astro-ph.IM - 仪器仪表和天体物理学方法
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.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.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.EM - 计量经济学
eess.IV - 图像与视频处理
eess.SP - 信号处理
hep-lat - 高能物理晶格
math.DS - 动力系统
math.OC - 优化与控制
math.PR - 概率
math.ST - 统计理论
physics.comp-ph - 计算物理学
physics.flu-dyn - 流体动力学
physics.soc-ph - 物理学与社会
q-bio.PE - 人口与发展
q-fin.ST - 统计金融学
quant-ph - 量子物理
stat.AP - 应用统计
stat.ME - 统计方法论
stat.ML - (统计)机器学习
• [astro-ph.IM]Self-supervised similarity search for large scientific datasets
• [cs.AI]Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey
• [cs.AI]Bootstrapping Concept Formation in Small Neural Networks
• [cs.AI]ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs
• [cs.AI]How Should AI Interpret Rules? A Defense of Minimally Defeasible Interpretive Argumentation
• [cs.AI]Learning Optimal Decision Trees Using MaxSAT
• [cs.AI]Towards Realistic Market Simulations: a Generative Adversarial Networks Approach
• [cs.CL]AVocaDo: Strategy for Adapting Vocabulary to Downstream Domain
• [cs.CL]An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling
• [cs.CL]Annotating Implicit Reasoning in Arguments with Causal Links
• [cs.CL]Assessing Evaluation Metrics for Speech-to-Speech Translation
• [cs.CL]Assessing the Sufficiency of Arguments through Conclusion Generation
• [cs.CL]Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios?
• [cs.CL]Decomposing Complex Questions Makes Multi-Hop QA Easier and More Interpretable
• [cs.CL]Findings from Experiments of On-line Joint Reinforcement Learning of Semantic Parser and Dialogue Manager with real Users
• [cs.CL]Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputs
• [cs.CL]Open Rule Induction
• [cs.CL]Part & Whole Extraction: Towards A Deep Understanding of Quantitative Facts for Percentages in Text
• [cs.CL]Simultaneous Neural Machine Translation with Constituent Label Prediction
• [cs.CL]Task-Specific Dependency-based Word Embedding Methods
• [cs.CL]Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis
• [cs.CL]WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
• [cs.CL]s2s-ft: Fine-Tuning Pretrained Transformer Encoders for Sequence-to-Sequence Learning
• [cs.CR]Bridging the gap to real-world for network intrusion detection systems with data-centric approach
• [cs.CR]DPCOVID: Privacy-Preserving Federated Covid-19 Detection
• [cs.CR]Measuring the Effectiveness of Digital Hygiene using Historical DNS Data
• [cs.CR]Precise URL Phishing Detection Using Neural Networks
• [cs.CR]Task-Aware Meta Learning-based Siamese Neural Network for Classifying Obfuscated Malware
• [cs.CV]A Horizon Detection Algorithm for Maritime Surveillance
• [cs.CV]A Light-weight Interpretable CompositionalNetwork for Nuclei Detection and Weakly-supervised Segmentation
• [cs.CV]A Normalized Gaussian Wasserstein Distance for Tiny Object Detection
• [cs.CV]A Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data
• [cs.CV]A Variational Graph Autoencoder for Manipulation Action Recognition and Prediction
• [cs.CV]A time-weighted metric for sets of trajectories to assess multi-object tracking algorithms
• [cs.CV]Addressing out-of-distribution label noise in webly-labelled data
• [cs.CV]Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
• [cs.CV]As if by magic: self-supervised training of deep despeckling networks with MERLIN
• [cs.CV]AugMax: Adversarial Composition of Random Augmentations for Robust Training
• [cs.CV]BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network
• [cs.CV]CTRN: Class-Temporal Relational Network for Action Detection
• [cs.CV]Camera-Based Physiological Sensing: Challenges and Future Directions
• [cs.CV]CloudFindr: A Deep Learning Cloud Artifact Masker for Satellite DEM Data
• [cs.CV]Contextual Similarity Aggregation with Self-attention for Visual Re-ranking
• [cs.CV]Cross-Region Building Counting in Satellite Imagery using Counting Consistency
• [cs.CV]DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples
• [cs.CV]Detecting speaking persons in video
• [cs.CV]Directional Self-supervised Learning for Risky Image Augmentations
• [cs.CV]Emotion recognition in talking-face videos using persistent entropy and neural networks
• [cs.CV]Facial Recognition in Collaborative Learning Videos
• [cs.CV]Generalized Multi-Task Learning from Substantially Unlabeled Multi-Source Medical Image Data
• [cs.CV]Generative Flows as a General Purpose Solution for Inverse Problems
• [cs.CV]H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motion
• [cs.CV]HR-RCNN: Hierarchical Relational Reasoning for Object Detection
• [cs.CV]History Aware Multimodal Transformer for Vision-and-Language Navigation
• [cs.CV]IIP-Transformer: Intra-Inter-Part Transformer for Skeleton-Based Action Recognition
• [cs.CV]IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning
• [cs.CV]Image Quality Assessment using Contrastive Learning
• [cs.CV]Incremental Learning for Animal Pose Estimation using RBF k-DPP
• [cs.CV]Learning Graph Representation of Person-specific Cognitive Processes from Audio-visual Behaviours for Automatic Personality Recognition
• [cs.CV]Learning Neural Transmittance for Efficient Rendering of Reflectance Fields
• [cs.CV]Learning Rich Features for Gait Recognition by Integrating Skeletons and Silhouettes
• [cs.CV]Meta-Learning for Multi-Label Few-Shot Classification
• [cs.CV]NeRV: Neural Representations for Videos
• [cs.CV]Pediatric Otoscopy Video Screening with Shift Contrastive Anomaly Detection
• [cs.CV]Plug-and-Play Few-shot Object Detection with Meta Strategy and Explicit Localization Inference
• [cs.CV]Pyramidal Blur Aware X-Corner Chessboard Detector
• [cs.CV]Response-based Distillation for Incremental Object Detection
• [cs.CV]Robust Ellipsoid-specific Fitting via Expectation Maximization
• [cs.CV]Robust Multi-view Registration of Point Sets with Laplacian Mixture Model
• [cs.CV]Self-Denoising Neural Networks for Few Shot Learning
• [cs.CV]Semantic Host-free Trojan Attack
• [cs.CV]Semi-supervised dry herbage mass estimation using automatic data and synthetic images
• [cs.CV]Single Morphing Attack Detection using Feature Selection and Visualisation based on Mutual Information
• [cs.CV]Spectral unmixing of Raman microscopic images of single human cells using Independent Component Analysis
• [cs.CV]Subject Adaptive EEG-based Visual Recognition
• [cs.CV]TNTC: two-stream network with transformer-based complementarity for gait-based emotion recognition
• [cs.CV]Transferring Domain-Agnostic Knowledge in Video Question Answering
• [cs.CV]TriBERT: Full-body Human-centric Audio-visual Representation Learning for Visual Sound Separation
• [cs.CV]Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo
• [cs.CV]Understanding the Role of Self-Supervised Learning in Out-of-Distribution Detection Task
• [cs.CV]ViDA-MAN: Visual Dialog with Digital Humans
• [cs.CV]YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs
• [cs.CV]Zero-Shot Action Recognition from Diverse Object-Scene Compositions
• [cs.CY]A Scalable Architecture for Electronic Payments
• [cs.CY]DASentimental: Detecting depression, anxiety and stress in texts via emotional recall, cognitive networks and machine learning
• [cs.CY]Exploring Content Moderation in the Decentralised Web: The Pleroma Case
• [cs.CY]Exposure of occupations to technologies of the fourth industrial revolution
• [cs.DC]A DPDK-Based Acceleration Method for Experience Sampling of Distributed Reinforcement Learning
• [cs.DC]A proposed method using GPU based SDO to optimize retail warehouses
• [cs.DC]BuffetFS: Serve Yourself Permission Checks without Remote Procedure Calls
• [cs.DC]Data intensive physics analysis in Azure cloud
• [cs.DC]Let’s Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud
• [cs.DC]OpenACC Acceleration of an Agent-Based Biological Simulation Framework
• [cs.DL]A Map of Science in Wikipedia
• [cs.HC]Visual Selective Attention System to Intervene User Attention in Sharing COVID-19 Misinformation
• [cs.IR]Managing Bias in Human-Annotated Data: Moving Beyond Bias Removal
• [cs.IR]Privacy-Preserving Multi-Target Multi-Domain Recommender Systems with Assisted AutoEncoders
• [cs.IT]Algorithms for the Communication of Samples
• [cs.IT]Controlling Smart Propagation Environments: Long-Term versus Short-Term Phase Shift Optimization
• [cs.IT]Enhanced User Grouping and Pairing Schemes for CoMP NOMA based Cellular Networks
• [cs.IT]Estimating Mutual Information via Geodesic NN
• [cs.IT]Estimation-Energy Tradeoff for Scalar Gauss-Markov Signals with Kalman Filtering
• [cs.IT]High-Throughput and Energy-Efficient VLSI Architecture for Ordered Reliability Bits GRAND
• [cs.IT]Overcoming Pedestrian Blockage in mm-Wave Bands using Ground Reflections
• [cs.IT]Support Recovery Guarantees for Periodic Signals with Nested Periodic Dictionaries
• [cs.IT]Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding
• [cs.LG]A Probabilistic Framework for Knowledge Graph Data Augmentation
• [cs.LG]A deep learning based surrogate model for stochastic simulators
• [cs.LG]A deep learning driven pseudospectral PCE based FFT homogenization algorithm for complex microstructures
• [cs.LG]An extended physics informed neural network for preliminary analysis of parametric optimal control problems
• [cs.LG]Arbitrary Distribution Modeling with Censorship in Real-Time Bidding Advertising
• [cs.LG]AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification
• [cs.LG]Automating Control of Overestimation Bias for Continuous Reinforcement Learning
• [cs.LG]Average-Reward Learning and Planning with Options
• [cs.LG]Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs
• [cs.LG]CSP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction
• [cs.LG]CLLD: Contrastive Learning with Label Distance for Text Classificatioin
• [cs.LG]CNNC: A Visual Analytics System for Comparative Studies of Deep Convolutional Neural Networks
• [cs.LG]Causal Effect Estimation using Variational Information Bottleneck
• [cs.LG]Coherent False Seizure Prediction in Epilepsy, Coincidence or Providence?
