cs.AI - 人工智能
cs.AR - 硬件体系结构
cs.CC - 计算复杂度
cs.CL - 计算与语言
cs.CR - 加密与安全
cs.CV - 机器视觉与模式识别
cs.CY - 计算与社会
cs.DC - 分布式、并行与集群计算
cs.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.MM - 多媒体
cs.NE - 神经与进化计算
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
econ.GN - 一般经济学
eess.AS - 语音处理
eess.IV - 图像与视频处理
eess.SP - 信号处理
eess.SY - 系统和控制
math.NA - 数值分析
math.OC - 优化与控制
math.ST - 统计理论
physics.soc-ph - 物理学与社会
q-bio.BM - 生物分子
q-bio.NC - 神经元与认知
stat.AP - 应用统计
stat.CO - 统计计算
stat.ME - 统计方法论
stat.ML - (统计)机器学习
• [cs.AI]A Data-Centric Approach for Training Deep Neural Networks with Less Data
• [cs.AI]A Fast Randomized Algorithm for Massive Text Normalization
• [cs.AI]Automated Testing of AI Models
• [cs.AI]Belief Evolution Network: Probability Transformation of Basic Belief Assignment and Fusion Conflict Probability
• [cs.AI]Cartoon Explanations of Image Classifiers
• [cs.AI]Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling
• [cs.AI]Efficient Sharpness-aware Minimization for Improved Training of Neural Networks
• [cs.AI]From Weighted Conditionals of Multilayer Perceptrons to a Gradual Argumentation Semantics
• [cs.AI]GNN is a Counter? Revisiting GNN for Question Answering
• [cs.AI]Goal-Directed Design Agents: Integrating Visual Imitation with One-Step Lookahead Optimization for Generative Design
• [cs.AI]Inferring Substitutable and Complementary Products with Knowledge-Aware Path Reasoning based on Dynamic Policy Network
• [cs.AI]Learning a Metacognition for Object Detection
• [cs.AI]SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming
• [cs.AI]Self-Evolutionary Optimization for Pareto Front Learning
• [cs.AI]Towards Federated Learning-Enabled Visible Light Communication in 6G Systems
• [cs.AR]Shift-BNN: Highly-Efficient Probabilistic Bayesian Neural Network Training via Memory-Friendly Pattern Retrieving
• [cs.CC]On the Complexity of Inductively Learning Guarded Rules
• [cs.CL]A Logic-Based Framework for Natural Language Inference in Dutch
• [cs.CL]Adversarial Retriever-Ranker for dense text retrieval
• [cs.CL]Applying Phonological Features in Multilingual Text-To-Speech
• [cs.CL]Back from the future: bidirectional CTC decoding using future information in speech recognition
• [cs.CL]Beam Search with Bidirectional Strategies for Neural Response Generation
• [cs.CL]Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot Filling
• [cs.CL]Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning in NLP
• [cs.CL]Cross-Language Learning for Entity Matching
• [cs.CL]Cut the CARP: Fishing for zero-shot story evaluation
• [cs.CL]GeSERA: General-domain Summary Evaluation by Relevance Analysis
• [cs.CL]HowSumm: A Multi-Document Summarization Dataset Derived from WikiHow Articles
• [cs.CL]Influence Tuning: Demoting Spurious Correlations via Instance Attribution and Instance-Driven Updates
• [cs.CL]Integrating Categorical Features in End-to-End ASR
• [cs.CL]Layer-wise Pruning of Transformer Attention Heads for Efficient Language Modeling
• [cs.CL]Magic dust for cross-lingual adaptation of monolingual wav2vec-2.0
• [cs.CL]Mandarin-English Code-switching Speech Recognition with Self-supervised Speech Representation Models
• [cs.CL]Multi-tasking Dialogue Comprehension with Discourse Parsing
• [cs.CL]NUS-IDS at FinCausal 2021: Dependency Tree in Graph Neural Network for Better Cause-Effect Span Detection
• [cs.CL]Noisy Text Data: Achilles’ Heel of popular transformer based NLP models
• [cs.CL]On Neurons Invariant to Sentence Structural Changes in Neural Machine Translation
• [cs.CL]PSG@HASOC-Dravidian CodeMixFIRE2021: Pretrained Transformers for Offensive Language Identification in Tanglish
• [cs.CL]PoNet: Pooling Network for Efficient Token Mixing in Long Sequences
• [cs.CL]Sequence-to-Sequence Lexical Normalization with Multilingual Transformers
• [cs.CL]Situated Dialogue Learning through Procedural Environment Generation
• [cs.CL]The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation
• [cs.CL]Towards Continual Knowledge Learning of Language Models
• [cs.CL]Transliteration of Foreign Words in Burmese
• [cs.CL]Unsupervised Multimodal Language Representations using Convolutional Autoencoders
• [cs.CL]mRAT-SQL+GAP:A Portuguese Text-to-SQL Transformer
• [cs.CR]Complex-valued deep learning with differential privacy
• [cs.CR]DoubleStar: Long-Range Attack Towards Depth Estimation based Obstacle Avoidance in Autonomous Systems
• [cs.CR]Neural Networks, Inside Out: Solving for Inputs Given Parameters (A Preliminary Investigation)
• [cs.CR]On The Vulnerability of Recurrent Neural Networks to Membership Inference Attacks
• [cs.CR]PWG-IDS: An Intrusion Detection Model for Solving Class Imbalance in IIoT Networks Using Generative Adversarial Networks
• [cs.CV]2nd Place Solution to Google Landmark Recognition Competition 2021
• [cs.CV]3rd Place Solution to Google Landmark Recognition Competition 2021
• [cs.CV]A Baseline Framework for Part-level Action Parsing and Action Recognition
• [cs.CV]A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction
• [cs.CV]A New Simple Vision Algorithm for Detecting the Enzymic Browning Defects in Golden Delicious Apples
• [cs.CV]ATISS: Autoregressive Transformers for Indoor Scene Synthesis
• [cs.CV]Burst Image Restoration and Enhancement
• [cs.CV]Camera Calibration through Camera Projection Loss
• [cs.CV]Colored Point Cloud to Image Alignment
• [cs.CV]Deep Learning Model Explainability for Inspection Accuracy Improvement in the Automotive Industry
• [cs.CV]DeepBBS: Deep Best Buddies for Point Cloud Registration
• [cs.CV]Dense Gaussian Processes for Few-Shot Segmentation
• [cs.CV]Design of an Intelligent Vision Algorithm for Recognition and Classification of Apples in an Orchard Scene
• [cs.CV]Differential Anomaly Detection for Facial Images
• [cs.CV]Dynamically Decoding Source Domain Knowledge For Unseen Domain Generalization
• [cs.CV]End-to-End Supermask Pruning: Learning to Prune Image Captioning Models
• [cs.CV]Estimating Image Depth in the Comics Domain
• [cs.CV]FOD-A: A Dataset for Foreign Object Debris in Airports
• [cs.CV]Gradient Step Denoiser for convergent Plug-and-Play
• [cs.CV]Improving Fractal Pre-training
• [cs.CV]InfoSeg: Unsupervised Semantic Image Segmentation with Mutual Information Maximization
• [cs.CV]Large-Scale Topological Radar Localization Using Learned Descriptors
• [cs.CV]Learning Canonical Embedding for Non-rigid Shape Matching
• [cs.CV]Learning to Regress Bodies from Images using Differentiable Semantic Rendering
• [cs.CV]MC-LCR: Multi-modal contrastive classification by locally correlated representations for effective face forgery detection
• [cs.CV]MGPSN: Motion-Guided Pseudo Siamese Network for Indoor Video Head Detection
• [cs.CV]MSHCNet: Multi-Stream Hybridized Convolutional Networks with Mixed Statistics in Euclidean/Non-Euclidean Spaces and Its Application to Hyperspectral Image Classification
• [cs.CV]Meta-UDA: Unsupervised Domain Adaptive Thermal Object Detection using Meta-Learning
• [cs.CV]Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data
• [cs.CV]Moment evolution equations and moment matching for stochastic image EPDiff
• [cs.CV]On Cropped versus Uncropped Training Sets in Tabular Structure Detection
• [cs.CV]Player Tracking and Identification in Ice Hockey
• [cs.CV]RAR: Region-Aware Point Cloud Registration
• [cs.CV]SPEED+: Next Generation Dataset for Spacecraft Pose Estimation across Domain Gap
• [cs.CV]Scale Invariant Domain Generalization Image Recapture Detection
• [cs.CV]Self-Supervised Depth Completion for Active Stereo
• [cs.CV]Towards Accurate Cross-Domain In-Bed Human Pose Estimation
• [cs.CV]TreeGCN-ED: Encoding Point Cloud using a Tree-Structured Graph Network
• [cs.CV]Unsupervised Image Decomposition with Phase-Correlation Networks
• [cs.CV]Using Contrastive Learning and Pseudolabels to learn representations for Retail Product Image Classification
• [cs.CV]Using Keypoint Matching and Interactive Self Attention Network to verify Retail POSMs
• [cs.CV]Virtual Multi-Modality Self-Supervised Foreground Matting for Human-Object Interaction
• [cs.CV]Vision-based Excavator Activity Analysis and Safety Monitoring System
• [cs.CV]Weakly Supervised Human-Object Interaction Detection in Video via Contrastive Spatiotemporal Regions
• [cs.CY]What motivates people to telework? Explorat
1000
ory study in a post-confinement context
• [cs.DC]I
1000
aaS Signature Change Detection with Performance Noise
• [cs.DC]MAPA: Multi-Accelerator Pattern Allocation Policy for Multi-Tenant GPU Servers
• [cs.HC]Evolutionary Computation-Assisted Brainwriting for Large-Scale Online Ideation
• [cs.HC]From the Head or the Heart? An Experimental Design on the Impact of Explanation on Cognitive and Affective Trust
• [cs.HC]Human in the Loop for Machine Creativity
• [cs.HC]Posture Recognition in the Critical Care Settings using Wearable Devices
• [cs.IR]Doing Data Right: How Lessons Learned Working with Conventional Data should Inform the Future of Synthetic Data for Recommender Systems
• [cs.IR]Optimized Recommender Systems with Deep Reinforcement Learning
• [cs.IR]Recent Advances in Heterogeneous Relation Learning for Recommendation
• [cs.IT]A Rate Splitting Strategy for Uplink CR-NOMA Systems
• [cs.IT]Minimum Message Length Autoregressive Moving Average Model Order Selection
• [cs.IT]Pointwise Bounds for Distribution Estimation under Communication Constraints
• [cs.IT]Privacy-Preserving Coded Mobile Edge Computing for Low-Latency Distributed Inference
• [cs.IT]Structured Channel Covariance Estimation from Limited Samples for Large Antenna Arrays
• [cs.IT]What Should 6G Architectures Be?
