cs.AI - 人工智能

    cs.AR - 硬件体系结构

    cs.CC - 计算复杂度

    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.MS - 数学软件

    cs.NE - 神经与进化计算

    cs.NI - 网络和互联网体系结构

    cs.RO - 机器人学

    cs.SD - 声音处理

    cs.SE - 软件工程

    cs.SI - 社交网络与信息网络

    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

    math.MG -公制几何

    math.OC - 优化与控制

    math.ST - 统计理论

    q-bio.NC - 神经元与认知

    q-fin.ST - 统计金融学

    stat.AP - 应用统计

    stat.CO - 统计计算

    stat.ME - 统计方法论

    stat.ML - (统计)机器学习

    • [cs.AI]Adaptive Belief Discretization for POMDP Planning

    • [cs.AI]Applying Personal Knowledge Graphs to Health

    • [cs.AI]Emotion Dynamics Modeling via BERT

    • [cs.AI]Ensemble of MRR and NDCG models for Visual Dialog

    • [cs.AI]Text Guide: Improving the quality of long text classification by a text selection method based on feature importance

    • [cs.AR]SISA: Set-Centric Instruction Set Architecture for Graph Mining on Processing-in-Memory Systems

    • [cs.CC]Sized Types with Usages for Parallel Complexity of Pi-Calculus Processes

    • [cs.CL]A Dual-Questioning Attention Network for Emotion-Cause Pair Extraction with Context Awareness

    • [cs.CL]A Sample-Based Training Method for Distantly Supervised Relation Extraction with Pre-Trained Transformers

    • [cs.CL]AdaPrompt: Adaptive Prompt-based Finetuning for Relation Extraction

    • [cs.CL]Adaptive Active Learning for Coreference Resolution

    • [cs.CL]Adaptive Sparse Transformer for Multilingual Translation

    • [cs.CL]An Alignment-Agnostic Model for Chinese Text Error Correction

    • [cs.CL]An Interpretability Illusion for BERT

    • [cs.CL]Annealing Knowledge Distillation

    • [cs.CL]Are Multilingual BERT models robust? A Case Study on Adversarial Attacks for Multilingual Question Answering

    • [cs.CL]BERT based Transformers lead the way in Extraction of Health Information from Social Media

    • [cs.CL]Bilingual Terminology Extraction from Non-Parallel E-Commerce Corpora

    • [cs.CL]Bilingual alignment transfers to multilingual alignment for unsupervised parallel text mining

    • [cs.CL]Consistency Training with Virtual Adversarial Discrete Perturbation

    • [cs.CL]Cross-Domain Label-Adaptive Stance Detection

    • [cs.CL]Data-QuestEval: A Referenceless Metric for Data to Text Semantic Evaluation

    • [cs.CL]Demystify Optimization Challenges in Multilingual Transformers

    • [cs.CL]Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering

    • [cs.CL]Disentangling Representations of Text by Masking Transformers

    • [cs.CL]Does Putting a Linguist in the Loop Improve NLU Data Collection?

    • [cs.CL]Effect of Post-processing on Contextualized Word Representations

    • [cs.CL]ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning

    • [cs.CL]First the worst: Finding better gender translations during beam search

    • [cs.CL]Generating Datasets with Pretrained Language Models

    • [cs.CL]Hierarchical Learning for Generation with Long Source Sequences

    • [cs.CL]Integration of Pre-trained Networks with Continuous Token Interface for End-to-End Spoken Language Understanding

    • [cs.CL]Lattice-BERT: Leveraging Multi-Granularity Representations in Chinese Pre-trained Language Models

    • [cs.CL]Learning Zero-Shot Multifaceted Visually Grounded Word Embeddingsvia Multi-Task Training

    • [cs.CL]Low-Resource Task-Oriented Semantic Parsing via Intrinsic Modeling

    • [cs.CL]Modeling Human Mental States with an Entity-based Narrative Graph

    • [cs.CL]Multitasking Inhibits Semantic Drift

    • [cs.CL]NT5?! Training T5 to Perform Numerical Reasoning

    • [cs.CL]Neural Sequence Segmentation as Determining the Leftmost Segments

    • [cs.CL]Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction

    • [cs.CL]On the Robustness of Goal Oriented Dialogue Systems to Real-world Noise

    • [cs.CL]Planning with Entity Chains for Abstractive Summarization

    • [cs.CL]Predicting Discourse Trees from Transformer-based Neural Summarizers

    • [cs.CL]Privacy-Adaptive BERT for Natural Language Understanding

    • [cs.CL]Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolution

    • [cs.CL]Quantifying Gender Bias Towards Politicians in Cross-Lingual Language Models

    • [cs.CL]RefSum: Refactoring Neural Summarization

    • [cs.CL]Reformulating Sentence Ordering as Conditional Text Generation

    • [cs.CL]Regularizing Models via Pointwise Mutual Information for Named Entity Recognition

    • [cs.CL]Rethinking Automatic Evaluation in Sentence Simplification

    • [cs.CL]Retrieval Augmentation Reduces Hallucination in Conversation

    • [cs.CL]Reward Optimization for Neural Machine Translation with Learned Metrics

    • [cs.CL]SINA-BERT: A pre-trained Language Model for Analysis of Medical Texts in Persian

    • [cs.CL]Sentence-Permuted Paragraph Generation

    • [cs.CL]Sequence Tagging for Biomedical Extractive Question Answering

    • [cs.CL]Simultaneous Multi-Pivot Neural Machine Translation

    • [cs.CL]Sometimes We Want Translationese

    • [cs.CL]Span Pointer Networks for Non-Autoregressive Task-Oriented Semantic Parsing

    • [cs.CL]Static Embeddings as Efficient Knowledge Bases?

    • [cs.CL]SummScreen: A Dataset for Abstractive Screenplay Summarization

    • [cs.CL]SummVis: Interactive Visual Analysis of Models, Data, and Evaluation for Text Summarization

    • [cs.CL]Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models

    • [cs.CL]TWEAC: Transformer with Extendable QA Agent Classifiers

    • [cs.CL]The Effect of Efficient Messaging and Input Variability on Neural-Agent Iterated Language Learning

    • [cs.CL]The MuSe 2021 Multimodal Sentiment Analysis Challenge: Sentiment, Emotion, Physiological-Emotion, and Stress

    • [cs.CL]The Role of Context in Detecting Previously Fact-Checked Claims

    • [cs.CL]Time-Stamped Language Model: Teaching Language Models to Understand the Flow of Events

    • [cs.CL]TorontoCL at CMCL 2021 Shared Task: RoBERTa with Multi-Stage Fine-Tuning for Eye-Tracking Prediction

    • [cs.CL]Towards Deconfounding the Influence of Subject’s Demographic Characteristics in Question Answering

    • [cs.CL]Tracking entities in technical procedures — a new dataset and baselines

    • [cs.CL]TransferNet: An Effective and Transparent Framework for Multi-hop Question Answering over Relation Graph

    • [cs.CL]UDALM: Unsupervised Domain Adaptation through Language Modeling

    • [cs.CL]UHD-BERT: Bucketed Ultra-High Dimensional Sparse Representations for Full Ranking

    • [cs.CL]UIT-E10dot3 at SemEval-2021 Task 5: Toxic Spans Detection with Named Entity Recognition and Question-Answering Approaches

    • [cs.CL]Unlocking Compositional Generalization in Pre-trained Models Using Intermediate Representations

    • [cs.CL]Unmasking the Mask — Evaluating Social Biases in Masked Language Models

    • [cs.CL]What Makes a Scientific Paper be Accepted for Publication?

    • [cs.CL]XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation

    • [cs.CL]Zero-Shot Cross-lingual Semantic Parsing

    • [cs.CR]An Explainable Machine Learning-based Network Intrusion Detection System for Enabling Generalisability in Securing IoT Networks

    • [cs.CR]Discover the Hidden Attack Path in Multi-domain Cyberspace Based on Reinforcement Learning

    • [cs.CR]Measuring the Impact of Blockchain and Smart Contract on Construction Supply Chain Visibility

    • [cs.CR]Robust Backdoor Attacks against Deep Neural Networks in Real Physical World

    • [cs.CV]3DCrowdNet: 2D Human Pose-Guided3D Crowd Human Pose and Shape Estimation in the Wild

    • [cs.CV]A Decomposition Model for Stereo Matching

    • [cs.CV]A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation

    • [cs.CV]A Simple Baseline for StyleGAN Inversion

    • [cs.CV]A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation

    • [cs.CV]Action Segmentation with Mixed Temporal Domain Adaptation

    • [cs.CV]Adaptive Intermediate Representations for Video Understanding

    • [cs.CV]An Improved Real-Time Face Recognition System at Low Resolution Based on Local Binary Pattern Histogram Algorithm and CLAHE

    • [cs.CV]Audio-Driven Emotional Video Portraits

    • [cs.CV]Camera View Adjustment Prediction for Improving Image Composition

    • [cs.CV]ContactOpt: Optimizing Contact to Improve Grasps

    • [cs.CV]Continual Learning From Unlabeled Data Via Deep Clustering

    • [cs.CV]Convolutions for Spatial Interaction Modeling

    • [cs.CV]Depth Completion using Plane-Residual Representation

    • [cs.CV]Do Deep Neural Networks Forget Facial Action Units? — Exploring the Effects of Transfer Learning in Health Related Facial Expression Recognition

    • [cs.CV]Fast Walsh-Hadamard Transform and Smooth-Thresholding Based Binary Layers in Deep Neural Networks

    • [cs.CV]Federated Learning-based Active Authentication on Mobile Devices

    • [cs.CV]GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worlds

    • [cs.CV]Geometry-Free View Synthesis: Transformers and no 3D Priors

    • [cs.CV]Graph-based Thermal-Inertial SLAM with Probabilistic Neural Networks

    • [cs.CV]Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation

    • [cs.CV]Learning Regional Attention over Multi-resolution Deep Convolutional Features for Trademark Retrieval

    • [cs.CV]Learning structure-aware semantic segmentation with image-level supervision

