Machine Learning (stat)

Papers filed under stat.ML on arXiv, each one already summarized by Paperlayer. Open any of them to read the summary beside the original PDF, with every point linked to the line, figure, or table it came from.

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2,341 to 2,400 of 6,792

Hilbert space embeddings and metrics on probability measures
Bharath K. Sriperumbudur, Arthur Gretton, Kenji Fukumizu +2
stat.MLmath.STarXiv:0907.5309v32009
Matrix Completion from Noisy Entries
Raghunandan H. Keshavan, Andrea Montanari, Sewoong Oh
cs.LGstat.MLarXiv:0906.2027v22009
Tree-guided group lasso for multi-response regression with structured sparsity, with an application to eQTL mapping
Seyoung Kim, Eric P. Xing
stat.MLq-bio.GNq-bio.QMarXiv:0909.1373v32009
A sticky HDP-HMM with application to speaker diarization
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan +1
stat.MEstat.APstat.MLarXiv:0905.2592v42009
QCD-Aware Recursive Neural Networks for Jet Physics
Gilles Louppe, Kyunghyun Cho, Cyril Becot +1
hep-phphysics.data-anstat.MLarXiv:1702.00748v22017
Choice of neighbor order in nearest-neighbor classification
Peter Hall, Byeong U. Park, Richard J. Samworth
math.STstat.MLarXiv:0810.5276v12008
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning
Olivier Catoni
stat.MLarXiv:0712.0248v12007
High-dimensional variable selection
Larry Wasserman, Kathryn Roeder
math.STstat.MLarXiv:0704.1139v22007
Neural ODE enhanced linear mixed effect models for estimating complex association patterns of time-varying covariates with the marker trajectory
Zhe Aurore Li, Quentin Clairon, Cécilia Samieri +3
stat.MLcs.LGarXiv:2608.29714v12026
Muon with Finite Newton-Schulz: The Smoothing Benefit in Nonsmooth Nonconvex Optimization
Mingyi Li, Taira Tsuchiya
cs.LGmath.OCstat.MLarXiv:2608.26288v12026
Optimal Alternating Regret for Online Learning and Games
Yixin Tao, Weiqiang Zheng
cs.LGcs.GTstat.MLarXiv:2608.24731v12026
Toward the Optimal Regret-Instability Trade-off in Multi-Armed Bandits
Kaifei Wang, Yinyu Ye, Han Zhong
stat.MLcs.LGmath.OCarXiv:2608.17841v12026
Expressivity In Multimodal Contrastive Learning
Andrew Stuart, Florian Wolf
stat.MLcs.LGmath.STarXiv:2608.17203v12026
Maximum Tsallis Entropy Distributions for Robust and Efficient Sparse Learning from Correlated Data
Kai Yang, Masoud Asgharian, Celia M. T. Greenwood
math.OCcs.AImath.STarXiv:2608.17244v12026
Transferring Robustness for Graph Neural Network Against Poisoning Attacks
Xianfeng Tang, Yandong Li, Yiwei Sun +3
cs.LGcs.CRcs.SIarXiv:1908.07558v32019
Learning reshapes power-law anisotropy in internal representations
Asahi Nakamuta, Jun-nosuke Teramae
cs.LGstat.MLarXiv:2608.15239v12026
Prediction Inference of Time Series with Standard ReLU Deep Neural Networks
Kejin Wu
stat.MLcs.LGstat.COarXiv:2608.15362v12026
Identifying parameter couplings and uncertainties of mixed-noise stochastic systems via full-covariance Gaussian mixture network
Xiaolong Wang, Xiangwen Hao, Jing Feng +2
stat.MLcs.LGphysics.comp-pharXiv:2608.15198v12026
Handover of In-Context Learning State Across Session Boundaries
Masahiro Kato, Taka Kato
cs.AIecon.EMmath.STarXiv:2608.14528v12026
Online Inference in Distributional Temporal-Difference Learning
Yang Peng, Liangyu Zhang
stat.MLcs.LGarXiv:2608.14408v12026
QUASAR: Lowering the Loss Floor of Quantization-Aware Training with Loss-Aware Reconstruction
Vincent Counathe, Ben Athiwaratkun, Christopher De Sa +1
cs.LGcs.CLstat.MLarXiv:2608.13966v12026
Robust XGBoosting for Regression
Iris Aragón Mladosich, Christophe Croux
cs.LGstat.COstat.MLarXiv:2608.13590v12026
Defensive Boosting for Online Probabilistic Forecasting
Georgy Noarov, Aaron Roth
cs.LGcs.CCcs.DSarXiv:2608.13554v12026
Summaries:한국어
Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure
Mingyuan Zhang
cs.LGstat.MLarXiv:2608.13549v12026
Summaries:한국어
BDH-CQ: In-Context Learning with Recurrent Latent Reasoning
Björn Engdahl, Adrian Kosowski, Jan Chorowski +6
cs.NEcs.AIcs.LGarXiv:2608.09888v12026
Data Movement Is All You Need: A Case Study on Optimizing Transformers
Andrei Ivanov, Nikoli Dryden, Tal Ben-Nun +2
cs.LGstat.MLarXiv:2007.00072v32020
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch
Gavin Weiguang Ding, Luyu Wang, Xiaomeng Jin
cs.LGcs.CRcs.CVarXiv:1902.07623v12019
When Does Trajectory-Level Supervision Permit Efficient Offline Reinforcement Learning?
Xuanfei Ren, Tengyang Xie
stat.MLcs.LGarXiv:2606.18531v12026
Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification
Brian d'Alessandro, Cathy O'Neil, Tom LaGatta
stat.MLcs.LGstat.COarXiv:1907.09013v12019
From Generalist to Specialist Representation
Yujia Zheng, Fan Feng, Yuke Li +3
cs.LGcs.AIstat.MLarXiv:2605.12733v12026
Diverse Dictionary Learning
Yujia Zheng, Zijian Li, Shunxing Fan +2
cs.LGmath.STstat.MLarXiv:2604.17568v12026
Spectral Condition for $μ$P under Width-Depth Scaling
Chenyu Zheng, Rongzhen Wang, Xinyu Zhang +1
cs.LGstat.MLarXiv:2603.00541v22026
Prescriptive Scaling Reveals the Evolution of Language Model Capabilities
Hanlin Zhang, Jikai Jin, Vasilis Syrgkanis +1
cs.LGcs.AIcs.CLarXiv:2602.15327v22026
Summaries:한국어
Vision Transformer Finetuning Benefits from Non-Smooth Components
Ambroise Odonnat, Laetitia Chapel, Romain Tavenard +1
cs.LGcs.CVstat.MLarXiv:2602.06883v32026
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields
Ilyes Batatia, Dávid Péter Kovács, Gregor N. C. Simm +2
stat.MLcond-mat.mtrl-scics.LGarXiv:2206.07697v22022
An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series
Astha Garg, Wenyu Zhang, Jules Samaran +2
cs.LGcs.AIstat.MLarXiv:2109.11428v12021
A Survey of Uncertainty in Deep Neural Networks
Jakob Gawlikowski, Cedrique Rovile Njieutcheu Tassi, Mohsin Ali +11
cs.LGstat.MLarXiv:2107.03342v32021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models
Sam Bond-Taylor, Adam Leach, Yang Long +1
cs.LGcs.CVstat.MLarXiv:2103.04922v42021
A Unifying Review of Deep and Shallow Anomaly Detection
Lukas Ruff, Jacob R. Kauffmann, Robert A. Vandermeulen +5
cs.LGcs.AIstat.MLarXiv:2009.11732v32020
Improving robustness against common corruptions by covariate shift adaptation
Steffen Schneider, Evgenia Rusak, Luisa Eck +3
cs.LGcs.CVstat.MLarXiv:2006.16971v22020
HiPPO: Recurrent Memory with Optimal Polynomial Projections
Albert Gu, Tri Dao, Stefano Ermon +2
cs.LGstat.MLarXiv:2008.07669v22020
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization
Jianyu Wang, Qinghua Liu, Hao Liang +2
cs.LGcs.DCstat.MLarXiv:2007.07481v12020
Denoising Diffusion Probabilistic Models
Jonathan Ho, Ajay Jain, Pieter Abbeel
cs.LGstat.MLarXiv:2006.11239v22020
Classification with Valid and Adaptive Coverage
Yaniv Romano, Matteo Sesia, Emmanuel J. Candès
stat.MEstat.MLarXiv:2006.02544v12020
EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfaces
Thorir Mar Ingolfsson, Michael Hersche, Xiaying Wang +3
eess.SPcs.HCcs.LGarXiv:2006.00622v12020
Learning under Concept Drift: A Review
Jie Lu, Anjin Liu, Fan Dong +3
cs.LGstat.MLarXiv:2004.05785v12020
Adaptive Federated Optimization
Sashank Reddi, Zachary Charles, Manzil Zaheer +5
cs.LGcs.DCmath.OCarXiv:2003.00295v52020
Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods
Mucahid Barstugan, Umut Ozkaya, Saban Ozturk
cs.CVcs.LGeess.IVarXiv:2003.09424v12020
Hybrid Linear Modeling via Local Best-fit Flats
Teng Zhang, Arthur Szlam, Yi Wang +1
cs.CVstat.MLarXiv:1010.3460v22010
Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach
Yi Liu, James J. Q. Yu, Jiawen Kang +2
cs.LGcs.CRstat.MLarXiv:2003.08725v12020
Federated Learning with Personalization Layers
Manoj Ghuhan Arivazhagan, Vinay Aggarwal, Aaditya Kumar Singh +1
cs.LGcs.DCstat.MLarXiv:1912.00818v12019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints
Felix Sattler, Klaus-Robert Müller, Wojciech Samek
cs.LGcs.DCstat.MLarXiv:1910.01991v12019
A Joint Learning and Communications Framework for Federated Learning over Wireless Networks
Mingzhe Chen, Zhaohui Yang, Walid Saad +3
cs.NIcs.LGstat.MLarXiv:1909.07972v42019
Invariant Risk Minimization
Martin Arjovsky, Léon Bottou, Ishaan Gulrajani +1
stat.MLcs.AIcs.LGarXiv:1907.02893v32019
A Survey of Optimization Methods from a Machine Learning Perspective
Shiliang Sun, Zehui Cao, Han Zhu +1
cs.LGmath.OCstat.MLarXiv:1906.06821v22019
Deep Learning for Spatio-Temporal Data Mining: A Survey
Senzhang Wang, Jiannong Cao, Philip S. Yu
cs.LGstat.MLarXiv:1906.04928v22019
Unlabeled Data Improves Adversarial Robustness
Yair Carmon, Aditi Raghunathan, Ludwig Schmidt +2
stat.MLcs.CVcs.LGarXiv:1905.13736v42019
Deep Learning for Audio Signal Processing
Hendrik Purwins, Bo Li, Tuomas Virtanen +3
cs.SDeess.ASstat.MLarXiv:1905.00078v22019
Dirichlet Process Mixtures of Generalized Linear Models
Lauren A. Hannah, David M. Blei, Warren B. Powell
stat.MLarXiv:0909.5194v22009
Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control
Tianshu Chu, Jie Wang, Lara Codecà +1
cs.LGstat.MLarXiv:1903.04527v12019