• [cs.LG]A Broad Ensemble Learning System for Drifting Stream Classification
• [cs.LG]A Model Selection Approach for Corruption Robust Reinforcement Learning
• [cs.LG]A Survey on Evidential Deep Learning For Single-Pass Uncertainty Estimation
• [cs.LG]A Uniform Framework for Anomaly Detection in Deep Neural Networks
• [cs.LG]Active Learning of Markov Decision Processes using Baum-Welch algorithm (Extended)
• [cs.LG]AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow
• [cs.LG]Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks
• [cs.LG]Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective
• [cs.LG]Bad-Policy Density: A Measure of Reinforcement Learning Hardness
• [cs.LG]Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators
• [cs.LG]Boxhead: A Dataset for Learning Hierarchical Representations
• [cs.LG]CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability
• [cs.LG]Coresets for Decision Trees of Signals
• [cs.LG]Creating Training Sets via Weak Indirect Supervision
• [cs.LG]Cross-Domain Imitation Learning via Optimal Transport
• [cs.LG]Darts: User-Friendly Modern Machine Learning for Time Series
• [cs.LG]Data-Centric AI Requires Rethinking Data Notion
• [cs.LG]Data-Centric Semi-Supervised Learning
• [cs.LG]Detecting Autism Spectrum Disorders with Machine Learning Models Using Speech Transcripts
• [cs.LG]Disentangling deep neural networks with rectified linear units using duality
• [cs.LG]Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees
• [cs.LG]Distributed Optimization of Graph Convolutional Network using Subgraph Variance
• [cs.LG]Double Descent in Adversarial Training: An Implicit Label Noise Perspective
• [cs.LG]EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits
• [cs.LG]EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback
• [cs.LG]Efficient Methods for Online Multiclass Logistic Regression
• [cs.LG]Enabling On-Device Training of Speech Recognition Models with Federated Dropout
• [cs.LG]EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware Detection
• [cs.LG]Explaining Deep Reinforcement Learning Agents In The Atari Domain through a Surrogate Model
• [cs.LG]Fast learning from label proportions with small bags
• [cs.LG]Federated Learning from Small Datasets
• [cs.LG]Federated Learning via Plurality Vote
• [cs.LG]Federating for Learning Group Fair Models
• [cs.LG]Frame Averaging for Invariant and Equivariant Network Design
• [cs.LG]Generalization in Deep RL for TSP Problems via Equivariance and Local Search
• [cs.LG]Generative Modeling with Optimal Transport Maps
• [cs.LG]Generative Optimization Networks for Memory Efficient Data Generation
• [cs.LG]How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents
• [cs.LG]Hybrid Pointer Networks for Traveling Salesman Problems Optimization
• [cs.LG]Hyperparameter Tuning with Renyi Differential Privacy
• [cs.LG]Improving Adversarial Robustness for Free with Snapshot Ensemble
• [cs.LG]Improving MC-Dropout Uncertainty Estimates with Calibration Error-based Optimization
• [cs.LG]Is Attention always needed? A Case Study on Language Identification from Speech
• [cs.LG]Joint calibration and mapping of satellite altimetry data using trainable variational models
• [cs.LG]Lagrangian Neural Network with Differential Symmetries and Relational Inductive Bias
• [cs.LG]Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect
• [cs.LG]Learning Multi-Objective Curricula for Deep Reinforcement Learning
• [cs.LG]Learning Pessimism for Robust and Efficient Off-Policy Reinforcement Learning
• [cs.LG]Learning the Optimal Recommendation from Explorative Users
• [cs.LG]Multi-Head ReLU Implicit Neural Representation Networks
• [cs.LG]Multi-objective Optimization by Learning Space Partitions
• [cs.LG]Multivariate Anomaly Detection based on Prediction Intervals Constructed using Deep Learning
• [cs.LG]Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver
• [cs.LG]Neural Tangent Kernel Empowered Federated Learning
• [cs.LG]Offline RL With Resource Constrained Online Deployment
• [cs.LG]On Margin Maximization in Linear and ReLU Networks
• [cs.LG]On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications
• [cs.LG]On the Latent Holes of VAEs for Text Generation
• [cs.LG]On the Optimal Memorization Power of ReLU Neural Networks
• [cs.LG]On the relationship between disentanglement and multi-task learning
• [cs.LG]One Thing to Fool them All: Generating Interpretable, Universal, and Physically-Realizable Adversarial Features
• [cs.LG]Online Markov Decision Processes with Non-oblivious Strategic Adversary
• [cs.LG]Permutation Compressors for Provably Faster Distributed Nonconvex Optimization
• [cs.LG]Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training
• [cs.LG]Probabilistic Metamodels for an Efficient Characterization of Complex Driving Scenarios
• [cs.LG]Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates
• [cs.LG]RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
• [cs.LG]SWAT Watershed Model Calibration using Deep Learning
• [cs.LG]Score-based Generative Neural Networks for Large-Scale Optimal Transport
• [cs.LG]Sparse MoEs meet Efficient Ensembles
• [cs.LG]The Connection between Out-of-Distribution Generalization and Privacy of ML Models
• [cs.LG]Tile Embedding: A General Representation for Procedural Level Generation via Machine Learning
• [cs.LG]To Charge or To Sell? EV Pack Useful Life Estimation via LSTMs and Autoencoders
• [cs.LG]Towards Robust and Transferable IIoT Sensor based Anomaly Classification using Artificial Intelligence
• [cs.LG]Training Stable Graph Neural Networks Through Constrained Learning
• [cs.LG]Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design
• [cs.LG]Tribuo: Machine Learning with Provenance in Java
• [cs.LG]Two-Bit Aggregation for Communication Efficient and Differentially Private Federated Learning
• [cs.LG]Understanding Domain Randomization for Sim-to-real Transfer
• [cs.LG]Universal Approximation Under Constraints is Possible with Transformers
• [cs.LG]Universality of Deep Neural Network Lottery Tickets: A Renormalization Group Perspective
• [cs.LG]Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective
• [cs.MA]School Virus Infection Simulator for Customizing School Schedules During COVID-19
• [cs.MM]TranSalNet: Visual saliency prediction using transformers
• [cs.NE]Assemblies of neurons can learn to classify well-separated distributions
• [cs.NE]Cloud Failure Prediction with Hierarchical Temporary Memory: An Empirical Assessment
• [cs.RO]Active Extrinsic Contact Sensing: Application to General Peg-in-Hole Insertion
• [cs.RO]Adaptive Safety Margin Estimation for Safe Real-Time Replanning under Time-Varying Disturbance
• [cs.RO]Correct Me if I am Wrong: Interactive Learning for Robotic Manipulation
• [cs.RO]Empirical Analysis of Bi-directional Wi-Fi Network Performance on Mobile Robots and Connected Vehicles
• [cs.RO]Evaluating model-based planning and planner amortization for continuous control
• [cs.RO]Human Capabilities as Guiding Lights for the Field of AI-HRI: Insights from Engineering Education
• [cs.RO]Improving Robot-Centric Learning from Demonstration via Personalized Embeddings
• [cs.RO]Injecting Planning-Awareness into Prediction and Detection Evaluation
• [cs.RO]Propagating State Uncertainty Through Trajectory Forecasting
• [cs.RO]RHH-LGP: Receding Horizon And Heuristics-Based Logic-Geometric Programming For Task And Motion Planning
• [cs.RO]Reactive Locomotion Decision-Making and Robust Motion Planning for Real-Time Perturbation
80e
Recovery
• [cs.RO]Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations
• [cs.SD]Attention is All You Need? Good Embeddings with Statistics are enough: Audio Understanding WITHOUT Convolutions/Transformers/BERTs/Mixers/Attention/RNNs or ….
• [cs.SD]Disentangled dimensionality reduction for noise-robust speaker diarisation
• [cs.SD]GANtron: Emotional Speech Synthesis with Generative Adversarial Networks
• [cs.SD]SERAB: A multi-lingual benchmark for speech emotion recognition
• [cs.SD]StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis
• [cs.SD]Transferring Voice Knowledge for Acoustic Event Detection: An Empirical Study
• [cs.SD]WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognition
• [cs.SE]DRAFT-What you always wanted to know but could not find about block-based environments
• [cs.SI]Analysis of the influence of political polarization in the vaccination stance: the Brazilian COVID-19 scenario
• [cs.SI]Joint inference of multiple graphs with hidden variables from stationary graph signals
• [cs.SI]Revisiting SVD to generate powerful Node Embeddings for Recommendation Systems
• [econ.EM]Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model
• [econ.GN]Unpacking the Black Box: Regulating Algorithmic Decisions
• [eess.AS]CTC Variations Through New WFST Topologies
• [eess.AS]Emphasis control for parallel neural TTS
• [eess.AS]End-to-end label uncertainty modeling for speech emotion recognition using Bayesian neural networks
• [eess.AS]Improving Confidence Estimation on Out-of-Domain Data for End-to-End Speech Recognition
• [eess.AS]Peer Collaborative Learning for Polyphonic Sound Event Detection
• [eess.AS]Transcribe-to-Diarize: Neural Speaker Diarization for Unlimited Number of Speakers using End-to-End Speaker-Attributed ASR
• [eess.AS]VisualTTS: TTS with Accurate Lip-Speech Synchronization for Automatic Voice Over
• [eess.IV]A transformer-based deep learning approach for classifying brain metastases into primary organ sites using clinical whole brain MRI images
• [eess.IV]AnoSeg: Anomaly Segmentation Network Using Self-Supervised Learning
• [eess.IV]Generic tool for numerical simulation of transformation-diffusion processes in complex volume geometric shapes: application to microbial decomposition of organic matter
• [eess.IV]Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
• [eess.IV]Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning
• [eess.IV]Multi-Scale Convolutional Neural Network for Automated AMD Classification using Retinal OCT Images
• [eess.IV]Optimized U-Net for Brain Tumor Segmentation
• [eess.IV]Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image Enhancement
• [eess.SP]Joint optimization of system design and reconstruction in MIMO radar imaging
• [eess.SY]Uncertainty Set Prediction of Aggregated Wind Power Generation based on Bayesian LSTM and Spatio-Temporal Analysis
• [math.NA]Time Series Forecasting Using Manifold Learning
• [math.OC]A Hybrid Direct-Iterative Method for Solving KKT Linear Systems
• [math.OC]A Stochastic Newton Algorithm for Distributed Convex Optimization
• [math.OC]Explicitly Multi-Modal Benchmarks for Multi-Objective Optimization
• [math.OC]Predictability and Fairness in Load Aggregation and Operations of Virtual Power Plants
• [math.OC]Solving Multistage Stochastic Linear Programming via Regularized Linear Decision Rules: An Application to Hydrothermal Dispatch Planning
• [math.ST]Graph sampling by lagged random walk
• [math.ST]High Dimensional Logistic Regression Under Network Dependence
• [math.ST]Neural Estimation of Statistical Divergences
• [physics.soc-ph]Physics-inspired analysis of the two-class income distribution in the USA in 1983-2018
• [q-bio.BM]Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond
• [q-bio.NC]A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint
• [stat.AP]A Critical Review of the Baseline Soldier Physical Readiness Requirements Study
• [stat.AP]Acoustic Signal based Non-Contact Ball Bearing Fault Diagnosis Using Adaptive Wavelet Denoising
• [stat.AP]Int
53f4
erpretable Machine Learning for Genomics
• [stat.AP]Regression markets and application to energy forecasting
• [stat.AP]Tracking the national and regional COVID-19 epidemic status in the UK using directed Principal Component Analysis
• [stat.CO]Accelerated Componentwise Gradient Boosting using Efficient Data Representation and Momentum-based Optimization
• [stat.CO]Fast methods for posterior inference of two-group normal-normal models
• [stat.CO]Smooth bootstrapping of copula functionals
• [stat.ME]A Fast and Effective Large-Scale Two-Sample Test Based on Kernels
• [stat.ME]Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models
• [stat.ME]Distribution-free and Model-free Multivariate Feature Screening via Multivariate Rank Distance Correlation
• [stat.ME]Ensemble Kalman Inversion for General Likelihoods
• [stat.ME]Heterogeneous Overdispersed Count Data Regressions via Double Penalized Estimations
• [stat.ML]:An Unbiased Stratified Statistic and a Fast Gradient Optimization Algorithm Based on It
• [stat.ML]Curved Markov Chain Monte Carlo for Network Learning
• [stat.ML]Detecting and Quantifying Malicious Activity with Simulation-based Inference
• [stat.ML]Pretrained Language Models are Symbolic Mathematics Solvers too!