    • [cs.CV]PURE: Passive mUlti-peRson idEntification via Deep Footstep Separation and Recognition

    • [cs.CV]Points as Queries: Weakly Semi-supervised Object Detection by Points

    • [cs.CV]SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements

    • [cs.CV]Self-Supervised Learning of Remote Sensing Scene Representations Using Contrastive Multiview Coding

    • [cs.CV]Self-supervised Learning of 3D Object Understanding by Data Association and Landmark Estimation for Image Sequence

    • [cs.CV]Self-supervised Video Object Segmentation by Motion Grouping

    • [cs.CV]SiamCorners: Siamese Corner Networks for Visual Tracking

    • [cs.CV]Spectral MVIR: Joint Reconstruction of 3D Shape and Spectral Reflectance

    • [cs.CV]StEP: Style-based Encoder Pre-training for Multi-modal Image Synthesis

    • [cs.CV]Street-Map Based Validation of Semantic Segmentation in Autonomous Driving

    • [cs.CV]Training Deep Capsule Networks with Residual Connections

    • [cs.CV]TransRPPG: Remote Photoplethysmography Transformer for 3D Mask Face Presentation Attack Detection

    • [cs.CV]Weakly Supervised Video Anomaly Detection via Center-guided Discriminative Learning

    • [cs.CV]Zooming SlowMo: An Efficient One-Stage Framework for Space-Time Video Super-Resolution

    • [cs.CY]Otaku: Intelligent Management System for Student-Intensive Dormitory

    • [cs.CY]Skilled and Mobile: Survey Evidence of Immigration Preferences of AI Researchers

    • [cs.DC]Coalescent Computing

    • [cs.DC]Minimizing privilege for building HPC containers

    • [cs.DC]Towards a Fast and Accurate Model of Intercontact Times for Epidemic Routing

    • [cs.DC]Who Needs Consensus? A Distributed Monetary System Between Rational Agents via Hearsay

    • [cs.DL]ROC: An Ontology for Country Responses towards COVID-19

    • [cs.HC]Towards A Process Model for Co-Creating AI Experiences

    • [cs.IR]A Large-Scale Analysis of Mixed Initiative in Information-Seeking Dialogues for Conversational Search

    • [cs.IR]COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List

    • [cs.IR]DebiasedRec: Bias-aware User Modeling and Click Prediction for Personalized News Recommendation

    • [cs.IR]Deep Learning-based Online Alternative Product Recommendations at Scale

    • [cs.IR]Dynamic Graph Neural Networks for Sequential Recommendation

    • [cs.IR]Empowering News Recommendation with Pre-trained Language Models

    • [cs.IR]Hyperbolic Neural Collaborative Recommender

    • [cs.IR]MM-Rec: Multimodal News Recommendation

    • [cs.IR]Two Birds with One Stone: Unified Model Learning for Both Recall and Ranking in News Recommendation

    • [cs.IT]Extending two families of maximum rank distance codes

    • [cs.IT]On Missing Mass Variance

    • [cs.IT]On the existence of quaternary Hermitian LCD codes with Hermitian dual distance 今日学术视野(2021.4.17) - 图1

    • [cs.IT]Performance of CRC Concatenated Pre-transformed RM-Polar Codes

    • [cs.IT]Phase noise in communication systems: from measures to models

    • [cs.IT]Stochastic-Adversarial Channels : Online Adversaries With Feedback Snooping

    • [cs.LG]Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)

    • [cs.LG]All-You-Can-Fit 8-Bit Flexible Floating-Point Format for Accurate and Memory-Efficient Inference of Deep Neural Networks

    • [cs.LG]Attentive Max Feature Map for Acoustic Scene Classification with Joint Learning considering the Abstraction of Classes

    • [cs.LG]Bayesian and Dempster-Shafer models for combining multiple sources of evidence in a fraud detection system

    • [cs.LG]D-Cliques: Compensating NonIIDness in Decentralized Federated Learning with Topology

    • [cs.LG]Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity

    • [cs.LG]DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

    • [cs.LG]Efficient Click-Through Rate Prediction for Developing Countries via Tabular Learning

    • [cs.LG]Embedding Adaptation is Still Needed for Few-Shot Learning

    • [cs.LG]Exact and Approximate Hierarchical Clustering Using A*

    • [cs.LG]Facilitating Machine Learning Model Comparison and Explanation Through A Radial Visualisation

    • [cs.LG]Fast Private Parameter Learning and Evaluation for Sum-Product Networks

    • [cs.LG]FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks

    • [cs.LG]FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems

    • [cs.LG]Generalising Discrete Action Spaces with Conditional Action Trees

    • [cs.LG]HIVE-COTE 2.0: a new meta ensemble for time series classification

    • [cs.LG]Iterative Barycenter Flows

    • [cs.LG]Lorentzian Graph Convolutional Networks

    • [cs.LG]Membership-Mappings for Data Representation Learning

    • [cs.LG]Multi-Agent Reinforcement Learning Based Coded Computation for Mobile Ad Hoc Computing

    • [cs.LG]Multivariate Deep Evidential Regression

    • [cs.LG]NICE: An Algorithm for Nearest Instance Counterfactual Explanations

    • [cs.LG]NeuSE: A Neural Snapshot Ensemble Method for Collaborative Filtering

    • [cs.LG]On Energy-Based Models with Overparametrized Shallow Neural Networks

    • [cs.LG]Orthogonalizing Convolutional Layers with the Cayley Transform

    • [cs.LG]Rehearsal revealed: The limits and merits of revisiting samples in continual learning

    • [cs.LG]Rehearsal revealed: The limits and merits of revisiting samples in continual learning

    • [cs.LG]Robust Neural Networks Outperform Attitude Estimation Filters

    • [cs.LG]Scale Invariant Solutions for Overdetermined Linear Systems with Applications to Reinforcement Learning

    • [cs.LG]See through Gradients: Image Batch Recovery via GradInversion

    • [cs.LG]Self-Supervised Exploration via Latent Bayesian Surprise

    • [cs.LG]Sparse online relative similarity learning

    • [cs.LG]State and Topology Estimation for Unobservable Distribution Systems using Deep Neural Networks

    • [cs.LG]The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector

    • [cs.LG]Towards Handling Uncertainty-at-Source in AI — A Review and Next Steps for Interval Regression

    • [cs.LG]Unsupervised low-rank representations for speech emotion recognition

    • [cs.LG]Variational Co-embedding Learning for Attributed Network Clustering

    • [cs.LG]When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution

    • [cs.MS]mlf-core: a framework for deterministic machine learning

    • [cs.NE]Multiple regression techniques for modeling dates of first performances of Shakespeare-era plays

    • [cs.NE]On the Assessment of Benchmark Suites for Algorithm Comparison

    • [cs.NI]QuickLoc: Adaptive Deep-Learning for Fast Indoor Localization with Mobile Devices

    • [cs.NI]Serverless Federated Learning for UAV Networks: Architecture, Challenges, and Opportunities

    • [cs.RO]Adaptive Neuro-Fuzzy Control of a Spherical Rolling Robot Using Sliding-Mode-Control-Theory-Based Online Learning Algorithm

    • [cs.RO]Advanced Lane Detection Model for the Virtual Development of Highly Automated Functions

    • [cs.RO]Auto-Tuned Sim-to-Real Transfer

    • [cs.RO]Data-Driven Robust Barrier Functions for Safe, Long-Term Operation

    • [cs.RO]Data-driven Actuator Selection for Artificial Muscle-Powered Robots

    • [cs.RO]Human-in-the-Loop Deep Reinforcement Learning with Application to Autonomous Driving

    • [cs.RO]Rule-Based Reinforcement Learning for Efficient Robot Navigation with Space Reduction

    • [cs.RO]Tabletop Object Rearrangement: Team ACRV’s Entry to OCRTOC

    • [cs.SD]Audio feature ranking for sound-based COVID-19 patient detection

    • [cs.SD]Continual Learning for Fake Audio Detection

    • [cs.SD]Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching

    • [cs.SD]On the Design of Deep Priors for Unsupervised Audio Restoration

    • [cs.SD]Spectrogram Inpainting for Interactive Generation of Instrument Sounds

    • [cs.SE]OneLog: Towards End-to-End Training in Software Log Anomaly Detection

    • [cs.SI]Community-Based Fact-Checking on Twitter’s Birdwatch Platform

    • [cs.SI]Tourist route optimization in the context of Covid-19 pandemic

    • [econ.GN]Curse of Democracy: Evidence from 2020

    • [econ.GN]Quantifying firm-level economic systemic risk from nation-wide supply networks

    • [eess.AS]Conditional independence for pretext task selection in Self-supervised speech representation learning

    • [eess.AS]Speaker Attentive Speech Emotion Recognition

    • [eess.AS]Towards end-to-end F0 voice conversion based on Dual-GAN with convolutional wavelet kernels

    • [eess.IV]Anatomy-guided Multimodal Registration by Learning Segmentation without Ground Truth: Application to Intraprocedural CBCT/MR Liver Segmentation and Registration

    • [eess.IV]BAM: A Lightweight and Efficient Balanced Attention Mechanism for Single Image Super Resolution

    • [eess.IV]Deep learning for COVID-19 diagnosis based feature selection using binary differential evolution algorithm

    • [eess.IV]Image Super-Resolution via Iterative Refinement

    • [eess.IV]SVS-net: A Novel Semantic Segmentation Network in Optical Coherence Tomography Angiography Images

    • [eess.IV]Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantification

    • [eess.SP]Channel Estimation and Hybrid Architectures for RIS-Assisted Communications

    • [eess.SP]Estimation of atrial fibrillation from lead-I ECGs: Comparison with cardiologists and machine learning model (CurAlive), a clinical validation study

    • [eess.SY]Collective Iterative Learning Control: Exploiting Diversity in Multi-Agent Systems for Reference Tracking Tasks

    • [eess.SY]Piecewise-linear modelling with feature selection for Li-ion battery end of life prognosis

    • [eess.SY]Ransomware Detection Using Deep Learning in the SCADA System of Electric Vehicle Charging Station