• [cs.LG]Concepts for Automated Machine Learning in Smart Grid Applications
• [cs.LG]Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features
• [cs.LG]Covariance-Generalized Matching Component Analysis for Data Fusion and Transfer Learning
• [cs.LG]Data-Driven Time Series Reconstruction for Modern Power Systems Research
• [cs.LG]Decomposed Inductive Procedure Learning
• [cs.LG]Deep Explicit Duration Switching Models for Time Series
• [cs.LG]DeepHelp: Deep Learning for Shout Crisis Text Conversations
• [cs.LG]Defensive Tensorization
• [cs.LG]Demystifying and Generalizing BinaryConnect
• [cs.LG]Disrupting Deep Uncertainty Estimation Without Harming Accuracy
• [cs.LG]Distributed Multi-Agent Deep Reinforcement Learning Framework for Whole-building HVAC Control
• [cs.LG]Distributional Reinforcement Learning for Multi-Dimensional Reward Functions
• [cs.LG]Distributionally Robust Recurrent Decoders with Random Network Distillation
• [cs.LG]Diversity and Generalization in Neural Network Ensembles
• [cs.LG]EDLaaS; Fully Homomorphic Encryption Over Neural Network Graphs
• [cs.LG]EarthGAN: Can we visualize the Earth’s mantle convection using a surrogate model?
• [cs.LG]Emulation of physical processes with Emukit
• [cs.LG]EnTRPO: Trust Region Policy Optimization Method with Entropy Regularization
• [cs.LG]Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications
• [cs.LG]Exponential Graph is Provably Efficient for Decentralized Deep Training
• [cs.LG]FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective
• [cs.LG]Fast PDE-constrained optimization via self-supervised operator learning
• [cs.LG]Geometric Transformer for End-to-End Molecule Properties Prediction
• [cs.LG]Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning
• [cs.LG]Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias
• [cs.LG]Gradient representations in ReLU networks as similarity functions
• [cs.LG]Heterogeneous Temporal Graph Neural Network
• [cs.LG]Hierarchical Transformers Are More Efficient Language Models
• [cs.LG]Hinge Policy Optimization: Rethinking Policy Improvement and Reinterpreting PPO
• [cs.LG]Identifying and Benchmarking Natural Out-of-Context Prediction Problems
• [cs.LG]Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning
• [cs.LG]Learning Robust Controllers Via Probabilistic Model-Based Policy Search
• [cs.LG]Learning to Pre-process Laser Induced Breakdown Spectroscopy Signals Without Clean Data
• [cs.LG]Learning to Simulate Self-Driven Particles System with Coordinated Policy Optimization
• [cs.LG]MarS-FL: A Market Share-based Decision Support Framework for Participation in Federated Learning
• [cs.LG]Multi-Faceted Hierarchical Multi-Task Learning for a Large Number of Tasks with Multi-dimensional Relations
• [cs.LG]Multi-Task Meta-Learning Modification with Stochastic Approximation
• [cs.LG]Multitask Adaptation by Retrospective Exploration with Learned World Models
• [cs.LG]Negotiating Networks in Oligopoly Markets for Price-Sensitive Products
• [cs.LG]Nested Graph Neural Networks
• [cs.LG]Non-Gaussian Gaussian Processes for Few-Shot Regression
• [cs.LG]Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis
• [cs.LG]On the Optimization Landscape of Maximum Mean Discrepancy
• [cs.LG]Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD
• [cs.LG]PARIS: Personalized Activity Recommendation for Improving Sleep Quality
• [cs.LG]Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks
• [cs.LG]Partial order: Finding Consensus among Uncertain Feature Attributions
• [cs.LG]Periodic Activation Functions Induce Stationarity
• [cs.LG]Prediction-focused Mixture Models
• [cs.LG]Probabilistic Entity Representation Model for Chain Reasoning over Knowledge Graphs
• [cs.LG]Probabilistic Hierarchical Forecasting with Deep Poisson Mixtures
• [cs.LG]Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes
• [cs.LG]Reconciling Risk Allocation and Prevalence Estimation in Public Health Using Batched Bandits
• [cs.LG]Relay Variational Inference: A Method for Accelerated Encoderless VI
• [cs.LG]Robust Learning of Physics Informed Neural Networks
• [cs.LG]Scale-Free Adversarial Multi-Armed Bandit with Arbitrary Feedback Delays
• [cs.LG]Semi-Supervised Federated Learning with non-IID Data: Algorithm and System Design
• [cs.LG]Shared Independent Component Analysis for Multi-Subject Neuroimaging
• [cs.LG]Sinusoidal Flow: A Fast Invertible Autoregressive Flow
• [cs.LG]TUNet: A Block-online Bandwidth Extension Model based on Transformers and Self-supervised Pretraining
• [cs.LG]Tackling Oversmoothing of GNNs with Contrastive Learning
• [cs.LG]Tensor Network Kalman Filtering for Large-Scale LS-SVMs
• [cs.LG]The Pareto Frontier of model selection for general Contextual Bandits
• [cs.LG]Topologically penalized regression on manifolds
• [cs.LG]Transportation Scenario Planning with Graph Neural Networks
• [cs.LG]Understanding Interlocking Dynamics of Cooperative Rationalization
• [cs.LG]Variational framework for partially-measured physical system control: examples of vision neuroscience and optical random media
• [cs.LG]Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices
• [cs.NE]An Embedded System for Image-based Crack Detection by using Fine-Tuning model of Adaptive Structural Learning of Deep Belief Network
• [cs.NI]Adaptive Probabilistic Model for Energy-Efficient Distance-based Clustering in WSNs (Adapt-P): A LEACH-based Analytical Study
• [cs.RO]2D Grid Map Generation for Deep-Learning-based Navigation Approaches
• [cs.RO]Driving Style Recognition Using Interval Type-2 Fuzzy Inference System and Multiple Experts Decision Making
• [cs.RO]Improving Robustness of Deep Neural Networks for Aerial Navigation by Incorporating Input Uncertainty
• [cs.RO]MEKF Ignoring Initial Conditions for Attitude Estimation Using Vector Observations
• [cs.RO]Research on the inverse kinematics prediction of a soft actuator via BP neural network
• [cs.RO]Synchronous-Clock Range-Angle Relative Acoustic Navigation: A Unified Approach to Multi-AUV Localization, Command, Control and Coordination
• [cs.RO]Towards More Generalizable One-shot Visual Imitation Learning
• [cs.SD]CS-Rep: Making Speaker Verification Networks Embracing Re-parameterization
• [cs.SD]Deep Learning Tools for Audacity: Helping Researchers Expand the Artist’s Toolkit
• [cs.SE]Automated Support for Unit Test Generation: A Tutorial Book Chapter
• [cs.SE]Memory visualization tool for training neural network
• [cs.SI]A Pipeline for Graph-Based Monitoring of the Changes in the Information Space of Russian Social Media during the Lockdown
• [cs.SI]Comparison of Indicators of Location Homophily Using Twitter Follow Graph
• [cs.SI]How to Quantify Polarization in Models of Opinion Dynamics
• [cs.SI]NetMF+: Network Embedding Based on Fast and Effective Single-Pass Randomized Matrix Factorization
• [cs.SI]Quantitative Evaluation of Snapshot Graphs for the Analysis of Temporal Networks
• [cs.SI]Sampling Multiple Nodes in Large Networks: Beyond Random Walks
• [cs.SI]TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation
• [cs.SI]The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks
• [econ.EM]A new inequality measurement tool: The Vinci index
• [econ.EM]Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust
• [econ.EM]Inference in Regression Discontinuity Designs with High-Dimensional Covariates
• [eess.IV]A Closer Look at Reference Learning for Fourier Phase Retrieval
• [eess.IV]A Precision Diagnostic Framework of Renal Cell Carcinoma on Whole-Slide Images using Deep Learning
• [eess.IV]An Automatic Detection Method Of Cerebral Aneurysms In Time-Of-Flight Magnetic Resonance Angiography Images Based On Attention 3D U-Net
• [eess.IV]Deep DIC: Deep Learning-Based Digital Image Correlation for End-to-End Displacement and Strain Measurement
• [eess.IV]Deep Learning-based Segmentation of Cerebral Aneurysms in 3D TOF-MRA using Coarse-to-Fine Framework
• [eess.IV]Image Magnification Network for Vessel Segmentation in OCTA Images
• [eess.IV]RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network
• [eess.IV]Real-time division-of-focal-plane polarization imaging system with progressive networks
