astro-ph.IM - 仪器仪表和天体物理学方法 astro-ph.SR - 太阳和天体物理学恒星 cs.AI - 人工智能 cs.CL - 计算与语言 cs.CR - 加密与安全 cs.CV - 机器视觉与模式识别 cs.CY - 计算与社会 cs.DC - 分布式、并行与集群计算 cs.DM - 离散数学 cs.DS - 数据结构与算法 cs.GT - 计算机科学与博弈论 cs.HC - 人机接口 cs.IR - 信息检索 cs.IT - 信息论 cs.LG - 自动学习 cs.MA - 多代理系统 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.PL - 编程语言 cs.RO - 机器人学 cs.SE - 软件工程 cs.SI - 社交网络与信息网络 econ.EM - 计量经济学 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.AG - 代数几何 math.OC - 优化与控制 math.PR - 概率 math.SP - 谱理论 math.ST - 统计理论 physics.flu-dyn - 流体动力学 physics.geo-ph - 地球物理学 physics.soc-ph - 物理学与社会 q-bio.NC - 神经元与认知 quant-ph - 量子物理 stat.AP - 应用统计 stat.CO - 统计计算 stat.ME - 统计方法论 stat.ML - (统计)机器学习
• [astro-ph.IM]Change point detection and image segmentation for time series of astrophysical images
• [astro-ph.SR]Automatic Detection of Occulted Hard X-ray Flares Using Deep-Learning Methods
• [cs.AI]Evolution of artificial intelligence languages, a systematic literature review
• [cs.AI]Learning task-agnostic representation via toddler-inspired learning
• [cs.AI]On formal concepts of random formal contexts
• [cs.AI]Privacy Information Classification: A Hybrid Approach
• [cs.CL]A Comparison of Approaches to Document-level Machine Translation
• [cs.CL]A phonetic model of non-native spoken word processing
• [cs.CL]Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling
• [cs.CL]An Empirical Study of Cross-Lingual Transferability in Generative Dialogue State Tracker
• [cs.CL]CLiMP: A Benchmark for Chinese Language Model Evaluation
• [cs.CL]Cross-Lingual Named Entity Recognition Using Parallel Corpus: A New Approach Using XLM-RoBERTa Alignment
• [cs.CL]Deep Subjecthood: Higher-Order Grammatical Features in Multilingual BERT
• [cs.CL]El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsing
• [cs.CL]Enquire One’s Parent and Child Before Decision: Fully Exploit Hierarchical Structure for Self-Supervised Taxonomy Expansion
• [cs.CL]Event-Driven News Stream Clustering using Entity-Aware Contextual Embeddings
• [cs.CL]Exploring multi-task multi-lingual learning of transformer models for hate speech and offensive speech identification in social media
• [cs.CL]Fine-Grained Named Entity Typing over Distantly Supervised Data via Refinement in Hyperbolic Space
• [cs.CL]First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
• [cs.CL]How to Evaluate a Summarizer: Study Design and Statistical An
1000
alysis for Manual Linguistic Quality Evaluation
• [cs.CL]Inheritance-guided Hierarchical Assignment for Clinical Automatic Diagnosis
• [cs.CL]Joint Coreference Resolution and Character Linkingfor Multiparty Conversation
• [cs.CL]KoreALBERT: Pretraining a Lite BERT Model for Korean Language Understanding
• [cs.CL]LSOIE: A Large-Scale Dataset for Supervised Open Information Extraction
• [cs.CL]Language Modelling as a Multi-Task Problem
• [cs.CL]Low Resource Recognition and Linking of Biomedical Concepts from a Large Ontology
• [cs.CL]Medical Segment Coloring of Clinical Notes
• [cs.CL]Meta-Learning for Effective Multi-task and Multilingual Modelling
• [cs.CL]Multilingual and cross-lingual document classification: A meta-learning approach
• [cs.CL]Muppet: Massive Multi-task Representations with Pre-Finetuning
• [cs.CL]Named Entity Recognition in the Style of Object Detection
• [cs.CL]Neural Sentence Ordering Based on Constraint Graphs
• [cs.CL]On the Evolution of Syntactic Information Encoded by BERT’s Contextualized Representations
• [cs.CL]Open-domain Topic Identification of Out-of-domain Utterances using Wikipedia
• [cs.CL]PPT: Parsimonious Parser Transfer for Unsupervised Cross-Lingual Adaptation
• [cs.CL]Recent Trends in Named Entity Recognition (NER)
• [cs.CL]SkillNER: Mining and Mapping Soft Skills from any Text
• [cs.CL]Summarising Historical Text in Modern Languages
• [cs.CL]Towards Robustness to Label Noise in Text Classification via Noise Modeling
• [cs.CL]Transformer Based Deliberation for Two-Pass Speech Recognition
• [cs.CL]Triangular Bidword Generation for Sponsored Search Auction
• [cs.CL]VisualMRC: Machine Reading Comprehension on Document Images
• [cs.CR]Defenses Against Multi-Sticker Physical Domain Attacks on Classifiers
• [cs.CR]Equivalence of Non-Perfect Secret Sharing and Symmetric Private Information Retrieval with General Access Structure
• [cs.CV]Arbitrary-Oriented Ship Detection through Center-Head Point Extraction
• [cs.CV]Automated Crop Field Surveillance using Computer Vision
• [cs.CV]Automatic Comic Generation with Stylistic Multi-page Layouts and Emotion-driven Text Balloon Generation
• [cs.CV]Automatic image annotation base on Naive Bayes and Decision Tree classifiers using MPEG-7
• [cs.CV]Bottleneck Transformers for Visual Recognition
• [cs.CV]CPTR: Full Transformer Network for Image Captioning
• [cs.CV]Controlling by Showing: i-Mimic: A Video-based Method to Control Robotic Arms
• [cs.CV]Convolutional Neural Network-Based Age Estimation Using B-Mode Ultrasound Tongue Image
• [cs.CV]Deep Image Retrieval: A Survey
• [cs.CV]Deep Video Inpainting Detection
• [cs.CV]DeepOIS: Gyroscope-Guided Deep Optical Image Stabilizer Compensation
• [cs.CV]Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting
• [cs.CV]Detecting Deepfake Videos Using Euler Video Magnification
• [cs.CV]EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, Featuring Prognostic Stratification Boosting
• [cs.CV]Edge-Labeling based Directed Gated Graph Network for Few-shot Learning
• [cs.CV]Effects of Image Size on Deep Learning
• [cs.CV]Efficient Video Summarization Framework using EEG and Eye-tracking Signals
• [cs.CV]GaitGraph: Graph Convolutional Network for Skeleton-Based Gait Recognition
• [cs.CV]Generative Multi-Label Zero-Shot Learning
• [cs.CV]Im2Mesh GAN: Accurate 3D Hand Mesh Recovery from a Single RGB Image
• [cs.CV]Multi-Hypothesis Pose Networks: Rethinking Top-Down Pose Estimation
• [cs.CV]NTU60-X: Towards Skeleton-based Recognition of Subtle Human Actions
• [cs.CV]New Algorithms for Computing Field of Vision over 2D Grids
• [cs.CV]On the Importance of Capturing a Sufficient Diversity of Perspective for the Classification of micro-PCBs
• [cs.CV]Puzzle-CAM: Improved localization via matching partial and full features
• [cs.CV]Reciprocal Landmark Detection and Tracking with Extremely Few Annotations
• [cs.CV]ResLT: Residual Learning for Long-tailed Recognition
• [cs.CV]Revisiting Contrastive Learning for Few-Shot Classification
• [cs.CV]Scheduled Sampling in Vision-Language Pretraining with Decoupled Encoder-Decoder Network
• [cs.CV]Self-Calibrating Active Binocular Vision via Active Efficient Coding with Deep Autoencoders
• [cs.CV]Shape or Texture: Understanding Discriminative Features in CNNs
• [cs.CV]Spatial-Channel Transformer Network for Trajectory Prediction on the Traffic Scenes
• [cs.CV]Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action Recognition
• [cs.CV]The Effect of Class Definitions on the Transferability of Adversarial Attacks Against Forensic CNNs
• [cs.CV]TorchPRISM: Principal Image Sections Mapping, a novel method for Convolutional Neural Network features visualization
• [cs.CV]Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search
• [cs.CV]Utilizing Uncertainty Estimation in Deep Learning Segmentation of Fluorescence Microscopy Images with Missing Markers
• [cs.CV]e-ACJ: Accurate Junction Extraction For Event Cameras
• [cs.CY]Hiding Behind Machines: When Blame Is Shifted to Artificial Agents
• [cs.CY]Low-skilled Occupations Face the Highest Re-skilling Pressure
• [cs.CY]On Small-World Networks: Survey and Properties Analysis
• [cs.CY]Pano: Engaging with News using Moral Framing towards Bridging Ideological Divides
• [cs.CY]Re-imagining Algorithmic Fairness in India and Beyond
• [cs.CY]The Work of Art in an Age of Mechanical Generation
• [cs.DC]C-for-Metal: High Performance SIMD Programming on Intel GPUs
• [cs.DC]RTGPU: Real-Time GPU Scheduling of Hard Deadline Parallel Tasks with Fine-Grain Utilization