    • [math.MG]On the Vapnik-Chervonenkis dimension of products of intervals in 今日学术视野(2021.4.17) - 图2

    • [math.OC]Internet of quantum blockchains: security modeling and dynamic resource pricing for stable digital currency

    • [math.ST]Logical contradictions in the One-way ANOVA and Tukey-Kramer multiple comparisons tests with more than two groups of observations

    • [math.ST]Polynomial methods in statistical inference: theory and practice

    • [math.ST]Rates of Bootstrap Approximation for Eigenvalues in High-Dimensional PCA

    • [q-bio.NC]A Novel Neuron Model of Visual Processor

    • [q-bio.NC]Neural population geometry: An approach for understanding biological and artificial neural networks

    • [q-fin.ST]A comparative study of Different Machine Learning Regressors For Stock Market Prediction

    • [stat.AP]COVID-19 Clinical footprint to infer about mortality

    • [stat.CO]Identification of unknown parameters and prediction with hierarchical matrices

    • [stat.CO]Reference and Probability-Matching Priors for the Parameters of a Univariate Student 今日学术视野(2021.4.17) - 图3-Distribution

    • [stat.CO]Variational Inference for the Smoothing Distribution in Dynamic Probit Models

    • [stat.ME]A Critique of Differential Abundance Analysis, and Advocacy for an Alternative

    • [stat.ME]Bayesian Synthetic Likelihood Estimation for Underreported Non-Stationary Time Series: Covid-19 Incidence in Spain

    • [stat.ME]Estimation of the Parameters of Vector Autoregressive (VAR) Time Series Model with Symmetric Stable Noise

    • [stat.ME]Fitting Infinitely divisible distribution: Case of Gamma-Variance Model

    • [stat.ME]Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives

    • [stat.ME]Partition-Mallows Model and Its Inference for Rank Aggregation

    • [stat.ME]Regularized regression on compositional tree with application to MRI analysis

    • [stat.ME]Robust Generalised Bayesian Inference for Intractable Likelihoods

    • [stat.ML]Coarse- and fine-scale geometric information content of Multiclass Classification and implied Data-driven Intelligence

    • [stat.ML]Mean-Squared Accuracy of Good-Turing Estimator

    • [stat.ML]Mean-Squared Accuracy of Good-Turing Estimator

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

    • [cs.AI]Adaptive Belief Discretization for POMDP Planning

    Divya Grover, Christos Dimitrakakis

    http://arxiv.org/abs/2104.07276v1

    • [cs.AI]Applying Personal Knowledge Graphs to Health

    Sola Shirai, Oshani Seneviratne, Deborah L. McGuinness

    http://arxiv.org/abs/2104.07587v1

    • [cs.AI]Emotion Dynamics Modeling via BERT

    Haiqin Yang, Jianping Shen

    http://arxiv.org/abs/2104.07252v1

    • [cs.AI]Ensemble of MRR and NDCG models for Visual Dialog

    Idan Schwartz

    http://arxiv.org/abs/2104.07511v1

    • [cs.AI]Text Guide: Improving the quality of long text classification by a text selection method based on feature importance

    Krzysztof Fiok, Waldemar Karwowski, Edgar Gutierrez, Mohammad Reza Davahli, Maciej Wilamowski, Tareq Ahram, Awad Al-Juaid, Jozef Zurada

    http://arxiv.org/abs/2104.07225v1

    • [cs.AR]SISA: Set-Centric Instruction Set Architecture for Graph Mining on Processing-in-Memory Systems

    Maciej Besta, Raghavendra Kanakagiri, Grzegorz Kwasniewski, Rachata Ausavarungnirun, Jakub Beránek, Konstantinos Kanellopoulos, Kacper Janda, Zur Vonarburg-Shmaria, Lukas Gianinazzi, Ioana Stefan, Juan Gómez Luna, Marcin Copik, Lukas Kapp-Schwoerer, Salvatore Di Girolamo, Marek Konieczny, Onur Mutlu, Torsten Hoefler

    http://arxiv.org/abs/2104.07582v1

    • [cs.CC]Sized Types with Usages for Parallel Complexity of Pi-Calculus Processes

    Patrick Baillot, Alexis Ghyselen, Naoki Kobayashi

    http://arxiv.org/abs/2104.07293v1

    • [cs.CL]A Dual-Questioning Attention Network for Emotion-Cause Pair Extraction with Context Awareness

    Qixuan Sun, Yaqi Yin, Hong Yu

    http://arxiv.org/abs/2104.07221v1

    • [cs.CL]A Sample-Based Training Method for Distantly Supervised Relation Extraction with Pre-Trained Transformers

    Mehrdad Nasser, Mohamad Bagher Sajadi, Behrouz Minaei-Bidgoli

    http://arxiv.org/abs/2104.07512v1

    • [cs.CL]AdaPrompt: Adaptive Prompt-based Finetuning for Relation Extraction

    Xiang Chen, Xin Xie, Ningyu Zhang, Jiahuan Yan, Shumin Deng, Chuanqi Tan, Fei Huang, Luo Si, Huajun Chen

    http://arxiv.org/abs/2104.07650v1

    • [cs.CL]Adaptive Active Learning for Coreference Resolution

    Michelle Yuan, Patrick Xia, Benjamin Van Durme, Jordan Boyd-Graber

    http://arxiv.org/abs/2104.07611v1

    • [cs.CL]Adaptive Sparse Transformer for Multilingual Translation

    Hongyu Gong, Xian Li, Dmitriy Genzel

    http://arxiv.org/abs/2104.07358v1

    • [cs.CL]An Alignment-Agnostic Model for Chinese Text Error Correction

    Liying Zheng, Yue Deng, Weishun Song, Liang Xu, Jing Xiao

    http://arxiv.org/abs/2104.07190v1

    • [cs.CL]An Interpretability Illusion for BERT

    Tolga Bolukbasi, Adam Pearce, Ann Yuan, Andy Coenen, Emily Reif, Fernanda Viégas, Martin Wattenberg

    http://arxiv.org/abs/2104.07143v1

    • [cs.CL]Annealing Knowledge Distillation

    Aref Jafari, Mehdi Rezagholizadeh, Pranav Sharma, Ali Ghodsi

    http://arxiv.org/abs/2104.07163v1

    • [cs.CL]Are Multilingual BERT models robust? A Case Study on Adversarial Attacks for Multilingual Question Answering

    Sara Rosenthal, Mihaela Bornea, Avirup Sil

    http://arxiv.org/abs/2104.07646v1

    • [cs.CL]BERT based Transformers lead the way in Extraction of Health Information from Social Media

    Sidharth R, Abhiraj Tiwari, Parthivi Choubey, Saisha Kashyap, Sahil Khose, Kumud Lakara, Nishesh Singh, Ujjwal Verma

    http://arxiv.org/abs/2104.07367v1

    • [cs.CL]Bilingual Terminology Extraction from Non-Parallel E-Commerce Corpora

    Hao Jia, Shuqin Gu, Yangbin Shi, Xiangyu Duan, Zhongkai Hu, Yuqi Zhang, Weihua Luo

    http://arxiv.org/abs/2104.07398v1

    • [cs.CL]Bilingual alignment transfers to multilingual alignment for unsupervised parallel text mining

    Chih-chan Tien, Shane Steinert-Threlkeld

    http://arxiv.org/abs/2104.07642v1

    • [cs.CL]Consistency Training with Virtual Adversarial Discrete Perturbation

    Jungsoo Park, Gyuwan Kim, Jaewoo Kang

    http://arxiv.org/abs/2104.07284v1

    • [cs.CL]Cross-Domain Label-Adaptive Stance Detection

    Momchil Hardalov, Arnav Arora, Preslav Nakov, Isabelle Augenstein

    http://arxiv.org/abs/2104.07467v1

    • [cs.CL]Data-QuestEval: A Referenceless Metric for Data to Text Semantic Evaluation

    Clément Rebuffel, Thomas Scialom, Laure Soulier, Benjamin Piwowarski, Sylvain Lamprier, Jacopo Staiano, Geoffrey Scoutheeten, Patrick Gallinari

    http://arxiv.org/abs/2104.07555v1

    • [cs.CL]Demystify Optimization Challenges in Multilingual Transformers

    Xian Li, Hongyu Gong

    http://arxiv.org/abs/2104.07639v1

    • [cs.CL]Designing a Minimal Retrieve-and-Read System for Open-Domain Question Answering

    Sohee Yang, Minjoon Seo

    http://arxiv.org/abs/2104.07242v1

    • [cs.CL]Disentangling Representations of Text by Masking Transformers

    Xiongyi Zhang, Jan-Willem van de Meent, Byron C. Wallace

    http://arxiv.org/abs/2104.07155v1

    • [cs.CL]Does Putting a Linguist in the Loop Improve NLU Data Collection?