• [eess.IV]W-Net: A Two-Stage Convolutional Network for Nucleus Detection in Histopathology Image
• [eess.SP]An Analysis of LOS Coverage in Vehicular Networks with Roadside Units and Relays
• [hep-lat]Machine learning spectral functions in lattice QCD
• [math.DS]Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme
• [math.OC]Faster Perturbed Stochastic Gradient Methods for Finding Local Minima
• [math.OC]On the Second-order Convergence Properties of Random Search Methods
• [math.PR]A Constructive Proof of the Glivenko-Cantelli Theorem
• [math.ST]Bayesian Estimation and Comparison of Conditional Moment Models
• [math.ST]Debiased and threshold ridge regression for linear model with heteroskedastic and dependent error
• [math.ST]Equivariant Estimation of the Selected Guarantee Time
• [math.ST]Note on the approximation of the conditional intensity of non-stationary cluster
5851
point processes
• [math.ST]Optimal Bayesian Estimation of a Regression Curve, a Conditional Density and a Conditional Distribution
• [physics.comp-ph]Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach
• [physics.flu-dyn]Physics Informed Machine Learning of SPH: Machine Learning Lagrangian Turbulence
• [physics.soc-ph]On the consequences of draw restrictions in knockout tournaments
• [physics.soc-ph]Relations between anomalous diffusion and fluctuation scaling: The case of ultraslow diffusion and time-scale-independent fluctuation scaling in language
• [q-bio.PE]Optimal non-pharmaceutical intervention policy for Covid-19 epidemic via neuroevolution algorithm
• [q-fin.ST]HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information
• [quant-ph]Quantum machine learning beyond kernel methods
• [stat.AP]A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses for Administrative Tax Data
• [stat.AP]Analyzing the Data of COVID-19 with Quasi-Distribution Fitting Based on Piecewise B-spline Curves
• [stat.AP]On the analysis of the temperature fluctuation in the Campi Flegrei caldera through a fractional Brownian motion-based model
• [stat.ME]Highly Scalable Maximum Likelihood and Conjugate Bayesian Inference for ERGMs on Graph Sets with Equivalent Vertices
• [stat.ME]On Monitoring High-Dimensional Multivariate Processes with Individual Observations
• [stat.ME]Phase I Analysis of High-Dimensional Multivariate Processes in the Presence of Outliers
• [stat.ME]Towards Optimal Variance Reduction in Online Controlled Experiments
• [stat.ML]Dynamic Causal Bayesian Optimization
• [stat.ML]Gradient-based Quadratic Multiform Separation
• [stat.ML]Improving the efficacy of Deep Learning models for Heart Beat detection on heterogeneous datasets
• [stat.ML]Integrative Clustering of Multi-View Data by Nonnegative Matrix Factorization
• [stat.ML]Min-similarity association rules for identifying past comorbidities of recurrent ED and inpatient patients
• [stat.ML]Modular Gaussian Processes for Transfer Learning
• [stat.ML]Online Variational Filtering and Parameter Learning
• [stat.ML]Post-processing for Individual Fairness
• [stat.ML]Revisiting randomized choices in isolation forests
• [stat.ML]Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN
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• [astro-ph.IM]Self-supervised similarity search for large scientific datasets
George Stein, Peter Harrington, Jacqueline Blaum, Tomislav Medan, Zarija Lukic
http://arxiv.org/abs/2110.13151v1
• [cs.AI]Applications of Multi-Agent Reinforcement Learning in Future Internet: A Comprehensive Survey
Tianxu Li, Kun Zhu, Nguyen Cong Luong, Dusit Niyato, Qihui Wu, Yang Zhang, Bing Chen
http://arxiv.org/abs/2110.13484v1
• [cs.AI]Bootstrapping Concept Formation in Small Neural Networks
Minija Tamosiunaite, Tomas Kulvicius, Florentin Wörgötter
http://arxiv.org/abs/2110.13665v1
• [cs.AI]ConE: Cone Embeddings for Multi-Hop Reasoning over Knowledge Graphs
Zhanqiu Zhang, Jie Wang, Jiajun Chen, Shuiwang Ji, Feng Wu
http://arxiv.org/abs/2110.13715v1
• [cs.AI]How Should AI Interpret Rules? A Defense of Minimally Defeasible Interpretive Argumentation
John Licato
http://arxiv.org/abs/2110.13341v1
• [cs.AI]Learning Optimal Decision Trees Using MaxSAT
Josep Alos, Carlos Ansotegui, Eduard Torres
http://arxiv.org/abs/2110.13854v1
• [cs.AI]Towards Realistic Market Simulations: a Generative Adversarial Networks Approach
Andrea Coletta, Matteo Prata, Michele Conti, Emanuele Mercanti, Novella Bartolini, Aymeric Moulin, Svitlana Vyetrenko
http://arxiv.org/abs/2110.13287v1
• [cs.CL]AVocaDo: Strategy for Adapting Vocabulary to Downstream Domain
Jimin Hong, Taehee Kim, Hyesu Lim, Jaegul Choo
http://arxiv.org/abs/2110.13434v1
• [cs.CL]An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling
Han Liu, Feng Zhang, Xiaotong Zhang, Siyang Zhao, Xianchao Zhang
http://arxiv.org/abs/2110.13691v1
• [cs.CL]Annotating Implicit Reasoning in Arguments with Causal Links
Keshav Singh, Naoya Inoue, Farjana Sultana Mim, Shoichi Naitoh, Kentaro Inui
http://arxiv.org/abs/2110.13692v1
• [cs.CL]Assessing Evaluation Metrics for Speech-to-Speech Translation
Elizabeth Salesky, Julian Mäder, Severin Klinger
http://arxiv.org/abs/2110.13877v1
• [cs.CL]Assessing the Sufficiency of Arguments through Conclusion Generation
Timon Gurcke, Milad Alshomary, Henning Wachsmuth
http://arxiv.org/abs/2110.13495v1
• [cs.CL]Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios?
Arij Riabi, Benoît Sagot, Djamé Seddah
http://arxiv.org/abs/2110.13658v1
• [cs.CL]Decomposing Complex Questions Makes Multi-Hop QA Easier and More Interpretable
Ruiliu Fu, Han Wang, Xuejun Zhang, Jun Zhou
http://arxiv.org/abs/2110.13472v1
• [cs.CL]Findings from Experiments of On-line Joint Reinforcement Learning of Semantic Parser and Dialogue Manager with real Users
Matthieu Riou, Bassam Jabaian, Stéphane Huet, Fabrice Lefèvre
http://arxiv.org/abs/2110.13213v1
• [cs.CL]Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputs
Monisha Jegadeesan, Sachin Kumar, John Wieting, Yulia Tsvetkov
http://arxiv.org/abs/2110.13231v1
• [cs.CL]Open Rule Induction
Wanyun Cui, Xingran Chen
http://arxiv.org/abs/2110.13577v1
• [cs.CL]Part & Whole Extraction: Towards A Deep Understanding of Quantitative Facts for Percentages in Text
Lei Fang, Jian-Guang Lou
http://arxiv.org/abs/2110.13505v1
• [cs.CL]Simultaneous Neural Machine Translation with Constituent Label Prediction
Yasumasa Kano, Katsuhito Sudoh, Satoshi Nakamura
http://arxiv.org/abs/2110.13480v1
• [cs.CL]Task-Specific Dependency-based Word Embedding Methods
Chengwei Wei, Bin Wang, C. -C. Jay Kuo
http://arxiv.org/abs/2110.13376v1
• [cs.CL]Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis
Juhua Liu, Qihuang Zhong, Liang Ding, Hua Jin, Bo Du, Dacheng Tao
http://arxiv.org/abs/2110.13398v1
• [cs.CL]WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing
Sanyuan Chen, Chengyi Wang, Zhengyang Chen, Yu Wu, Shujie Liu, Zhuo Chen, Jinyu Li, Naoyuki Kanda, Takuya Yoshioka, Xiong Xiao, Jian Wu, Long Zhou, Shuo Ren, Yanmin Qian, Yao Qian, Jian Wu, Micheal Zeng, Furu Wei
http://arxiv.org/abs/2110.13900v1
• [cs.CL]s2s-ft: Fine-Tuning Pretrained Transformer Encoders for Sequence-to-Sequence Learning
Hangbo Bao, Li Dong, Wenhui Wang, Nan Yang, Furu Wei
http://arxiv.org/abs/2110.13640v1
• [cs.CR]Bridging the gap to real-world for network intrusion detection systems with data-centric approach
Gustavo de Carvalho Bertoli, Lourenço Alves Pereira Junior, Filipe Alves Neto Verri, Aldri Luiz dos Santos, Osamu Saotome
http://arxiv.org/abs/2110.13655v1
• [cs.CR]DPCOVID: Privacy-Preserving Federated Covid-19 Detection
Trang-Thi Ho, Yennun-Huang
http://arxiv.org/abs/2110.13760v1
• [cs.CR]Measuring the Effectiveness of Digital Hygiene using Historical DNS Data
Oliver Farnan, Gregory Walton, Joss Wright
http://arxiv.org/abs/2110.13562v1
• [cs.CR]Precise URL Phishing Detection Using Neural Networks
Aman Rangapur, Dr Ajith Jubilson
http://arxiv.org/abs/2110.13424v1
• [cs.CR]Task-Aware Meta Learning-based Siamese Neural Network for Classifying Obfuscated Malware
Jinting Zhu, Julian Jang-Jaccard, Amardeep Singh, Paul A. Watters, Seyit Camtepe