• [cs.DC]Response-Time Analysis and Optimization for Probabilistic Conditional Parallel DAG Tasks
• [cs.DC]Self-stabilizing Algorithm for Maximal Distance-2 Independent Set
• [cs.DM]Logical-Combinatorial Approaches in Dynamic Recognition Problems
• [cs.DS]A Neighborhood-preserving Graph Summarization
• [cs.GT]A Balance for Fairness: Fair Distribution Utilising Physics in Games of Characteristic Function Form
• [cs.HC]Developing for personalised learning: the long road from educational objectives to development and feedback
• [cs.IR]Advances and Challenges in Conversational Recommender Systems: A Survey
• [cs.IR]Investigating Diffusion of Scientific Knowledge on Twitter: A Study of Topic Networks of Opioid Publications
• [cs.IR]Mining the Stars: Learning Quality Ratings with User-facing Explanations for Vacation Rentals
• [cs.IR]One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Prediction
• [cs.IR]Powering COVID-19 community Q&A with Curated Side Information
• [cs.IT]A Coding Theory Perspective on MultiplexedMolecular Profiling of Biological Tissues
• [cs.IT]Bayes-Optimal Convolutional AMP
• [cs.IT]Constructing new APN functions through relative trace functions
• [cs.IT]Coverage Analysis of Broadcast Networks with Users Having Heterogeneous Content/Advertisement Preferences
• [cs.IT]Improved algorithms for non-adaptive group testing with consecutive positives
• [cs.IT]Joint Active and Passive Beamforming for Intelligent Reflecting Surface Aided Multiuser MIMO Communications
• [cs.IT]Joint Source-Channel Coding for Semantics-Aware Grant-Free Radio Access in IoT Fog Networks
• [cs.IT]Non-Asymptotic Converse Bounds Via Auxiliary Channels
• [cs.IT]Nonconvex Regularized Gradient Projection Sparse Reconstruction for Massive MIMO Channel Estimation
• [cs.IT]On Massive IoT Connectivity with Temporally-Correlated User Activity
• [cs.IT]On the Automorphism Group of Polar Codes
• [cs.IT]Rate Splitting Multiple Access for Multi-Antenna Multi-Carrier Joint Communications and Jamming
• [cs.IT]Real-time oblivious erasure correction with linear time decoding and constant feedback
• [cs.IT]Sequential decoding of high-rate Reed-Muller codes
• [cs.IT]Streaming Erasure Codes over the Multiple Access Relay Channel
• [cs.IT]Strengthened Cutset Upper Bounds on the Capacity of the Relay Channel and Applications
• [cs.IT]Super-Resolution for Doubly-Dispersive Channel Estimation
• [cs.IT]The fundamental limits of sparse linear regression with sublinear sparsity
• [cs.IT]Variational Encoders and Autoencoders : Information-theoretic Inference and Closed-form Solutions
• [cs.LG]A Note on the Representation Power of GHHs
• [cs.LG]Accuracy and Privacy Evaluations of Collaborative Data Analysis
• [cs.LG]Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
• [cs.LG]Adaptivity without Compromise: A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization
• [cs.LG]Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials
• [cs.LG]Adversaries in Online Learning Revisited: with applications in Robust Optimization and Adversarial training
• [cs.LG]An explainable Transformer-based deep learning model for the prediction of incident heart failure
• [cs.LG]Autoencoder-based Condition Monitoring and Anomaly Detection Method for Rotating Machines
• [cs.LG]Average Localised Proximity: a new data descriptor with good default one-class classification performance
• [cs.LG]Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression
• [cs.LG]Combat Data Shift in Few-shot Learning with Knowledge Graph
• [cs.LG]Decision Machines: Interpreting Decision Tree as a Model Combination Method
• [cs.LG]Detecting discriminatory risk through data annotation based on Bayesian inferences
• [cs.LG]Efficient Graph Deep Learning in TensorFlow with tf_geometric
• [cs.LG]Evolutionary Generative Adversarial Networks with Crossover Based Knowledge Distillation
• [cs.LG]FedH2L: Federated Learning with Model and Statistical Heterogeneity
• [cs.LG]Graph Neural Network for Traffic Forecasting: A Survey
• [cs.LG]Improving Graph Representation Learning by Contrastive Regularization
• [cs.LG]Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond
• [cs.LG]Learning Abstract Representations through Lossy Compression of Multi-Modal Signals
• [cs.LG]Learning Non-linear Wavelet Transformation via Normalizing Flow
• [cs.LG]Meta Adversarial Training
• [cs.LG]OffCon: What is state of the art anyway?
• [cs.LG]On the Interpretability of Deep Learning Based Models for Knowledge Tracing
• [cs.LG]Partition of unity networks: deep hp-approximation
• [cs.LG]Pitfalls of Assessing Extracted Hierarchies for Multi-Class Classification
• [cs.LG]Property Inference From Poisoning
• [cs.LG]Safe Multi-Agent Reinforcement Learning via Shielding
• [cs.LG]Similarity of Classification Tasks
• [cs.LG]Supervised Tree-Wasserstein Distance
• [cs.LG]The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors
• [cs.LG]Tropical Support Vector Machines: Evaluations and Extension to Function Spaces
• [cs.LG]Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection
• [cs.MA]Modelling the Impact of Scandals: the case of the 2017 French Presidential Election
• [cs.MA]Multi-agent simulation of voter’s behaviour
• [cs.MS]FDApy: a Python package for functional data
• [cs.NE]Particle Swarm Optimization: Fundamental Study and its Application to Optimization and to Jetty Scheduling Problems
• [cs.NE]Pseudo-Adaptive Penalization to Handle Constraints in Particle Swarm Optimizers
• [cs.NE]Scale-free Network-based Differential Evolution
• [cs.NI]Cloud based VANET Simulator (CVANETSIM)
• [cs.PL]Compositional Semantics for Probabilistic Programs with Exact Conditioning
• [cs.RO]ADMM-based Adaptive Sampling Strategy for Nonholonomic Mobile Robotic Sensor Networks
• [cs.RO]An Integrated Localisation, Motion Planning and Obstacle Avoidance Algorithm in Belief Space
• [cs.RO]Autonomous Off-road Navigation over Extreme Terrains with Perceptually-challenging Conditions
• [cs.RO]Dexterous Manipulation Primitives for the Real Robot Challenge
• [cs.RO]Exact and Approximate Heterogeneous Bayesian Decentralized Data Fusion
• [cs.RO]Non-Monotone Energy-Aware Information Gathering for Heterogeneous Robot Teams
• [cs.RO]Online Extrinsic Calibration based on Per-Sensor Ego-Motion Using Dual Quaternions
• [cs.SE]Can Offline Testing of Deep Neural Networks Replace Their Online Testing?
• [cs.SI]Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection
• [cs.SI]Deriving the Traveler Behavior Information from Social Media: A Case Study in Manhattan with Twitter
• [cs.SI]Launchers and Targets in Social Networks
• [cs.SI]Measuring Law Over Time: A Network Analytical Framework with an Application to Statutes and Regulations in the United States and Germany
• [cs.SI]Modeling opinion leader’s role in the diffusion of innovation
• [cs.SI]REFORM: Fast and Adaptive Solution for Subteam Replacement
• [cs.SI]Why polls fail to predict elections
• [econ.EM]Predictive Quantile Regression with Mixed Roots and Increasing Dimensions
• [eess.IV]An Interpretation of Regularization by Denoising and its Application with the Back-Projected Fidelity Term
• [eess.IV]Automatic Segmentation of Gross Target Volume of Nasopharynx Cancer using Ensemble of Multiscale Deep Neural Networks with Spatial Attention
• [eess.IV]Boosting Segmentation Performance across datasets using histogram specification with application to pelvic bone segmentation
• [eess.IV]Synthetic Generation of Three-Dimensional Cancer Cell Models from Histopathological Images
• [eess.SP]Anti-Aliasing Add-On for Deep Prior Seismic Data Interpolation
• [eess.SP]Statistical guided-waves-based SHM via stochastic non-parametric time series models
• [eess.SY]GymD2D: A Device-to-Device Underlay Cellular Offload Evaluation Platform
• [hep-ex]A Convolutional Neural Network based Cascade Reconstruction for the IceCube Neutrino Observatory
• [hep-ex]Parallelizing the Unpacking and Clustering of Detector Data for Reconstruction of Charged Particle Tracks on Multi-core CPUs and Many-core GPUs