    Alicia Parrish, William Huang, Omar Agha, Soo-Hwan Lee, Nikita Nangia, Alex Warstadt, Karmanya Aggarwal, Emily Allaway, Tal Linzen, Samuel R. Bowman

    http://arxiv.org/abs/2104.07179v1

    • [cs.CL]Effect of Post-processing on Contextualized Word Representations

    Hassan Sajjad, Firoj Alam, Fahim Dalvi, Nadir Durrani

    http://arxiv.org/abs/2104.07456v1

    • [cs.CL]ExplaGraphs: An Explanation Graph Generation Task for Structured Commonsense Reasoning

    Swarnadeep Saha, Prateek Yadav, Lisa Bauer, Mohit Bansal

    http://arxiv.org/abs/2104.07644v1

    • [cs.CL]First the worst: Finding better gender translations during beam search

    *Danielle Saunders, Rosi

    1000

    e Sallis, Bill Byrne*

    http://arxiv.org/abs/2104.07429v1

    • [cs.CL]Generating Datasets with Pretrained Language Models

    Timo Schick, Hinrich Schütze

    http://arxiv.org/abs/2104.07540v1

    • [cs.CL]Hierarchical Learning for Generation with Long Source Sequences

    Tobias Rohde, Xiaoxia Wu, Yinhan Liu

    http://arxiv.org/abs/2104.07545v1

    • [cs.CL]Integration of Pre-trained Networks with Continuous Token Interface for End-to-End Spoken Language Understanding

    Seunghyun Seo, Donghyun Kwak, Bowon Lee

    http://arxiv.org/abs/2104.07253v1

    • [cs.CL]Lattice-BERT: Leveraging Multi-Granularity Representations in Chinese Pre-trained Language Models

    Yuxuan Lai, Yijia Liu, Yansong Feng, Songfang Huang, Dongyan Zhao

    http://arxiv.org/abs/2104.07204v1

    • [cs.CL]Learning Zero-Shot Multifaceted Visually Grounded Word Embeddingsvia Multi-Task Training

    Hassan Shahmohammadi, Hendrik P. A. Lensch, R. Harald Baayen

    http://arxiv.org/abs/2104.07500v1

    • [cs.CL]Low-Resource Task-Oriented Semantic Parsing via Intrinsic Modeling

    Shrey Desai, Akshat Shrivastava, Alexander Zotov, Ahmed Aly

    http://arxiv.org/abs/2104.07224v1

    • [cs.CL]Modeling Human Mental States with an Entity-based Narrative Graph

    I-Ta Lee, Maria Leonor Pacheco, Dan Goldwasser

    http://arxiv.org/abs/2104.07079v1

    • [cs.CL]Multitasking Inhibits Semantic Drift

    Athul Paul Jacob, Mike Lewis, Jacob Andreas

    http://arxiv.org/abs/2104.07219v1

    • [cs.CL]NT5?! Training T5 to Perform Numerical Reasoning

    Peng-Jian Yang, Ying Ting Chen, Yuechan Chen, Daniel Cer

    http://arxiv.org/abs/2104.07307v1

    • [cs.CL]Neural Sequence Segmentation as Determining the Leftmost Segments

    Yangming Li, Lemao Liu, Kaisheng Yao

    http://arxiv.org/abs/2104.07217v1

    • [cs.CL]Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction

    Dai Quoc Nguyen, Vinh Tong, Dinh Phung, Dat Quoc Nguyen

    http://arxiv.org/abs/2104.07396v1

    • [cs.CL]On the Robustness of Goal Oriented Dialogue Systems to Real-world Noise

    Jason Krone, Sailik Sengupta, Saab Mansoor

    http://arxiv.org/abs/2104.07149v1

    • [cs.CL]Planning with Entity Chains for Abstractive Summarization

    Shashi Narayan, Yao Zhao, Joshua Maynez, Gonçalo Simoes, Ryan McDonald

    http://arxiv.org/abs/2104.07606v1

    • [cs.CL]Predicting Discourse Trees from Transformer-based Neural Summarizers

    Wen Xiao, Patrick Huber, Giuseppe Carenini

    http://arxiv.org/abs/2104.07058v1

    • [cs.CL]Privacy-Adaptive BERT for Natural Language Understanding

    Chen Qu, Weize Kong, Liu Yang, Mingyang Zhang, Michael Bendersky, Marc Najork

    http://arxiv.org/abs/2104.07504v1

    • [cs.CL]Pseudo Zero Pronoun Resolution Improves Zero Anaphora Resolution

    Ryuto Konno, Shun Kiyono, Yuichiroh Matsubayashi, Hiroki Ouchi, Kentaro Inui

    http://arxiv.org/abs/2104.07425v1

    • [cs.CL]Quantifying Gender Bias Towards Politicians in Cross-Lingual Language Models

    Karolina Stańczak, Sagnik Ray Choudhury, Tiago Pimentel, Ryan Cotterell, Isabelle Augenstein

    http://arxiv.org/abs/2104.07505v1

    • [cs.CL]RefSum: Refactoring Neural Summarization

    Yixin Liu, Zi-Yi Dou, Pengfei Liu

    http://arxiv.org/abs/2104.07210v1

    • [cs.CL]Reformulating Sentence Ordering as Conditional Text Generation

    Somnath Basu Roy Chowdhury, Faeze Brahman, Snigdha Chaturvedi

    http://arxiv.org/abs/2104.07064v1

    • [cs.CL]Regularizing Models via Pointwise Mutual Information for Named Entity Recognition

    Minbyul Jeong, Jaewoo Kang

    http://arxiv.org/abs/2104.07249v1

    • [cs.CL]Rethinking Automatic Evaluation in Sentence Simplification

    Thomas Scialom, Louis Martin, Jacopo Staiano, Éric Villemonte de la Clergerie, Benoît Sagot

    http://arxiv.org/abs/2104.07560v1

    • [cs.CL]Retrieval Augmentation Reduces Hallucination in Conversation

    Kurt Shuster, Spencer Poff, Moya Chen, Douwe Kiela, Jason Weston

    http://arxiv.org/abs/2104.07567v1

    • [cs.CL]Reward Optimization for Neural Machine Translation with Learned Metrics

    Raphael Shu, Kang Min Yoo, Jung-Woo Ha

    http://arxiv.org/abs/2104.07541v1

    • [cs.CL]SINA-BERT: A pre-trained Language Model for Analysis of Medical Texts in Persian

    Nasrin Taghizadeh, Ehsan Doostmohammadi, Elham Seifossadat, Hamid R. Rabiee, Maedeh S. Tahaei

    http://arxiv.org/abs/2104.07613v1

    • [cs.CL]Sentence-Permuted Paragraph Generation

    Wenhao Yu, Chenguang Zhu, Tong Zhao, Zhichun Guo, Meng Jiang

    http://arxiv.org/abs/2104.07228v1

    • [cs.CL]Sequence Tagging for Biomedical Extractive Question Answering

    Wonjin Yoon, Richard Jackson, Jaewoo Kang, Aron Lagerberg

    http://arxiv.org/abs/2104.07535v1

    • [cs.CL]Simultaneous Multi-Pivot Neural Machine Translation

    Raj Dabre, Aizhan Imankulova, Masahiro Kaneko, Abhisek Chakrabarty

    http://arxiv.org/abs/2104.07410v1

    • [cs.CL]Sometimes We Want Translationese

    Prasanna Parthasarathi, Koustuv Sinha, Joelle Pineau, Adina Williams

    http://arxiv.org/abs/2104.07623v1

    • [cs.CL]Span Pointer Networks for Non-Autoregressive Task-Oriented Semantic Parsing

    Akshat Shrivastava, Pierce Chuang, Arun Babu, Shrey Desai, Abhinav Arora, Alexander Zotov, Ahmed Aly

    http://arxiv.org/abs/2104.07275v1

    • [cs.CL]Static Embeddings as Efficient Knowledge Bases?

    Philipp Dufter, Nora Kassner, Hinrich Schütze

    http://arxiv.org/abs/2104.07094v1

    • [cs.CL]SummScreen: A Dataset for Abstractive Screenplay Summarization

    Mingda Chen, Zewei Chu, Sam Wiseman, Kevin Gimpel

    http://arxiv.org/abs/2104.07091v1

    • [cs.CL]SummVis: Interactive Visual Analysis of Models, Data, and Evaluation for Text Summarization

    Jesse Vig, Wojciech Kryscinski, Karan Goel, Nazneen Fatema Rajani

    http://arxiv.org/abs/2104.07605v1

    • [cs.CL]Syntactic Perturbations Reveal Representational Correlates of Hierarchical Phrase Structure in Pretrained Language Models

    Matteo Alleman, Jonathan Mamou, Miguel A Del Rio, Hanlin Tang, Yoon Kim, SueYeon Chung

    http://arxiv.org/abs/2104.07578v1

    • [cs.CL]TWEAC: Transformer with Extendable QA Agent Classifiers

    Gregor Geigle, Nils Reimers, Andreas Rücklé, Iryna Gurevych

    http://arxiv.org/abs/2104.07081v1

    • [cs.CL]The Effect of Efficient Messaging and Input Variability on Neural-Agent Iterated Language Learning

    Yuchen Lian, Arianna Bisazza, Tessa Verhoef

    http://arxiv.org/abs/2104.07637v1

    • [cs.CL]The MuSe 2021 Multimodal Sentiment Analysis Challenge: Sentiment, Emotion, Physiological-Emotion, and Stress

    Lukas Stappen, Alice Baird, Lukas Christ, Lea Schumann, Benjamin Sertolli, Eva-Maria Messner, Erik Cambria, Guoying Zhao, Björn W. Schuller

    http://arxiv.org/abs/2104.07123v1

    • [cs.CL]The Role of Context in Detecting Previously Fact-Checked Claims

    Shaden Shaar, Firoj Alam, Giovanni Da San Martino, Preslav Nakov

    http://arxiv.org/abs/2104.07423v1

    • [cs.CL]Time-Stamped Language Model: Teaching Language Models to Understand the Flow of Events

    Hossein Rajaby Faghihi, Parisa Kordjamshidi

    http://arxiv.org/abs/2104.07635v1

    • [cs.CL]TorontoCL at CMCL 2021 Shared Task: RoBERTa with Multi-Stage Fine-Tuning for Eye-Tracking Prediction

    Bai Li, Frank Rudzicz

    http://arxiv.org/abs/2104.07244v1

    • [cs.CL]Towards Deconfounding the Influence of Subject’s Demographic Characteristics in Question Answering

    Maharshi Gor, Kellie Webster, Jordan Boyd-Graber

    http://arxiv.org/abs/2104.07571v1

    • [cs.CL]Tracking entities in technical procedures — a new dataset and baselines

    Saransh Goyal, Pratyush Pandey, Garima Gaur, Subhalingam D, Srikanta Bedathur, Maya Ramanath

    http://arxiv.org/abs/2104.07378v1

    • [cs.CL]TransferNet: An Effective and Transparent Framework for Multi-hop Question Answering over Relation Graph

    Jiaxin Shi, Shulin Cao, Lei Hou, Juanzi Li, Hanwang Zhang

    http://arxiv.org/abs/2104.07302v1

    • [cs.CL]UDALM: Unsupervised Domain Adaptation through Language Modeling

    Constantinos Karouzos, Georgios Paraskevopoulos, Alexandros Potamianos

    http://arxiv.org/abs/2104.07078v1

    • [cs.CL]UHD-BERT: Bucketed Ultra-High Dimensional Sparse Representations for Full Ranking

    Kyoung-Rok Jang, Junmo Kang, Giwon Hong, Sung-Hyon Myaeng, Joohee Park, Taewon Yoon, Heecheol Seo

    http://arxiv.org/abs/2104.07198v1

    • [cs.CL]UIT-E10dot3 at SemEval-2021 Task 5: Toxic Spans Detection with Named Entity Recognition and Question-Answering Approaches

    Phu Gia Hoang, Luan Thanh Nguyen, Kiet Van Nguyen

    http://arxiv.org/abs/2104.07376v1

    • [cs.CL]Unlocking Compositional Generalization in Pre-trained Models Using Intermediate Representations

    Jonathan Herzig, Peter Shaw, Ming-Wei Chang, Kelvin Guu, Panupong Pasupat, Yuan Zhang

    http://arxiv.org/abs/2104.07478v1

    • [cs.CL]Unmasking the Mask — Evaluating Social Biases in Masked Language Models

    Masahiro Kaneko, Danushka Bollegala

    http://arxiv.org/abs/2104.07496v1

    • [cs.CL]What Makes a Scientific Paper be Accepted for Publication?