• [stat.ML]Robust Algorithms for GMM Estimation: A Finite Sample Viewpoint
• [stat.ML]Robustness and reliability when training with noisy labels
• [stat.ML]Ship Performance Monitoring using Machine-learning
• [stat.ML]Solving the Dirichlet problem for the Monge-Ampère equation using neural networks
• [stat.ML]Tighter Sparse Approximation Bounds for ReLU Neural Networks
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• [cs.AI]A Data-Centric Approach for Training Deep Neural Networks with Less Data
Mohammad Motamedi, Nikolay Sakharnykh, Tim Kaldewey
http://arxiv.org/abs/2110.03613v1
• [cs.AI]A Fast Randomized Algorithm for Massive Text Normalization
Nan Jiang, Chen Luo, Vihan Lakshman, Yesh Dattatreya, Yexiang Xue
http://arxiv.org/abs/2110.03024v1
• [cs.AI]Automated Testing of AI Models
Swagatam Haldar, Deepak Vijaykeerthy, Diptikalyan Saha
http://arxiv.org/abs/2110.03320v1
• [cs.AI]Belief Evolution Network: Probability Transformation of Basic Belief Assignment and Fusion Conflict Probability
Qianli Zhou, Yusheng Huang, Yong Deng
http://arxiv.org/abs/2110.03468v1
• [cs.AI]Cartoon Explanations of Image Classifiers
Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok
http://arxiv.org/abs/2110.03485v1
• [cs.AI]Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling
Naveen Raman, Sanket Shah, John Dickerson
http://arxiv.org/abs/2110.03524v1
• [cs.AI]Efficient Sharpness-aware Minimization for Improved Training of Neural Networks
Jiawei Du, Hanshu Yan, Jiashi Feng, Joey Tianyi Zhou, Liangli Zhen, Rick Siow Mong Goh, Vincent Y. F. Tan
http://arxiv.org/abs/2110.03141v1
• [cs.AI]From Weighted Conditionals of Multilayer Perceptrons to a Gradual Argumentation Semantics
Laura Giordano
http://arxiv.org/abs/2110.03643v1
• [cs.AI]GNN is a Counter? Revisiting GNN for Question Answering
Kuan Wang, Yuyu Zhang, Diyi Yang, Le Song, Tao Qin
http://arxiv.org/abs/2110.03192v1
• [cs.AI]Goal-Directed Design Agents: Integrating Visual Imitation with One-Step Lookahead Optimization for Generative Design
Ayush Raina, Lucas Puentes, Jonathan Cagan, Christopher McComb
http://arxiv.org/abs/2110.03223v1
• [cs.AI]Inferring Substitutable and Complementary Products with Knowledge-Aware Path Reasoning based on Dynamic Policy Network
Zijing Yang, Jiabo Ye, Linlin Wang, Xin Lin, Liang He
http://arxiv.org/abs/2110.03276v1
• [cs.AI]Learning a Metacognition for Object Detection
Marlene Berke, Mario Belledonne, Zhangir Azerbayez, Julian Jara-Ettinger
http://arxiv.org/abs/2110.03105v1
• [cs.AI]SLASH: Embracing Probabilistic Circuits into Neural Answer Set Programming
Arseny Skryagin, Wolfgang Stammer, Daniel Ochs, Devendra Singh Dhami, Kristian Kersting
http://arxiv.org/abs/2110.03395v1
• [cs.AI]Self-Evolutionary Optimization for Pareto Front Learning
Simyung Chang, KiYoon Yoo, Jiho Jang, Nojun Kwak
http://arxiv.org/abs/2110.03461v1
• [cs.AI]Towards Federated Learning-Enabled Visible Light Communication in 6G Systems
Shimaa Naser, Lina Bariah, Sami Muhaidat, Mahmoud Al-Qutayri, Ernesto Damiani, Merouane Debbah, Paschalis C. Sofotasios
http://arxiv.org/abs/2110.03319v1
• [cs.AR]Shift-BNN: Highly-Efficient Probabilistic Bayesian Neural Network Training via Memory-Friendly Pattern Retrieving
Qiyu Wan, Haojun Xia, Xingyao Zhang, Lening Wang, Shuaiwen Leon Song, Xin Fu
http://arxiv.org/abs/2110.03553v1
• [cs.CC]On the Complexity of Inductively Learning Guarded Rules
Andrei Draghici, Georg Gottlob, Matthias Lanzinger
http://arxiv.org/abs/2110.03624v1
• [cs.CL]A Logic-Based Framework for Natural Language Inference in Dutch
Lasha Abzianidze, Konstantinos Kogkalidis
http://arxiv.org/abs/2110.03323v1
• [cs.CL]Adversarial Retriever-Ranker for dense text retrieval
Hang Zhang, Yeyun Gong, Yelong Shen, Jiancheng Lv, Nan Duan, Weizhu Chen
http://arxiv.org/abs/2110.03611v1
• [cs.CL]Applying Phonological Features in Multilingual Text-To-Speech
Cong Zhang, Huinan Zeng, Huang Liu, Jiewen Zheng
http://arxiv.org/abs/2110.03609v1
• [cs.CL]Back from the future: bidirectional CTC decoding using future information in speech recognition
Namkyu Jung, Geonmin Kim, Han-Gyu Kim
http://arxiv.org/abs/2110.03326v1
• [cs.CL]Beam Search with Bidirectional Strategies for Neural Response Generation
Pierre Colombo, Chouchang Yang, Giovanna Varni, Chloé Clavel
http://arxiv.org/abs/2110.03389v1
• [cs.CL]Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot Filling
Liwen Wang, Xuefeng Li, Jiachi Liu, Keqing He, Yuanmeng Yan, Weiran Xu
http://arxiv.org/abs/2110.03572v1
• [cs.CL]Causal Direction of Data Collection Matters: Implications of Causal and Anticausal Learning in NLP
Zhijing Jin, Julius von Kügelgen, Jingwei Ni, Tejas Vaidhya, Ayush Kaushal, Mrinmaya Sachan, Bernhard Schoelkopf
http://arxiv.org/abs/2110.03618v1
• [cs.CL]Cross-Language Learning for Entity Matching
Ralph Peeters, Christian Bizer
http://arxiv.org/abs/2110.03338v1
• [cs.CL]Cut the CARP: Fishing for zero-shot story evaluation
Shahbuland Matiana, JR Smith, Ryan Teehan, Louis Castricato, Stella Biderman, Leo Gao, Spencer Frazier
http://arxiv.org/abs/2110.03111v1
• [cs.CL]GeSERA: General-domain Summary Evaluation by Relevance Analysis
Jessica López Espejel, Gaël de Chalendar, Jorge Garcia Flores, Thierry Charnois, Ivan Vladimir Meza Ruiz
http://arxiv.org/abs/2110.03567v1
• [cs.CL]HowSumm: A Multi-Document Summarization Dataset Derived from WikiHow Articles
Odellia Boni, Guy Feigenblat, Guy Lev, Michal Shmueli-Scheuer, Benjamin Sznajder, David Konopnicki
http://arxiv.org/abs/2110.03179v1
• [cs.CL]Influence Tuning: Demoting Spurious Correlations via Instance Attribution and Instance-Driven Updates
Xiaochuang Han, Yulia Tsvetkov
http://arxiv.org/abs/2110.03212v1
• [cs.CL]Integrating Categorical Features in End-to-End ASR
Rongqing Huang
http://arxiv.org/abs/2110.03047v1
• [cs.CL]Layer-wise Pruning of Transformer Attention Heads for Efficient Language Modeling
Kyuhong Shim, Iksoo Choi, Wonyong Sung, Jungwook Choi
http://arxiv.org/abs/2110.03252v1
• [cs.CL]Magic dust for cross-lingual adaptation of monolingual wav2vec-2.0
Sameer Khurana, Antoine Laurent, James Glass
http://arxiv.org/abs/2110.03560v1
• [cs.CL]Mandarin-English Code-switching Speech Recognition with Self-supervised Speech Representation Models
Liang-Hsuan Tseng, Yu-Kuan Fu, Heng-Jui Chang, Hung-yi Lee
http://arxiv.org/abs/2110.03504v1
• [cs.CL]Multi-tasking Dialogue Comprehension with Discourse Parsing
Yuchen He, Zhuosheng Zhang, Hai Zhao
http://arxiv.org/abs/2110.03269v1
• [cs.CL]NUS-IDS at FinCausal 2021: Dependency Tree in Graph Neural Network for Better Cause-Effect Span Detection
Fiona Anting Tan, See-Kiong Ng
http://arxiv.org/abs/2110.02991v1
• [cs.CL]Noisy Text Data: Achilles’ Heel of popular transformer based NLP models
Kartikay Bagla, Ankit Kumar, Shivam Gupta, Anuj Gupta
http://arxiv.org/abs/2110.03353v1
• [cs.CL]On Neurons Invariant to Sentence Structural Changes in Neural Machine Translation
Gal Patel, Leshem Choshen, Omri Abend
http://arxiv.org/abs/2110.03067v1
• [cs.CL]PSG@HASOC-Dravidian CodeMixFIRE2021: Pretrained Transformers for Offensive Language Identification in Tanglish
Sean Benhur, Kanchana Sivanraju
http://arxiv.org/abs/2110.02852v2
• [cs.CL]PoNet: Pooling Network for Efficient Token Mixing in Long Sequences
Chao-Hong Tan, Qian Chen, Wen Wang, Qinglin Zhang, Siqi Zheng, Zhen-Hua Ling
http://arxiv.org/abs/2110.02442v2
• [cs.CL]Sequence-to-Sequence Lexical Normalization with Multilingual Transformers
Ana-Maria Bucur, Adrian Cosma, Liviu P. Dinu
http://arxiv.org/abs/2110.02869v2
• [cs.CL]Situated Dialogue Learning through Procedural Environment Generation
Prithviraj Ammanabrolu, Renee Jia, Mark O. Riedl
http://arxiv.org/abs/2110.03262v1
• [cs.CL]The Low-Resource Double Bind: An Empirical Study of Pruning for Low-Resource Machine Translation
Orevaoghene Ahia, Julia Kreutzer, Sara Hooker
http://arxiv.org/abs/2110.03036v1
• [cs.CL]Towards Continual Knowledge Learning of Language Models
Joel Jang, Seonghyeon Ye, Sohee Yang, Joongbo Shin, Janghoon Han, Gyeonghun Kim, Stanley Jungkyu Choi, Minjoon Seo
http://arxiv.org/abs/2110.03215v1
• [cs.CL]Transliteration of Foreign Words in Burmese
Chenchen Ding
http://arxiv.org/abs/2110.03163v1
• [cs.CL]Unsupervised Multimodal Language Representations using Convolutional Autoencoders