• [math.AG]Kähler Geometry of Quiver Varieties and Machine Learning
• [math.OC]Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems
• [math.OC]Formulating and solving integrated order batching and routing in multi-depot AGV-assisted mixed-shelves warehouses
• [math.OC]Inadequacy of Linear Methods for Minimal Sensor Placement and Feature Selection in Nonlinear Systems; a New Approach Using Secants
• [math.OC]New Riemannian preconditioned algorithms for tensor completion via polyadic decomposition
• [math.PR]Functional inequalities for perturbed measures with applications to log-concave measures and to some Bayesian problems
• [math.SP]LDLE: Low Distortion Local Eigenmaps
• [math.ST]A general method for power analysis in testing high dimensional covariance matrices
• [math.ST]Motif-based tests for bipartite networks
• [physics.flu-dyn]Echo State Network for two-dimensional turbulent moist Rayleigh-Bénard convection
• [physics.flu-dyn]State estimation with limited sensors — A deep learning based approach
• [physics.geo-ph]Periodic seismicity detection without declustering
• [physics.soc-ph]A Model of Densifying Collaboration Networks
• [physics.soc-ph]Individual and Social Behaviour in Particle Swarm Optimizers
• [q-bio.NC]Identification of brain states, transitions, and communities using functional MRI
• [quant-ph]Quantum Generative Adversarial Networks in a Continuous-Variable Architecture to Simulate High Energy Physics Detectors
• [quant-ph]Quantum machine learning models are kernel methods
• [stat.AP]A study on information behavior of scholars for article keywords selection
• [stat.AP]Boost-S: Gradient Boosted Trees for Spatial Data and Its Application to FDG-PET Imaging Data
• [stat.AP]Solar Radiation Anomaly Events Modeling Using Spatial-Temporal Mutually Interactive Processes
• [stat.AP]Transporting a prediction model for use in a new target population
• [stat.CO]Log-Normalization Constant Estimation using the Ensemble Kalman-Bucy Filter with Application to High-Dimensional Models
• [stat.ME]An Early Stopping Bayesian Data Assimilation Approach for Mixed-Logit Estimation
• [stat.ME]Bayesian Paired-Comparison with the bpcs Package
• [stat.ME]Computational methods for Bayesian semiparametric Item Response Theory models
• [stat.ME]D-STEM v2: A Software for Modelling Functional Spatio-Temporal Data
• [stat.ME]Most Powerful Test Sequences with Early Stopping Options
• [stat.ME]To tune or not to tune, a case study of ridge logistic regression in small or sparse datasets
• [stat.ME]Tree boosting for learning probability measures
• [stat.ML]Generalized Doubly Reparameterized Gradient Estimators
• [stat.ML]Reproducing kernel Hilbert C*-module and kernel mean embeddings
·····································
• [astro-ph.IM]Change point detection and image segmentation for time series of astrophysical images
Cong Xu, Hans Moritz Günther, Vinay L. Kashyap, Thomas C. M. Lee, Andreas Zezas
http://arxiv.org/abs/2101.11202v1
• [astro-ph.SR]Automatic Detection of Occulted Hard X-ray Flares Using Deep-Learning Methods
Shin-nosuke Ishikawa, Hideaki Matsumura, Yasunobu Uchiyama, Lindsay Glesener
http://arxiv.org/abs/2101.11550v1
• [cs.AI]Evolution of artificial intelligence languages, a systematic literature review
Emmanuel Adetiba, Temitope John, Adekunle Akinrinmade, Funmilayo Moninuola, Oladipupo Akintade, Joke Badejo
http://arxiv.org/abs/2101.11501v1
• [cs.AI]Learning task-agnostic representation via toddler-inspired learning
Kwanyoung Park, Junseok Park, Hyunseok Oh, Byoung-Tak Zhang, Youngki Lee
http://arxiv.org/abs/2101.11221v1
• [cs.AI]On formal concepts of random formal contexts
Taro Sakurai
http://arxiv.org/abs/2101.11023v1
• [cs.AI]Privacy Information Classification: A Hybrid Approach
Jiaqi Wu, Weihua Li, Quan Bai, Takayuki Ito, Ahmed Moustafa
http://arxiv.org/abs/2101.11574v1
• [cs.CL]A Comparison of Approaches to Document-level Machine Translation
Zhiyi Ma, Sergey Edunov, Michael Auli
http://arxiv.org/abs/2101.11040v1
• [cs.CL]A phonetic model of non-native spoken word processing
Yevgen Matusevych, Herman Kamper, Thomas Schatz, Naomi H. Feldman, Sharon Goldwater
http://arxiv.org/abs/2101.11332v1
• [cs.CL]Adversarial Stylometry in the Wild: Transferable Lexical Substitution Attacks on Author Profiling
Chris Emmery, Ákos Kádár, Grzegorz Chrupała
http://arxiv.org/abs/2101.11310v1
• [cs.CL]An Empirical Study of Cross-Lingual Transferability in Generative Dialogue State Tracker
Yen-Ting Lin, Yun-Nung Chen
http://arxiv.org/abs/2101.11360v1
• [cs.CL]CLiMP: A Benchmark for Chinese Language Model Evaluation
Beilei Xiang, Changbing Yang, Yu Li, Alex Warstadt, Katharina Kann
http://arxiv.org/abs/2101.11131v1
• [cs.CL]Cross-Lingual Named Entity Recognition Using Parallel Corpus: A New Approach Using XLM-RoBERTa Alignment
Bing Li, Yujie He, Wenjin Xu
http://arxiv.org/abs/2101.11112v1
• [cs.CL]Deep Subjecthood: Higher-Order Grammatical Features in Multilingual BERT
Isabel Papadimitriou, Ethan A. Chi, Richard Futrell, Kyle Mahowald
http://arxiv.org/abs/2101.11043v1
• [cs.CL]El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsing
Arash Einolghozati, Abhinav Arora, Lorena Sainz-Maza Lecanda, Anuj Kumar, Sonal Gupta
http://arxiv.org/abs/2101.10524v2
• [cs.CL]Enquire One’s Parent and Child Before Decision: Fully Exploit Hierarchical Structure for Self-Supervised Taxonomy Expansion
Suyuchen Wang, Ruihui Zhao, Xi Chen, Yefeng Zheng, Bang Liu
http://arxiv.org/abs/2101.11268v1
• [cs.CL]Event-Driven News Stream Clustering using Entity-Aware Contextual Embeddings
Kailash Karthik Saravanakumar, Miguel Ballesteros, Muthu Kumar Chandrasekaran, Kathleen McKeown
http://arxiv.org/abs/2101.11059v1
• [cs.CL]Exploring multi-task multi-lingual learning of transformer models for hate speech and offensive speech identification in social media
Sudhanshu Mishra, Shivangi Prasad, Shubhanshu Mishra
http://arxiv.org/abs/2101.11155v1
• [cs.CL]Fine-Grained Named Entity Typing over Distantly Supervised Data via Refinement in Hyperbolic Space
Muhammad Asif Ali, Yifang Sun, Bing Li, Wei Wang
http://arxiv.org/abs/2101.11212v1
• [cs.CL]First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
Benjamin Muller, Yanai Elazar, Benoît Sagot, Djamé Seddah
http://arxiv.org/abs/2101.11109v1
• [cs.CL]How to Evaluate a Summarizer: Study Design and Statistical An
1000
alysis for Manual Linguistic Quality Evaluation
Julius Steen, Katja Markert
http://arxiv.org/abs/2101.11298v1
• [cs.CL]Inheritance-guided Hierarchical Assignment for Clinical Automatic Diagnosis
Yichao Du, Pengfei Luo, Xudong Hong, Tong Xu, Zhe Zhang, Chao Ren, Yi Zheng, Enhong Chen
http://arxiv.org/abs/2101.11374v1
• [cs.CL]Joint Coreference Resolution and Character Linkingfor Multiparty Conversation
Jiaxin Bai, Hongming Zhang, Yangqiu Song, Kun Xu
http://arxiv.org/abs/2101.11204v1
• [cs.CL]KoreALBERT: Pretraining a Lite BERT Model for Korean Language Understanding
Hyunjae Lee, Jaewoong Yoon, Bonggyu Hwang, Seongho Joe, Seungjai Min, Youngjune Gwon
http://arxiv.org/abs/2101.11363v1
• [cs.CL]LSOIE: A Large-Scale Dataset for Supervised Open Information Extraction
Jacob Solawetz, Stefan Larson
http://arxiv.org/abs/2101.11177v1
• [cs.CL]Language Modelling as a Multi-Task Problem
Lucas Weber, Jaap Jumelet, Elia Bruni, Dieuwke Hupkes
http://arxiv.org/abs/2101.11287v1
• [cs.CL]Low Resource Recognition and Linking of Biomedical Concepts from a Large Ontology
Sunil Mohan, Rico Angell, Nick Monath, Andrew McCallum
http://arxiv.org/abs/2101.10587v2
• [cs.CL]Medical Segment Coloring of Clinical Notes
Maha Alkhairy
http://arxiv.org/abs/2101.11477v1
• [cs.CL]Meta-Learning for Effective Multi-task and Multilingual Modelling
Ishan Tarunesh, Sushil Khyalia, Vishwajeet Kumar, Ganesh Ramakrishnan, Preethi Jyothi
http://arxiv.org/abs/2101.10368v2
• [cs.CL]Multilingual and cross-lingual document classification: A meta-learning approach
Niels van der Heijden, Helen Yannakoudakis, Pushkar Mishra, Ekaterina Shutova
