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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1,861 to 1,920 of 6,772

Deep Reinforcement Learning for List-wise Recommendations
Xiangyu Zhao, Liang Zhang, Long Xia +3
cs.LGstat.MLarXiv:1801.00209v32017
Fantastic Pretraining Optimizers and Where to Find Them
Kaiyue Wen, David Hall, Tengyu Ma +1
cs.LGcs.AIstat.MLarXiv:2509.02046v22025
Learning Action Representations for Reinforcement Learning
Yash Chandak, Georgios Theocharous, James Kostas +2
cs.LGstat.MLarXiv:1902.00183v22019
Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination
Nathan Kallus, Xiaojie Mao, Angela Zhou
stat.MLcs.LGmath.OCarXiv:1906.00285v22019
Communication Lower Bounds for Statistical Estimation Problems via a Distributed Data Processing Inequality
Mark Braverman, Ankit Garg, Tengyu Ma +2
cs.LGcs.CCcs.ITarXiv:1506.07216v32015
Deep Learning Approach to Diabetic Retinopathy Detection
Borys Tymchenko, Philip Marchenko, Dmitry Spodarets
cs.LGstat.MLarXiv:2003.02261v12020
Curriculum Adversarial Training
Qi-Zhi Cai, Min Du, Chang Liu +1
cs.LGcs.CRstat.MLarXiv:1805.04807v12018
Probabilistic Logic Neural Networks for Reasoning
Meng Qu, Jian Tang
cs.LGcs.AIstat.MLarXiv:1906.08495v22019
PCGRL: Procedural Content Generation via Reinforcement Learning
Ahmed Khalifa, Philip Bontrager, Sam Earle +1
cs.LGcs.AIstat.MLarXiv:2001.09212v32020
Learning Mixed Graphical Models
Jason D. Lee, Trevor J. Hastie
stat.MLcs.CVcs.LGarXiv:1205.5012v32012
Combinatorial Sleeping Bandits with Fairness Constraints
Fengjiao Li, Jia Liu, Bo Ji
cs.LGcs.PFstat.MLarXiv:1901.04891v32019
Sub-sampled Cubic Regularization for Non-convex Optimization
Jonas Moritz Kohler, Aurelien Lucchi
cs.LGmath.OCstat.MLarXiv:1705.05933v32017
Active Learning for Regression Using Greedy Sampling
Dongrui Wu, Chin-Teng Lin, Jian Huang
cs.LGcs.AIstat.MLarXiv:1808.04245v12018
A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation
Xinyu Chen, Jinming Yang, Lijun Sun
stat.MLcs.LGarXiv:2003.10271v22020
Stochastic Cubic Regularization for Fast Nonconvex Optimization
Nilesh Tripuraneni, Mitchell Stern, Chi Jin +2
cs.LGmath.OCstat.MLarXiv:1711.02838v22017
Neural Networks can Learn Representations with Gradient Descent
Alex Damian, Jason D. Lee, Mahdi Soltanolkotabi
cs.LGcs.ITstat.MLarXiv:2206.15144v12022
Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control
Armin Lederer, Jonas Umlauft, Sandra Hirche
cs.LGeess.SYstat.MLarXiv:1906.01376v22019
PHYRE: A New Benchmark for Physical Reasoning
Anton Bakhtin, Laurens van der Maaten, Justin Johnson +2
cs.LGcs.AIstat.MLarXiv:1908.05656v12019
Adaptive Gradient Descent without Descent
Yura Malitsky, Konstantin Mishchenko
math.OCcs.LGmath.NAarXiv:1910.09529v22019
Provably Efficient Safe Exploration via Primal-Dual Policy Optimization
Dongsheng Ding, Xiaohan Wei, Zhuoran Yang +2
cs.LGmath.OCstat.MLarXiv:2003.00534v22020
Unifying Conformal Language Tasks with In-Context Ensembles
Xiao Shi Huang, Chen-Yuan Lin, Bruce Kuwahara +2
cs.CLcs.LGstat.MLarXiv:2609.03005v12026
The Geometry of Ignorance: LLMs Know When to Temper Bayesian Priors
Toni J. B. Liu, Jiajun Bao, Yizhou Liu +4
cs.LGcs.AIcs.CLarXiv:2609.02959v12026
Learning Deep Networks from Noisy Labels with Dropout Regularization
Ishan Jindal, Matthew Nokleby, Xuewen Chen
cs.CVcs.LGstat.MLarXiv:1705.03419v12017
Defining and Characterizing Reward Hacking
Joar Skalse, Nikolaus H. R. Howe, Dmitrii Krasheninnikov +1
cs.LGstat.MLarXiv:2209.13085v22022
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection
Andy Brown, Aaron Tuor, Brian Hutchinson +1
cs.LGcs.NEstat.MLarXiv:1803.04967v12018
On the Power and Limitations of Random Features for Understanding Neural Networks
Gilad Yehudai, Ohad Shamir
cs.LGcs.NEstat.MLarXiv:1904.00687v42019
Unifying Graph Convolutional Neural Networks and Label Propagation
Hongwei Wang, Jure Leskovec
cs.LGstat.MLarXiv:2002.06755v12020
What matters for Representation Alignment: Global Information or Spatial Structure?
Jaskirat Singh, Xingjian Leng, Zongze Wu +4
cs.CVcs.AIcs.GRarXiv:2512.10794v12025
Low-Rank Modeling and Its Applications in Image Analysis
Xiaowei Zhou, Can Yang, Hongyu Zhao +1
cs.CVcs.LGstat.MLarXiv:1401.3409v32014
Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier
Joseph Futoma, Sanjay Hariharan, Katherine Heller
stat.MLstat.APstat.MEarXiv:1706.04152v12017