Panagiotis Koromilas, Theodoros Giannakopoulos
http://arxiv.org/abs/2110.03007v1
• [cs.CL]mRAT-SQL+GAP:A Portuguese Text-to-SQL Transformer
Marcelo Archanjo José, Fabio Gagliardi Cozman
http://arxiv.org/abs/2110.03546v1
• [cs.CR]Complex-valued deep learning with differential privacy
Alexander Ziller, Dmitrii Usynin, Moritz Knolle, Kerstin Hammernik, Daniel Rueckert, Georgios Kaissis
http://arxiv.org/abs/2110.03478v1
• [cs.CR]DoubleStar: Long-Range Attack Towards Depth Estimation based Obstacle Avoidance in Autonomous Systems
Ce Zhou, Qiben Yan, Yan Shi, Lichao Sun
http://arxiv.org/abs/2110.03154v1
• [cs.CR]Neural Networks, Inside Out: Solving for Inputs Given Parameters (A Preliminary Investigation)
Mohammad Sadeq Dousti
http://arxiv.org/abs/2110.03649v1
• [cs.CR]On The Vulnerability of Recurrent Neural Networks to Membership Inference Attacks
Yunhao Yang, Parham Gohari, Ufuk Topcu
http://arxiv.org/abs/2110.03054v1
• [cs.CR]PWG-IDS: An Intrusion Detection Model for Solving Class Imbalance in IIoT Networks Using Generative Adversarial Networks
Lei Zhang, Shuaimin Jiang, Xiajiong Shen, Brij B. Gupta, Zhihong Tian
http://arxiv.org/abs/2110.03445v1
• [cs.CV]2nd Place Solution to Google Landmark Recognition Competition 2021
Shubin Dai
http://arxiv.org/abs/2110.02638v2
• [cs.CV]3rd Place Solution to Google Landmark Recognition Competition 2021
Cheng Xu, Weimin Wang, Shuai Liu, Yong Wang, Yuxiang Tang, Tianling Bian, Yanyu Yan, Qi She, Cheng Yang
http://arxiv.org/abs/2110.02794v2
• [cs.CV]A Baseline Framework for Part-level Action Parsing and Action Recognition
Xiaodong Chen, Xinchen Liu, Kun Liu, Wu Liu, Tao Mei
http://arxiv.org/abs/2110.03368v1
• [cs.CV]A Hierarchical Variational Neural Uncertainty Model for Stochastic Video Prediction
Moitreya Chatterjee, Narendra Ahuja, Anoop Cherian
http://arxiv.org/abs/2110.03446v1
• [cs.CV]A New Simple Vision Algorithm for Detecting the Enzymic Browning Defects in Golden Delicious Apples
Hamid Majidi Balanji
http://arxiv.org/abs/2110.03574v1
• [cs.CV]ATISS: Autoregressive Transformers for Indoor Scene Synthesis
Despoina Paschalidou, Amlan Kar, Maria Shugrina, Karsten Kreis, Andreas Geiger, Sanja Fidler
http://arxiv.org/abs/2110.03675v1
• [cs.CV]Burst Image Restoration and Enhancement
Akshay Dudhane, Syed Waqas Zamir, Salman Khan, Fahad Khan, Ming-Hsuan Yang
http://arxiv.org/abs/2110.03680v1
• [cs.CV]Camera Calibration through Camera Projection Loss
Talha Hanif Butt, Murtaza Taj
http://arxiv.org/abs/2110.03479v1
• [cs.CV]Colored Point Cloud to Image Alignment
Noam Rotstein, Amit Bracha, Ron Kimmel
http://arxiv.org/abs/2110.03249v1
• [cs.CV]Deep Learning Model Explainability for Inspection Accuracy Improvement in the Automotive Industry
Anass El Houd, Charbel El Hachem, Loic Painvin
http://arxiv.org/abs/2110.03384v1
• [cs.CV]DeepBBS: Deep Best Buddies for Point Cloud Registration
Itan Hezroni, Amnon Drory, Raja Giryes, Shai Avidan
http://arxiv.org/abs/2110.03016v1
• [cs.CV]Dense Gaussian Processes for Few-Shot Segmentation
Joakim Johnander, Johan Edstedt, Michael Felsberg, Fahad Shahbaz Khan, Martin Danelljan
http://arxiv.org/abs/2110.03674v1
• [cs.CV]Design of an Intelligent Vision Algorithm for Recognition and Classification of Apples in an Orchard Scene
Hamid Majidi Balanji, Alaeedin Rahmani Didar, Mohamadali Hadad Derafshi
http://arxiv.org/abs/2110.03232v1
• [cs.CV]Differential Anomaly Detection for Facial Images
Mathias Ibsen, Lázaro J. González-Soler, Christian Rathgeb, Pawel Drozdowski, Marta Gomez-Barrero, Christoph Busch
http://arxiv.org/abs/2110.03464v1
• [cs.CV]Dynamically Decoding Source Domain Knowledge For Unseen Domain Generalization
Cuicui Kang, Karthik Nandakumar
http://arxiv.org/abs/2110.03027v1
• [cs.CV]End-to-End Supermask Pruning: Learning to Prune Image Captioning Models
Jia Huei Tan, Chee Seng Chan, Joon Huang Chuah
http://arxiv.org/abs/2110.03298v1
• [cs.CV]Estimating Image Depth in the Comics Domain
Deblina Bhattacharjee, Martin Everaert, Mathieu Salzmann, Sabine Süsstrunk
http://arxiv.org/abs/2110.03575v1
• [cs.CV]FOD-A: A Dataset for Foreign Object Debris in Airports
Travis Munyer, Pei-Chi Huang, Chenyu Huang, Xin Zhong
http://arxiv.org/abs/2110.03072v1
• [cs.CV]Gradient Step Denoiser for convergent Plug-and-Play
Samuel Hurault, Arthur Leclaire, Nicolas Papadakis
http://arxiv.org/abs/2110.03220v1
• [cs.CV]Improving Fractal Pre-training
Connor Anderson, Ryan Farrell
http://arxiv.org/abs/2110.03091v1
• [cs.CV]InfoSeg: Unsupervised Semantic Image Segmentation with Mutual Information Maximization
Robert Harb, Patrick Knöbelreiter
http://arxiv.org/abs/2110.03477v1
• [cs.CV]Large-Scale Topological Radar Localization Using Learned Descriptors
Jacek Komorowski, Monika Wysoczanska, Tomasz Trzcinski
http://arxiv.org/abs/2110.03081v1
• [cs.CV]Learning Canonical Embedding for Non-rigid Shape Matching
Abhishek Sharma, Maks Ovsjanikov
http://arxiv.org/abs/2110.02994v1
• [cs.CV]Learning to Regress Bodies from Images using Differentiable Semantic Rendering
Sai Kumar Dwivedi, Nikos Athanasiou, Muhammed Kocabas, Michael J. Black
http://arxiv.org/abs/2110.03480v1
• [cs.CV]MC-LCR: Multi-modal contrastive classification by locally correlated representations for effective face forgery detection
Gaojian Wang, Qian Jiang, Xin Jin, Wei Li, Xiaohui Cui
http://arxiv.org/abs/2110.03290v1
• [cs.CV]MGPSN: Motion-Guided Pseudo Siamese Network for Indoor Video Head Detection
Kailai Sun, Xiaoteng Ma, Qianchuan Zhao, Peng Liu
http://arxiv.org/abs/2110.03302v1
• [cs.CV]MSHCNet: Multi-Stream Hybridized Convolutional Networks with Mixed Statistics in Euclidean/Non-Euclidean Spaces and Its Application to Hyperspectral Image Classification
Shuang He, Haitong Tang, Xia Lu, Hongjie Yan, Nizhuan Wang
http://arxiv.org/abs/2110.03346v1
• [cs.CV]Meta-UDA: Unsupervised Domain Adaptive Thermal Object Detection using Meta-Learning
Vibashan VS, Domenick Poster, Suya You, Shuowen Hu, Vishal M. Patel
http://arxiv.org/abs/2110.03143v1
• [cs.CV]Model Adaptation: Historical Contrastive Learning for Unsupervised Domain Adaptation without Source Data
Jiaxing Huang, Dayan Guan, Aoran Xiao, Shijian Lu
http://arxiv.org/abs/2110.03374v1
• [cs.CV]Moment evolution equations and moment matching for stochastic image EPDiff
Alexander Christgau, Alexis Arnaudon, Stefan Sommer
http://arxiv.org/abs/2110.03337v1
• [cs.CV]On Cropped versus Uncropped Training Sets in Tabular Structure Detection
Yakup Akkaya, Murat Simsek, Burak Kantarci, Shahzad Khan
http://arxiv.org/abs/2110.02933v2
• [cs.CV]Player Tracking and Identification in Ice Hockey
Kanav Vats, Pascale Walters, Mehrnaz Fani, David A. Clausi, John Zelek
http://arxiv.org/abs/2110.03090v1
• [cs.CV]RAR: Region-Aware Point Cloud Registration
Yu Hao, Yi Fang
http://arxiv.org/abs/2110.03544v1
• [cs.CV]SPEED+: Next Generation Dataset for Spacecraft Pose Estimation across Domain Gap
Tae Ha Park, Marcus Märtens, Gurvan Lecuyer, Dario Izzo, Simone D’Amico
http://arxiv.org/abs/2110.03101v1
• [cs.CV]Scale Invariant Domain Generalization Image Recapture Detection
Jinian Luo, Jie Guo, Weidong Qiu, Zheng Huang, Hong Hui
http://arxiv.org/abs/2110.03496v1
• [cs.CV]Self-Supervised Depth Completion for Active Stereo
Frederik Warburg, Daniel Hernandez-Juarez, Juan Tarrio, Alexander Vakhitov, Ujwal Bonde, Pablo Alcantarilla
http://arxiv.org/abs/2110.03234v1
• [cs.CV]Towards Accurate Cross-Domain In-Bed Human Pose Estimation
Mohamed Afham, Udith Haputhanthri, Jathurshan Pradeepkumar, Mithunjha Anandakumar, Ashwin De Silva, Chamira Edussooriya
http://arxiv.org/abs/2110.03578v1
• [cs.CV]TreeGCN-ED: Encoding Point Cloud using a Tree-Structured Graph Network
Prajwal Singh, Kaustubh Sadekar, Shanmuganathan Raman
http://arxiv.org/abs/2110.03170v1
• [cs.CV]Unsupervised Image Decomposition with Phase-Correlation Networks
Angel Villar-Corrales, Sven Behnke
http://arxiv.org/abs/2110.03473v1
• [cs.CV]Using Contrastive Learning and Pseudolabels to learn representations for Retail Product Image Classification
Muktabh Mayank Srivastava
http://arxiv.org/abs/2110.03639v1
• [cs.CV]Using Keypoint Matching and Interactive Self Attention Network to verify Retail POSMs
Harshita Seth, Sonaal Kant, Muktabh Mayank Srivastava