http://arxiv.org/abs/2101.11302v1
• [cs.CL]Muppet: Massive Multi-task Representations with Pre-Finetuning
Armen Aghajanyan, Anchit Gupta, Akshat Shrivastava, Xilun Chen, Luke Zettlemoyer, Sonal Gupta
http://arxiv.org/abs/2101.11038v1
• [cs.CL]Named Entity Recognition in the Style of Object Detection
Bing Li
http://arxiv.org/abs/2101.11122v1
• [cs.CL]Neural Sentence Ordering Based on Constraint Graphs
Yutao Zhu, Kun Zhou, Jian-Yun Nie, Shengchao Liu, Zhicheng Dou
http://arxiv.org/abs/2101.11178v1
• [cs.CL]On the Evolution of Syntactic Information Encoded by BERT’s Contextualized Representations
Laura Perez-Mayos, Roberto Carlini, Miguel Ballesteros, Leo Wanner
http://arxiv.org/abs/2101.11492v1
• [cs.CL]Open-domain Topic Identification of Out-of-domain Utterances using Wikipedia
A. Augustin, A. Papangelis, M. Kotti, P. Vougiouklis, J. Hare, N. Braunschweiler
http://arxiv.org/abs/2101.11134v1
• [cs.CL]PPT: Parsimonious Parser Transfer for Unsupervised Cross-Lingual Adaptation
Kemal Kurniawan, Lea Frermann, Philip Schulz, Trevor Cohn
http://arxiv.org/abs/2101.11216v1
• [cs.CL]Recent Trends in Named Entity Recognition (NER)
Arya Roy
http://arxiv.org/abs/2101.11420v1
• [cs.CL]SkillNER: Mining and Mapping Soft Skills from any Text
Silvia Fareri, Nicola Melluso, Filippo Chiarello, Gualtiero Fantoni
http://arxiv.org/abs/2101.11431v1
• [cs.CL]Summarising Historical Text in Modern Languages
Xutan Peng, Yi Zheng, Chenghua Lin, Advaith Siddharthan
http://arxiv.org/abs/2101.10759v2
• [cs.CL]Towards Robustness to Label Noise in Text Classification via Noise Modeling
Siddhant Garg, Goutham Ramakrishnan, Varun Thumb
1000
e
http://arxiv.org/abs/2101.11214v1
• [cs.CL]Transformer Based Deliberation for Two-Pass Speech Recognition
Ke Hu, Ruoming Pang, Tara N. Sainath, Trevor Strohman
http://arxiv.org/abs/2101.11577v1
• [cs.CL]Triangular Bidword Generation for Sponsored Search Auction
Zhenqiao Song, Jiaze Chen, Hao Zhou, Lei Li
http://arxiv.org/abs/2101.11349v1
• [cs.CL]VisualMRC: Machine Reading Comprehension on Document Images
Ryota Tanaka, Kyosuke Nishida, Sen Yoshida
http://arxiv.org/abs/2101.11272v1
• [cs.CR]Defenses Against Multi-Sticker Physical Domain Attacks on Classifiers
Xinwei Zhao, Matthew C. Stamm
http://arxiv.org/abs/2101.11060v1
• [cs.CR]Equivalence of Non-Perfect Secret Sharing and Symmetric Private Information Retrieval with General Access Structure
Seunghoan Song, Masahito Hayashi
http://arxiv.org/abs/2101.11194v1
• [cs.CV]Arbitrary-Oriented Ship Detection through Center-Head Point Extraction
Feng Zhang, Xueying Wang, Shilin Zhou, Yingqian Wang
http://arxiv.org/abs/2101.11189v1
• [cs.CV]Automated Crop Field Surveillance using Computer Vision
Tejas Atul Khare, Anuradha C. Phadke
http://arxiv.org/abs/2101.11217v1
• [cs.CV]Automatic Comic Generation with Stylistic Multi-page Layouts and Emotion-driven Text Balloon Generation
Xin Yang, Zongliang Ma, Letian Yu, Ying Cao, Baocai Yin, Xiaopeng Wei, Qiang Zhang, Rynson W. H. Lau
http://arxiv.org/abs/2101.11111v1
• [cs.CV]Automatic image annotation base on Naive Bayes and Decision Tree classifiers using MPEG-7
Jafar Majidpour, Samer Kais Jameel
http://arxiv.org/abs/2101.11222v1
• [cs.CV]Bottleneck Transformers for Visual Recognition
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, Ashish Vaswani
http://arxiv.org/abs/2101.11605v1
• [cs.CV]CPTR: Full Transformer Network for Image Captioning
Wei Liu, Sihan Chen, Longteng Guo, Xinxin Zhu, Jing Liu
http://arxiv.org/abs/2101.10804v2
• [cs.CV]Controlling by Showing: i-Mimic: A Video-based Method to Control Robotic Arms
Debarati B. Chakraborty, Mukesh Sharma, Bhaskar Vijay
http://arxiv.org/abs/2101.11451v1
• [cs.CV]Convolutional Neural Network-Based Age Estimation Using B-Mode Ultrasound Tongue Image
Kele Xu, Tamas Gábor Csapó, Ming Feng
http://arxiv.org/abs/2101.11245v1
• [cs.CV]Deep Image Retrieval: A Survey
Wei Chen, Yu Liu, Weiping Wang, Erwin Bakker, Theodoros Georgiou, Paul Fieguth, Li Liu, Michael S. Lew
http://arxiv.org/abs/2101.11282v1
• [cs.CV]Deep Video Inpainting Detection
Peng Zhou, Ning Yu, Zuxuan Wu, Larry S. Davis, Abhinav Shrivastava, Ser-Nam Lim
http://arxiv.org/abs/2101.11080v1
• [cs.CV]DeepOIS: Gyroscope-Guided Deep Optical Image Stabilizer Compensation
Haipeng Li, Shuaicheng Liu, Jue Wang
http://arxiv.org/abs/2101.11183v1
• [cs.CV]Detecting Adversarial Examples by Input Transformations, Defense Perturbations, and Voting
Federico Nesti, Alessandro Biondi, Giorgio Buttazzo
http://arxiv.org/abs/2101.11466v1
• [cs.CV]Detecting Deepfake Videos Using Euler Video Magnification
Rashmiranjan Das, Gaurav Negi, Alan F. Smeaton
http://arxiv.org/abs/2101.11563v1
• [cs.CV]EPIC-Survival: End-to-end Part Inferred Clustering for Survival Analysis, Featuring Prognostic Stratification Boosting
Hassan Muhammad, Chensu Xie, Carlie S. Sigel, Michael Doukas, Lindsay Alpert, Thomas J. Fuchs
http://arxiv.org/abs/2101.11085v1
• [cs.CV]Edge-Labeling based Directed Gated Graph Network for Few-shot Learning
Peixiao Zheng, Xin Guo, Lin Qi
http://arxiv.org/abs/2101.11299v1
• [cs.CV]Effects of Image Size on Deep Learning
Olivier Rukundo
http://arxiv.org/abs/2101.11508v1
• [cs.CV]Efficient Video Summarization Framework using EEG and Eye-tracking Signals
Sai Sukruth Bezugam, Swatilekha Majumdar, Chetan Ralekar, Tapan Kumar Gandhi
http://arxiv.org/abs/2101.11249v1
• [cs.CV]GaitGraph: Graph Convolutional Network for Skeleton-Based Gait Recognition
Torben Teepe, Ali Khan, Johannes Gilg, Fabian Herzog, Stefan Hörmann, Gerhard Rigoll
http://arxiv.org/abs/2101.11228v1
• [cs.CV]Generative Multi-Label Zero-Shot Learning
Akshita Gupta, Sanath Narayan, Salman Khan, Fahad Shahbaz Khan, Ling Shao, Joost van de Weijer
http://arxiv.org/abs/2101.11606v1
• [cs.CV]Im2Mesh GAN: Accurate 3D Hand Mesh Recovery from a Single RGB Image
Akila Pemasiri, Kien Nguyen Thanh, Sridha Sridharan, Clinton Fookes
http://arxiv.org/abs/2101.11239v1
• [cs.CV]Multi-Hypothesis Pose Networks: Rethinking Top-Down Pose Estimation
Rawal Khirodkar, Visesh Chari, Amit Agrawal, Ambrish Tyagi
http://arxiv.org/abs/2101.11223v1
• [cs.CV]NTU60-X: Towards Skeleton-based Recognition of Subtle Human Actions
Anirudh Thatipelli, Neel Trivedi, Ravi Kiran Sarvadevabhatla
http://arxiv.org/abs/2101.11529v1
• [cs.CV]New Algorithms for Computing Field of Vision over 2D Grids
Evan R. M. Debenham, Roberto Solis-Oba
http://arxiv.org/abs/2101.11002v1
• [cs.CV]On the Importance of Capturing a Sufficient Diversity of Perspective for the Classification of micro-PCBs
Adam Byerly, Tatiana Kalganova, Anthony J. Grichnik
http://arxiv.org/abs/2101.11164v1
• [cs.CV]Puzzle-CAM: Improved localization via matching partial and full features
Sanhyun Jo, In-Jae Yu
http://arxiv.org/abs/2101.11253v1
• [cs.CV]Reciprocal Landmark Detection and Tracking with Extremely Few Annotations
Jianzhe Lin, Ghazal Sahebzamani, Christina Luong, Fatemeh Taheri Dezaki, Mohammad Jafari, Purang Abolmaesumi, Teresa Tsang
http://arxiv.org/abs/2101.11224v1
• [cs.CV]ResLT: Residual Learning for Long-tailed Recognition
Jiequan Cui, Shu Liu, Zhuotao Tian, Zhisheng Zhong, Jiaya Jia
http://arxiv.org/abs/2101.10633v2
• [cs.CV]Revisiting Contrastive Learning for Few-Shot Classification
Orchid Majumder, Avinash Ravichandran, Subhransu Maji, Marzia Polito, Rahul Bhotika, Stefano Soatto
http://arxiv.org/abs/2101.11058v1
• [cs.CV]Scheduled Sampling in Vision-Language Pretraining with Decoupled Encoder-Decoder Network
Yehao Li, Yingwei Pan, Ting Yao, Jingwen Chen, Tao Mei
http://arxiv.org/abs/2101.11562v1
• [cs.CV]Self-Calibrating Active Binocular Vision via Active Efficient Coding with Deep Autoencoders
Charles Wilmot, Bertram E. Shi, Jochen Triesch
http://arxiv.org/abs/2101.11391v1
• [cs.CV]Shape or Texture: Understanding Discriminative Features in CNNs
Md Amirul Islam, Matthew Kowal, Patrick Esser, Sen Jia, Bjorn Ommer, Konstantinos G. Derpanis, Neil Bruce
http://arxiv.org/abs/2101.11604v1
• [cs.CV]Spatial-Channel Transformer Network for Trajectory Prediction on the Traffic Scenes