    Panagiotis Fytas, Georgios Rizos, Lucia Specia

    http://arxiv.org/abs/2104.07112v1

    • [cs.CL]XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation

    Sebastian Ruder, Noah Constant, Jan Botha, Aditya Siddhant, Orhan Firat, Jinlan Fu, Pengfei Liu, Junjie Hu, Graham Neubig, Melvin Johnson

    http://arxiv.org/abs/2104.07412v1

    • [cs.CL]Zero-Shot Cross-lingual Semantic Parsing

    Tom Sherborne, Mirella Lapata

    http://arxiv.org/abs/2104.07554v1

    • [cs.CR]An Explainable Machine Learning-based Network Intrusion Detection System for Enabling Generalisability in Securing IoT Networks

    Mohanad Sarhan, Siamak Layeghy, Marius Portmann

    http://arxiv.org/abs/2104.07183v1

    • [cs.CR]Discover the Hidden Attack Path in Multi-domain Cyberspace Based on Reinforcement Learning

    Lei Zhang, Wei Bai, Wei Li, Shiming Xia, Qibin Zheng

    http://arxiv.org/abs/2104.07195v1

    • [cs.CR]Measuring the Impact of Blockchain and Smart Contract on Construction Supply Chain Visibility

    Hesam Hamledari, Martin Fischer

    http://arxiv.org/abs/2104.07532v1

    • [cs.CR]Robust Backdoor Attacks against Deep Neural Networks in Real Physical World

    Mingfu Xue, Can He, Shichang Sun, Jian Wang, Weiqiang Liu

    http://arxiv.org/abs/2104.07395v1

    • [cs.CV]3DCrowdNet: 2D Human Pose-Guided3D Crowd Human Pose and Shape Estimation in the Wild

    Hongsuk Choi, Gyeongsik Moon, JoonKyu Park, Kyoung Mu Lee

    http://arxiv.org/abs/2104.07300v1

    • [cs.CV]A Decomposition Model for Stereo Matching

    Chengtang Yao, Yunde Jia, Huijun Di, Pengxiang Li, Yuwei Wu

    http://arxiv.org/abs/2104.07516v1

    • [cs.CV]A Simple Baseline for Semi-supervised Semantic Segmentation with Strong Data Augmentation

    Jianlong Yuan, Yifan Liu, Chunhua Shen, Zhibin Wang, Hao Li

    http://arxiv.org/abs/2104.07256v1

    • [cs.CV]A Simple Baseline for StyleGAN Inversion

    Tianyi Wei, Dongdong Chen, Wenbo Zhou, Jing Liao, Weiming Zhang, Lu Yuan, Gang Hua, Nenghai Yu

    http://arxiv.org/abs/2104.07661v1

    • [cs.CV]A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation

    Jiteng Mu, Weichao Qiu, Adam Kortylewski, Alan Yuille, Nuno Vasconcelos, Xiaolong Wang

    http://arxiv.org/abs/2104.07645v1

    • [cs.CV]Action Segmentation with Mixed Temporal Domain Adaptation

    Min-Hung Chen, Baopu Li, Yingze Bao, Ghassan AlRegib

    http://arxiv.org/abs/2104.07461v1

    • [cs.CV]Adaptive Intermediate Representations for Video Understanding

    Juhana Kangaspunta, AJ Piergiovanni, Rico Jonschkowski, Michael Ryoo, Anelia Angelova

    http://arxiv.org/abs/2104.07135v1

    • [cs.CV]An Improved Real-Time Face Recognition System at Low Resolution Based on Local Binary Pattern Histogram Algorithm and CLAHE

    Kamal Chandra Paul, Semih Aslan

    http://arxiv.org/abs/2104.07234v1

    • [cs.CV]Audio-Driven Emotional Video Portraits

    Xinya Ji, Hang Zhou, Kaisiyuan Wang, Wayne Wu, Chen Change Loy, Xun Cao, Feng Xu

    http://arxiv.org/abs/2104.07452v1

    • [cs.CV]Camera View Adjustment Prediction for Improving Image Composition

    Yu-Chuan Su, Raviteja Vemulapalli, Ben Weiss, Chun-Te Chu, Philip Andrew Mansfield, Lior Shapira, Colvin Pitts

    http://arxiv.org/abs/2104.07608v1

    • [cs.CV]ContactOpt: Optimizing Contact to Improve Grasps

    Patrick Grady, Chengcheng Tang, Christopher D. Twigg, Minh Vo, Samarth Brahmbhatt, Charles C. Kemp

    http://arxiv.org/abs/2104.07267v1

    • [cs.CV]Continual Learning From Unlabeled Data Via Deep Clustering

    Jiangpeng He, Fengqing Zhu

    http://arxiv.org/abs/2104.07164v1

    • [cs.CV]Convolutions for Spatial Interaction Modeling

    Zhaoen Su, Chao Wang, David Bradley, Carlos Vallespi-Gonzalez, Carl Wellington, Nemanja Djuric

    http://arxiv.org/abs/2104.07182v1

    • [cs.CV]Depth Completion using Plane-Residual Representation

    Byeong-Uk Lee, Kyunghyun Lee, In So Kweon

    http://arxiv.org/abs/2104.07350v1

    • [cs.CV]Do Deep Neural Networks Forget Facial Action Units? — Exploring the Effects of Transfer Learning in Health Related Facial Expression Recognition

    Pooja Prajod, Dominik Schiller, Tobias Huber, Elisabeth André

    http://arxiv.org/abs/2104.07389v1

    • [cs.CV]Fast Walsh-Hadamard Transform and Smooth-Thresholding Based Binary Layers in Deep Neural Networks

    Hongyi Pan, Diaa Dabawi, Ahmet Enis Cetin

    http://arxiv.org/abs/2104.07085v1

    • [cs.CV]Federated Learning-based Active Authentication on Mobile Devices

    Poojan Oza, Vishal M. Patel

    http://arxiv.org/abs/2104.07158v1

    • [cs.CV]GANcraft: Unsupervised 3D Neural Rendering of Minecraft Worlds

    Zekun Hao, Arun Mallya, Serge Belongie, Ming-Yu Liu

    http://arxiv.org/abs/2104.07659v1

    • [cs.CV]Geometry-Free View Synthesis: Transformers and no 3D Priors

    Robin Rombach, Patrick Esser, Björn Ommer

    http://arxiv.org/abs/2104.07652v1

    • [cs.CV]Graph-based Thermal-Inertial SLAM with Probabilistic Neural Networks

    Muhamad Risqi U. Saputra, Pedro P. B. de Gusmao, Bing Wang, Andrew Markham, Niki Trigoni

    http://arxiv.org/abs/2104.07196v1

    • [cs.CV]Investigations on Output Parameterizations of Neural Networks for Single Shot 6D Object Pose Estimation

    Kilian Kleeberger, Markus Völk, Richard Bormann, Marco F. Huber

    http://arxiv.org/abs/2104.07528v1

    • [cs.CV]Learning Regional Attention over Multi-resolution Deep Convolutional Features for Trademark Retrieval

    Osman Tursun, Simon Denman, Sridha Sridharan, Clinton Fookes

    http://arxiv.org/abs/2104.07240v1

    • [cs.CV]Learning structure-aware semantic segmentation with image-level supervision

    Jiawei Liu, Jing Zhang, Yicong Hong, Nick Barnes

    http://arxiv.org/abs/2104.07216v1

    • [cs.CV]PURE: Passive mUlti-peRson idEntification via Deep Footstep Separation and Recognition

    Chao Cai, Ruinan Jin, Peng Wang, Liyuan Ye, Hongbo Jiang, Jun Luo

    http://arxiv.org/abs/2104.07177v1

    • [cs.CV]Points as Queries: Weakly Semi-supervised Object Detection by Points

    Liangyu Chen, Tong Yang, Xiangyu Zhang, Wei Zhang, Jian Sun

    http://arxiv.org/abs/2104.07434v1

    • [cs.CV]SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elements

    Qianli Ma, Shunsuke Saito, Jinlong Yang, Siyu Tang, Michael J. Black

    http://arxiv.org/abs/2104.07660v1

    • [cs.CV]Self-Supervised Learning of Remote Sensing Scene Representations Using Contrastive Multiview Coding

    Vladan Stojnić, Vladimir Risojević

    http://arxiv.org/abs/2104.07070v1

    • [cs.CV]Self-supervised Learning of 3D Object Understanding by Data Association and Landmark Estimation for Image Sequence

    Hyeonwoo Yu, Jean Oh

    http://arxiv.org/abs/2104.07077v1

    • [cs.CV]Self-supervised Video Object Segmentation by Motion Grouping

    Charig Yang, Hala Lamdouar, Erika Lu, Andrew Zisserman, Weidi Xie

    http://arxiv.org/abs/2104.07658v1

    • [cs.CV]SiamCorners: Siamese Corner Networks for Visual Tracking

    Kai Yang, Zhenyu He, Wenjie Pei, Zikun Zhou, Xin Li, Di Yuan, Haijun Zhang

    http://arxiv.org/abs/2104.07303v1

    • [cs.CV]Spectral MVIR: Joint Reconstruction of 3D Shape and Spectral Reflectance