Network cross-validation by edge sampling
Tianxi Li, Elizaveta Levina, Ji Zhu
stat.MEstat.MLarXiv:1612.04717v72016
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning
Elise van der Pol, Daniel E. Worrall, Herke van Hoof +2
cs.LGstat.MLarXiv:2006.16908v22020
BREEDS: Benchmarks for Subpopulation Shift
Shibani Santurkar, Dimitris Tsipras, Aleksander Madry
cs.CVcs.LGstat.MLarXiv:2008.04859v12020
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
Vadim Popov, Ivan Vovk, Vladimir Gogoryan +3
cs.SDcs.LGstat.MLarXiv:2109.13821v22021
Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks
Gauthier Gidel, Francis Bach, Simon Lacoste-Julien
cs.LGmath.OCstat.MLarXiv:1904.13262v22019
Z-Forcing: Training Stochastic Recurrent Networks
Anirudh Goyal, Alessandro Sordoni, Marc-Alexandre Côté +2
stat.MLcs.LGarXiv:1711.05411v22017
Self-Supervised Policy Adaptation during Deployment
Nicklas Hansen, Rishabh Jangir, Yu Sun +5
cs.LGcs.CVcs.ROarXiv:2007.04309v32020
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
Nicholas Frosst, Nicolas Papernot, Geoffrey Hinton
stat.MLcs.LGarXiv:1902.01889v12019
Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path
X. Y. Han, Vardan Papyan, David L. Donoho
cs.LGcs.AImath.DGarXiv:2106.02073v42021
Exact and Inexact Subsampled Newton Methods for Optimization
Raghu Bollapragada, Richard Byrd, Jorge Nocedal
math.OCstat.MLarXiv:1609.08502v12016
Sponge Examples: Energy-Latency Attacks on Neural Networks
Ilia Shumailov, Yiren Zhao, Daniel Bates +3
cs.LGcs.CLcs.CRarXiv:2006.03463v22020
Training Agents Inside of Scalable World Models
Danijar Hafner, Wilson Yan, Timothy Lillicrap
cs.AIcs.LGcs.ROarXiv:2509.24527v12025
Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm
Simon Fischer, Ingo Steinwart
stat.MLarXiv:1702.07254v32017
A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce
Wei Xiong, Jiarui Yao, Yuhui Xu +8
cs.LGcs.AIcs.CLarXiv:2504.11343v22025
Towards Understanding Regularization in Batch Normalization
Ping Luo, Xinjiang Wang, Wenqi Shao +1
cs.LGcs.CVeess.SYarXiv:1809.00846v42018
Day-Ahead Hourly Forecasting of Power Generation from Photovoltaic Plants
Lorenzo Gigoni, Alessandro Betti, Emanuele Crisostomi +4
cs.LGstat.MLarXiv:1903.06800v12019
Committee neural network potentials control generalization errors and enable active learning
Christoph Schran, Krystof Brezina, Ondrej Marsalek
physics.chem-phcs.LGphysics.comp-pharXiv:2006.01541v22020
Introduction to Online Convex Optimization
Elad Hazan
cs.LGmath.OCstat.MLarXiv:1909.05207v32019
Informative Label Missingness in Multiclass Classification Information Geometry and Excess Risk
Fariborz Setoudehtazang, Geoffrey J. McLachlan
stat.MLcs.LGarXiv:2608.30561v12026
Geometry-Constrained Kolmogorov-Arnold Networks: Learning Edge Geometry via Banach Duality
K S Sesh Kumar
cs.LGstat.MLarXiv:2608.25807v12026
Deep Skew-t Mixture Models
Jinran Wu, You-Gan Wang, Geoffrey J. McLachlan
stat.MEstat.COstat.MLarXiv:2609.00773v12026
Structured Learning on Mapper Representations
George Babus, Farzana Nasrin
stat.MLcs.LGarXiv:2608.22044v12026
Reinforcement Learning with Action Chunking
Qiyang Li, Zhiyuan Zhou, Sergey Levine
cs.LGcs.AIcs.ROarXiv:2507.07969v42025
Learning to Act from Actionless Videos through Dense Correspondences
Po-Chen Ko, Jiayuan Mao, Yilun Du +2
cs.ROcs.CVcs.LGarXiv:2310.08576v12023
Simplified and Generalized Masked Diffusion for Discrete Data
Jiaxin Shi, Kehang Han, Zhe Wang +2
cs.LGstat.MLarXiv:2406.04329v42024
Unexpected Improvements to Expected Improvement for Bayesian Optimization
Sebastian Ament, Samuel Daulton, David Eriksson +2
cs.LGmath.NAstat.MLarXiv:2310.20708v32023
Summaries:한국어
Negative Momentum for Improved Game Dynamics
Gauthier Gidel, Reyhane Askari Hemmat, Mohammad Pezeshki +4
cs.LGstat.MLarXiv:1807.04740v52018
From parcel to continental scale -- A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations
Raphaël d'Andrimont, Astrid Verhegghen, Guido Lemoine +3
stat.MLcs.LGstat.AParXiv:2105.09261v22021
Anomaly Detection in Univariate Time-series: A Survey on the State-of-the-Art
Mohammad Braei, Sebastian Wagner
cs.LGstat.MLarXiv:2004.00433v12020
Deep ROC Analysis and AUC as Balanced Average Accuracy to Improve Model Selection, Understanding and Interpretation
André M. Carrington, Douglas G. Manuel, Paul W. Fieguth +9
stat.MEcs.AIcs.LGarXiv:2103.11357v12021