Jingwen Zhao, Xuanpeng Li, Qifan Xue, Weigong Zhang
http://arxiv.org/abs/2101.11472v1
• [cs.CV]Syntactically Guided Generative Embeddings for Zero-Shot Skeleton Action Recognition
Pranay Gupta, Divyanshu Sharma, Ravi Kiran Sarvadevabhatla
http://arxiv.org/abs/2101.11530v1
• [cs.CV]The Effect of Class Definitions on the Transferability of Adversarial Attacks Against Forensic CNNs
Xinwei Zhao, Matthew C. Stamm
http://arxiv.org/abs/2101.11081v1
• [cs.CV]TorchPRISM: Principal Image Sections Mapping, a novel method for Convolutional Neural Network features visualization
Tomasz Szandala
http://arxiv.org/abs/2101.11266v1
• [cs.CV]Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search
Yibo Yang, Shan You, Hongyang Li, Fei Wang, Chen Qian, Zhouchen Lin
http://arxiv.org/abs/2101.11342v1
• [cs.CV]Utilizing Uncertainty Estimation in Deep Learning Segmentation of Fluorescence Microscopy Images with Missing Markers
Alvaro Gomariz, Raphael Egli, Tiziano Portenier, César Nombela-Arrieta, Orcun Goksel
http://arxiv.org/abs/2101.11476v1
• [cs.CV]e-ACJ: Accurate Junction Extraction For Event Cameras
Zhihao Liu, Yuqian Fu
http://arxiv.org/abs/2101.11251v1
• [cs.CY]Hiding Behind Machines: When Blame Is Shifted to Artificial Agents
Till Feier, Jan Gogoll, Matthias Uhl
http://arxiv.org/abs/2101.11465v1
• [cs.CY]Low-skilled Occupations Face the Highest Re-skilling Pressure
Di Tong, Lingfei Wu, James Allen Evans
http://arxiv.org/abs/2101.11505v1
• [cs.CY]On Small-World Networks: Survey and Properties Analysis
Alaa Eddin Alchalabi
http://arxiv.org/abs/2101.11191v1
• [cs.CY]Pano: Engaging with News using Moral Framing towards Bridging Ideological Divides
Jessica Wang, Amy Zhang, David Karger
http://arxiv.org/abs/2101.11231v1
• [cs.CY]Re-imagining Algorithmic Fairness in India and Beyond
Nithya Sambasivan, Erin Arnesen, Ben Hutchinson, Tulsee Doshi, Vinodkumar Prabhakaran
http://arxiv.org/abs/2101.09995v2
• [cs.CY]The Work of Art in an Age of Mechanical Generation
Steven J. Frank
http://arxiv.org/abs/2101.11587v1
• [cs.DC]C-for-Metal: High Performance SIMD Programming on Intel GPUs
Guei-Yuan Lueh, Kaiyu Chen, Gang Chen, Joel Fuentes, Wei-Yu Chen, Fangwen Fu, Hong Jiang, Hongzheng Li, Daniel Rhee
http://arxiv.org/abs/2101.11049v1
• [cs.DC]RTGPU: Real-Time GPU Scheduling of Hard Deadline Parallel Tasks with Fine-Grain Utilization
An Zou, Jing Li, Christopher D. Gill, Xuan Zhang
http://arxiv.org/abs/2101.10463v2
• [cs.DC]Response-Time Analysis and Optimization for Probabilistic Conditional Parallel DAG Tasks
Niklas Ueter, Mario Günzel, Jian-Jia Chen
http://arxiv.org/abs/2101.11053v1
• [cs.DC]Self-stabilizing Algorithm for Maximal Distance-2 Independent Set
Badreeddine Benregui, Hamouma Moumen, Soheila Bouam, Chafik Arar
http://arxiv.org/abs/2101.11126v1
• [cs.DM]Logical-Combinatorial Approaches in Dynamic Recognition Problems
L. Aslanyan, V. Krasnoproshin, V. Ryazanov, H. Sahakyan
http://arxiv.org/abs/2101.11066v1
• [cs.DS]A Neighborhood-preserving Graph Summarization
Abd Errahmane Kiouche, Julien Baste, Mohammed Haddad, Hamida Seba
http://arxiv.org/abs/2101.11559v1
• [cs.GT]A Balance for Fairness: Fair Distribution Utilising Physics in Games of Characteristic Function Form
Song-Ju Kim, Taiki Takahashi, Kazuo Sano
http://arxiv.org/abs/2101.11496v1
• [cs.HC]Developing for personalised learning: the long road from educational objectives to development and feedback
George Tsatiris, Kostas Karpouzis
http://arxiv.org/abs/2101.11333v1
• [cs.IR]Advances and Challenges in Conversational Recommender Systems: A Survey
Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke, Tat-Seng Chua
http://arxiv.org/abs/2101.09459v3
• [cs.IR]Investigating Diffusion of Scientific Knowledge on Twitter: A Study of Topic Networks of Opioid Publications
Robin Haunschild, Lutz Bornmann, Devendra Potnis, Iman Tahamtan
http://arxiv.org/abs/2101.11483v1
• [cs.IR]Mining the Stars: Learning Quality Ratings with User-facing Explanations for Vacation Rentals
Anastasiia Kornilova, Lucas Bernardi
http://arxiv.org/abs/2101.10737v2
• [cs.IR]One Model to Serve All: Star Topology Adaptive Recommender for Multi-Domain CTR Prediction
Xiang-Rong Sheng, Liqin Zhao, Guorui Zhou, Xinyao Ding, Binding Dai, Qiang Luo, Siran Yang, Jingshan Lv, Chi Zhang, Xiaoqiang Zhu
http://arxiv.org/abs/2101.11427v1
• [cs.IR]Powering COVID-19 community Q&A with Curated Side Information
Manisha Verma, Kapil Thadani, Shaunak Mishra
http://arxiv.org/abs/2101.11556v1
• [cs.IT]A Coding Theory Perspective on MultiplexedMolecular Profiling of Biological Tissues
Luca D’Alessio, Litian Liu, Ken Duffy, Yonina C. Eldar, Muriel Medard, Mehrtash Babadi
http://arxiv.org/abs/2101.11123v1
• [cs.IT]Bayes-Optimal Convolutional AMP
Keigo Takeuchi
http://arxiv.org/abs/2101.11185v1
• [cs.IT]Constructing new APN functions through relative trace functions
Lijing Zheng, Haibin Kan, Yanjun Li, Jie Peng, Deng Tang
http://arxiv.org/abs/2101.11535v1
• [cs.IT]Coverage Analysis of Broadcast Networks with Users Having Heterogeneous Content/Advertisement Preferences
Kanchan Chaurasia, Reena Sahu, Abhishek Gupta
http://arxiv.org/abs/2101.11356v1
• [cs.IT]Improved algorithms for non-adaptive group testing with consecutive positives
Thach V. Bui, Mahdi Cheraghchi, Thuc D. Nguyen
http://arxiv.org/abs/2101.11294v1
• [cs.IT]Joint Active and Passive Beamforming for Intelligent Reflecting Surface Aided Multiuser MIMO Communications
Xingyu Zhao, Tian Lin, Yu Zhu
http://arxiv.org/abs/2101.10071v2
• [cs.IT]Joint Source-Channel Coding for Semantics-Aware Grant-Free Radio Access in IoT Fog Networks
Johannes Dommel, Zoran Utkovski, Osvaldo Simeone, Slawomir Stanczak
http://arxiv.org/abs/2101.11309v1
• [cs.IT]Non-Asymptotic Converse Bounds Via Auxiliary Channels
Ioannis Papoutsidakis, Robert J. Piechocki, Angela Doufexi
http://arxiv.org/abs/2101.11490v1
• [cs.IT]Nonconvex Regularized Gradient Projection Sparse Reconstruction for Massive MIMO Channel Estimation
Pengxia Wu, Julian Cheng
http://arxiv.org/abs/2101.11091v1
• [cs.IT]On Massive IoT Connectivity with Temporally-Correlated User Activity
Qipeng Wang, Liang Liu, Shuowen Zhang, Francis C. M. Lau
http://arxiv.org/abs/2101.11344v1
• [cs.IT]On the Automorphism Group of Polar Codes
Marvin Geiselhart, Ahmed Elkelesh, Moustafa Ebada, Sebastian Cammerer, Stephan ten Brink
http://arxiv.org/abs/2101.09679v2
• [cs.IT]Rate Splitting Multiple Access for Multi-Antenna Multi-Carrier Joint Communications and Jamming
Onur Dizdar, Bruno Clerckx
http://arxiv.org/abs/2101.11318v1
• [cs.IT]Real-time oblivious erasure correction with linear time decoding and constant feedback
Shashwat Silas
http://arxiv.org/abs/2101.11136v1
• [cs.IT]Sequential decoding of high-rate Reed-Muller codes
Mikhail Kamenev
http://arxiv.org/abs/2101.11328v1
• [cs.IT]Streaming Erasure Codes over the Multiple Access Relay Channel
Gustavo Kasper Facenda, Elad Domanovitz, Ashish Khisti, Wai-Tian Tan, John Apostolopoulos
http://arxiv.org/abs/2101.11117v1
• [cs.IT]Strengthened Cutset Upper Bounds on the Capacity of the Relay Channel and Applications
Abbas El Gamal, Amin Gohari, Chandra Nair
http://arxiv.org/abs/2101.11139v1
• [cs.IT]Super-Resolution for Doubly-Dispersive Channel Estimation
Robert Beinert, Peter Jung, Gabriele Steidl, Tom Szollmann
http://arxiv.org/abs/2101.11544v1
• [cs.IT]The fundamental limits of sparse linear regression with sublinear sparsity
Lan V. Truong
http://arxiv.org/abs/2101.11156v1
• [cs.IT]Variational Encoders and Autoencoders : Information-theoretic Inference and Closed-form Solutions
Karthik Duraisamy
http://arxiv.org/abs/2101.11428v1
• [cs.LG]A Note on the Representation Power of GHHs
Zhou Lu
http://arxiv.org/abs/2101.11286v1
• [cs.LG]Accuracy and Privacy Evaluations of Collaborative Data Analysis
Akira Imakura, Anna Bogdanova, Takaya Yamazoe, Kazumasa Omote, Tetsuya Sakurai
http://arxiv.org/abs/2101.11144v1
• [cs.LG]Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning
Haibo Yang, Minghong Fang, Jia Liu