http://arxiv.org/abs/2110.13409v1
• [cs.CV]A Horizon Detection Algorithm for Maritime Surveillance
Yassir Zardoua, Astito Abdelali, Boulaala Mohammed
http://arxiv.org/abs/2110.13694v1
• [cs.CV]A Light-weight Interpretable CompositionalNetwork for Nuclei Detection and Weakly-supervised Segmentation
Yixiao Zhang, Adam Kortylewski, Qing Liu, Seyoun Park, Benjamin Green, Elizabeth Engle, Guillermo Almodovar, Ryan Walk, Sigfredo Soto-Diaz, Janis Taube, Alex Szalay, Alan Yuille
http://arxiv.org/abs/2110.13846v1
• [cs.CV]A Normalized Gaussian Wasserstein Distance for Tiny Object Detection
Jinwang Wang, Chang Xu, Wen Yang, Lei Yu
http://arxiv.org/abs/2110.13389v1
• [cs.CV]A Personalized Diagnostic Generation Framework Based on Multi-source Heterogeneous Data
Jialun Wu, Zeyu Gao, Haichuan Zhang, Ruonan Zhang, Tieliang Gong, Chunbao Wang, Chen Li
http://arxiv.org/abs/2110.13677v1
• [cs.CV]A Variational Graph Autoencoder for Manipulation Action Recognition and Prediction
Gamze Akyol, Sanem Sariel, Eren Erdal Aksoy
http://arxiv.org/abs/2110.13280v1
• [cs.CV]A time-weighted metric for sets of trajectories to assess multi-object tracking algorithms
Ángel F. García-Fernández, Abu Sajana Rahmathullah, Lennart Svensson
http://arxiv.org/abs/2110.13444v1
• [cs.CV]Addressing out-of-distribution label noise in webly-labelled data
Paul Albert, Diego Ortego, Eric Arazo, Noel O’Connor, Kevin McGuinness
http://arxiv.org/abs/2110.13699v1
• [cs.CV]Alpha-IoU: A Family of Power Intersection over Union Losses for Bounding Box Regression
Jiabo He, Sarah Erfani, Xingjun Ma, James Bailey, Ying Chi, Xian-Sheng Hua
http://arxiv.org/abs/2110.13675v1
• [cs.CV]As if by magic: self-supervised training of deep despeckling networks with MERLIN
Emanuele Dalsasso, Loïc Denis, Florence Tupin
http://arxiv.org/abs/2110.13148v1
• [cs.CV]AugMax: Adversarial Composition of Random Augmentations for Robust Training
Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, Zhangyang Wang
http://arxiv.org/abs/2110.13771v1
• [cs.CV]BioIE: Biomedical Information Extraction with Multi-head Attention Enhanced Graph Convolutional Network
Jialun Wu, Yang Liu, Zeyu Gao, Tieliang Gong, Chunbao Wang, Chen Li
http://arxiv.org/abs/2110.13683v1
• [cs.CV]CTRN: Class-Temporal Relational Network for Action Detection
Rui Dai, Srijan Das, Francois Bremond
http://arxiv.org/abs/2110.13473v1
• [cs.CV]Camera-Based Physiological Sensing: Challenges and Future Directions
Xin Liu, Shwetak Patel, Daniel McDuff
http://arxiv.org/abs/2110.13362v1
• [cs.CV]CloudFindr: A Deep Learning Cloud Artifact Masker for Satellite DEM Data
Kalina Borkiewicz, Viraj Shah, J. P. Naiman, Chuanyue Shen, Stuart Levy, Jeff Carpenter
http://arxiv.org/abs/2110.13819v1
• [cs.CV]Contextual Similarity Aggregation with Self-attention for Visual Re-ranking
Jianbo Ouyang, Hui Wu, Min Wang, Wengang Zhou, Houqiang Li
http://arxiv.org/abs/2110.13430v1
• [cs.CV]Cross-Region Building Counting in Satellite Imagery using Counting Consistency
Muaaz Zakria, Hamza Rawal, Waqas Sultani, Mohsen Ali
http://arxiv.org/abs/2110.13558v1
• [cs.CV]DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples
Yi Xu, Jiandong Ding, Lu Zhang, Shuigeng Zhou
http://arxiv.org/abs/2110.13740v1
• [cs.CV]Detecting speaking persons in video
Hannes Fassold
http://arxiv.org/abs/2110.13806v1
• [cs.CV]Directional Self-supervised Learning for Risky Image Augmentations
Yalong Bai, Yifan Yang, Wei Zhang, Tao Mei
http://arxiv.org/abs/2110.13555v1
• [cs.CV]Emotion recognition in talking-face videos using persistent entropy and neural networks
Eduardo Paluzo-Hidalgo, Guillermo Aguirre-Carrazana, Rocio Gonzalez-Diaz
http://arxiv.org/abs/2110.13571v1
• [cs.CV]Facial Recognition in Collaborative Learning Videos
Phuong Tran, Marios Pattichis, Sylvia Celedón-Pattichis, Carlos LópezLeiva
http://arxiv.org/abs/2110.13269v1
• [cs.CV]Generalized Multi-Task Learning from Substantially Unlabeled Multi-Source Medical Image Data
Ayaan Haque, Abdullah-Al-Zubaer Imran, Adam Wang, Demetri Terzopoulos
http://arxiv.org/abs/2110.13185v1
• [cs.CV]Generative Flows as a General Purpose Solution for Inverse Problems
José A. Chávez
http://arxiv.org/abs/2110.13285v1
• [cs.CV]H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motion
Hongyi Xu, Thiemo Alldieck, Cristian Sminchisescu
http://arxiv.org/abs/2110.13746v1
• [cs.CV]HR-RCNN: Hierarchical Relational Reasoning for Object Detection
Hao Chen, Abhinav Shrivastava
http://arxiv.org/abs/2110.13892v1
• [cs.CV]History Aware Multimodal Transformer for Vision-and-Language Navigation
Shizhe Chen, Pierre-Louis Guhur, Cordelia Schmid, Ivan Laptev
http://arxiv.org/abs/2110.13309v1
• [cs.CV]IIP-Transformer: Intra-Inter-Part Transformer for Skeleton-Based Action Recognition
Qingtian Wang, Jianlin Peng, Shuze Shi, Tingxi Liu, Jiabin He, Renliang Weng
http://arxiv.org/abs/2110.13385v1
• [cs.CV]IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning
Pan Lu, Liang Qiu, Jiaqi Chen, Tony Xia, Yizhou Zhao, Wei Zhang, Zhou Yu, Xiaodan Liang, Song-Chun Zhu
http://arxiv.org/abs/2110.13214v1
• [cs.CV]Image Quality Assessment using Contrastive Learning
Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli, Alan C. Bovik
http://arxiv.org/abs/2110.13266v1
• [cs.CV]Incremental Learning for Animal Pose Estimation using RBF k-DPP
Gaurav Kumar Nayak, Het Shah, Anirban Chakraborty
http://arxiv.org/abs/2110.13598v1
• [cs.CV]Learning Graph Representation of Person-specific Cognitive Processes from Audio-visual Behaviours for Automatic Personality Recognition
Siyang Song, Zilong Shao, Shashank Jaiswal, Linlin Shen, Michel Valstar, Hatice Gunes
http://arxiv.org/abs/2110.13570v1
• [cs.CV]Learning Neural Transmittance for Efficient Rendering of Reflectance Fields
Mohammad Shafiei, Sai Bi, Zhengqin Li, Aidas Liaudanskas, Rodrigo Ortiz-Cayon, Ravi Ramamoorthi
http://arxiv.org/abs/2110.13272v1
• [cs.CV]Learning Rich Features for Gait Recognition by Integrating Skeletons and Silhouettes
Yunjie Peng, Saihui Hou, Kang Ma, Yang Zhang, Yongzhen Huang, Zhiqiang He
http://arxiv.org/abs/2110.13408v1
• [cs.CV]Meta-Learning for Multi-Label Few-Shot Classification
Christian Simon, Piotr Koniusz, Mehrtash Harandi
http://arxiv.org/abs/2110.13494v1
• [cs.CV]NeRV: Neural Representations for Videos
Hao Chen, Bo He, Hanyu Wang, Yixuan Ren, Ser-Nam Lim, Abhinav Shrivastava
http://arxiv.org/abs/2110.13903v1
• [cs.CV]Pediatric Otoscopy Video Screening with Shift Contrastive Anomaly Detection
Weiyao Wang, Aniruddha Tamhane, Christine Santos, John R. Rzasa, James H. Clark, Therese L. Canares, Mathias Unberath
http://arxiv.org/abs/2110.13254v1
• [cs.CV]Plug-and-Play Few-shot Object Detection with Meta Strategy and Explicit Localization Inference
Junying Huang, Fan Chen, Liang Lin, Dongyu Zhang
http://arxiv.org/abs/2110.13377v1
• [cs.CV]Pyramidal Blur Aware X-Corner Chessboard Detector
Peter Abeles
http://arxiv.org/abs/2110.13793v1
• [cs.CV]Response-based Distillation for Incremental Object Detection
Tao Feng, Mang Wang
http://arxiv.org/abs/2110.13471v1
• [cs.CV]Robust Ellipsoid-specific Fitting via Expectation Maximization
Zhao Mingyang, Jia Xiaohong, Ma Lei, Qiu Xinlin, Jiang Xin, Yan Dong-Ming
http://arxiv.org/abs/2110.13337v1
• [cs.CV]Robust Multi-view Registration of Point Sets with Laplacian Mixture Model
Jin Zhang, Mingyang Zhao, Xin Jiang, Dong-Ming Yan
http://arxiv.org/abs/2110.13744v1
• [cs.CV]Self-Denoising Neural Networks for Few Shot Learning
Steven Schwarcz, Sai Saketh Rambhatla, Rama Chellappa
http://arxiv.org/abs/2110.13386v1
• [cs.CV]Semantic Host-free Trojan Attack
Haripriya Harikumar, Kien Do, Santu Rana, Sunil Gupta, Svetha Venkatesh
http://arxiv.org/abs/2110.13414v1
• [cs.CV]Semi-supervised dry herbage mass estimation using automatic data and synthetic images
Paul Albert, Mohamed Saadeldin, Badri Narayanan, Brian Mac Namee, Deirdre Hennessy, Aisling O’Connor, Noel O’Connor, Kevin McGuinness
http://arxiv.org/abs/2110.13719v1
• [cs.CV]Single Morphing Attack Detection using Feature Selection and Visualisation based on Mutual Information
Juan Tapia, Christoph Busch
http://arxiv.org/abs/2110.13552v1
