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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2,161 to 2,220 of 6,792

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model
Benjamin Letham, Cynthia Rudin, Tyler H. McCormick +1
stat.APcs.LGstat.MLarXiv:1511.01644v12015
Probabilistic Numerics and Uncertainty in Computations
Philipp Hennig, Michael A Osborne, Mark Girolami
math.NAcs.AIcs.LGarXiv:1506.01326v12015
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting
Jakub Konečný, Jie Liu, Peter Richtárik +1
cs.LGstat.MLarXiv:1504.04407v22015
Gaussian Processes for Data-Efficient Learning in Robotics and Control
Marc Peter Deisenroth, Dieter Fox, Carl Edward Rasmussen
stat.MLcs.LGcs.ROarXiv:1502.02860v22015
Exact tensor completion using t-SVD
Zemin Zhang, Shuchin Aeron
cs.LGmath.NAstat.MLarXiv:1502.04689v22015
Robust Data-Collection Policy Learning for Low-Variance Online Policy Evaluation
Claire Chen, Shuze Daniel Liu, Licheng Luo +3
cs.LGstat.MLarXiv:2608.24146v12026
Generalization, memorization, and overfitting for diffusion models trained in the lazy high-dimensional regime
Hugo Latourelle-Vigeant, Sinho Chewi, Aram-Alexandre Pooladian +2
stat.MLcs.LGmath.STarXiv:2608.23938v12026
Revenge of Monosemanticity: Specialized Neurons Improve Data Efficiency in MLPs
Amirhesam Abedsoltan, Enric Boix-Adsera, Fivos Kalogiannis +1
cs.LGstat.MLarXiv:2608.24007v12026
Online Optimization : Competing with Dynamic Comparators
Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour +1
cs.LGmath.OCstat.MLarXiv:1501.06225v12015
Conditional-Independence-Regularized Distributional Autoencoders for Mixed-Type Data
Siyuan Tang, Gongjun Xu, Ji Zhu
stat.MEcs.LGstat.MLarXiv:2608.20562v12026
Machine Learning for Neuroimaging with Scikit-Learn
Alexandre Abraham, Fabian Pedregosa, Michael Eickenberg +6
cs.LGcs.CVstat.MLarXiv:1412.3919v12014
Minimax Optimality of Score-Entropy Discrete Diffusion
Cholyeon Cho, Yuchen Wu
stat.MLcs.LGarXiv:2608.20635v12026
Achieving Exact Cluster Recovery Threshold via Semidefinite Programming
Bruce Hajek, Yihong Wu, Jiaming Xu
stat.MLcs.DSmath.PRarXiv:1412.6156v22014
Convex Optimization for Big Data
Volkan Cevher, Stephen Becker, Mark Schmidt
math.OCcs.LGstat.MLarXiv:1411.0972v12014
Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements
Naoki Egami, Sooahn Shin
stat.MEcs.AIcs.CLarXiv:2608.18294v12026
SPACE: Sample-cloud Predictive Adaptive Conformal Ellipsoids for Multivariate Time-Series Forecasting
Baishi Li, Kelvin J. L. Koa, Ke-Wei Huang
stat.MLcs.AIcs.LGarXiv:2608.17333v12026
LiD-GLM: Lipschitz-constrained Deep Generalized Linear Models
Tom Splittgerber, Niklas Koenen, Marvin N. Wright +1
stat.MLcs.LGarXiv:2608.16340v12026
Density-Reweighted Entropic Optimal Transport: Decoupling Geometry from Sampling Density
Keyi Li, Yuval Kluger, Boris Landa
stat.MLcs.LGstat.AParXiv:2608.16506v12026
Improved Regret Analysis for Parallel Gaussian Process Bandit Optimization
Shion Takeno, Shogo Iwazaki
stat.MLcs.LGarXiv:2608.16492v12026
EMS Coreset: An Efficient Expectation-Maximization Algorithm for Sinkhorn Coreset
Haoyun Yin, Chuanhui Liu, Xiao Wang
stat.MLcs.LGarXiv:2608.16101v12026
Generalized Linear Bandits with Memory
Heesang Ann, Hyunjun Choi, Taehyun Hwang +3
stat.MLcs.LGarXiv:2608.15848v12026
On Stopping Rules and Spatial Adaptation for CART
Zineng Xu, Yuchao Cai, Yan Shuo Tan
stat.MLcs.LGmath.STarXiv:2608.15649v12026
Optimal Watermark Localization in Mixed-Source Large Language Model Texts
Jose H. Blanchet, T. Tony Cai, Xiang Li +3
stat.MEcs.CLcs.LGarXiv:2608.14906v12026
Designing Reinforcement Learning for Diffusion Models: A Unified Path-Space View
Yixian Xu, Yuanrui Zhang, Shengjie Luo +2
cs.LGcs.CVstat.MLarXiv:2608.14430v12026
DC approximation approaches for sparse optimization
Hoai An Le Thi, Tao Pham Dinh, Hoai Minh Le +1
math.NAcs.LGstat.MLarXiv:1407.0286v22014
The Loss Does Not See the Basis, but Adam Does
Devender Singh
cs.LGmath.OCstat.MLarXiv:2608.05136v12026
Consistency of random forests
Erwan Scornet, Gérard Biau, Jean-Philippe Vert
math.STstat.MLarXiv:1405.2881v42014
The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction
Shu Wan, Abhinav Gorantla, Huan Liu +1
cs.LGcs.AIstat.MEarXiv:2605.29411v22026
Automatic Construction and Natural-Language Description of Nonparametric Regression Models