http://arxiv.org/abs/2101.11203v1
• [cs.LG]Adaptivity without Compromise: A Momentumized, Adaptive, Dual Averaged Gradient Method for Stochastic Optimization
Aaron Defazio, Samy Jelassi
http://arxiv.org/abs/2101.11075v1
• [cs.LG]Adversarial Attacks on Uncertainty Enable Active Learning for Neural Network Potentials
Daniel Schwalbe-Koda, Aik Rui Tan, Rafael Gómez-Bombarelli
http://arxiv.org/abs/2101.11588v1
• [cs.LG]Adversaries in Online Learning Revisited: with applications in Robust Optimization and Adversarial training
Sebastian Pokutta, Huan Xu
http://arxiv.org/abs/2101.11443v1
• [cs.LG]An explainable Transformer-based deep learning model for the prediction of incident heart failure
Shishir Rao, Yikuan Li, Rema Ramakrishnan, Abdelaali Hassaine, Dexter Canoy, John Cleland, Thomas Lukasiewicz, Gholamreza Salimi-Khorshidi, Kazem Rahimi
http://arxiv.org/abs/2101.11359v1
• [cs.LG]Autoencoder-based Condition Monitoring and Anomaly Detection Method for Rotating Machines
Sabtain Ahmad, Kevin Styp-Rekowski, Sasho Nedelkoski, Odej Kao
http://arxiv.org/abs/2101.11539v1
• [cs.LG]Average Localised Proximity: a new data descriptor with good default one-class classification performance
Oliver Urs Lenz, Daniel Peralta, Chris Cornelis
http://arxiv.org/abs/2101.11037v1
• [cs.LG]Bayesian Nested Neural Networks for Uncertainty Calibration and Adaptive Compression
Yufei Cui, Ziquan Liu, Qiao Li, Yu Mao, Antoni B. Chan, Chun Jason Xue
http://arxiv.org/abs/2101.11353v1
• [cs.LG]Combat Data Shift in Few-shot Learning with Knowledge Graph
Yongchun zhu, Fuzhen Zhuang, Xiangliang Zhang, Zhiyuan Qi, Zhiping Shi, Qing He
http://arxiv.org/abs/2101.11354v1
• [cs.LG]Decision Machines: Interpreting Decision Tree as a Model Combination Method
Jinxiong Zhang
http://arxiv.org/abs/2101.11347v1
• [cs.LG]Detecting discriminatory risk through data annotation based on Bayesian inferences
Elena Beretta, Antonio Vetrò, Bruno Lepri, Juan Carlos De Martin
http://arxiv.org/abs/2101.11358v1
• [cs.LG]Efficient Graph Deep Learning in TensorFlow with tf_geometric
Jun Hu, Shengsheng Qian, Quan Fang, Youze Wang, Quan Zhao, Huaiwen Zhang, Changsheng Xu
http://arxiv.org/abs/2101.11552v1
• [cs.LG]Evolutionary Generative Adversarial Networks with Crossover Based Knowledge Distillation
Junjie Li, Junwei Zhang, Xiaoyu Gong, Shuai Lü
http://arxiv.org/abs/2101.11186v1
• [cs.LG]FedH2L: Federated Learning with Model and Statistical Heterogeneity
Yiying Li, Wei Zhou, Huaimin Wang, Haibo Mi, Timothy M. Hospedales
http://arxiv.org/abs/2101.11296v1
• [cs.LG]Graph Neural Network for Traffic Forecasting: A Survey
Weiwei Jiang, Jiayun Luo
http://arxiv.org/abs/2101.11174v1
• [cs.LG]Improving Graph Representation Learning by Contrastive Regularization
Kaili Ma, Haochen Yang, Han Yang, Tatiana Jin, Pengfei Chen, Yongqiang Chen, Barakeel Fanseu Kamhoua, James Cheng
http://arxiv.org/abs/2101.11525v1
• [cs.LG]Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond
Risheng Liu, Jiaxin Gao, Jin Zhang, Deyu Meng, Zhouchen Lin
http://arxiv.org/abs/2101.11517v1
• [cs.LG]Learning Abstract Representations through Lossy Compression of Multi-Modal Signals
Charles Wilmot, Jochen Triesch
http://arxiv.org/abs/2101.11376v1
• [cs.LG]Learning Non-linear Wavelet Transformation via Normalizing Flow
Shuo-Hui Li
http://arxiv.org/abs/2101.11306v1
• [cs.LG]Meta Adversarial Training
Jan Hendrik Metzen, Nicole Finnie, Robin Hutmacher
http://arxiv.org/abs/2101.11453v1
• [cs.LG]OffCon: What is state of the art anyway?
Philip J. Ball, Stephen J. Roberts
http://arxiv.org/abs/2101.11331v1
• [cs.LG]On the Interpretability of Deep Learning Based Models for Knowledge Tracing
Xinyi Ding, Eric C. Larson
http://arxiv.org/abs/2101.11335v1
• [cs.LG]Partition of unity networks: deep hp-approximation
Kookjin Lee, Nathaniel A. Trask, Ravi G. Patel, Mamikon A. Gulian, Eric C. Cyr
http://arxiv.org/abs/2101.11256v1
• [cs.LG]Pitfalls of Assessing Extracted Hierarchies for Multi-Class Classification
Pablo del Moral, Slawomir Nowaczyk, Anita Sant’Anna, Sepideh Pashami
http://arxiv.org/abs/2101.11095v1
• [cs.LG]Property Inference From Poisoning
Melissa Chase, Esha Ghosh, Saeed Mahloujifar
http://arxiv.org/abs/2101.11073v1
• [cs.LG]Safe Multi-Agent Reinforcement Learning via Shielding
Ingy Elsayed-Aly, Suda Bharadwaj, Christopher Amato, Rüdiger Ehlers, Ufuk Topcu, Lu Feng
http://arxiv.org/abs/2101.11196v1
• [cs.LG]Similarity of Classification Tasks
Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro
http://arxiv.org/abs/2101.11201v1
• [cs.LG]Supervised Tree-Wasserstein Distance
Yuki Takezawa, Ryoma Sato, Makoto Yamada
http://arxiv.org/abs/2101.11520v1
• [cs.LG]The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors
William H. Guss, Mario Ynocente Castro, Sam Devlin, Brandon Houghton, Noboru Sean Kuno, Crissman Loomis, Stephanie Milani, Sharada Mohanty, Keisuke Nakata, Ruslan Salakhutdinov, John Schulman, Shinya Shiroshita, Nicholay Topin, Avinash Ummadisingu, Oriol Vinyals
http://arxiv.org/abs/2101.11071v1
• [cs.LG]Tropical Support Vector Machines: Evaluations and Extension to Function Spaces
Ruriko Yoshida, Misaki Takamori, Hideyuki Matsumoto, Keiji Miura
http://arxiv.org/abs/2101.11531v1
• [cs.LG]Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection
Ece Calikus, Slawomir Nowaczyk, Mohamed-Rafik Bouguelia, Onur Dikmen
http://arxiv.org/abs/2101.11560v1
• [cs.MA]Modelling the Impact of Scandals: the case of the 2017 French Presidential Election
Yassine Bouachrine, Carole Adam
http://arxiv.org/abs/2101.11548v1
• [cs.MA]Multi-agent simulation of voter’s behaviour
Albin Soutif, Carole Adam, Sylvain Bouveret
http://arxiv.org/abs/2101.11538v1
• [cs.MS]FDApy: a Python package for functional data
Steven Golovkine
http://arxiv.org/abs/2101.11003v1
• [cs.NE]Particle Swarm Optimization: Fundamental Study and its Application to Optimization and to Jetty Scheduling Problems
Johann Sienz, Mauro S. Innocente
http://arxiv.org/abs/2101.11096v1
• [cs.NE]Pseudo-Adaptive Penalization to Handle Constraints in Particle Swarm Optimizers
Mauro S. Innocente, Johann Sienz
http://arxiv.org/abs/2101.11441v1
• [cs.NE]Scale-free Network-based Differential Evolution
Yang Yu, Shangce Gao, MengChu Zhou, Yirui Wang, Zhenyu Lei, Tengfei Zhang, Jiahai Wang
http://arxiv.org/abs/2101.11275v1
• [cs.NI]Cloud based VANET Simulator (CVANETSIM)
Mohammad Mukhtaruzzaman, Mohammed Atiquzzaman
http://arxiv.org/abs/2101.11147v1
• [cs.PL]Compositional Semantics for Probabilistic Programs with Exact Conditioning
Dario Stein, Sam Staton
http://arxiv.org/abs/2101.11351v1
• [cs.RO]ADMM-based Adaptive Sampling Strategy for Nonholonomic Mobile Robotic Sensor Networks
Viet-Anh Le, Linh Nguyen, Truong X. Nghiem
http://arxiv.org/abs/2101.10500v2
• [cs.RO]An Integrated Localisation, Motion Planning and Obstacle Avoidance Algorithm in Belief Space
Antony Thomas, Fulvio Mastrogiovanni, Marco Baglietto
http://arxiv.org/abs/2101.11566v1
• [cs.RO]Autonomous Off-road Navigation over Extreme Terrains with Perceptually-challenging Conditions
Rohan Thakker, Nikhilesh Alatur, David D. Fan, Jesus Tordesillas, Michael Paton, Kyohei Otsu, Olivier Toupet, Ali-akbar Agha-mohammadi
http://arxiv.org/abs/2101.11110v1
• [cs.RO]Dexterous Manipulation Primitives for the Real Robot Challenge
Claire Chen, Krishnan Srinivasan, Jeffrey Zhang, Junwu Zhang
http://arxiv.org/abs/2101.11597v1
• [cs.RO]Exact and Approximate Heterogeneous Bayesian Decentralized Data Fusion
Ofer Dagan, Nisar R. Ahmed
http://arxiv.org/abs/2101.11116v1
• [cs.RO]Non-Monotone Energy-Aware Information Gathering for Heterogeneous Robot Teams
Xiaoyi Cai, Brent Schlotfeldt, Kasra Khosoussi, Nikolay Atanasov, George J. Pappas, Jonathan P. How
http://arxiv.org/abs/2101.11093v1
• [cs.RO]Online Extrinsic Calibration based on Per-Sensor Ego-Motion Using Dual Quaternions
Markus Horn, Thomas Wodtko, Michael Buchholz, Klaus Dietmayer
http://arxiv.org/abs/2101.11440v1
• [cs.SE]Can Offline Testing of Deep Neural Networks Replace Their Online Testing?