    Chunyu Li, Yusuke Monno, Masatoshi Okutomi

    http://arxiv.org/abs/2104.07308v1

    • [cs.CV]StEP: Style-based Encoder Pre-training for Multi-modal Image Synthesis

    Moustafa Meshry, Yixuan Ren, Larry S Davis, Abhinav Shrivastava

    http://arxiv.org/abs/2104.07098v1

    • [cs.CV]Street-Map Based Validation of Semantic Segmentation in Autonomous Driving

    Laura von Rueden, Tim Wirtz, Fabian Hueger, Jan David Schneider, Nico Piatkowski, Christian Bauckhage

    http://arxiv.org/abs/2104.07538v1

    • [cs.CV]Training Deep Capsule Networks with Residual Connections

    Josef Gugglberger, David Peer, Antonio Rodriguez-Sanchez

    http://arxiv.org/abs/2104.07393v1

    • [cs.CV]TransRPPG: Remote Photoplethysmography Transformer for 3D Mask Face Presentation Attack Detection

    Zitong Yu, Xiaobai Li, Pichao Wang, Guoying Zhao

    http://arxiv.org/abs/2104.07419v1

    • [cs.CV]Weakly Supervised Video Anomaly Detection via Center-guided Discriminative Learning

    Boyang Wan, Yuming Fang, Xue Xia, Jiajie Mei

    http://arxiv.org/abs/2104.07268v1

    • [cs.CV]Zooming SlowMo: An Efficient One-Stage Framework for Space-Time Video Super-Resolution

    Xiaoyu Xiang, Yapeng Tian, Yulun Zhang, Yun Fu, Jan P. Allebach, Chenliang Xu

    http://arxiv.org/abs/2104.07473v1

    • [cs.CY]Otaku: Intelligent Management System for Student-Intensive Dormitory

    Yuanzhe Jin, Chenrui Zhang, Maorong Wang

    http://arxiv.org/abs/2104.07630v1

    • [cs.CY]Skilled and Mobile: Survey Evidence of Immigration Preferences of AI Researchers

    Remco Zwetsloot, Baobao Zhang, Noemi Dreksler, Lauren Kahn, Markus Anderljung, Allan Dafoe, Michael C. Horowitz

    http://arxiv.org/abs/2104.07237v1

    • [cs.DC]Coalescent Computing

    Kyle C. Hale

    http://arxiv.org/abs/2104.07122v1

    • [cs.DC]Minimizing privilege for building HPC containers

    Reid Priedhorsky, R. Shane Canon, Timothy Randles, Andrew J. Younge

    http://arxiv.org/abs/2104.07508v1

    • [cs.DC]Towards a Fast and Accurate Model of Intercontact Times for Epidemic Routing

    Fabricio Cravo, Thomas Nowak

    http://arxiv.org/abs/2104.07298v1

    • [cs.DC]Who Needs Consensus? A Distributed Monetary System Between Rational Agents via Hearsay

    Yanni Georghiades, Robert Streit, Vijay Garg

    http://arxiv.org/abs/2104.07574v1

    • [cs.DL]ROC: An Ontology for Country Responses towards COVID-19

    Jamal Al Qundus, Ralph Schäfermeier, Naouel Karam, Silvio Peikert, Adrian Paschke

    http://arxiv.org/abs/2104.07345v1

    • [cs.HC]Towards A Process Model for Co-Creating AI Experiences

    Hariharan Subramonyam, Colleen Seifert, Eytan Adar

    http://arxiv.org/abs/2104.07595v1

    • [cs.IR]A Large-Scale Analysis of Mixed Initiative in Information-Seeking Dialogues for Conversational Search

    Svitlana Vakulenko, Evangelos Kanoulas, Maarten de Rijke

    http://arxiv.org/abs/2104.07096v1

    • [cs.IR]COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List

    Luyu Gao, Zhuyun Dai, Jamie Callan

    http://arxiv.org/abs/2104.07186v1

    • [cs.IR]DebiasedRec: Bias-aware User Modeling and Click Prediction for Personalized News Recommendation

    Jingwei Yi, Fangzhao Wu, Chuhan Wu, Qifei Li, Guangzhong Sun, Xing Xie

    http://arxiv.org/abs/2104.07360v1

    • [cs.IR]Deep Learning-based Online Alternative Product Recommendations at Scale

    Mingming Guo, Nian Yan, Xiquan Cui, San He Wu, Unaiza Ahsan, Rebecca West, Khalifeh Al Jadda

    http://arxiv.org/abs/2104.07572v1

    • [cs.IR]Dynamic Graph Neural Networks for Sequential Recommendation

    Mengqi Zhang, Shu Wu, Xueli Yu, Liang Wang

    http://arxiv.org/abs/2104.07368v1

    • [cs.IR]Empowering News Recommendation with Pre-trained Language Models

    Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang

    http://arxiv.org/abs/2104.07413v1

    • [cs.IR]Hyperbolic Neural Collaborative Recommender

    Anchen Li, Bo Yang, Hongxu Chen, Guandong Xu

    http://arxiv.org/abs/2104.07414v1

    • [cs.IR]MM-Rec: Multimodal News Recommendation

    Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang

    http://arxiv.org/abs/2104.07407v1

    • [cs.IR]Two Birds with One Stone: Unified Model Learning for Both Recall and Ranking in News Recommendation

    Chuhan Wu, Fangzhao Wu, Tao Qi, Yongfeng Huang

    http://arxiv.org/abs/2104.07404v1

    • [cs.IT]Extending two families of maximum rank distance codes

    Alessandro Neri, Paolo Santonastaso, Ferdinando Zullo

    http://arxiv.org/abs/2104.07602v1

    • [cs.IT]On Missing Mass Variance

    Maciej Skorski

    http://arxiv.org/abs/2104.07028v1

    • [cs.IT]On the existence of quaternary Hermitian LCD codes with Hermitian dual distance 今日学术视野(2021.4.17) - 图4

    Keita Ishizuka, Ken Saito

    http://arxiv.org/abs/2104.07432v1

    • [cs.IT]Performance of CRC Concatenated Pre-transformed RM-Polar Codes

    Bin Li, Jiaqi Gu, Huazi Zhang

    http://arxiv.org/abs/2104.07486v1

    • [cs.IT]Phase noise in communication systems: from measures to models

    Amina Piemontese, Giulio Colavolpe, Thomas Eriksson

    http://arxiv.org/abs/2104.07264v1

    • [cs.IT]Stochastic-Adversarial Channels : Online Adversaries With Feedback Snooping

    Vinayak Suresh, Eric Ruzomberka, David J. Love

    http://arxiv.org/abs/2104.07194v1

    • [cs.LG]Accelerating Neural Network Training with Distributed Asynchronous and Selective Optimization (DASO)

    Daniel Coquelin, Charlotte Debus, Markus Götz, Fabrice von der Lehr, James Kahn, Martin Siggel, Achim Streit

    http://arxiv.org/abs/2104.05588v2

    • [cs.LG]All-You-Can-Fit 8-Bit Flexible Floating-Point Format for Accurate and Memory-Efficient Inference of Deep Neural Networks

    Cheng-Wei Huang, Tim-Wei Chen, Juinn-Dar Huang

    http://arxiv.org/abs/2104.07329v1

    • [cs.LG]Attentive Max Feature Map for Acoustic Scene Classification with Joint Learning considering the Abstraction of Classes

    Hye-jin Shim, Ju-ho Kim, Jee-weon Jung, Ha-Jin Yu

    http://arxiv.org/abs/2104.07213v1

    • [cs.LG]Bayesian and Dempster-Shafer models for combining multiple sources of evidence in a fraud detection system

    Fabrice Daniel

    http://arxiv.org/abs/2104.07440v1

    • [cs.LG]D-Cliques: Compensating NonIIDness in Decentralized Federated Learning with Topology

    Aurélien Bellet, Anne-Marie Kermarrec, Erick Lavoie

    http://arxiv.org/abs/2104.07365v1

    • [cs.LG]Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity

    Nicha C. Dvornek, Xiaoxiao Li, Juntang Zhuang, Pamela Ventola, James S. Duncan

    http://arxiv.org/abs/2104.07654v1

    • [cs.LG]DistGNN: Scalable Distributed Training for Large-Scale Graph Neural Networks

    Vasimuddin Md, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha

    http://arxiv.org/abs/2104.06700v2

    • [cs.LG]Efficient Click-Through Rate Prediction for Developing Countries via Tabular Learning

    Joonyoung Yi, Buru Chang

    http://arxiv.org/abs/2104.07553v1

    • [cs.LG]Embedding Adaptation is Still Needed for Few-Shot Learning

    Sébastien M. R. Arnold, Fei Sha

    http://arxiv.org/abs/2104.07255v1

    • [cs.LG]Exact and Approximate Hierarchical Clustering Using A*

    Craig S. Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, Andrew McCallum

    http://arxiv.org/abs/2104.07061v1

    • [cs.LG]Facilitating Machine Learning Model Comparison and Explanation Through A Radial Visualisation