James Robert Lloyd, David Duvenaud, Roger Grosse +2
stat.MLcs.LGarXiv:1402.4304v32014
Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers
Tim Tsz-Kit Lau, Weijie Su
math.OCcs.AIcs.LGarXiv:2605.18106v42026
Reliable Chain-of-Thought via Prefix Consistency
Naoto Iwase, Yuki Ichihara, Mohammad Atif Quamar +1
stat.MLcs.CLcs.LGarXiv:2605.07654v12026
Multi-Step-Ahead Time Series Prediction using Multiple-Output Support Vector Regression
Yukun Bao, Tao Xiong, Zhongyi Hu
cs.LGstat.MLarXiv:1401.2504v12014
Addressing Performance Saturation for LLM RL via Precise Entropy Curve Control
Bolian Li, Yifan Wang, Yi Ding +3
cs.LGcs.CLstat.MLarXiv:2604.26326v22026
Consistency of spectral clustering in stochastic block models
Jing Lei, Alessandro Rinaldo
math.STstat.MLarXiv:1312.2050v32013
Cactus: Accelerating Auto-Regressive Decoding with Constrained Acceptance Speculative Sampling
Yongchang Hao, Lili Mou
cs.LGcs.AImath.OCarXiv:2604.04987v12026
Understanding Behavior Cloning with Action Quantization
Haoqun Cao, Tengyang Xie
cs.LGstat.MLarXiv:2603.20538v12026
CAM: Causal additive models, high-dimensional order search and penalized regression
Peter Bühlmann, Jonas Peters, Jan Ernest
stat.MEcs.LGstat.MLarXiv:1310.1533v22013
Taming VAEs
Danilo Jimenez Rezende, Fabio Viola
stat.MLcs.LGarXiv:1810.00597v12018
A Theoretical Analysis of NDCG Type Ranking Measures
Yining Wang, Liwei Wang, Yuanzhi Li +3
cs.LGcs.IRstat.MLarXiv:1304.6480v12013
Adaptive piecewise polynomial estimation via trend filtering
Ryan J. Tibshirani
math.STstat.MEstat.MLarXiv:1304.2986v22013
A Deep Learning Framework for Assessing Physical Rehabilitation Exercises
Y. Liao, A. Vakanski, M. Xian
cs.LGstat.MLarXiv:1901.10435v32019
Learning Longer-term Dependencies in RNNs with Auxiliary Losses
Trieu H. Trinh, Andrew M. Dai, Minh-Thang Luong +1
cs.LGcs.AIstat.MLarXiv:1803.00144v32018
Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization
Xiao Wang, Shiqian Ma, Donald Goldfarb +1
math.OCcs.LGmath.NAarXiv:1607.01231v42016
Cross-Entropy Loss Functions: Theoretical Analysis and Applications
Anqi Mao, Mehryar Mohri, Yutao Zhong
cs.LGstat.MLarXiv:2304.07288v22023
Galactica: A Large Language Model for Science
Ross Taylor, Marcin Kardas, Guillem Cucurull +6
cs.CLstat.MLarXiv:2211.09085v12022
An Introductory Study on Time Series Modeling and Forecasting
Ratnadip Adhikari, R. K. Agrawal
cs.LGstat.MLarXiv:1302.6613v12013
Robust subspace clustering
Mahdi Soltanolkotabi, Ehsan Elhamifar, Emmanuel J. Candès
cs.LGcs.ITmath.OCarXiv:1301.2603v32013
DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps
Cheng Lu, Yuhao Zhou, Fan Bao +3
cs.LGstat.MLarXiv:2206.00927v32022
When and why PINNs fail to train: A neural tangent kernel perspective
Sifan Wang, Xinling Yu, Paris Perdikaris
cs.LGmath.NAstat.MLarXiv:2007.14527v12020
Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction
Hyungjin Chung, Byeongsu Sim, Jong Chul Ye
eess.IVcs.CVcs.LGarXiv:2112.05146v22021
CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
Yusuke Tashiro, Jiaming Song, Yang Song +1
cs.LGstat.MLarXiv:2107.03502v22021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks
Sifan Wang, Hanwen Wang, Paris Perdikaris
cs.LGcs.AIstat.MLarXiv:2012.10047v12020
Underspecification Presents Challenges for Credibility in Modern Machine Learning
Alexander D'Amour, Katherine Heller, Dan Moldovan +37
cs.LGstat.MLarXiv:2011.03395v22020
Rethinking Attention with Performers
Krzysztof Choromanski, Valerii Likhosherstov, David Dohan +10
cs.LGcs.CLstat.MLarXiv:2009.14794v42020
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems
Ruoxi Wang, Rakesh Shivanna, Derek Z. Cheng +4
cs.IRcs.LGstat.MLarXiv:2008.13535v22020
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization
Shai Shalev-Shwartz, Tong Zhang
stat.MLcs.LGmath.OCarXiv:1209.1873v22012
QPLEX: Duplex Dueling Multi-Agent Q-Learning
Jianhao Wang, Zhizhou Ren, Terry Liu +2
cs.LGcs.AIcs.MAarXiv:2008.01062v32020
On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice
Li Yang, Abdallah Shami
cs.LGstat.MLarXiv:2007.15745v32020
Early-Learning Regularization Prevents Memorization of Noisy Labels
Sheng Liu, Jonathan Niles-Weed, Narges Razavian +1
cs.LGcs.CVstat.MLarXiv:2007.00151v22020
Personalized Federated Learning with Moreau Envelopes
Canh T. Dinh, Nguyen H. Tran, Tuan Dung Nguyen
cs.LGcs.DCstat.MLarXiv:2006.08848v32020