Fitash Ul Haq, Donghwan Shin, Shiva Nejati, Lionel Briand
http://arxiv.org/abs/2101.11118v1
• [cs.SI]Adversarial Active Learning based Heterogeneous Graph Neural Network for Fake News Detection
Yuxiang Ren, Bo Wang, Jiawei Zhang, Yi Chang
http://arxiv.org/abs/2101.11206v1
• [cs.SI]Deriving the Traveler Behavior Information from Social Media: A Case Study in Manhattan with Twitter
Zhenhua Zhang
http://arxiv.org/abs/2101.11482v1
• [cs.SI]Launchers and Targets in Social Networks
Pedro Martins, Filipa Alarcão Martins
http://arxiv.org/abs/2101.11337v1
• [cs.SI]Measuring Law Over Time: A Network Analytical Framework with an Application to Statutes and Regulations in the United States and Germany
Corinna Coupette, Janis Beckedorf, Dirk Hartung, Michael Bommarito, Daniel Martin Katz
http://arxiv.org/abs/2101.11284v1
• [cs.SI]Modeling opinion leader’s role in the diffusion of innovation
Natasa Vodopivec, Carole Adam, Jean-Pierre Chanteau
http://arxiv.org/abs/2101.11260v1
• [cs.SI]REFORM: Fast and Adaptive Solution for Subteam Replacement
Zhaoheng Li, Xinyu Pi, Mingyuan Wu, Hanghang Tong
http://arxiv.org/abs/2101.11070v1
• [cs.SI]Why polls fail to predict elections
Zhenkun Zhou, Matteo Serafino, Luciano Cohan, Guido Caldarelli, Hernan A. Makse
http://arxiv.org/abs/2101.11389v1
• [econ.EM]Predictive Quantile Regression with Mixed Roots and Increasing Dimensions
Rui Fan, Ji Hyung Lee, Youngki Shin
http://arxiv.org/abs/2101.11568v1
• [eess.IV]An Interpretation of Regularization by Denoising and its Application with the Back-Projected Fidelity Term
Einav Yogev-Ofer, Tom Tirer, Raja Giryes
http://arxiv.org/abs/2101.11599v1
• [eess.IV]Automatic Segmentation of Gross Target Volume of Nasopharynx Cancer using Ensemble of Multiscale Deep Neural Networks with Spatial Attention
Haochen Mei, Wenhui Lei, Ran Gu, Shan Ye, Zhengwentai Sun, Shichuan Zhang, Guotai Wang
http://arxiv.org/abs/2101.11254v1
• [eess.IV]Boosting Segmentation Performance across datasets using histogram specification with application to pelvic bone segmentation
Prabhakara Subramanya Jois, Aniketh Manjunath, Thomas Fevens
http://arxiv.org/abs/2101.11135v1
• [eess.IV]Synthetic Generation of Three-Dimensional Cancer Cell Models from Histopathological Images
Yoav Alon, Huiyu Zhou
http://arxiv.org/abs/2101.11600v1
• [eess.SP]Anti-Aliasing Add-On for Deep Prior Seismic Data Interpolation
Francesco Picetti, Vincenzo Lipari, Paolo Bestagini, Stefano Tubaro
http://arxiv.org/abs/2101.11361v1
• [eess.SP]Statistical guided-waves-based SHM via stochastic non-parametric time series models
Ahmad Amer, Fotis Kopsaftopoulos
http://arxiv.org/abs/2101.11208v1
• [eess.SY]GymD2D: A Device-to-Device Underlay Cellular Offload Evaluation Platform
David Cotton, Zenon Chaczko
http://arxiv.org/abs/2101.11188v1
• [hep-ex]A Convolutional Neural Network based Cascade Reconstruction for the IceCube Neutrino Observatory
R. Abbasi, M. Ackermann, J. Adams, J. A. Aguilar, M. Ahlers, M. Ahrens, C. Alispach, A. A. Alves Jr., N. M. Amin, R. An, K. Andeen, T. Anderson, I. Ansseau, G. Anton, C. Argüelles, S. Axani, X. Bai, A. Balagopal V., A. Barbano, S. W. Barwick, B. Bastian, V. Basu, V. Baum, S. Baur, R. Bay, J. J. Beatty, K. -H. Becker, J. Becker Tjus, C. Bellenghi, S. BenZvi, D. Berley, E. Bernardini, D. Z. Besson, G. Binder, D. Bindig, E. Blaufuss, S. Blot, S. Böser, O. Botner, J. Böttcher, E. Bourbeau, J. Bourbeau, F. Bradascio, J. Braun, S. Bron, J. Brostean-Kaiser, A. Burgman, R. S. Busse, M. A. Campana, C. Chen, D. Chirkin, S. Choi, B. A. Clark, K. Clark, L. Classen, A. Coleman, G. H. Collin, J. M. Conrad, P. Coppin, P. Correa, D. F. Cowen, R. Cross, P. Dave, C. De Clercq, J. J. DeLaunay, H. Dembinski, K. Deoskar, S. De Ridder, A. Desai, P. Desiati, K. D. de Vries, G. de Wasseige, M. de With, T. DeYoung, S. Dharani, A. Diaz, J. C. Díaz-Vélez, H. Dujmovic, M. Dunkman, M. A. DuVernois, E. Dvorak, T. Ehrhardt, P. Eller, R. Engel, J. Evans, P. A. Evenson, S. Fahey, A. R. Fazely, S. Fiedlschuster, A. T. Fienberg, K. Filimonov, C. Finley, L. Fischer, D. Fox, A. Franckowiak, E. Friedman, A. Fritz, P. Fürst, T. K. Gaisser, J. Gallagher, E. Ganster, S. Garrappa, L. Gerhardt, A. Ghadimi, C. Glaser, T. Glauch, T. Glüsenkamp, A. Goldschmidt, J. G. Gonzalez, S. Goswami, D. Grant, T. Grégoire, Z. Griffith, S. Griswold, M. Gündüz, C. Haack, A. Hallgren, R. Halliday, L. Halve, F. Halzen, M. Ha Minh, K. Hanson, J. Hardin, A. A. Harnisch, A. Haungs, S. Hauser, D. Hebecker, K. Helbing, F. Henningsen, E. C. Hettinger, S. Hickford, J. Hignight, C. Hill, G. C. Hill, K. D. Hoffman, R. Hoffmann, T. Hoinka, B. Hokanson-Fasig, K. Hoshina, F. Huang, M. Huber, T. Huber, K. Hultqvist, M. Hünnefeld, R. Hussain, S. In, N. Iovine, A. Ishihara, M. Jansson, G. S. Japaridze, M. Jeong, B. J. P. Jones, R. Joppe, D. Kang, W. Kang, X. Kang, A. Kappes, D. Kappesser, T. Karg, M. Karl, A. Karle, U. Katz, M. Kauer, M. Kellermann, J. L. Kelley, A. Kheirandish, J. Kim, K. Kin, T. Kintscher, J. Kiryluk, S. R. Klein, R. Koirala, H. Kolanoski, L. Köpke, C. Kopper, S. Kopper, D. J. Koskinen, P. Koundal, M. Kovacevich, M. Kowalski, K. Krings, G. Krückl, N. Kurahashi, A. Kyriacou, C. Lagunas Gualda, J. L. Lanfranchi, M. J. Larson, F. Lauber, J. P. Lazar, K. Leonard, A. Leszczyńska, Y. Li, Q. R. Liu, E. Lohfink, C. J. Lozano Mariscal, L. Lu, F. Lucarelli, A. Ludwig, W. Luszczak, Y. Lyu, W. Y. Ma, J. Madsen, K. B. M. Mahn, Y. Makino, P. Mallik, S. Mancina, I. C. Mari{ş}, R. Maruyama, K. Mase, F. McNally, K. Meagher, A. Medina, M. Meier, S. Meighen-Berger, J. Merz, J. Micallef, D. Mockler, G. Momenté, T. Montaruli, R. W. Moore, K. Morik, R. Morse, M. Moulai, R. Naab, R. Nagai, U. Naumann, J. Necker, L. V. Nguy{~{ê}}n, H. Niederhausen, M. U. Nisa, S. C. Nowicki, D. R. Nygren, A. Obertacke Pollmann, M. Oehler, A. Olivas, E. O’Sullivan, H. Pandya, D. V. Pankova, N. Park, G. K. Parker, E. N. Paudel, P. Peiffer, C. Pérez de los Heros, S. Philippen, D. Pieloth, S. Pieper, A. Pizzuto, M. Plum, Y. Popovych, A. Porcelli, M. Prado Rodriguez, P. B. Price, B. Pries, G. T. Przybylski, C. Raab, A. Raissi, M. Rameez, K. Rawlins, I. C. Rea, A. Rehman, R. Reimann, M. Renschler, G. Renzi, E. Resconi, S. Reusch, W. Rhode, M. Richman, B. Riedel, S. Robertson, G. Roellinghoff, M. Rongen, C. Rott, T. Ruhe, D. Ryckbosch, D. Rysewyk Cantu, I. Safa, S. E. Sanchez Herrera, A. Sandrock, J. Sandroos, M. Santander, S. Sarkar, S. Sarkar, K. Satalecka, M. Scharf, M. Schaufel, H. Schieler, P. Schlunder, T. Schmidt, A. Schneider, J. Schneider, F. G. Schröder, L. Schumacher, S. Sclafani, D. Seckel, S. Seunarine, A. Sharma, S. Shefali, M. Silva, B. Skrzypek, B. Smithers, R. Snihur, J. Soedingrekso, D. Soldin, G. M. Spiczak, C. Spiering, J. Stachurska, M. Stamatikos, T. Stanev, R. Stein, J. Stettner, A. Steuer, T. Stezelberger, R. G. Stokstad, T. Stürwald, T. Stuttard, G. W. Sullivan, I. Taboada, F. Tenholt, S. Ter-Antonyan, S. Tilav, F. Tischbein, K. Tollefson, L. Tomankova, C. Tönnis, S. Toscano, D. Tosi, A. Trettin, M. Tselengidou, C. F. Tung, A. Turcati, R. Turcotte, C. F. Turley, J. P. Twagirayezu, B. Ty, M. A. Unland Elorrieta, N. Valtonen-Mattila, J. Vandenbroucke, D. van Eijk, N. van Eijndhoven, D. Vannerom, J. van Santen, S. Verpoest, M. Vraeghe, C. Walck, A. Wallace, T. B. Watson, C. Weaver, A. Weindl, M. J. Weiss, J. Weldert, C. Wendt, J. Werthebach, M. Weyrauch, B. J. Whelan, N. Whitehorn, K. Wiebe, C. H. Wiebusch, D. R. Williams, M. Wolf, K. Woschnagg, G. Wrede, J. Wulff, X. W. Xu, Y. Xu, J. P. Yanez, S. Yoshida, T. Yuan, Z. Zhang