Machine Learning (stat)

Deep Reinforcement Learning for List-wise Recommendations

Fantastic Pretraining Optimizers and Where to Find Them

Learning Action Representations for Reinforcement Learning

Assessing Algorithmic Fairness with Unobserved Protected Class Using Data Combination

Communication Lower Bounds for Statistical Estimation Problems via a Distributed Data Processing Inequality

Deep Learning Approach to Diabetic Retinopathy Detection

Curriculum Adversarial Training

Probabilistic Logic Neural Networks for Reasoning

PCGRL: Procedural Content Generation via Reinforcement Learning

Learning Mixed Graphical Models

Combinatorial Sleeping Bandits with Fairness Constraints

Sub-sampled Cubic Regularization for Non-convex Optimization

Active Learning for Regression Using Greedy Sampling

A Nonconvex Low-Rank Tensor Completion Model for Spatiotemporal Traffic Data Imputation

Stochastic Cubic Regularization for Fast Nonconvex Optimization

Neural Networks can Learn Representations with Gradient Descent

Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control

PHYRE: A New Benchmark for Physical Reasoning

Adaptive Gradient Descent without Descent

Provably Efficient Safe Exploration via Primal-Dual Policy Optimization

Unifying Conformal Language Tasks with In-Context Ensembles

The Geometry of Ignorance: LLMs Know When to Temper Bayesian Priors

Learning Deep Networks from Noisy Labels with Dropout Regularization

Defining and Characterizing Reward Hacking

Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection

On the Power and Limitations of Random Features for Understanding Neural Networks

Unifying Graph Convolutional Neural Networks and Label Propagation

What matters for Representation Alignment: Global Information or Spatial Structure?

Low-Rank Modeling and Its Applications in Image Analysis

Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier

Network cross-validation by edge sampling

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning

BREEDS: Benchmarks for Subpopulation Shift

Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme

Implicit Regularization of Discrete Gradient Dynamics in Linear Neural Networks

Z-Forcing: Training Stochastic Recurrent Networks

Self-Supervised Policy Adaptation during Deployment

Analyzing and Improving Representations with the Soft Nearest Neighbor Loss

Neural Collapse Under MSE Loss: Proximity to and Dynamics on the Central Path

Exact and Inexact Subsampled Newton Methods for Optimization

Sponge Examples: Energy-Latency Attacks on Neural Networks

Training Agents Inside of Scalable World Models

Sobolev Norm Learning Rates for Regularized Least-Squares Algorithm

A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce

Towards Understanding Regularization in Batch Normalization

Day-Ahead Hourly Forecasting of Power Generation from Photovoltaic Plants

Committee neural network potentials control generalization errors and enable active learning

Introduction to Online Convex Optimization

Informative Label Missingness in Multiclass Classification Information Geometry and Excess Risk

Geometry-Constrained Kolmogorov-Arnold Networks: Learning Edge Geometry via Banach Duality

Deep Skew-t Mixture Models

Structured Learning on Mapper Representations

Reinforcement Learning with Action Chunking

Learning to Act from Actionless Videos through Dense Correspondences

Simplified and Generalized Masked Diffusion for Discrete Data

Unexpected Improvements to Expected Improvement for Bayesian Optimization

Negative Momentum for Improved Game Dynamics

From parcel to continental scale -- A first European crop type map based on Sentinel-1 and LUCAS Copernicus in-situ observations

Anomaly Detection in Univariate Time-series: A Survey on the State-of-the-Art

Deep ROC Analysis and AUC as Balanced Average Accuracy to Improve Model Selection, Understanding and Interpretation