http://arxiv.org/abs/2110.03646v1
• [cs.CV]Virtual Multi-Modality Self-Supervised Foreground Matting for Human-Object Interaction
Bo Xu, Han Huang, Cheng Lu, Ziwen Li, Yandong Guo
http://arxiv.org/abs/2110.03278v1
• [cs.CV]Vision-based Excavator Activity Analysis and Safety Monitoring System
Sibo Zhang, Liangjun Zhang
http://arxiv.org/abs/2110.03083v1
• [cs.CV]Weakly Supervised Human-Object Interaction Detection in Video via Contrastive Spatiotemporal Regions
Shuang Li, Yilun Du, Antonio Torralba, Josef Sivic, Bryan Russell
http://arxiv.org/abs/2110.03562v1
• [cs.CY]What motivates people to telework? Explorat
1000
ory study in a post-confinement context
Steve Berberat, Damien Rosat, Armand Kouadio
http://arxiv.org/abs/2110.03399v1
• [cs.DC]I
1000
aaS Signature Change Detection with Performance Noise
Sheik Mohammad Mostakim Fattah, Athman Bouguettaya
http://arxiv.org/abs/2110.03229v1
• [cs.DC]MAPA: Multi-Accelerator Pattern Allocation Policy for Multi-Tenant GPU Servers
Kiran Ranganath, Joshua D. Suetterlein, Joseph B. Manzano, Shuaiwen Leon Song, Daniel Wong
http://arxiv.org/abs/2110.03214v1
• [cs.HC]Evolutionary Computation-Assisted Brainwriting for Large-Scale Online Ideation
Nobuo Namura, Tatsuya Hasebe
http://arxiv.org/abs/2110.03205v1
• [cs.HC]From the Head or the Heart? An Experimental Design on the Impact of Explanation on Cognitive and Affective Trust
Qiaoning Zhang, X. Jessie Yang, Lionel P. Robert Jr
http://arxiv.org/abs/2110.03433v1
• [cs.HC]Human in the Loop for Machine Creativity
Neo Christopher Chung
http://arxiv.org/abs/2110.03569v1
• [cs.HC]Posture Recognition in the Critical Care Settings using Wearable Devices
Anis Davoudi, Patrick J. Tighe, Azra Bihorac, Parisa Rashidi
http://arxiv.org/abs/2110.02768v2
• [cs.IR]Doing Data Right: How Lessons Learned Working with Conventional Data should Inform the Future of Synthetic Data for Recommender Systems
Manel Slokom, Martha Larson
http://arxiv.org/abs/2110.03275v1
• [cs.IR]Optimized Recommender Systems with Deep Reinforcement Learning
Lucas Farris
http://arxiv.org/abs/2110.03039v1
• [cs.IR]Recent Advances in Heterogeneous Relation Learning for Recommendation
Chao Huang
http://arxiv.org/abs/2110.03455v1
• [cs.IT]A Rate Splitting Strategy for Uplink CR-NOMA Systems
Hongwu Liu, Zhiquan Bai, Hongjiang Lei, Gaofeng Pan, Kyeong Jin Kim, Theodoros A. Tsiftsis
http://arxiv.org/abs/2110.02281v2
• [cs.IT]Minimum Message Length Autoregressive Moving Average Model Order Selection
Zheng Fang, David L. Dowe, Shelton Peiris, Dedi Rosadi
http://arxiv.org/abs/2110.03250v1
• [cs.IT]Pointwise Bounds for Distribution Estimation under Communication Constraints
Wei-Ning Chen, Peter Kairouz, Ayfer Özgür
http://arxiv.org/abs/2110.03189v1
• [cs.IT]Privacy-Preserving Coded Mobile Edge Computing for Low-Latency Distributed Inference
Reent Schlegel, Siddhartha Kumar, Eirik Rosnes, Alexandre Graell i Amat
http://arxiv.org/abs/2110.03545v1
• [cs.IT]Structured Channel Covariance Estimation from Limited Samples for Large Antenna Arrays
Tianyu Yang, Mahdi Barzegar Khalilsarai, Saeid Haghighatshoar, Giuseppe Caire
http://arxiv.org/abs/2110.03324v1
• [cs.IT]What Should 6G Architectures Be?
Lu Yang, Ping Li, Miaomiao Dong, Bo Bai, Zaporozhets Dmitry, Xiang Chen, Wei Han, Baochun Li
http://arxiv.org/abs/2110.03157v1
• [cs.LG]A Broad Ensemble Learning System for Drifting Stream Classification
Sepehr Bakhshi, Pouya Ghahramanian, Hamed Bonab, Fazli Can
http://arxiv.org/abs/2110.03540v1
• [cs.LG]A Model Selection Approach for Corruption Robust Reinforcement Learning
Chen-Yu Wei, Christoph Dann, Julian Zimmert
http://arxiv.org/abs/2110.03580v1
• [cs.LG]A Survey on Evidential Deep Learning For Single-Pass Uncertainty Estimation
Dennis Ulmer
http://arxiv.org/abs/2110.03051v1
• [cs.LG]A Uniform Framework for Anomaly Detection in Deep Neural Networks
Chenyi Zhang, Naipeng Dong, Zefeng You, Zhenxin Wu
http://arxiv.org/abs/2110.03092v1
• [cs.LG]Active Learning of Markov Decision Processes using Baum-Welch algorithm (Extended)
Giovanni Bacci, Anna Ingólfsdóttir, Kim Larsen, Raphaël Reynouard
http://arxiv.org/abs/2110.03014v1
• [cs.LG]AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow
Haiyan Jiang, Haoyi Xiong, Dongrui Wu, Ji Liu, Dejing Dou
http://arxiv.org/abs/2110.03273v1
• [cs.LG]Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks
Soroush Nasiriany, Huihan Liu, Yuke Zhu
http://arxiv.org/abs/2110.03655v1
• [cs.LG]Automatic Tuning of Federated Learning Hyper-Parameters from System Perspective
Huanle Zhang, Mi Zhang, Xin Liu, Prasant Mohapatra, Michael DeLucia
http://arxiv.org/abs/2110.03061v1
• [cs.LG]Bad-Policy Density: A Measure of Reinforcement Learning Hardness
David Abel, Cameron Allen, Dilip Arumugam, D. Ellis Hershkowitz, Michael L. Littman, Lawson L. S. Wong
http://arxiv.org/abs/2110.03424v1
• [cs.LG]Bias-Variance Tradeoffs in Single-Sample Binary Gradient Estimators
Alexander Shekhovtsov
http://arxiv.org/abs/2110.03549v1
• [cs.LG]Boxhead: A Dataset for Learning Hierarchical Representations
Yukun Chen, Frederik Träuble, Andrea Dittadi, Stefan Bauer, Bernhard Schölkopf
http://arxiv.org/abs/2110.03628v1
• [cs.LG]CLEVA-Compass: A Continual Learning EValuation Assessment Compass to Promote Research Transparency and Comparability
Martin Mundt, Steven Lang, Quentin Delfosse, Kristian Kersting
http://arxiv.org/abs/2110.03331v1
• [cs.LG]Coresets for Decision Trees of Signals
Ibrahim Jubran, Ernesto Evgeniy Sanches Shayda, Ilan Newman, Dan Feldman
http://arxiv.org/abs/2110.03195v1
• [cs.LG]Creating Training Sets via Weak Indirect Supervision
Jieyu Zhang, Bohan Wang, Xiangchen Song, Yujing Wang, Yaming Yang, Jing Bai, Alexander Ratner
http://arxiv.org/abs/2110.03484v1
• [cs.LG]Cross-Domain Imitation Learning via Optimal Transport
Arnaud Fickinger, Samuel Cohen, Stuart Russell, Brandon Amos
http://arxiv.org/abs/2110.03684v1
• [cs.LG]Darts: User-Friendly Modern Machine Learning for Time Series
Julien Herzen, Francesco Lässig, Samuele Giuliano Piazzetta, Thomas Neuer, Léo Tafti, Guillaume Raille, Tomas Van Pottelbergh, Marek Pasieka, Andrzej Skrodzki, Nicolas Huguenin, Maxime Dumonal, Jan Kościsz, Dennis Bader, Frédérick Gusset, Mounir Benheddi, Camila Williamson, Michal Kosinski, Matej Petrik, Gaël Grosch
http://arxiv.org/abs/2110.03224v1
• [cs.LG]Data-Centric AI Requires Rethinking Data Notion
Mustafa Hajij, Ghada Zamzmi, Karthikeyan Natesan Ramamurthy, Aldo Guzman Saenz
http://arxiv.org/abs/2110.02491v2
• [cs.LG]Data-Centric Semi-Supervised Learning
Xudong Wang, Long Lian, Stella X. Yu
http://arxiv.org/abs/2110.03006v1
• [cs.LG]Detecting Autism Spectrum Disorders with Machine Learning Models Using Speech Transcripts
Vikram Ramesh, Rida Assaf
http://arxiv.org/abs/2110.03281v1
• [cs.LG]Disentangling deep neural networks with rectified linear units using duality
Chandrashekar Lakshminarayanan, Amit Vikram Singh
http://arxiv.org/abs/2110.03403v1
• [cs.LG]Distributed Methods with Compressed Communication for Solving Variational Inequalities, with Theoretical Guarantees
Aleksandr Beznosikov, Peter Richtárik, Michael Diskin, Max Ryabinin, Alexander Gasnikov
http://arxiv.org/abs/2110.03313v1
• [cs.LG]Distributed Optimization of Graph Convolutional Network using Subgraph Variance
Taige Zhao, Xiangyu Song, Jianxin Li, Wei Luo, Imran Razzak
http://arxiv.org/abs/2110.02987v1
• [cs.LG]Double Descent in Adversarial Training: An Implicit Label Noise Perspective
Chengyu Dong, Liyuan Liu, Jingbo Shang
http://arxiv.org/abs/2110.03135v1
• [cs.LG]EE-Net: Exploitation-Exploration Neural Networks in Contextual Bandits
Yikun Ban, Yuchen Yan, Arindam Banerjee, Jingrui He
http://arxiv.org/abs/2110.03177v1
• [cs.LG]EF21 with Bells & Whistles: Practical Algorithmic Extensions of Modern Error Feedback
Ilyas Fatkhullin, Igor Sokolov, Eduard Gorbunov, Zhize Li, Peter Richtárik
http://arxiv.org/abs/2110.03294v1
• [cs.LG]Efficient Methods for Online Multiclass Logistic Regression
Naman Agarwal, Satyen Kale, Julian Zimmert
http://arxiv.org/abs/2110.03020v1
• [cs.LG]Enabling On-Device Training of Speech Recognition Models with Federated Dropout
Dhruv Guliani, Lillian Zhou, Changwan Ryu, Tien-Ju Yang, Harry Zhang, Yonghui Xiao, Francoise Beaufays, Giovanni Motta