http://arxiv.org/abs/2101.11589v1
• [hep-ex]Parallelizing the Unpacking and Clustering of Detector Data for Reconstruction of Charged Particle Tracks on Multi-core CPUs and Many-core GPUs
Giuseppe Cerati, Peter Elmer, Brian Gravelle, Matti Kortelainen, Vyacheslav Krutelyov, Steven Lantz, Mario Masciovecchio, Kevin McDermott, Boyana Norris, Allison Reinsvold Hall, Micheal Reid, Daniel Riley, Matevž Tadel, Peter Wittich, Bei Wang, Frank Würthwein, Avraham Yagil
http://arxiv.org/abs/2101.11489v1
• [math.AG]Kähler Geometry of Quiver Varieties and Machine Learning
George Jeffreys, Siu-Cheong Lau
http://arxiv.org/abs/2101.11487v1
• [math.OC]Complementary Composite Minimization, Small Gradients in General Norms, and Applications to Regression Problems
Jelena Diakonikolas, Cristóbal Guzmán
http://arxiv.org/abs/2101.11041v1
• [math.OC]Formulating and solving integrated order batching and routing in multi-depot AGV-assisted mixed-shelves warehouses
Lin Xie, Hanyi Li, Laurin Luttmann
http://arxiv.org/abs/2101.11473v1
• [math.OC]Inadequacy of Linear Methods for Minimal Sensor Placement and Feature Selection in Nonlinear Systems; a New Approach Using Secants
Samuel E. Otto, Clarence W. Rowley
http://arxiv.org/abs/2101.11162v1
• [math.OC]New Riemannian preconditioned algorithms for tensor completion via polyadic decomposition
Shuyu Dong, Bin Gao, Yu Guan, François Glineur
http://arxiv.org/abs/2101.11108v1
• [math.PR]Functional inequalities for perturbed measures with applications to log-concave measures and to some Bayesian problems
Patrick Cattiaux, Arnaud Guillin
http://arxiv.org/abs/2101.11257v1
• [math.SP]LDLE: Low Distortion Local Eigenmaps
Dhruv Kohli, Alexander Cloninger, Gal Mishne
http://arxiv.org/abs/2101.11055v1
• [math.ST]A general method for power analysis in testing high dimensional covariance matrices
Qiyang Han, Tiefeng Jiang, Yandi Shen
http://arxiv.org/abs/2101.11086v1
• [math.ST]Motif-based tests for bipartite networks
Sarah Ouadah, Pierre Latouche, Stéphane Robin
http://arxiv.org/abs/2101.11381v1
• [physics.flu-dyn]Echo State Network for two-dimensional turbulent moist Rayleigh-Bénard convection
Florian Heyder, Jörg Schumacher
http://arxiv.org/abs/2101.11325v1
• [physics.flu-dyn]State estimation with limited sensors — A deep learning based approach
Yash Kumar, Pranav Bahl, Souvik Chakraborty
http://arxiv.org/abs/2101.11513v1
• [physics.geo-ph]Periodic seismicity detection without declustering
Timothy Park, Franz J. Kiraly, Stephen J. Bourne
http://arxiv.org/abs/2101.11533v1
• [physics.soc-ph]A Model of Densifying Collaboration Networks
Keith A. Burghardt, Allon G. Percus, Kristina Lerman
http://arxiv.org/abs/2101.11056v1
• [physics.soc-ph]Individual and Social Behaviour in Particle Swarm Optimizers
Johann Sienz, Mauro S. Innocente
http://arxiv.org/abs/2101.11439v1
• [q-bio.NC]Identification of brain states, transitions, and communities using functional MRI
Lingbin Bian, Tiangang Cui, B. T. Thomas Yeo, Alex Fornito, Adeel Razi, Jonathan Keith
http://arxiv.org/abs/2101.10617v1
• [quant-ph]Quantum Generative Adversarial Networks in a Continuous-Variable Architecture to Simulate High Energy Physics Detectors
Su Yeon Chang, Sofia Vallecorsa, Elías F. Combarro, Federico Carminati
http://arxiv.org/abs/2101.11132v1
• [quant-ph]Quantum machine learning models are kernel methods
Maria Schuld
http://arxiv.org/abs/2101.11020v1
• [stat.AP]A study on information behavior of scholars for article keywords selection
Z. X. Lian
http://arxiv.org/abs/2101.11446v1
• [stat.AP]Boost-S: Gradient Boosted Trees for Spatial Data and Its Application to FDG-PET Imaging Data
Reza Iranzad, Xiao Liu, W. Art Chaovalitwongse, Daniel S. Hippe, Shouyi Wang, Jie Han, Phawis Thammasorn, Chunyan Duan, Jing Zeng, Stephen R. Bowen
http://arxiv.org/abs/2101.11190v1
• [stat.AP]Solar Radiation Anomaly Events Modeling Using Spatial-Temporal Mutually Interactive Processes
Minghe Zhang, Chen Xu, Andy Sun, Feng Qiu, Yao Xie
http://arxiv.org/abs/2101.11179v1
• [stat.AP]Transporting a prediction model for use in a new target population
Jon A. Steingrimsson, Constantine Gatsonis, Issa J. Dahabreh
http://arxiv.org/abs/2101.11182v1
• [stat.CO]Log-Normalization Constant Estimation using the Ensemble Kalman-Bucy Filter with Application to High-Dimensional Models
Dan Crisan, Pierre Del Moral, Ajay Jasra, Hamza Ruzayqat
http://arxiv.org/abs/2101.11460v1
• [stat.ME]An Early Stopping Bayesian Data Assimilation Approach for Mixed-Logit Estimation
Shanshan Xie, Tim Hillel, Ying Jin
http://arxiv.org/abs/2101.11159v1
• [stat.ME]Bayesian Paired-Comparison with the bpcs Package
David Issa Mattos, Érika Martins Silva Ramos
http://arxiv.org/abs/2101.11227v1
• [stat.ME]Computational methods for Bayesian semiparametric Item Response Theory models
Sally Paganin, Christopher J. Paciorek, Claudia Wehrhahn, Abel Rodriguez, Sophia Rabe-Hesketh, Perry de Valpine
http://arxiv.org/abs/2101.11583v1
• [stat.ME]D-STEM v2: A Software for Modelling Functional Spatio-Temporal Data
Yaqiong Wang, Francesco Finazzi, Alessandro Fassò
http://arxiv.org/abs/2101.11370v1
• [stat.ME]Most Powerful Test Sequences with Early Stopping Options
Sergey Tarima, Nancy Flournoy
http://arxiv.org/abs/2101.11595v1
• [stat.ME]To tune or not to tune, a case study of ridge logistic regression in small or sparse datasets
Hana Šinkovec, Georg Heinze, Rok Blagus, Angelika Geroldinger
http://arxiv.org/abs/2101.11230v1
• [stat.ME]Tree boosting for learning probability measures
Naoki Awaya, Li Ma
http://arxiv.org/abs/2101.11083v1
• [stat.ML]Generalized Doubly Reparameterized Gradient Estimators
Matthias Bauer, Andriy Mnih
http://arxiv.org/abs/2101.11046v1
• [stat.ML]**Reproducing kernel Hilbert C-module and kernel mean embeddings
Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda, Fuyuta Komura, Takeshi Katsura, Yoshinobu Kawahara
http://arxiv.org/abs/2101.11410v1
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