• [cs.CV]Spectral unmixing of Raman microscopic images of single human cells using Independent Component Analysis
M. Hamed Mozaffari, Li-Lin Tay
http://arxiv.org/abs/2110.13189v1
• [cs.CV]Subject Adaptive EEG-based Visual Recognition
Pilhyeon Lee, Sunhee Hwang, Seogkyu Jeon, Hyeran Byun
http://arxiv.org/abs/2110.13470v1
• [cs.CV]TNTC: two-stream network with transformer-based complementarity for gait-based emotion recognition
Chuanfei Hu, Weijie Sheng, Bo Dong, Xinde Li
http://arxiv.org/abs/2110.13708v1
• [cs.CV]Transferring Domain-Agnostic Knowledge in Video Question Answering
Tianran Wu, Noa Garcia, Mayu Otani, Chenhui Chu, Yuta Nakashima, Haruo Takemura
http://arxiv.org/abs/2110.13395v1
• [cs.CV]TriBERT: Full-body Human-centric Audio-visual Representation Learning for Visual Sound Separation
Tanzila Rahman, Mengyu Yang, Leonid Sigal
http://arxiv.org/abs/2110.13412v1
• [cs.CV]Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo
Daniel Grzech, Mohammad Farid Azampour, Huaqi Qiu, Ben Glocker, Bernhard Kainz, Loïc Le Folgoc
http://arxiv.org/abs/2110.13289v1
• [cs.CV]Understanding the Role of Self-Supervised Learning in Out-of-Distribution Detection Task
Jiuhai Chen, Chen Zhu, Bin Dai
http://arxiv.org/abs/2110.13435v1
• [cs.CV]ViDA-MAN: Visual Dialog with Digital Humans
Tong Shen, Jiawei Zuo, Fan Shi, Jin Zhang, Liqin Jiang, Meng Chen, Zhengchen Zhang, Wei Zhang, Xiaodong He, Tao Mei
http://arxiv.org/abs/2110.13384v1
• [cs.CV]YOLO-ReT: Towards High Accuracy Real-time Object Detection on Edge GPUs
Prakhar Ganesh, Yao Chen, Yin Yang, Deming Chen, Marianne Winslett
http://arxiv.org/abs/2110.13713v1
• [cs.CV]Zero-Shot Action Recognition from Diverse Object-Scene Compositions
Carlo Bretti, Pascal Mettes
http://arxiv.org/abs/2110.13479v1
• [cs.CY]A Scalable Architecture for Electronic Payments
Geoff Goodell, D. R. Toliver, Hazem Danny Nakib
http://arxiv.org/abs/2110.13840v1
• [cs.CY]DASentimental: Detecting depression, anxiety and stress in texts via emotional recall, cognitive networks and machine learning
Asra Fatima, Li Ying, Thomas Hills, Massimo Stella
http://arxiv.org/abs/2110.13710v1
• [cs.CY]Exploring Content Moderation in the Decentralised Web: The Pleroma Case
Anaobi Ishaku Hassan, Aravindh Raman, Ignacio Castro, Haris Bin Zia, Emiliano De Cristofaro, Nishanth Sastry, Gareth Tyson
http://arxiv.org/abs/2110.13500v1
• [cs.CY]Exposure of occupations to technologies of the fourth industrial revolution
Benjamin Meindl, Morgan R. Frank, Joana Mendonça
http://arxiv.org/abs/2110.13317v1
• [cs.DC]A DPDK-Based Acceleration Method for Experience Sampling of Distributed Reinforcement Learning
Masaki Furukawa, Hiroki Matsutani
http://arxiv.org/abs/2110.13506v1
• [cs.DC]A proposed method using GPU based SDO to optimize retail warehouses
Magnus Bengtsson, Jonas Waidringer
http://arxiv.org/abs/2110.13693v1
• [cs.DC]BuffetFS: Serve Yourself Permission Checks without Remote Procedure Calls
Yanliang Zou, Bin Yang, Jian Zhang, Wei Xue, Shu Yin
http://arxiv.org/abs/2110.13551v1
• [cs.DC]Data intensive physics analysis in Azure cloud
Igor Sfiligoi, Frank Würthwein, Diego Davila
http://arxiv.org/abs/2110.13187v1
• [cs.DC]Let’s Wait Awhile: How Temporal Workload Shifting Can Reduce Carbon Emissions in the Cloud
Philipp Wiesner, Ilja Behnke, Dominik Scheinert, Kordian Gontarska, Lauritz Thamsen
http://arxiv.org/abs/2110.13234v1
• [cs.DC]OpenACC Acceleration of an Agent-Based Biological Simulation Framework
Matt Stack, Paul Macklin, Robert Searles, Sunita Chandrasekaran
http://arxiv.org/abs/2110.13368v1
• [cs.DL]A Map of Science in Wikipedia
Puyu Yang, Giovanni Colavizza
http://arxiv.org/abs/2110.13790v1
• [cs.HC]Visual Selective Attention System to Intervene User Attention in Sharing COVID-19 Misinformation
Zaid Amin, Nazlena Mohamad Ali, Alan F. Smeaton
http://arxiv.org/abs/2110.13489v1
• [cs.IR]Managing Bias in Human-Annotated Data: Moving Beyond Bias Removal
Gianluca Demartini, Kevin Roitero, Stefano Mizzaro
http://arxiv.org/abs/2110.13504v1
• [cs.IR]Privacy-Preserving Multi-Target Multi-Domain Recommender Systems with Assisted AutoEncoders
Enmao Diao, Vahid Tarokh, Jie Ding
http://arxiv.org/abs/2110.13340v1
• [cs.IT]Algorithms for the Communication of Samples
Lucas Theis, Noureldin Yosri
http://arxiv.org/abs/2110.12805v2
• [cs.IT]Controlling Smart Propagation Environments: Long-Term versus Short-Term Phase Shift Optimization
Trinh Van Chien, Lam Thanh Tu, Dinh-Hieu Tran, Hieu Van Nguyen, Symeon Chatzinotas, Marco Di Renzo, Björn Ottersten
http://arxiv.org/abs/2110.13288v1
• [cs.IT]Enhanced User Grouping and Pairing Schemes for CoMP NOMA based Cellular Networks
Akhileswar Chowdary, Garima Chopra, Abhinav Kumar, Linga Reddy Cenkeramaddi
http://arxiv.org/abs/2110.13468v1
• [cs.IT]Estimating Mutual Information via Geodesic NN
Alexander Marx, Jonas Fischer
http://arxiv.org/abs/2110.13883v1
• [cs.IT]Estimation-Energy Tradeoff for Scalar Gauss-Markov Signals with Kalman Filtering
Ioannis Krikidis, Constantinos Psomas
http://arxiv.org/abs/2110.13458v1
• [cs.IT]High-Throughput and Energy-Efficient VLSI Architecture for Ordered Reliability Bits GRAND
Syed Mohsin Abbas, Thibaud Tonnellier, Furkan Ercan, Marwan Jalaleddine, Warren J. Gross
http://arxiv.org/abs/2110.13776v1
• [cs.IT]Overcoming Pedestrian Blockage in mm-Wave Bands using Ground Reflections
Santosh Ganji, Romil Sonigra, P. R. Kumar
http://arxiv.org/abs/2110.13884v1
• [cs.IT]Support Recovery Guarantees for Periodic Signals with Nested Periodic Dictionaries
Pouria Saidi, George K. Atia
http://arxiv.org/abs/2110.13200v1
• [cs.IT]Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding
Qiyu Hu, Yunlong Cai, Kai Kang, Guanding Yu, Jakob Hoydis, Yonina C. Eldar
http://arxiv.org/abs/2110.12059v2
• [cs.LG]A Probabilistic Framework for Knowledge Graph Data Augmentation
Jatin Chauhan, Priyanshu Gupta, Pasquale Minervini
http://arxiv.org/abs/2110.13205v1
• [cs.LG]A deep learning based surrogate model for stochastic simulators
Akshay Thakur, Souvik Chakraborty
http://arxiv.org/abs/2110.13809v1
• [cs.LG]A deep learning driven pseudospectral PCE based FFT homogenization algorithm for complex microstructures
Alexander Henkes, Ismail Caylak, Rolf Mahnken
http://arxiv.org/abs/2110.13440v1
• [cs.LG]An extended physics informed neural network for preliminary analysis of parametric optimal control problems
Nicola Demo, Maria Strazzullo, Gianluigi Rozza
http://arxiv.org/abs/2110.13530v1
• [cs.LG]Arbitrary Distribution Modeling with Censorship in Real-Time Bidding Advertising
Xu Li, Michelle Ma Zhang, Youjun Tong, Zhenya Wang
http://arxiv.org/abs/2110.13587v1
• [cs.LG]AutoDEUQ: Automated Deep Ensemble with Uncertainty Quantification
Romain Egele, Romit Maulik, Krishnan Raghavan, Prasanna Balaprakash, Bethany Lusch
http://arxiv.org/abs/2110.13511v1
• [cs.LG]Automating Control of Overestimation Bias for Continuous Reinforcement Learning
Arsenii Kuznetsov, Alexander Grishin, Artem Tsypin, Arsenii Ashukha, Dmitry Vetrov
http://arxiv.org/abs/2110.13523v1
• [cs.LG]Average-Reward Learning and Planning with Options
Yi Wan, Abhishek Naik, Richard S. Sutton
http://arxiv.org/abs/2110.13855v1
• [cs.LG]Breaking the Moments Condition Barrier: No-Regret Algorithm for Bandits with Super Heavy-Tailed Payoffs
Han Zhong, Jiayi Huang, Lin F. Yang, Liwei Wang
http://arxiv.org/abs/2110.13876v1
• [cs.LG]CSP-Net: Joint Compression and Classification Network for Epilepsy Seizure Prediction
Di Wu, Yi Shi, Ziyu Wang, Jie Yang, Mohamad Sawan
http://arxiv.org/abs/2110.13674v1
• [cs.LG]CLLD: Contrastive Learning with Label Distance for Text Classificatioin
Jinhe Lan, Qingyuan Zhan, Chenhao Jiang, Kunping Yuan, Desheng Wang
http://arxiv.org/abs/2110.13656v1
• [cs.LG]CNNC: A Visual Analytics System for Comparative Studies of Deep Convolutional Neural Networks
Xiwei Xuan, Xiaoyu Zhang, Oh-Hyun Kwon, Kwan-Liu Ma
http://arxiv.org/abs/2110.13252v1
• [cs.LG]Causal Effect Estimation using Variational Information Bottleneck
Zhenyu Lu, Yurong Cheng, Mingjun Zhong, George Stoian, Ye Yuan, Guoren Wang
http://arxiv.org/abs/2110.13705v1
• [cs.LG]Coherent False Seizure Prediction in Epilepsy, Coincidence or Providence?