http://arxiv.org/abs/2110.03634v1
• [cs.LG]EvadeDroid: A Practical Evasion Attack on Machine Learning for Black-box Android Malware Detection
Hamid Bostani, Veelasha Moonsamy
http://arxiv.org/abs/2110.03301v1
• [cs.LG]Explaining Deep Reinforcement Learning Agents In The Atari Domain through a Surrogate Model
Alexander Sieusahai, Matthew Guzdial
http://arxiv.org/abs/2110.03184v1
• [cs.LG]Fast learning from label proportions with small bags
Denis Baručić, Jan Kybic
http://arxiv.org/abs/2110.03426v1
• [cs.LG]Federated Learning from Small Datasets
Michael Kamp, Jonas Fischer, Jilles Vreeken
http://arxiv.org/abs/2110.03469v1
• [cs.LG]Federated Learning via Plurality Vote
Kai Yue, Richeng Jin, Chau-Wai Wong, Huaiyu Dai
http://arxiv.org/abs/2110.02998v1
• [cs.LG]Federating for Learning Group Fair Models
Afroditi Papadaki, Natalia Martinez, Martin Bertran, Guillermo Sapiro, Miguel Rodrigues
http://arxiv.org/abs/2110.01999v2
• [cs.LG]Frame Averaging for Invariant and Equivariant Network Design
Omri Puny, Matan Atzmon, Heli Ben-Hamu, Edward J. Smith, Ishan Misra, Aditya Grover, Yaron Lipman
http://arxiv.org/abs/2110.03336v1
• [cs.LG]Generalization in Deep RL for TSP Problems via Equivariance and Local Search
Wenbin Ouyang, Yisen Wang, Paul Weng, Shaochen Han
http://arxiv.org/abs/2110.03595v1
• [cs.LG]Generative Modeling with Optimal Transport Maps
Litu Rout, Alexander Korotin, Evgeny Burnaev
http://arxiv.org/abs/2110.02999v1
• [cs.LG]Generative Optimization Networks for Memory Efficient Data Generation
Shreshth Tuli, Shikhar Tuli, Giuliano Casale, Nicholas R. Jennings
http://arxiv.org/abs/2110.02912v2
• [cs.LG]How to Sense the World: Leveraging Hierarchy in Multimodal Perception for Robust Reinforcement Learning Agents
Miguel Vasco, Hang Yin, Francisco S. Melo, Ana Paiva
http://arxiv.org/abs/2110.03608v1
• [cs.LG]Hybrid Pointer Networks for Traveling Salesman Problems Optimization
Ahmed Stohy, Heba-Tullah Abdelhakam, Sayed Ali, Mohammed Elhenawy, Abdallah A Hassan, Mahmoud Masoud, Sebastien Glaser, Andry Rakotonirainy
http://arxiv.org/abs/2110.03104v1
• [cs.LG]Hyperparameter Tuning with Renyi Differential Privacy
Nicolas Papernot, Thomas Steinke
http://arxiv.org/abs/2110.03620v1
• [cs.LG]Improving Adversarial Robustness for Free with Snapshot Ensemble
Yihao Wang
http://arxiv.org/abs/2110.03124v1
• [cs.LG]Improving MC-Dropout Uncertainty Estimates with Calibration Error-based Optimization
Afshar Shamsi, Hamzeh Asgharnezhad, Moloud Abdar, AmirReza Tajally, Abbas Khosravi, Saeid Nahavandi, Henry Leung
http://arxiv.org/abs/2110.03260v1
• [cs.LG]Is Attention always needed? A Case Study on Language Identification from Speech
Atanu Mandal, Santanu Pal, Indranil Dutta, Mahidas Bhattacharya, Sudip Kumar Naskar
http://arxiv.org/abs/2110.03427v1
• [cs.LG]Joint calibration and mapping of satellite altimetry data using trainable variational models
Quentin Febvre, Ronan Fablet, Julien Le Sommer, Clément Ubelmann
http://arxiv.org/abs/2110.03405v1
• [cs.LG]Lagrangian Neural Network with Differential Symmetries and Relational Inductive Bias
Ravinder Bhattoo, Sayan Ranu, N. M. Anoop Krishnan
http://arxiv.org/abs/2110.03266v1
• [cs.LG]Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect
Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao
http://arxiv.org/abs/2110.03677v1
• [cs.LG]Learning Multi-Objective Curricula for Deep Reinforcement Learning
Jikun Kang, Miao Liu, Abhinav Gupta, Chris Pal, Xue Liu, Jie Fu
http://arxiv.org/abs/2110.03032v1
• [cs.LG]Learning Pessimism for Robust and Efficient Off-Policy Reinforcement Learning
Edoardo Cetin, Oya Celiktutan
http://arxiv.org/abs/2110.03375v1
• [cs.LG]Learning the Optimal Recommendation from Explorative Users
Fan Yao, Chuanhao Li, Denis Nekipelov, Hongning Wang, Haifeng Xu
http://arxiv.org/abs/2110.03068v1
• [cs.LG]Multi-Head ReLU Implicit Neural Representation Networks
Arya Aftab, Alireza Morsali
http://arxiv.org/abs/2110.03448v1
• [cs.LG]Multi-objective Optimization by Learning Space Partitions
Yiyang Zhao, Linnan Wang, Kevin Yang, Tianjun Zhang, Tian Guo, Yuandong Tian
http://arxiv.org/abs/2110.03173v1
• [cs.LG]Multivariate Anomaly Detection based on Prediction Intervals Constructed using Deep Learning
Thabang Mathonsi, Terence L. van Zyl
http://arxiv.org/abs/2110.03393v1
• [cs.LG]Near-Optimal Reward-Free Exploration for Linear Mixture MDPs with Plug-in Solver
Xiaoyu Chen, Jiachen Hu, Lin F. Yang, Liwei Wang
http://arxiv.org/abs/2110.03244v1
• [cs.LG]Neural Tangent Kernel Empowered Federated Learning
Kai Yue, Richeng Jin, Ryan Pilgrim, Chau-Wai Wong, Dror Baron, Huaiyu Dai
http://arxiv.org/abs/2110.03681v1
• [cs.LG]Offline RL With Resource Constrained Online Deployment
Jayanth Reddy Regatti, Aniket Anand Deshmukh, Frank Cheng, Young Hun Jung, Abhishek Gupta, Urun Dogan
http://arxiv.org/abs/2110.03165v1
• [cs.LG]On Margin Maximization in Linear and ReLU Networks
Gal Vardi, Ohad Shamir, Nathan Srebro
http://arxiv.org/abs/2110.02732v2
• [cs.LG]On the Generalization of Models Trained with SGD: Information-Theoretic Bounds and Implications
Ziqiao Wang, Yongyi Mao
http://arxiv.org/abs/2110.03128v1
• [cs.LG]On the Latent Holes of VAEs for Text Generation
Ruizhe Li, Xutan Peng, Chenghua Lin
http://arxiv.org/abs/2110.03318v1
• [cs.LG]On the Optimal Memorization Power of ReLU Neural Networks
Gal Vardi, Gilad Yehudai, Ohad Shamir
http://arxiv.org/abs/2110.03187v1
• [cs.LG]On the relationship between disentanglement and multi-task learning
Łukasz Maziarka, Aleksandra Nowak, Maciej Wołczyk, Andrzej Bedychaj
http://arxiv.org/abs/2110.03498v1
• [cs.LG]One Thing to Fool them All: Generating Interpretable, Universal, and Physically-Realizable Adversarial Features
Stephen Casper, Max Nadeau, Gabriel Kreiman
http://arxiv.org/abs/2110.03605v1
• [cs.LG]Online Markov Decision Processes with Non-oblivious Strategic Adversary
Le Cong Dinh, David Henry Mguni, Long Tran-Thanh, Jun Wang, Yaodong Yang
http://arxiv.org/abs/2110.03604v1
• [cs.LG]Permutation Compressors for Provably Faster Distributed Nonconvex Optimization
Rafał Szlendak, Alexander Tyurin, Peter Richtárik
http://arxiv.org/abs/2110.03300v1
• [cs.LG]Physics-informed neural network simulation of multiphase poroelasticity using stress-split sequential training
Ehsan Haghighat, Danial Amini, Ruben Juanes
http://arxiv.org/abs/2110.03049v1
• [cs.LG]Probabilistic Metamodels for an Efficient Characterization of Complex Driving Scenarios
Max Winkelmann, Mike Kohlhoff, Hadj Hamma Tadjine, Steffen Müller
http://arxiv.org/abs/2110.02892v2
• [cs.LG]Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates
Oytun Demirbilek, Islem Rekik
http://arxiv.org/abs/2110.03453v1
• [cs.LG]RieszNet and ForestRiesz: Automatic Debiased Machine Learning with Neural Nets and Random Forests
Victor Chernozhukov, Whitney K. Newey, Victor Quintas-Martinez, Vasilis Syrgkanis
http://arxiv.org/abs/2110.03031v1
• [cs.LG]SWAT Watershed Model Calibration using Deep Learning
M. K. Mudunuru, K. Son, P. Jiang, X. Chen
http://arxiv.org/abs/2110.03097v1
• [cs.LG]Score-based Generative Neural Networks for Large-Scale Optimal Transport
Max Daniels, Tyler Maunu, Paul Hand
http://arxiv.org/abs/2110.03237v1
• [cs.LG]Sparse MoEs meet Efficient Ensembles
James Urquhart Allingham, Florian Wenzel, Zelda E Mariet, Basil Mustafa, Joan Puigcerver, Neil Houlsby, Ghassen Jerfel, Vincent Fortuin, Balaji Lakshminarayanan, Jasper Snoek, Dustin Tran, Carlos Riquelme Ruiz, Rodolphe Jenatton
http://arxiv.org/abs/2110.03360v1
• [cs.LG]The Connection between Out-of-Distribution Generalization and Privacy of ML Models
Divyat Mahajan, Shruti Tople, Amit Sharma
http://arxiv.org/abs/2110.03369v1
• [cs.LG]Tile Embedding: A General Representation for Procedural Level Generation via Machine Learning
Mrunal Jadhav, Matthew Guzdial
http://arxiv.org/abs/2110.03181v1
• [cs.LG]To Charge or To Sell? EV Pack Useful Life Estimation via LSTMs and Autoencoders
Michael Bosello, Carlo Falcomer, Claudio Rossi, Giovanni Pau
http://arxiv.org/abs/2110.03585v1
• [cs.LG]Towards Robust and Transferable IIoT Sensor based Anomaly Classification using Artificial Intelligence
Jana Kemnitz, Thomas Bierweiler, Herbert Grieb, Stefan von Dosky, Daniel Schall
