimality and Computational Efficiency of Nyström Kernel PCA
    Nicholas Sterge, Bharath Sriperumbudur
    http://arxiv.org/abs/2105.08875v1