Jens Müller, Hongliu Yang, Matthias Eberlein, Georg Leonhardt, Ortrud Uckermann, Levin Kuhlmann, Ronald Tetzlaff
http://arxiv.org/abs/2110.13550v1
• [cs.LG]Concepts for Automated Machine Learning in Smart Grid Applications
Stefan Meisenbacher, Janik Pinter, Tim Martin, Veit Hagenmeyer, Ralf Mikut
http://arxiv.org/abs/2110.13585v1
• [cs.LG]Convergent Boosted Smoothing for Modeling Graph Data with Tabular Node Features
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
http://arxiv.org/abs/2110.13413v1
• [cs.LG]Covariance-Generalized Matching Component Analysis for Data Fusion and Transfer Learning
Nick Lorenzo, Sean O’Rourke, Theresa Scarnati
http://arxiv.org/abs/2110.13194v1
• [cs.LG]Data-Driven Time Series Reconstruction for Modern Power Systems Research
Minas Chatzos, Mathieu Tanneau, Pascal Van Hentenryck
http://arxiv.org/abs/2110.13772v1
• [cs.LG]Decomposed Inductive Procedure Learning
Daniel Weitekamp, Christopher MacLellan, Erik Harpstead, Kenneth Koedinger
http://arxiv.org/abs/2110.13233v1
• [cs.LG]Deep Explicit Duration Switching Models for Time Series
Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Turkmen, Harold Soh, Alexander J. Smola, Yuyang Wang, Tim Januschowski
http://arxiv.org/abs/2110.13878v1
• [cs.LG]DeepHelp: Deep Learning for Shout Crisis Text Conversations
Daniel Cahn
http://arxiv.org/abs/2110.13244v1
• [cs.LG]Defensive Tensorization
Adrian Bulat, Jean Kossaifi, Sourav Bhattacharya, Yannis Panagakis, Timothy Hospedales, Georgios Tzimiropoulos, Nicholas D Lane, Maja Pantic
http://arxiv.org/abs/2110.13859v1
• [cs.LG]Demystifying and Generalizing BinaryConnect
Tim Dockhorn, Yaoliang Yu, Eyyüb Sari, Mahdi Zolnouri, Vahid Partovi Nia
http://arxiv.org/abs/2110.13220v1
• [cs.LG]Disrupting Deep Uncertainty Estimation Without Harming Accuracy
Ido Galil, Ran El-Yaniv
http://arxiv.org/abs/2110.13741v1
• [cs.LG]Distributed Multi-Agent Deep Reinforcement Learning Framework for Whole-building HVAC Control
Vinay Hanumaiah, Sahika Genc
http://arxiv.org/abs/2110.13450v1
• [cs.LG]Distributional Reinforcement Learning for Multi-Dimensional Reward Functions
Pushi Zhang, Xiaoyu Chen, Li Zhao, Wei Xiong, Tao Qin, Tie-Yan Liu
http://arxiv.org/abs/2110.13578v1
• [cs.LG]Distributionally Robust Recurrent Decoders with Random Network Distillation
Antonio Valerio Miceli-Barone, Alexandra Birch, Rico Sennrich
http://arxiv.org/abs/2110.13229v1
• [cs.LG]Diversity and Generalization in Neural Network Ensembles
Luis A. Ortega, Rafael Cabañas, Andrés R. Masegosa
http://arxiv.org/abs/2110.13786v1
• [cs.LG]EDLaaS; Fully Homomorphic Encryption Over Neural Network Graphs
George Onoufriou, Marc Hanheide, Georgios Leontidis
http://arxiv.org/abs/2110.13638v1
• [cs.LG]EarthGAN: Can we visualize the Earth’s mantle convection using a surrogate model?
Tim von Hahn, Chris K. Mechefske
http://arxiv.org/abs/2110.13315v1
• [cs.LG]Emulation of physical processes with Emukit
Andrei Paleyes, Mark Pullin, Maren Mahsereci, Cliff McCollum, Neil D. Lawrence, Javier Gonzalez
http://arxiv.org/abs/2110.13293v1
• [cs.LG]EnTRPO: Trust Region Policy Optimization Method with Entropy Regularization
Sahar Roostaie, Mohammad Mehdi Ebadzadeh
http://arxiv.org/abs/2110.13373v1
• [cs.LG]Exploring System Performance of Continual Learning for Mobile and Embedded Sensing Applications
Young D. Kwon, Jagmohan Chauhan, Abhishek Kumar, Pan Hui, Cecilia Mascolo
http://arxiv.org/abs/2110.13290v1
• [cs.LG]Exponential Graph is Provably Efficient for Decentralized Deep Training
Bicheng Ying, Kun Yuan, Yiming Chen, Hanbin Hu, Pan Pan, Wotao Yin
http://arxiv.org/abs/2110.13363v1
• [cs.LG]FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective
Jingwei Sun, Ang Li, Louis DiValentin, Amin Hassanzadeh, Yiran Chen, Hai Li
http://arxiv.org/abs/2110.13864v1
• [cs.LG]Fast PDE-constrained optimization via self-supervised operator learning
Sifan Wang, Mohamed Aziz Bhouri, Paris Perdikaris
http://arxiv.org/abs/2110.13297v1
• [cs.LG]Geometric Transformer for End-to-End Molecule Properties Prediction
Yoni Choukroun, Lior Wolf
http://arxiv.org/abs/2110.13721v1
• [cs.LG]Goal-Aware Cross-Entropy for Multi-Target Reinforcement Learning
Kibeom Kim, Min Whoo Lee, Yoonsung Kim, Je-Hwan Ryu, Minsu Lee, Byoung-Tak Zhang
http://arxiv.org/abs/2110.12985v2
• [cs.LG]Gradient Descent on Two-layer Nets: Margin Maximization and Simplicity Bias
Kaifeng Lyu, Zhiyuan Li, Runzhe Wang, Sanjeev Arora
http://arxiv.org/abs/2110.13905v1
• [cs.LG]Gradient representations in ReLU networks as similarity functions
Dániel Rácz, Bálint Daróczy
http://arxiv.org/abs/2110.13581v1
• [cs.LG]Heterogeneous Temporal Graph Neural Network
Yujie Fan, Mingxuan Ju, Chuxu Zhang, Liang Zhao, Yanfang Ye
http://arxiv.org/abs/2110.13889v1
• [cs.LG]Hierarchical Transformers Are More Efficient Language Models
Piotr Nawrot, Szymon Tworkowski, Michał Tyrolski, Łukasz Kaiser, Yuhuai Wu, Christian Szegedy, Henryk Michalewski
http://arxiv.org/abs/2110.13711v1
• [cs.LG]Hinge Policy Optimization: Rethinking Policy Improvement and Reinterpreting PPO
Hsuan-Yu Yao, Ping-Chun Hsieh, Kuo-Hao Ho, Kai-Chun Hu, Liang-Chun Ouyang, I-Chen Wu
http://arxiv.org/abs/2110.13799v1
• [cs.LG]Identifying and Benchmarking Natural Out-of-Context Prediction Problems
David Madras, Richard Zemel
http://arxiv.org/abs/2110.13223v1
• [cs.LG]Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning
Junsu Kim, Younggyo Seo, Jinwoo Shin
http://arxiv.org/abs/2110.13625v1
• [cs.LG]Learning Robust Controllers Via Probabilistic Model-Based Policy Search
Valentin Charvet, Bjørn Sand Jensen, Roderick Murray-Smith
http://arxiv.org/abs/2110.13576v1
• [cs.LG]Learning to Pre-process Laser Induced Breakdown Spectroscopy Signals Without Clean Data
Juan Castorena, Diane Oyen
http://arxiv.org/abs/2110.13748v1
• [cs.LG]Learning to Simulate Self-Driven Particles System with Coordinated Policy Optimization
Zhenghao Peng, Quanyi Li, Ka Ming Hui, Chunxiao Liu, Bolei Zhou
http://arxiv.org/abs/2110.13827v1
• [cs.LG]MarS-FL: A Market Share-based Decision Support Framework for Participation in Federated Learning
Xiaohu Wu, Han Yu
http://arxiv.org/abs/2110.13464v1
• [cs.LG]Multi-Faceted Hierarchical Multi-Task Learning for a Large Number of Tasks with Multi-dimensional Relations
Junning Liu, Zijie Xia, Yu Lei, Xinjian Li, Xu Wang
http://arxiv.org/abs/2110.13365v1
• [cs.LG]Multi-Task Meta-Learning Modification with Stochastic Approximation
Andrei Boiarov, Konstantin Khabarlak, Igor Yastrebov
http://arxiv.org/abs/2110.13188v1
• [cs.LG]Multitask Adaptation by Retrospective Exploration with Learned World Models
Artem Zholus, Aleksandr I. Panov
http://arxiv.org/abs/2110.13241v1
• [cs.LG]Negotiating Networks in Oligopoly Markets for Price-Sensitive Products
Naman Shukla, Kartik Yellepeddi
http://arxiv.org/abs/2110.13303v1
• [cs.LG]Nested Graph Neural Networks
Muhan Zhang, Pan Li
http://arxiv.org/abs/2110.13197v1
• [cs.LG]Non-Gaussian Gaussian Processes for Few-Shot Regression
Marcin Sendera, Jacek Tabor, Aleksandra Nowak, Andrzej Bedychaj, Massimiliano Patacchiola, Tomasz Trzciński, Przemysław Spurek, Maciej Zięba
http://arxiv.org/abs/2110.13561v1
• [cs.LG]Non-convex Distributionally Robust Optimization: Non-asymptotic Analysis
Jikai Jin, Bohang Zhang, Haiyang Wang, Liwei Wang
http://arxiv.org/abs/2110.12459v2
• [cs.LG]On the Optimization Landscape of Maximum Mean Discrepancy
Itai Alon, Amir Globerson, Ami Wiesel
http://arxiv.org/abs/2110.13452v1
• [cs.LG]Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD
Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu
http://arxiv.org/abs/2110.13750v1
• [cs.LG]PARIS: Personalized Activity Recommendation for Improving Sleep Quality
Meghna Singh, Saksham Goel, Abhiraj Mohan, Louis Kazaglis, Jaideep Srivastava
http://arxiv.org/abs/2110.13745v1
• [cs.LG]Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks
Pengyong Li, Jun Wang, Ziliang Li, Yixuan Qiao, Xianggen Liu, Fei Ma, Peng Gao, Seng Song, Guotong Xie
http://arxiv.org/abs/2110.13567v1