    Jianlong Zhou, Weidong Huang, Fang Chen

    http://arxiv.org/abs/2104.07377v1

    • [cs.LG]Fast Private Parameter Learning and Evaluation for Sum-Product Networks

    Ernst Althaus, Mohammad Sadeq Dousti, Stefan Kramer

    http://arxiv.org/abs/2104.07353v1

    • [cs.LG]FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks

    Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Yu Rong, Peilin Zhao, Junzhou Huang, Murali Annavaram, Salman Avestimehr

    http://arxiv.org/abs/2104.07145v1

    • [cs.LG]FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems

    Li Li, Moming Duan, Duo Liu, Yu Zhang, Ao Ren, Xianzhang Chen, Yujuan Tan, Chengliang Wang

    http://arxiv.org/abs/2104.07515v1

    • [cs.LG]Generalising Discrete Action Spaces with Conditional Action Trees

    Christopher Bamford, Alvaro Ovalle

    http://arxiv.org/abs/2104.07294v1

    • [cs.LG]HIVE-COTE 2.0: a new meta ensemble for time series classification

    Matthew Middlehurst, James Large, Michael Flynn, Jason Lines, Aaron Bostrom, Anthony Bagnall

    http://arxiv.org/abs/2104.07551v1

    • [cs.LG]Iterative Barycenter Flows

    David I. Inouye, Zeyu Zhou, Ziyu Gong, Pradeep Ravikumar

    http://arxiv.org/abs/2104.07232v1

    • [cs.LG]Lorentzian Graph Convolutional Networks

    Yiding Zhang, Xiao Wang, Chuan Shi, Nian Liu, Guojie Song

    http://arxiv.org/abs/2104.07477v1

    • [cs.LG]Membership-Mappings for Data Representation Learning

    Mohit Kumar, Bernhard A. Moser, Lukas Fischer, Bernhard Freudenthaler

    http://arxiv.org/abs/2104.07060v1

    • [cs.LG]Multi-Agent Reinforcement Learning Based Coded Computation for Mobile Ad Hoc Computing

    Baoqian Wang, Junfei Xie, Kejie Lu, Yan Wan, Shengli Fu

    http://arxiv.org/abs/2104.07539v1

    • [cs.LG]Multivariate Deep Evidential Regression

    Nis Meinert, Alexander Lavin

    http://arxiv.org/abs/2104.06135v2

    • [cs.LG]NICE: An Algorithm for Nearest Instance Counterfactual Explanations

    Dieter Brughmans, David Martens

    http://arxiv.org/abs/2104.07411v1

    • [cs.LG]NeuSE: A Neural Snapshot Ensemble Method for Collaborative Filtering

    Dongsheng Li, Haodong Liu, Chao Chen, Yingying Zhao, Stephen M. Chu, Bo Yang

    http://arxiv.org/abs/2104.07269v1

    • [cs.LG]On Energy-Based Models with Overparametrized Shallow Neural Networks

    Carles Domingo-Enrich, Alberto Bietti, Eric Vanden-Eijnden, Joan Bruna

    http://arxiv.org/abs/2104.07531v1

    • [cs.LG]Orthogonalizing Convolutional Layers with the Cayley Transform

    Asher Trockman, J. Zico Kolter

    http://arxiv.org/abs/2104.07167v1

    • [cs.LG]Rehearsal revealed: The limits and merits of revisiting samples in continual learning

    Eli Verwimp, Matthias De Lange, Tinne Tuytelaars

    http://arxiv.org/abs/2104.07446v1

    • [cs.LG]Rehearsal revealed: The limits and merits of revisiting samples in continual learning

    Eli Verwimp, Matthias De Lange, Tinne Tuytelaars

    http://arxiv.org/abs/rg/abs/2104.07446v1

    • [cs.LG]Robust Neural Networks Outperform Attitude Estimation Filters

    Daniel Weber, Clemens Gühmann, Thomas Seel

    http://arxiv.org/abs/2104.07391v1

    • [cs.LG]Scale Invariant Solutions for Overdetermined Linear Systems with Applications to Reinforcement Learning

    Rahul Madhavan, Gugan Thoppe, Hemanta Makwana

    http://arxiv.org/abs/2104.07361v1

    • [cs.LG]See through Gradients: Image Batch Recovery via GradInversion

    Hongxu Yin, Arun Mallya, Arash Vahdat, Jose M. Alvarez, Jan Kautz, Pavlo Molchanov

    http://arxiv.org/abs/2104.07586v1

    • [cs.LG]Self-Supervised Exploration via Latent Bayesian Surprise

    Pietro Mazzaglia, Ozan Catal, Tim Verbelen, Bart Dhoedt

    http://arxiv.org/abs/2104.07495v1

    • [cs.LG]Sparse online relative similarity learning

    Dezhong Yao, Peilin Zhao, Chen Yu, Hai Jin, Bin Li

    http://arxiv.org/abs/2104.07501v1

    • [cs.LG]State and Topology Estimation for Unobservable Distribution Systems using Deep Neural Networks

    B. Azimian, R. Sen Biswas, A. Pal, Lang Tong, Gautam Dasarathy

    http://arxiv.org/abs/2104.07208v1

    • [cs.LG]The Role of Cross-Silo Federated Learning in Facilitating Data Sharing in the Agri-Food Sector

    Aiden Durrant, Milan Markovic, David Matthews, David May, Jessica Enright, Georgios Leontidis

    http://arxiv.org/abs/2104.07468v1

    • [cs.LG]Towards Handling Uncertainty-at-Source in AI — A Review and Next Steps for Interval Regression

    Shaily Kabir, Christian Wagner, Zack Ellerby

    http://arxiv.org/abs/2104.07245v1

    • [cs.LG]Unsupervised low-rank representations for speech emotion recognition

    Georgios Paraskevopoulos, Efthymios Tzinis, Nikolaos Ellinas, Theodoros Giannakopoulos, Alexandros Potamianos

    http://arxiv.org/abs/2104.07072v1

    • [cs.LG]Variational Co-embedding Learning for Attributed Network Clustering

    Shuiqiao Yang, Sunny Verma, Borui Cai, Jiaojiao Jiang, Kun Yu, Fang Chen, Shui Yu

    http://arxiv.org/abs/2104.07295v1

    • [cs.LG]When and Whom to Collaborate with in a Changing Environment: A Collaborative Dynamic Bandit Solution

    Chuanhao Li, Qingyun Wu, Hongning Wang

    http://arxiv.org/abs/2104.07150v1

    • [cs.MS]mlf-core: a framework for deterministic machine learning

    Lukas Heumos, Philipp Ehmele, Kevin Menden, Luis Kuhn Cuellar, Edmund Miller, Steffen Lemke, Gisela Gabernet, Sven Nahnsen

    http://arxiv.org/abs/2104.07651v1

    • [cs.NE]Multiple regression techniques for modeling dates of first performances of Shakespeare-era plays

    Pablo Moscato, Hugh Craig, Gabriel Egan, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan, Jon Corrales de Oliveira

    http://arxiv.org/abs/2104.05929v2

    • [cs.NE]On the Assessment of Benchmark Suites for Algorithm Comparison

    David Issa Mattos, Lucas Ruud, Jan Bosch, Helena Holmström Olsson

    http://arxiv.org/abs/2104.07381v1

    • [cs.NI]QuickLoc: Adaptive Deep-Learning for Fast Indoor Localization with Mobile Devices

    Saideep Tiku, Prathmesh Kale, Sudeep Pasricha

    http://arxiv.org/abs/2104.07521v1

    • [cs.NI]Serverless Federated Learning for UAV Networks: Architecture, Challenges, and Opportunities

    Yuben Qu, Haipeng Dai, Yan Zhuang, Jiafa Chen, Chao Dong, Fan Wu, Song Guo

    http://arxiv.org/abs/2104.07557v1

    • [cs.RO]Adaptive Neuro-Fuzzy Control of a Spherical Rolling Robot Using Sliding-Mode-Control-Theory-Based Online Learning Algorithm

    Erkan Kayacan, Erdal Kayacan, Herman Ramon, Wouter Saeys

    http://arxiv.org/abs/2104.07160v1

    • [cs.RO]Advanced Lane Detection Model for the Virtual Development of Highly Automated Functions

    Philip Pannagger, Demin Nalic, Faris Orucevic, Arno Eichberger, Branko Rogic

    http://arxiv.org/abs/2104.07481v1

    • [cs.RO]Auto-Tuned Sim-to-Real Transfer

    Yuqing Du, Olivia Watkins, Trevor Darrell, Pieter Abbeel, Deepak Pathak

    http://arxiv.org/abs/2104.07662v1

    • [cs.RO]Data-Driven Robust Barrier Functions for Safe, Long-Term Operation

    Yousef Emam, Paul Glotfelter, Sean Wilson, Gennaro Notomista, Magnus Egerstedt

    http://arxiv.org/abs/2104.07592v1

    • [cs.RO]Data-driven Actuator Selection for Artificial Muscle-Powered Robots

    Taylor West Henderson, Yuheng Zhi, Angela Liu, Michael C. Yip

    http://arxiv.org/abs/2104.07168v1

    • [cs.RO]Human-in-the-Loop Deep Reinforcement Learning with Application to Autonomous Driving

    Jingda Wu, Zhiyu Huang, Chao Huang, Zhongxu Hu, Peng Hang, Yang Xing, Chen Lv

    http://arxiv.org/abs/2104.07246v1

    • [cs.RO]Rule-Based Reinforcement Learning for Efficient Robot Navigation with Space Reduction

    Yuanyang Zhu, Zhi Wang, Chunlin Chen, Daoyi Dong

    http://arxiv.org/abs/2104.07282v1

    • [cs.RO]Tabletop Object Rearrangement: Team ACRV’s Entry to OCRTOC

    Zheyu Zhang, Rhys Newbury, Kerry He, Steven Martin, Gavin Suddrey, Jun Kwan, Peter Corke, Akansel Cosgun

    http://arxiv.org/abs/2104.07188v1

    • [cs.SD]Audio feature ranking for sound-based COVID-19 patient detection

    Julia A. Meister, Khuong An Nguyen, Zhiyuan Luo

    http://arxiv.org/abs/2104.07128v1

    • [cs.SD]Continual Learning for Fake Audio Detection

    Haoxin Ma, Jiangyan Yi, Jianhua Tao, Ye Bai, Zhengkun Tian, Chenglong Wang

    http://arxiv.org/abs/2104.07286v1

    • [cs.SD]Cross-domain Speech Recognition with Unsupervised Character-level Distribution Matching