Machine Learning (stat)

Hilbert space embeddings and metrics on probability measures

Matrix Completion from Noisy Entries

Tree-guided group lasso for multi-response regression with structured sparsity, with an application to eQTL mapping

A sticky HDP-HMM with application to speaker diarization

QCD-Aware Recursive Neural Networks for Jet Physics

Choice of neighbor order in nearest-neighbor classification

Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning

High-dimensional variable selection

Neural ODE enhanced linear mixed effect models for estimating complex association patterns of time-varying covariates with the marker trajectory

Muon with Finite Newton-Schulz: The Smoothing Benefit in Nonsmooth Nonconvex Optimization

Optimal Alternating Regret for Online Learning and Games

Toward the Optimal Regret-Instability Trade-off in Multi-Armed Bandits

Expressivity In Multimodal Contrastive Learning

Maximum Tsallis Entropy Distributions for Robust and Efficient Sparse Learning from Correlated Data

Transferring Robustness for Graph Neural Network Against Poisoning Attacks

Learning reshapes power-law anisotropy in internal representations

Prediction Inference of Time Series with Standard ReLU Deep Neural Networks

Identifying parameter couplings and uncertainties of mixed-noise stochastic systems via full-covariance Gaussian mixture network

Handover of In-Context Learning State Across Session Boundaries

Online Inference in Distributional Temporal-Difference Learning

QUASAR: Lowering the Loss Floor of Quantization-Aware Training with Loss-Aware Reconstruction

Robust XGBoosting for Regression

Defensive Boosting for Online Probabilistic Forecasting

Exponential Convex Calibration Dimension for the Multi-Label Jaccard Measure

BDH-CQ: In-Context Learning with Recurrent Latent Reasoning

Data Movement Is All You Need: A Case Study on Optimizing Transformers

advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch

When Does Trajectory-Level Supervision Permit Efficient Offline Reinforcement Learning?

Conscientious Classification: A Data Scientist's Guide to Discrimination-Aware Classification

From Generalist to Specialist Representation

Diverse Dictionary Learning

Spectral Condition for $μ$P under Width-Depth Scaling

Prescriptive Scaling Reveals the Evolution of Language Model Capabilities

Vision Transformer Finetuning Benefits from Non-Smooth Components

MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields

An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series

A Survey of Uncertainty in Deep Neural Networks

Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models

A Unifying Review of Deep and Shallow Anomaly Detection

Improving robustness against common corruptions by covariate shift adaptation

HiPPO: Recurrent Memory with Optimal Polynomial Projections

Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization

Denoising Diffusion Probabilistic Models

Classification with Valid and Adaptive Coverage

EEG-TCNet: An Accurate Temporal Convolutional Network for Embedded Motor-Imagery Brain-Machine Interfaces

Learning under Concept Drift: A Review

Adaptive Federated Optimization

Coronavirus (COVID-19) Classification using CT Images by Machine Learning Methods

Hybrid Linear Modeling via Local Best-fit Flats

Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach

Federated Learning with Personalization Layers

Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints

A Joint Learning and Communications Framework for Federated Learning over Wireless Networks

Invariant Risk Minimization

A Survey of Optimization Methods from a Machine Learning Perspective

Deep Learning for Spatio-Temporal Data Mining: A Survey

Unlabeled Data Improves Adversarial Robustness

Deep Learning for Audio Signal Processing

Dirichlet Process Mixtures of Generalized Linear Models

Multi-Agent Deep Reinforcement Learning for Large-scale Traffic Signal Control