• [cs.LG]Partial order: Finding Consensus among Uncertain Feature Attributions
Gabriel Laberge, Yann Pequignot, Foutse Khomh, Mario Marchand, Alexandre Mathieu
http://arxiv.org/abs/2110.13369v1
• [cs.LG]Periodic Activation Functions Induce Stationarity
Lassi Meronen, Martin Trapp, Arno Solin
http://arxiv.org/abs/2110.13572v1
• [cs.LG]Prediction-focused Mixture Models
Sanjana Narayanan, Abhishek Sharma, Catherine Zeng, Finale Doshi-Velez
http://arxiv.org/abs/2110.13221v1
• [cs.LG]Probabilistic Entity Representation Model for Chain Reasoning over Knowledge Graphs
Nurendra Choudhary, Nikhil Rao, Sumeet Katariya, Karthik Subbian, Chandan K. Reddy
http://arxiv.org/abs/2110.13522v1
• [cs.LG]Probabilistic Hierarchical Forecasting with Deep Poisson Mixtures
Kin G. Olivares, Nganba Meetei, Ruijun Ma, Rohan Reddy, Mengfei Cao
http://arxiv.org/abs/2110.13179v1
• [cs.LG]Qu-ANTI-zation: Exploiting Quantization Artifacts for Achieving Adversarial Outcomes
Sanghyun Hong, Michael-Andrei Panaitescu-Liess, Yiğitcan Kaya, Tudor Dumitraş
http://arxiv.org/abs/2110.13541v1
• [cs.LG]Reconciling Risk Allocation and Prevalence Estimation in Public Health Using Batched Bandits
Ben Chugg, Daniel E. Ho
http://arxiv.org/abs/2110.13306v1
• [cs.LG]Relay Variational Inference: A Method for Accelerated Encoderless VI
Amir Zadeh, Santiago Benoit, Louis-Philippe Morency
http://arxiv.org/abs/2110.13422v1
• [cs.LG]Robust Learning of Physics Informed Neural Networks
Chandrajit Bajaj, Luke McLennan, Timothy Andeen, Avik Roy
http://arxiv.org/abs/2110.13330v1
• [cs.LG]Scale-Free Adversarial Multi-Armed Bandit with Arbitrary Feedback Delays
Jiatai Huang, Yan Dai, Longbo Huang
http://arxiv.org/abs/2110.13400v1
• [cs.LG]Semi-Supervised Federated Learning with non-IID Data: Algorithm and System Design
Zhe Zhang, Shiyao Ma, Jiangtian Nie, Yi Wu, Qiang Yan, Xiaoke Xu, Dusit Niyato
http://arxiv.org/abs/2110.13388v1
• [cs.LG]Shared Independent Component Analysis for Multi-Subject Neuroimaging
Hugo Richard, Pierre Ablin, Bertrand Thirion, Alexandre Gramfort, Aapo Hyvärinen
http://arxiv.org/abs/2110.13502v1
• [cs.LG]Sinusoidal Flow: A Fast Invertible Autoregressive Flow
Yumou Wei
http://arxiv.org/abs/2110.13344v1
• [cs.LG]TUNet: A Block-online Bandwidth Extension Model based on Transformers and Self-supervised Pretraining
Viet-Anh Nguyen, Anh H. T. Nguyen, Andy W. H. Khong
http://arxiv.org/abs/2110.13492v1
• [cs.LG]Tackling Oversmoothing of GNNs with Contrastive Learning
Lecheng Zheng, Dongqi Fu, Jingrui He
http://arxiv.org/abs/2110.13798v1
• [cs.LG]Tensor Network Kalman Filtering for Large-Scale LS-SVMs
Maximilian Lucassen, Johan A. K. Suykens, Kim Batselier
http://arxiv.org/abs/2110.13501v1
• [cs.LG]The Pareto Frontier of model selection for general Contextual Bandits
Teodor V. Marinov, Julian Zimmert
http://arxiv.org/abs/2110.13282v1
• [cs.LG]Topologically penalized regression on manifolds
Olympio Hacquard, Krishnakumar Balasubramanian, Gilles Blanchard, Wolfgang Polonik, Clément Levrard
http://arxiv.org/abs/2110.13749v1
• [cs.LG]Transportation Scenario Planning with Graph Neural Networks
Ana Alice Peregrino, Soham Pradhan, Zhicheng Liu, Nivan Ferreira, Fabio Miranda
http://arxiv.org/abs/2110.13202v1
• [cs.LG]Understanding Interlocking Dynamics of Cooperative Rationalization
Mo Yu, Yang Zhang, Shiyu Chang, Tommi S. Jaakkola
http://arxiv.org/abs/2110.13880v1
• [cs.LG]Variational framework for partially-measured physical system control: examples of vision neuroscience and optical random media
Babak Rahmani, Demetri Psaltis, Christophe Moser
http://arxiv.org/abs/2110.13228v1
• [cs.LG]Vector-valued Distance and Gyrocalculus on the Space of Symmetric Positive Definite Matrices
Federico López, Beatrice Pozzetti, Steve Trettel, Michael Strube, Anna Wienhard
http://arxiv.org/abs/2110.13475v1
• [cs.NE]An Embedded System for Image-based Crack Detection by using Fine-Tuning model of Adaptive Structural Learning of Deep Belief Network
Shin Kamada, Takumi Ichimura
http://arxiv.org/abs/2110.13145v1
• [cs.NI]Adaptive Probabilistic Model for Energy-Efficient Distance-based Clustering in WSNs (Adapt-P): A LEACH-based Analytical Study
Husam Suleiman, Mohammad Hamdan
http://arxiv.org/abs/2110.13300v1
• [cs.RO]2D Grid Map Generation for Deep-Learning-based Navigation Approaches
Gabriel O. Flores-Aquino, Jheison Duvier Díaz Ortega, Ricardo Yahir Almazan Arvizu, Raúl López Muñoz, O. Octavio Gutierrez-Frias, J. Irving Vasquez-Gomez
http://arxiv.org/abs/2110.13242v1
• [cs.RO]Driving Style Recognition Using Interval Type-2 Fuzzy Inference System and Multiple Experts Decision Making
Iago Pachêco Gomes, Denis Fernando Wolf
http://arxiv.org/abs/2110.13805v1
• [cs.RO]Improving Robustness of Deep Neural Networks for Aerial Navigation by Incorporating Input Uncertainty
Fabio Arnez, Huascar Espinoza, Ansgar Radermarcher, François Terrier
http://arxiv.org/abs/2110.13729v1
• [cs.RO]MEKF Ignoring Initial Conditions for Attitude Estimation Using Vector Observations
Lubin Chang
http://arxiv.org/abs/2110.13666v1
• [cs.RO]Research on the inverse kinematics prediction of a soft actuator via BP neural network
Huichen Ma, Junjie Zhou, Jian Zhang, Lingyu Zhang
http://arxiv.org/abs/2110.13418v1
• [cs.RO]Synchronous-Clock Range-Angle Relative Acoustic Navigation: A Unified Approach to Multi-AUV Localization, Command, Control and Coordination
Nicholas R. Rypkema, Henrik Schmidt, Erin M. Fischell
http://arxiv.org/abs/2110.13825v1
• [cs.RO]Towards More Generalizable One-shot Visual Imitation Learning
Zhao Mandi, Fangchen Liu, Kimin Lee, Pieter Abbeel
http://arxiv.org/abs/2110.13423v1
• [cs.SD]CS-Rep: Making Speaker Verification Networks Embracing Re-parameterization
Ruiteng Zhang, Jianguo Wei, Wenhuan Lu, Lin Zhang, Yantao Ji, Junhai Xu, Xugang Lu
http://arxiv.org/abs/2110.13465v1
• [cs.SD]Deep Learning Tools for Audacity: Helping Researchers Expand the Artist’s Toolkit
Hugo Flores Garcia, Aldo Aguilar, Ethan Manilow, Dmitry Vedenko, Bryan Pardo
http://arxiv.org/abs/2110.13323v1
• [cs.SE]Automated Support for Unit Test Generation: A Tutorial Book Chapter
Afonso Fontes, Gregory Gay, Francisco Gomes de Oliveira Neto, Robert Feldt
http://arxiv.org/abs/2110.13575v1
• [cs.SE]Memory visualization tool for training neural network
Mahendran N
http://arxiv.org/abs/2110.13264v1
• [cs.SI]A Pipeline for Graph-Based Monitoring of the Changes in the Information Space of Russian Social Media during the Lockdown
V. Danilova, S. Popova, V. Karpova
http://arxiv.org/abs/2110.13626v1
• [cs.SI]Comparison of Indicators of Location Homophily Using Twitter Follow Graph
Shiori Hironaka, Mitsuo Yoshida, Kyoji Umemura
http://arxiv.org/abs/2110.13410v1
• [cs.SI]How to Quantify Polarization in Models of Opinion Dynamics
Christopher Musco, Indu Ramesh, Johan Ugander, R. Teal Witter
http://arxiv.org/abs/2110.11981v2
• [cs.SI]NetMF+: Network Embedding Based on Fast and Effective Single-Pass Randomized Matrix Factorization
Yuyang Xie, Jiezhong Qiu, Wenjian Yu, Xu Feng, Yuxiang Chen, Jie Tang
http://arxiv.org/abs/2110.12782v2
• [cs.SI]Quantitative Evaluation of Snapshot Graphs for the Analysis of Temporal Networks
Alessandro Chiappori, Rémy Cazabet
http://arxiv.org/abs/2110.13466v1
• [cs.SI]Sampling Multiple Nodes in Large Networks: Beyond Random Walks
Omri Ben-Eliezer, Talya Eden, Joel Oren, Dimitris Fotakis
http://arxiv.org/abs/2110.13324v1
• [cs.SI]TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation
Ling Chen, Da Wang, Dandan Lyu, Xing Tang, Hongyu Shi
http://arxiv.org/abs/2110.13596v1
• [cs.SI]The Mont Blanc of Twitter: Identifying Hierarchies of Outstanding Peaks in Social Networks
Maximilian Stubbemann, Gerd Stumme
http://arxiv.org/abs/2110.13774v1
• [econ.EM]A new inequality measurement tool: The Vinci index
Mario Schlemmer
http://arxiv.org/abs/2110.13847v1
• [econ.EM]Covariate Balancing Methods for Randomized Controlled Trials Are Not Adversarially Robust
Hossein Babaei, Sina Alemohammad, Richard Baraniuk
http://arxiv.org/abs/2110.13262v1