http://arxiv.org/abs/2110.03440v1
• [cs.LG]Training Stable Graph Neural Networks Through Constrained Learning
Juan Cervino, Luana Ruiz, Alejandro Ribeiro
http://arxiv.org/abs/2110.03576v1
• [cs.LG]Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design
Ye Yuan, Yuda Song, Zhengyi Luo, Wen Sun, Kris Kitani
http://arxiv.org/abs/2110.03659v1
• [cs.LG]Tribuo: Machine Learning with Provenance in Java
Adam Pocock
http://arxiv.org/abs/2110.03022v1
• [cs.LG]Two-Bit Aggregation for Communication Efficient and Differentially Private Federated Learning
Mohammad Aghapour, Aidin Ferdowsi, Walid Saad
http://arxiv.org/abs/2110.03017v1
• [cs.LG]Understanding Domain Randomization for Sim-to-real Transfer
Xiaoyu Chen, Jiachen Hu, Chi Jin, Lihong Li, Liwei Wang
http://arxiv.org/abs/2110.03239v1
• [cs.LG]Universal Approximation Under Constraints is Possible with Transformers
Anastasis Kratsios, Behnoosh Zamanlooy, Tianlin Liu, Ivan Dokmanić
http://arxiv.org/abs/2110.03303v1
• [cs.LG]Universality of Deep Neural Network Lottery Tickets: A Renormalization Group Perspective
William T. Redman, Tianlong Chen, Akshunna S. Dogra, Zhangyang Wang
http://arxiv.org/abs/2110.03210v1
• [cs.LG]Which Shortcut Cues Will DNNs Choose? A Study from the Parameter-Space Perspective
Luca Scimeca, Seong Joon Oh, Sanghyuk Chun, Michael Poli, Sangdoo Yun
http://arxiv.org/abs/2110.03095v1
• [cs.MA]School Virus Infection Simulator for Customizing School Schedules During COVID-19
Satoshi Takahashi, Masaki Kitazawa, Atsushi Yoshikawa
http://arxiv.org/abs/2110.03615v1
• [cs.MM]TranSalNet: Visual saliency prediction using transformers
Jianxun Lou, Hanhe Lin, David Marshall, Dietmar Saupe, Hantao Liu
http://arxiv.org/abs/2110.03593v1
• [cs.NE]Assemblies of neurons can learn to classify well-separated distributions
Max Dabagia, Christos H. Papadimitriou, Santosh S. Vempala
http://arxiv.org/abs/2110.03171v1
• [cs.NE]Cloud Failure Prediction with Hierarchical Temporary Memory: An Empirical Assessment
Oliviero Riganelli, Paolo Saltarel, Alessandro Tundo, Marco Mobilio, Leonardo Mariani
http://arxiv.org/abs/2110.03431v1
• [cs.RO]Active Extrinsic Contact Sensing: Application to General Peg-in-Hole Insertion
Sangwoon Kim, Alberto Rodriguez
http://arxiv.org/abs/2110.03555v1
• [cs.RO]Adaptive Safety Margin Estimation for Safe Real-Time Replanning under Time-Varying Disturbance
Cherie Ho, Jay Patrikar, Rogerio Bonatti, Sebastian Scherer
http://arxiv.org/abs/2110.03119v1
• [cs.RO]Correct Me if I am Wrong: Interactive Learning for Robotic Manipulation
Eugenio Chisari, Tim Welschehold, Joschka Boedecker, Wolfram Burgard, Abhinav Valada
http://arxiv.org/abs/2110.03316v1
• [cs.RO]Empirical Analysis of Bi-directional Wi-Fi Network Performance on Mobile Robots and Connected Vehicles
Pranav Pandey, Ramviyas Parasuraman
http://arxiv.org/abs/2110.03011v1
• [cs.RO]Evaluating model-based planning and planner amortization for continuous control
Arunkumar Byravan, Leonard Hasenclever, Piotr Trochim, Mehdi Mirza, Alessandro Davide Ialongo, Yuval Tassa, Jost Tobias Springenberg, Abbas Abdolmaleki, Nicolas Heess, Josh Merel, Martin Riedmiller
http://arxiv.org/abs/2110.03363v1
• [cs.RO]Human Capabilities as Guiding Lights for the Field of AI-HRI: Insights from Engineering Education
Tom Williams, Ruchen Wen
http://arxiv.org/abs/2110.03026v1
• [cs.RO]Improving Robot-Centric Learning from Demonstration via Personalized Embeddings
Mariah L. Schrum, Erin Hedlund, Matthew C. Gombolay
http://arxiv.org/abs/2110.03134v1
• [cs.RO]Injecting Planning-Awareness into Prediction and Detection Evaluation
Boris Ivanovic, Marco Pavone
http://arxiv.org/abs/2110.03270v1
• [cs.RO]Propagating State Uncertainty Through Trajectory Forecasting
Boris Ivanovic, Yifeng, Lin, Shubham Shrivastava, Punarjay Chakravarty, Marco Pavone
http://arxiv.org/abs/2110.03267v1
• [cs.RO]RHH-LGP: Receding Horizon And Heuristics-Based Logic-Geometric Programming For Task And Motion Planning
Cornelius V. Braun, Joaquim Ortiz-Haro, Marc Toussaint, Ozgur S. Oguz
http://arxiv.org/abs/2110.03420v1
• [cs.RO]Reactive Locomotion Decision-Making and Robust Motion Planning for Real-Time Perturbation
80e
Recovery
Zhaoyuan Gu, Nathan Boyd, Ye Zhao
http://arxiv.org/abs/2110.03037v1
• [cs.RO]Robotic Lever Manipulation using Hindsight Experience Replay and Shapley Additive Explanations
Sindre Benjamin Remman, Anastasios M. Lekkas
http://arxiv.org/abs/2110.03292v1
• [cs.SD]Attention is All You Need? Good Embeddings with Statistics are enough: Audio Understanding WITHOUT Convolutions/Transformers/BERTs/Mixers/Attention/RNNs or ….
Prateek Verma
http://arxiv.org/abs/2110.03183v1
• [cs.SD]Disentangled dimensionality reduction for noise-robust speaker diarisation
You Jin Kim, Hee-Soo Heo, Jee-weon Jung, Youngki Kwon, Bong-Jin Lee, Joon Son Chung
http://arxiv.org/abs/2110.03380v1
• [cs.SD]GANtron: Emotional Speech Synthesis with Generative Adversarial Networks
Enrique Hortal, Rodrigo Brechard Alarcia
http://arxiv.org/abs/2110.03390v1
• [cs.SD]SERAB: A multi-lingual benchmark for speech emotion recognition
Neil Scheidwasser-Clow, Mikolaj Kegler, Pierre Beckmann, Milos Cernak
http://arxiv.org/abs/2110.03414v1
• [cs.SD]StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis
Rui Liu, Berrak Sisman, Haizhou Li
http://arxiv.org/abs/2110.03156v1
• [cs.SD]Transferring Voice Knowledge for Acoustic Event Detection: An Empirical Study
Dawei Liang, Yangyang Shi, Yun Wang, Nayan Singhal, Alex Xiao, Jonathan Shaw, Edison Thomaz, Ozlem Kalinli, Mike Seltzer
http://arxiv.org/abs/2110.03174v1
• [cs.SD]WenetSpeech: A 10000+ Hours Multi-domain Mandarin Corpus for Speech Recognition
Binbin Zhang, Hang Lv, Pengcheng Guo, Qijie Shao, Chao Yang, Lei Xie, Xin Xu, Hui Bu, Xiaoyu Chen, Chenchen Zeng, Di Wu, Zhendong Peng
http://arxiv.org/abs/2110.03370v1
• [cs.SE]DRAFT-What you always wanted to know but could not find about block-based environments
Mauricio Verano Merino, Jurgen Vinju, Mark van den Brand
http://arxiv.org/abs/2110.03073v1
• [cs.SI]Analysis of the influence of political polarization in the vaccination stance: the Brazilian COVID-19 scenario
Régis Ebeling, Carlos Abel Córdova Sáenz, Jeferson Nobre, Karin Becker
http://arxiv.org/abs/2110.03382v1
• [cs.SI]Joint inference of multiple graphs with hidden variables from stationary graph signals
Samuel Rey, Andrei Buciulea, Madeline Navarro, Santiago Segarra, Antonio G. Marques
http://arxiv.org/abs/2110.03666v1
• [cs.SI]Revisiting SVD to generate powerful Node Embeddings for Recommendation Systems
Amar Budhiraja
http://arxiv.org/abs/2110.03665v1
• [econ.EM]Investigating Growth at Risk Using a Multi-country Non-parametric Quantile Factor Model
Todd E. Clark, Florian Huber, Gary Koop, Massimiliano Marcellino, Michael Pfarrhofer
http://arxiv.org/abs/2110.03411v1
• [econ.GN]Unpacking the Black Box: Regulating Algorithmic Decisions
Laura Blattner, Scott Nelson, Jann Spiess
http://arxiv.org/abs/2110.03443v1
• [eess.AS]CTC Variations Through New WFST Topologies
Aleksandr Laptev, Somshubra Majumdar, Boris Ginsburg
http://arxiv.org/abs/2110.03098v1
• [eess.AS]Emphasis control for parallel neural TTS
Shreyas Seshadri, Tuomo Raitio, Dan Castellani, Jiangchuan Li
http://arxiv.org/abs/2110.03012v1
• [eess.AS]End-to-end label uncertainty modeling for speech emotion recognition using Bayesian neural networks
Navin Raj Prabhu, Guillaume Carbajal, Nale Lehmann-Willenbrock, Timo Gerkmann
http://arxiv.org/abs/2110.03299v1
• [eess.AS]Improving Confidence Estimation on Out-of-Domain Data for End-to-End Speech Recognition
Qiujia Li, Yu Zhang, David Qiu, Yanzhang He, Liangliang Cao, Philip C. Woodland
http://arxiv.org/abs/2110.03327v1
• [eess.AS]Peer Collaborative Learning for Polyphonic Sound Event Detection
Hayato Endo, Hiromitsu Nishizaki
http://arxiv.org/abs/2110.03511v1
• [eess.AS]Transcribe-to-Diarize: Neural Speaker Diarization for Unlimited Number of Speakers using End-to-End Speaker-Attributed ASR
Naoyuki Kanda, Xiong Xiao, Yashesh Gaur, Xiaofei Wang, Zhong Meng, Zhuo Chen, Takuya Yoshioka
http://arxiv.org/abs/2110.03151v1
• [eess.AS]VisualTTS: TTS with Accurate Lip-Speech Synchronization for Automatic Voice Over
Junchen Lu, Berrak Sisman, Rui Liu, Mingyang Zhang, Haizhou Li