    Wenxin Hou, Jindong Wang, Xu Tan, Tao Qin, Takahiro Shinozaki

    http://arxiv.org/abs/2104.07491v1

    • [cs.SD]On the Design of Deep Priors for Unsupervised Audio Restoration

    Vivek Sivaraman Narayanaswamy, Jayaraman J. Thiagarajan, Andreas Spanias

    http://arxiv.org/abs/2104.07161v1

    • [cs.SD]Spectrogram Inpainting for Interactive Generation of Instrument Sounds

    Théis Bazin, Gaëtan Hadjeres, Philippe Esling, Mikhail Malt

    http://arxiv.org/abs/2104.07519v1

    • [cs.SE]OneLog: Towards End-to-End Training in Software Log Anomaly Detection

    Shayan Hashemi, Mika Mäntylä

    http://arxiv.org/abs/2104.07324v1

    • [cs.SI]Community-Based Fact-Checking on Twitter’s Birdwatch Platform

    Nicolas Pröllochs

    http://arxiv.org/abs/2104.07175v1

    • [cs.SI]Tourist route optimization in the context of Covid-19 pandemic

    Cristina Maria Pacurar, Ruxandra-Gabriela Albu, Victor-Dan Pacurar

    http://arxiv.org/abs/2104.07663v1

    • [econ.GN]Curse of Democracy: Evidence from 2020

    Yusuke Narita, Ayumi Sudo

    http://arxiv.org/abs/2104.07617v1

    • [econ.GN]Quantifying firm-level economic systemic risk from nation-wide supply networks

    Christian Diem, András Borsos, Tobias Reisch, János Kertész, Stefan Thurner

    http://arxiv.org/abs/2104.07260v1

    • [eess.AS]Conditional independence for pretext task selection in Self-supervised speech representation learning

    Salah Zaiem, Titouan Parcollet, Slim Essid

    http://arxiv.org/abs/2104.07388v1

    • [eess.AS]Speaker Attentive Speech Emotion Recognition

    Clément Le Moine, Nicolas Obin, Axel Roebel

    http://arxiv.org/abs/2104.07288v1

    • [eess.AS]Towards end-to-end F0 voice conversion based on Dual-GAN with convolutional wavelet kernels

    Clément Le Moine Veillon, Nicolas Obin, Axel Roebel

    http://arxiv.org/abs/2104.07283v1

    • [eess.IV]Anatomy-guided Multimodal Registration by Learning Segmentation without Ground Truth: Application to Intraprocedural CBCT/MR Liver Segmentation and Registration

    Bo Zhou, Zachary Augenfeld, Julius Chapiro, S. Kevin Zhou, Chi Liu, James S. Duncan

    http://arxiv.org/abs/2104.07056v1

    • [eess.IV]BAM: A Lightweight and Efficient Balanced Attention Mechanism for Single Image Super Resolution

    Fanyi Wang, Haotian Hu, Cheng Shen

    http://arxiv.org/abs/2104.07566v1

    • [eess.IV]Deep learning for COVID-19 diagnosis based feature selection using binary differential evolution algorithm

    Mohammad Saber Iraji, Mohammad-Reza Feizi-Derakhshi, Jafar Tanha

    http://arxiv.org/abs/2104.07279v1

    • [eess.IV]Image Super-Resolution via Iterative Refinement

    Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi

    http://arxiv.org/abs/2104.07636v1

    • [eess.IV]SVS-net: A Novel Semantic Segmentation Network in Optical Coherence Tomography Angiography Images

    Yih-Cherng Lee, Ling Yeung

    http://arxiv.org/abs/2104.07083v1

    • [eess.IV]Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantification

    Sangjoon Park, Gwanghyun Kim, Yujin Oh, Joon Beom Seo, Sang Min Lee, Jin Hwan Kim, Sungjun Moon, Jae-Kwang Lim, Jong Chul Ye

    http://arxiv.org/abs/2104.07235v1

    • [eess.SP]Channel Estimation and Hybrid Architectures for RIS-Assisted Communications

    Jiguang He, Nhan Thanh Nguyen, Rafaela Schroeder, Visa Tapio, Joonas Kokkoniemi, Markku Juntti

    http://arxiv.org/abs/2104.07115v1

    • [eess.SP]Estimation of atrial fibrillation from lead-I ECGs: Comparison with cardiologists and machine learning model (CurAlive), a clinical validation study

    N. Korucuk, C. Polat, E. S. Gunduz, O. Karaman, V. Tosun, M. Onac, N. Yildirim, Y. Cete, K. Polat

    http://arxiv.org/abs/2104.07427v1

    • [eess.SY]Collective Iterative Learning Control: Exploiting Diversity in Multi-Agent Systems for Reference Tracking Tasks

    Michael Meindl, Fabio Molinari, Dustin Lehmann, Thomas Seel

    http://arxiv.org/abs/2104.07620v1

    • [eess.SY]Piecewise-linear modelling with feature selection for Li-ion battery end of life prognosis

    Samuel Greenbank, David A. Howey

    http://arxiv.org/abs/2104.07576v1

    • [eess.SY]Ransomware Detection Using Deep Learning in the SCADA System of Electric Vehicle Charging Station

    Manoj Basnet, Manoj Basnet, Mohd. Hasan Ali, Dipankar Dasgupta

    http://arxiv.org/abs/2104.07409v1

    • [math.MG]On the Vapnik-Chervonenkis dimension of products of intervals in 今日学术视野(2021.4.17) - 图5

    Alirio Gómez Gómez, Pedro L. Kaufmann

    http://arxiv.org/abs/2104.07136v1

    • [math.OC]Internet of quantum blockchains: security modeling and dynamic resource pricing for stable digital currency

    Wanyang Dai

    http://arxiv.org/abs/2104.07323v1

    • [math.ST]Logical contradictions in the One-way ANOVA and Tukey-Kramer multiple comparisons tests with more than two groups of observations

    Vladimir Gurvich, Mariya Naumova

    http://arxiv.org/abs/2104.07552v1

    • [math.ST]Polynomial methods in statistical inference: theory and practice

    Yihong Wu, Pengkun Yang

    http://arxiv.org/abs/2104.07317v1

    • [math.ST]Rates of Bootstrap Approximation for Eigenvalues in High-Dimensional PCA

    Junwen Yao, Miles E. Lopes

    http://arxiv.org/abs/2104.07328v1

    • [q-bio.NC]A Novel Neuron Model of Visual Processor

    Jizhao Liu, Jing Lian, J C Sprott, Yide Ma

    http://arxiv.org/abs/2104.07257v1

    • [q-bio.NC]Neural population geometry: An approach for understanding biological and artificial neural networks

    SueYeon Chung, L. F. Abbott

    http://arxiv.org/abs/2104.07059v1

    • [q-fin.ST]A comparative study of Different Machine Learning Regressors For Stock Market Prediction

    Nazish Ashfaq, Zubair Nawaz, Muhammad Ilyas

    http://arxiv.org/abs/2104.07469v1

    • [stat.AP]COVID-19 Clinical footprint to infer about mortality

    Carlos E. Rodríguez, Ramsés H. Mena

    http://arxiv.org/abs/2104.07172v1

    • [stat.CO]Identification of unknown parameters and prediction with hierarchical matrices

    Alexander Litvinenko, Ronald Kriemann, Vladimir Berikov

    http://arxiv.org/abs/2104.07146v1

    • [stat.CO]Reference and Probability-Matching Priors for the Parameters of a Univariate Student 今日学术视野(2021.4.17) - 图6-Distribution

    A. J. van der Merwe, M. J. von Maltitz, J. H. Meyer

    http://arxiv.org/abs/2104.07386v1

    • [stat.CO]Variational Inference for the Smoothing Distribution in Dynamic Probit Models

    Augusto Fasano, Giovanni Rebaudo

    http://arxiv.org/abs/2104.07537v1

    • [stat.ME]A Critique of Differential Abundance Analysis, and Advocacy for an Alternative

    Thomas P Quinn, Elliott Gordon-Rodriguez, Ionas Erb

    http://arxiv.org/abs/2104.07266v1

    • [stat.ME]Bayesian Synthetic Likelihood Estimation for Underreported Non-Stationary Time Series: Covid-19 Incidence in Spain

    David Moriña, Amanda Fernández-Fontelo, Alejandra Cabaña, Argimiro Arratia, Pedro Puig

    http://arxiv.org/abs/2104.07575v1

    • [stat.ME]Estimation of the Parameters of Vector Autoregressive (VAR) Time Series Model with Symmetric Stable Noise

    Aastha M. Sathe, N. S. Upadhye

    http://arxiv.org/abs/2104.07262v1

    • [stat.ME]Fitting Infinitely divisible distribution: Case of Gamma-Variance Model

    A. H. Nzokem

    http://arxiv.org/abs/2104.07580v1

    • [stat.ME]Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives

    Hussein Hazimeh, Rahul Mazumder, Peter Radchenko

    http://arxiv.org/abs/2104.07084v1

    • [stat.ME]Partition-Mallows Model and Its Inference for Rank Aggregation

    Wanchuang Zhu, Yingkai Jiang, Jun S. Liu, Ke Deng

    http://arxiv.org/abs/2104.07261v1

    • [stat.ME]Regularized regression on compositional tree with application to MRI analysis

    *Bingkai Wang, Brian S. Caff

    5c41

    o, Xi Luo, Chin-Fu Liu, Andreia V. Faria, Michael I. Miller, Yi Zhao*

    http://arxiv.org/abs/2104.07113v1

    • [stat.ME]Robust Generalised Bayesian Inference for Intractable Likelihoods

    Takuo Matsubara, Jeremias Knoblauch, François-Xavier Briol, Chris. J. Oates

    http://arxiv.org/abs/2104.07359v1

    • [stat.ML]Coarse- and fine-scale geometric information content of Multiclass Classification and implied Data-driven Intelligence

    Fushing Hsieh, Xiaodong Wang

    http://arxiv.org/abs/2104.07191v1

    • [stat.ML]Mean-Squared Accuracy of Good-Turing Estimator

    Maciej Skorski

    [http://arxiv.org/abs/

    69d

    /2104.07029v1](http://arxiv.org/abs/

    69d

    /2104.07029v1)

    • [stat.ML]Mean-Squared Accuracy of Good-Turing Estimator

    Maciej Skorski

    http://arxiv.org/abs/2104.07029v1