Machine Learning (stat)

Interpretable classifiers using rules and Bayesian analysis: Building a better stroke prediction model

Probabilistic Numerics and Uncertainty in Computations

Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting

Gaussian Processes for Data-Efficient Learning in Robotics and Control

Exact tensor completion using t-SVD

Robust Data-Collection Policy Learning for Low-Variance Online Policy Evaluation

Generalization, memorization, and overfitting for diffusion models trained in the lazy high-dimensional regime

Revenge of Monosemanticity: Specialized Neurons Improve Data Efficiency in MLPs

Online Optimization : Competing with Dynamic Comparators

Conditional-Independence-Regularized Distributional Autoencoders for Mixed-Type Data

Machine Learning for Neuroimaging with Scikit-Learn

Minimax Optimality of Score-Entropy Discrete Diffusion

Achieving Exact Cluster Recovery Threshold via Semidefinite Programming

Convex Optimization for Big Data

Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements

SPACE: Sample-cloud Predictive Adaptive Conformal Ellipsoids for Multivariate Time-Series Forecasting

LiD-GLM: Lipschitz-constrained Deep Generalized Linear Models

Density-Reweighted Entropic Optimal Transport: Decoupling Geometry from Sampling Density

Improved Regret Analysis for Parallel Gaussian Process Bandit Optimization

EMS Coreset: An Efficient Expectation-Maximization Algorithm for Sinkhorn Coreset

Generalized Linear Bandits with Memory

On Stopping Rules and Spatial Adaptation for CART

Optimal Watermark Localization in Mixed-Source Large Language Model Texts

Designing Reinforcement Learning for Diffusion Models: A Unified Path-Space View

DC approximation approaches for sparse optimization

The Loss Does Not See the Basis, but Adam Does

Consistency of random forests

The Good, the Bad, and the Ugly of Markov Boundary for Tabular Prediction

Automatic Construction and Natural-Language Description of Nonparametric Regression Models

Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers

Reliable Chain-of-Thought via Prefix Consistency

Multi-Step-Ahead Time Series Prediction using Multiple-Output Support Vector Regression

Addressing Performance Saturation for LLM RL via Precise Entropy Curve Control

Consistency of spectral clustering in stochastic block models

Cactus: Accelerating Auto-Regressive Decoding with Constrained Acceptance Speculative Sampling

Understanding Behavior Cloning with Action Quantization

CAM: Causal additive models, high-dimensional order search and penalized regression

Taming VAEs

A Theoretical Analysis of NDCG Type Ranking Measures

Adaptive piecewise polynomial estimation via trend filtering

A Deep Learning Framework for Assessing Physical Rehabilitation Exercises

Learning Longer-term Dependencies in RNNs with Auxiliary Losses

Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization

Cross-Entropy Loss Functions: Theoretical Analysis and Applications

Galactica: A Large Language Model for Science

An Introductory Study on Time Series Modeling and Forecasting

Robust subspace clustering

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps

When and why PINNs fail to train: A neural tangent kernel perspective

Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction

CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation

On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks

Underspecification Presents Challenges for Credibility in Modern Machine Learning

Rethinking Attention with Performers

DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems

Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization

QPLEX: Duplex Dueling Multi-Agent Q-Learning

On Hyperparameter Optimization of Machine Learning Algorithms: Theory and Practice

Early-Learning Regularization Prevents Memorization of Noisy Labels

Personalized Federated Learning with Moreau Envelopes