http://arxiv.org/abs/2110.03342v1
• [eess.IV]A transformer-based deep learning approach for classifying brain metastases into primary organ sites using clinical whole brain MRI images
Qing Lyu, Sanjeev V. Namjoshi, Emory McTyre, Umit Topaloglu, Richard Barcus, Michael D. Chan, Christina K. Cramer, Waldemar Debinski, Metin N. Gurcan, Glenn J. Lesser, Hui-Kuan Lin, Reginald F. Munden, Boris C. Pasche, Kiran Kumar Solingapuram Sai, Roy E. Strowd, Stephen B. Tatter, Kounosuke Watabe, Wei Zhang, Ge Wang, Christopher T. Whitlow
http://arxiv.org/abs/2110.03588v1
• [eess.IV]AnoSeg: Anomaly Segmentation Network Using Self-Supervised Learning
Jouwon Song, Kyeongbo Kong, Ye-In Park, Seong-Gyun Kim, Suk-Ju Kang
http://arxiv.org/abs/2110.03396v1
• [eess.IV]Generic tool for numerical simulation of transformation-diffusion processes in complex volume geometric shapes: application to microbial decomposition of organic matter
Olivier Monga, Frédéric Hecht, Serge Moto, Bruno Mbe, Patricia Garnier, Valérie Pot
http://arxiv.org/abs/2110.03130v1
• [eess.IV]Improving Pneumonia Localization via Cross-Attention on Medical Images and Reports
Riddhish Bhalodia, Ali Hatamizadeh, Leo Tam, Ziyue Xu, Xiaosong Wang, Evrim Turkbey, Daguang Xu
http://arxiv.org/abs/2110.03094v1
• [eess.IV]Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning
B
2fa
asar Demir, Alaa Bessadok, Islem Rekik
http://arxiv.org/abs/2110.03452v1
• [eess.IV]Multi-Scale Convolutional Neural Network for Automated AMD Classification using Retinal OCT Images
Saman Sotoudeh-Paima, Ata Jodeiri, Fedra Hajizadeh, Hamid Soltanian-Zadeh
http://arxiv.org/abs/2110.03002v1
• [eess.IV]Optimized U-Net for Brain Tumor Segmentation
Michał Futrega, Alexandre Milesi, Michal Marcinkiewicz, Pablo Ribalta
http://arxiv.org/abs/2110.03352v1
• [eess.IV]Uncertainty-aware GAN with Adaptive Loss for Robust MRI Image Enhancement
Uddeshya Upadhyay, Viswanath P. Sudarshan, Suyash P. Awate
http://arxiv.org/abs/2110.03343v1
• [eess.SP]Joint optimization of system design and reconstruction in MIMO radar imaging
Tomer Weiss, Nissim Peretz, Sanketh Vedula, Arie Feuer, Alex Bronstein
http://arxiv.org/abs/2110.03218v1
• [eess.SY]Uncertainty Set Prediction of Aggregated Wind Power Generation based on Bayesian LSTM and Spatio-Temporal Analysis
Xiaopeng Li, Jiang Wu, Zhanbo Xu, Kun Liu, Jun Yu, Xiaohong Guan
http://arxiv.org/abs/2110.03358v1
• [math.NA]Time Series Forecasting Using Manifold Learning
Panagiotis Papaioannou, Ronen Talmon, Daniela di Serafino, Constantinos Siettos
http://arxiv.org/abs/2110.03625v1
• [math.OC]A Hybrid Direct-Iterative Method for Solving KKT Linear Systems
Shaked Regev, Nai-Yuan Chiang, Eric Darve, Cosmin G. Petra, Michael A. Saunders, Kasia Świrydowicz, Slaven Peleš
http://arxiv.org/abs/2110.03636v1
• [math.OC]A Stochastic Newton Algorithm for Distributed Convex Optimization
Brian Bullins, Kumar Kshitij Patel, Ohad Shamir, Nathan Srebro, Blake Woodworth
http://arxiv.org/abs/2110.02954v1
• [math.OC]Explicitly Multi-Modal Benchmarks for Multi-Objective Optimization
Reiya Hagiwara, Takahiro Yamamoto, Naoki Hamada, Daisuke Sakurai
http://arxiv.org/abs/2110.03196v1
• [math.OC]Predictability and Fairness in Load Aggregation and Operations of Virtual Power Plants
Jakub Marecek, Michal Roubalik, Ramen Ghosh, Robert N. Shorten, Fabian R. Wirth
http://arxiv.org/abs/2110.03001v1
• [math.OC]Solving Multistage Stochastic Linear Programming via Regularized Linear Decision Rules: An Application to Hydrothermal Dispatch Planning
Felipe Nazare, Alexandre Street
http://arxiv.org/abs/2110.03146v1
• [math.ST]Graph sampling by lagged random walk
Li-Chun Zhang
http://arxiv.org/abs/2110.03459v1
• [math.ST]High Dimensional Logistic Regression Under Network Dependence
Somabha Mukherjee, Sagnik Halder, Bhaswar B. Bhattacharya, George Michailidis
http://arxiv.org/abs/2110.03200v1
• [math.ST]Neural Estimation of Statistical Divergences
Sreejith Sreekumar, Ziv Goldfeld
http://arxiv.org/abs/2110.03652v1
• [physics.soc-ph]Physics-inspired analysis of the two-class income distribution in the USA in 1983-2018
Danial Ludwig, Victor M. Yakovenko
http://arxiv.org/abs/2110.03140v1
• [q-bio.BM]Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond
Dinghuai Zhang, Jie Fu, Yoshua Bengio, Aaron Courville
http://arxiv.org/abs/2110.03372v1
• [q-bio.NC]A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint
Alaa Bessadok, Ahmed Nebli, Mohamed Ali Mahjoub, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik
http://arxiv.org/abs/2110.03535v1
• [stat.AP]A Critical Review of the Baseline Soldier Physical Readiness Requirements Study
Kyle A. Novak
http://arxiv.org/abs/2110.03062v1
• [stat.AP]Acoustic Signal based Non-Contact Ball Bearing Fault Diagnosis Using Adaptive Wavelet Denoising
Wonho Jung, Jaewoong Bae, Yong-Hwa Park
http://arxiv.org/abs/2110.03348v1
• [stat.AP]Int
53f4
erpretable Machine Learning for Genomics
David S. Watson
http://arxiv.org/abs/2110.03063v1
• [stat.AP]Regression markets and application to energy forecasting
Pierre Pinson, Liyang Han, Jalal Kazempour
http://arxiv.org/abs/2110.03633v1
• [stat.AP]Tracking the national and regional COVID-19 epidemic status in the UK using directed Principal Component Analysis
Ben Swallow, Wen Xiang, Jasmina Panovska-Griffiths
http://arxiv.org/abs/2110.03626v1
• [stat.CO]Accelerated Componentwise Gradient Boosting using Efficient Data Representation and Momentum-based Optimization
Daniel Schalk, Bernd Bischl, David Rügamer
http://arxiv.org/abs/2110.03513v1
• [stat.CO]Fast methods for posterior inference of two-group normal-normal models
Philip Greengard, Jeremy Hoskins, Charles C. Margossian, Andrew Gelman, Aki Vehtari
http://arxiv.org/abs/2110.03055v1
• [stat.CO]Smooth bootstrapping of copula functionals
Maximilian Coblenz, Oliver Grothe, Klaus Herrmannm, Marius Hofert
http://arxiv.org/abs/2110.03397v1
• [stat.ME]A Fast and Effective Large-Scale Two-Sample Test Based on Kernels
Hoseung Song, Hao Chen
http://arxiv.org/abs/2110.03118v1
• [stat.ME]Causal inference in survival analysis using longitudinal observational data: Sequential trials and marginal structural models
Ruth H. Keogh, Jon Michael Gran, Shaun R. Seaman, Gwyneth Davies, Stijn Vansteelandt
http://arxiv.org/abs/2110.03117v1
• [stat.ME]Distribution-free and Model-free Multivariate Feature Screening via Multivariate Rank Distance Correlation
Shaofei Zhao, Guifang Fu
http://arxiv.org/abs/2110.03145v1
• [stat.ME]Ensemble Kalman Inversion for General Likelihoods
Samuel Duffield, Sumeetpal S. Singh
http://arxiv.org/abs/2110.03034v1
• [stat.ME]Heterogeneous Overdispersed Count Data Regressions via Double Penalized Estimations
Shaomin Li, Haoyu Wei, Xiaoyu Lei
http://arxiv.org/abs/2110.03552v1
• [stat.ML]:An Unbiased Stratified Statistic and a Fast Gradient Optimization Algorithm Based on It
Aixiang Chen
http://arxiv.org/abs/2110.03354v1
• [stat.ML]Curved Markov Chain Monte Carlo for Network Learning
John Sigbeku, Emil Saucan, Anthea Monod
http://arxiv.org/abs/2110.03413v1
• [stat.ML]Detecting and Quantifying Malicious Activity with Simulation-based Inference
Andrew Gambardella, Bogdan State, Naeemullah Khan, Leo Tsourides, Philip H. S. Torr, Atılım Güneş Baydin
http://arxiv.org/abs/2110.02483v2
• [stat.ML]Pretrained Language Models are Symbolic Mathematics Solvers too!
Kimia Noorbakhsh, Modar Sulaiman, Mahdi Sharifi, Kallol Roy, Pooyan Jamshidi
http://arxiv.org/abs/2110.03501v1
• [stat.ML]Robust Algorithms for GMM Estimation: A Finite Sample Viewpoint
Dhruv Rohatgi, Vasilis Syrgkanis
http://arxiv.org/abs/2110.03070v1
• [stat.ML]Robustness and reliability when training with noisy labels
Amanda Olmin, Fredrik Lindsten
http://arxiv.org/abs/2110.03321v1
• [stat.ML]Ship Performance Monitoring using Machine-learning
Prateek Gupta, Adil Rasheed, Sverre Steen
http://arxiv.org/abs/2110.03594v1
• [stat.ML]Solving the Dirichlet problem for the Monge-Ampère equation using neural networks
Kaj Nyström, Matias Vestberg
http://arxiv.org/abs/2110.03310v1
• [stat.ML]Tighter Sparse Approximation Bounds for ReLU Neural Networks
Carles Domingo-Enrich, Youssef Mroueh
http://arxiv.org/abs/2110.03673v1
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