• [econ.EM]Inference in Regression Discontinuity Designs with High-Dimensional Covariates
Alexander Kreiß, Christoph Rothe
http://arxiv.org/abs/2110.13725v1
• [eess.IV]A Closer Look at Reference Learning for Fourier Phase Retrieval
Tobias Uelwer, Nick Rucks, Stefan Harmeling
http://arxiv.org/abs/2110.13688v1
• [eess.IV]A Precision Diagnostic Framework of Renal Cell Carcinoma on Whole-Slide Images using Deep Learning
Jialun Wu, Haichuan Zhang, Zeyu Gao, Xinrui Bao, Tieliang Gong, Chunbao Wang, Chen Li
http://arxiv.org/abs/2110.13652v1
• [eess.IV]An Automatic Detection Method Of Cerebral Aneurysms In Time-Of-Flight Magnetic Resonance Angiography Images Based On Attention 3D U-Net
Chen Geng, Meng Chen, Ruoyu Di, Dongdong Wang, Liqin Yang, Wei Xia, Yuxin Li, Daoying Geng
http://arxiv.org/abs/2110.13367v1
• [eess.IV]Deep DIC: Deep Learning-Based Digital Image Correlation for End-to-End Displacement and Strain Measurement
Ru Yang, Yang Li, Danielle Zeng, Danielle Zeng
http://arxiv.org/abs/2110.13720v1
• [eess.IV]Deep Learning-based Segmentation of Cerebral Aneurysms in 3D TOF-MRA using Coarse-to-Fine Framework
Meng Chen, Chen Geng, Dongdong Wang, Jiajun Zhang, Ruoyu Di, Fengmei Li, Zhiyong Zhou, Sirong Piao, Yuxin Li, Yaikang Dai
http://arxiv.org/abs/2110.13432v1
• [eess.IV]Image Magnification Network for Vessel Segmentation in OCTA Images
Mingchao Li, Yerui Chen, Weiwei Zhang, Qiang Chen
http://arxiv.org/abs/2110.13428v1
• [eess.IV]RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network
Rao Muhammad Umer, Christian Micheloni
http://arxiv.org/abs/2110.13217v1
• [eess.IV]Real-time division-of-focal-plane polarization imaging system with progressive networks
Rongyuan Wu, Yongqiang Zhao, Ning Li, Seong G. Kong
http://arxiv.org/abs/2110.13823v1
• [eess.IV]W-Net: A Two-Stage Convolutional Network for Nucleus Detection in Histopathology Image
Anyu Mao, Jialun Wu, Xinrui Bao, Zeyu Gao, Tieliang Gong, Chen Li
http://arxiv.org/abs/2110.13670v1
• [eess.SP]An Analysis of LOS Coverage in Vehicular Networks with Roadside Units and Relays
Chang-Sik Choi, François Baccelli
http://arxiv.org/abs/2110.13436v1
• [hep-lat]Machine learning spectral functions in lattice QCD
S. -Y. Chen, H. -T. Ding, F. -Y. Liu, G. Papp, C. -B. Yang
http://arxiv.org/abs/2110.13521v1
• [math.DS]Real-time Human Response Prediction Using a Non-intrusive Data-driven Model Reduction Scheme
Jonas Kneifl, Julian Hay, Jörg Fehr
http://arxiv.org/abs/2110.13583v1
• [math.OC]Faster Perturbed Stochastic Gradient Methods for Finding Local Minima
Zixiang Chen, Dongruo Zhou, Quanquan Gu
http://arxiv.org/abs/2110.13144v1
• [math.OC]On the Second-order Convergence Properties of Random Search Methods
Aurelien Lucchi, Antonio Orvieto, Adamos Solomou
http://arxiv.org/abs/2110.13265v1
• [math.PR]A Constructive Proof of the Glivenko-Cantelli Theorem
Daniel Salnikov
http://arxiv.org/abs/2110.13236v1
• [math.ST]Bayesian Estimation and Comparison of Conditional Moment Models
Siddhartha Chib, Minchul Shin, Anna Simoni
http://arxiv.org/abs/2110.13531v1
• [math.ST]Debiased and threshold ridge regression for linear model with heteroskedastic and dependent error
Yunyi Zhang, Dimitris N. Politis
http://arxiv.org/abs/2110.13498v1
• [math.ST]Equivariant Estimation of the Selected Guarantee Time
Masihuddin, Neeraj Misra
http://arxiv.org/abs/2110.13842v1
• [math.ST]Note on the approximation of the conditional intensity of non-stationary cluster
5851
point processes
Edith Gabriel, Joël Chadoeuf
http://arxiv.org/abs/2110.13738v1
• [math.ST]Optimal Bayesian Estimation of a Regression Curve, a Conditional Density and a Conditional Distribution
A. G. Nogales
http://arxiv.org/abs/2110.13427v1
• [physics.comp-ph]Physics-Informed Neural Networks (PINNs) for Parameterized PDEs: A Metalearning Approach
Michael Penwarden, Shandian Zhe, Akil Narayan, Robert M. Kirby
http://arxiv.org/abs/2110.13361v1
• [physics.flu-dyn]Physics Informed Machine Learning of SPH: Machine Learning Lagrangian Turbulence
Michael Woodward, Yifeng Tian, Criston Hyett, Chris Fryer, Daniel Livescu, Mikhail Stepanov, Michael Chertkov
http://arxiv.org/abs/2110.13311v1
• [physics.soc-ph]On the consequences of draw restrictions in knockout tournaments
László Csató
http://arxiv.org/abs/2110.13641v1
• [physics.soc-ph]Relations between anomalous diffusion and fluctuation scaling: The case of ultraslow diffusion and time-scale-independent fluctuation scaling in language
Hayafumi Watanabe
http://arxiv.org/abs/2110.13868v1
• [q-bio.PE]Optimal non-pharmaceutical intervention policy for Covid-19 epidemic via neuroevolution algorithm
Arash Saeidpour, Pejman Rohani
http://arxiv.org/abs/2110.13633v1
• [q-fin.ST]HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information
Wentao Xu, Weiqing Liu, Lewen Wang, Yingce Xia, Jiang Bian, Jian Yin, Tie-Yan Liu
http://arxiv.org/abs/2110.13716v1
• [quant-ph]Quantum machine learning beyond kernel methods
Sofiene Jerbi, Lukas J. Fiderer, Hendrik Poulsen Nautrup, Jonas M. Kübler, Hans J. Briegel, Vedran Dunjko
http://arxiv.org/abs/2110.13162v1
• [stat.AP]A Feasibility Study of Differentially Private Summary Statistics and Regression Analyses for Administrative Tax Data
Andrés F. Barrientos, Aaron R. Williams, Joshua Snoke, Claire McKay Bowen
http://arxiv.org/abs/2110.12055v1
• [stat.AP]Analyzing the Data of COVID-19 with Quasi-Distribution Fitting Based on Piecewise B-spline Curves
Qingliang Zhao, Zhenhuan Lu, Yiduo Wang
http://arxiv.org/abs/2110.13391v1
• [stat.AP]On the analysis of the temperature fluctuation in the Campi Flegrei caldera through a fractional Brownian motion-based model
A. Di Crescenzo, B. Martinucci, V. Mustaro
http://arxiv.org/abs/2110.13546v1
• [stat.ME]Highly Scalable Maximum Likelihood and Conjugate Bayesian Inference for ERGMs on Graph Sets with Equivalent Vertices
Fan Yin, Carter T. Butts
http://arxiv.org/abs/2110.13527v1
• [stat.ME]On Monitoring High-Dimensional Multivariate Processes with Individual Observations
Mohsen Ebadi, Shojaeddin Chenouri, Stefan H. Steiner
http://arxiv.org/abs/2110.13696v1
• [stat.ME]Phase I Analysis of High-Dimensional Multivariate Processes in the Presence of Outliers
Mohsen Ebadi, Shojaeddin Chenouri, Stefan H. Steiner
http://arxiv.org/abs/2110.13689v1
• [stat.ME]Towards Optimal Variance Reduction in Online Controlled Experiments
Ying Jin, Shan Ba
http://arxiv.org/abs/2110.13406v1
• [stat.ML]Dynamic Causal Bayesian Optimization
Virginia Aglietti, Neil Dhir, Javier González, Theodoros Damoulas
http://arxiv.org/abs/2110.13891v1
• [stat.ML]Gradient-based Quadratic Multiform Separation
Wen-Teng Chang
http://arxiv.org/abs/2110.13006v2
• [stat.ML]Improving the efficacy of Deep Learning models for Heart Beat detection on heterogeneous datasets
Andrea Bizzego, Giulio Gabrieli, Michelle Jin-Yee Neoh, Gianluca Esposito
http://arxiv.org/abs/2110.13732v1
• [stat.ML]Integrative Clustering of Multi-View Data by Nonnegative Matrix Factorization
Shuo Shuo Liu, Lin Lin
http://arxiv.org/abs/2110.13240v1
• [stat.ML]Min-similarity association rules for identifying past comorbidities of recurrent ED and inpatient patients
Luoluo Liu, Eran Simhon, Chaitanya Kulkarni, Ronny Mans
http://arxiv.org/abs/2110.13769v1
• [stat.ML]Modular Gaussian Processes for Transfer Learning
Pablo Moreno-Muñoz, Antonio Artés-Rodríguez, Mauricio A. Álvarez
http://arxiv.org/abs/2110.13515v1
• [stat.ML]Online Variational Filtering and Parameter Learning
Andrew Campbell, Yuyang Shi, Tom Rainforth, Arnaud Doucet
http://arxiv.org/abs/2110.13549v1
• [stat.ML]Post-processing for Individual Fairness
Felix Petersen, Debarghya Mukherjee, Yuekai Sun, Mikhail Yurochkin
http://arxiv.org/abs/2110.13796v1
• [stat.ML]Revisiting randomized choices in isolation forests
David Cortes
http://arxiv.org/abs/2110.13402v1
• [stat.ML]Uncertainty quantification in a mechanical submodel driven by a Wasserstein-GAN
Hamza Boukraichi, Nissrine Akkari, Fabien Casenave, David Ryckelynck
http://arxiv.org/abs/2110.13680v1
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