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.

Search paper metadata (including unsummarized papers)

1,381 to 1,440 of 6,790

On the Connection Between Adversarial Robustness and Saliency Map Interpretability
Christian Etmann, Sebastian Lunz, Peter Maass +1
stat.MLcs.CVcs.LGarXiv:1905.04172v12019
Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels
Haim Avron, Vikas Sindhwani, Jiyan Yang +1
stat.MLcs.LGmath.NAarXiv:1412.8293v22014
Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $ \ell^1 $ and $ \ell^0 $ Controls
Jason M. Klusowski, Andrew R. Barron
stat.MLmath.STarXiv:1607.07819v32016
Smart "Predict, then Optimize"
Adam N. Elmachtoub, Paul Grigas
math.OCcs.LGstat.MLarXiv:1710.08005v52017
From Predictive to Prescriptive Analytics
Dimitris Bertsimas, Nathan Kallus
stat.MLcs.LGmath.OCarXiv:1402.5481v42014
Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers
Yonatan Geifman, Guy Uziel, Ran El-Yaniv
cs.LGstat.MLarXiv:1805.08206v42018
Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage
Masatoshi Uehara, Wen Sun
cs.LGcs.AIstat.MLarXiv:2107.06226v42021
Notes on Computational Hardness of Hypothesis Testing: Predictions using the Low-Degree Likelihood Ratio
Dmitriy Kunisky, Alexander S. Wein, Afonso S. Bandeira
math.STcs.CCcs.DSarXiv:1907.11636v12019
Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs
Nikolaos Karalias, Andreas Loukas
cs.LGstat.MLarXiv:2006.10643v42020
Power-SMC: Low-Latency Sequence-Level Power Sampling for Training-Free LLM Reasoning
Seyedarmin Azizi, Erfan Baghaei Potraghloo, Minoo Ahmadi +2
stat.MLcs.LGarXiv:2602.10273v22026
DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks
Xingjian Li, Haoyi Xiong, Hanchao Wang +4
cs.LGstat.MLarXiv:1901.09229v42019
Deep learning observables in computational fluid dynamics
Kjetil O. Lye, Siddhartha Mishra, Deep Ray
physics.comp-phcs.LGmath.NAarXiv:1903.03040v22019
Geometric Mean Metric Learning
Pourya Habib Zadeh, Reshad Hosseini, Suvrit Sra
stat.MLcs.LGarXiv:1607.05002v12016
Reliable and Explainable Machine Learning Methods for Accelerated Material Discovery
Bhavya Kailkhura, Brian Gallagher, Sookyung Kim +2
physics.comp-phcond-mat.mtrl-scistat.MLarXiv:1901.02717v22019
Reinforcement Learning with Quantum Variational Circuits
Owen Lockwood, Mei Si
quant-phcs.LGstat.MLarXiv:2008.07524v32020
Building Damage Detection in Satellite Imagery Using Convolutional Neural Networks
Joseph Z. Xu, Wenhan Lu, Zebo Li +2
cs.CVcs.LGeess.IVarXiv:1910.06444v12019
Deriving Neural Scaling Laws from the statistics of natural language
Francesco Cagnetta, Allan Raventós, Surya Ganguli +1
cs.LGcs.AIstat.MLarXiv:2602.07488v32026
The information geometry of product-reference discrete diffusion: Interaction growth complexity and optimal scheduling
Martin J. Wainwright
stat.MLcs.AIcs.LGarXiv:2608.28949v12026
Preconditioning Benefits of Spectral Orthogonalization in Muon
Jianhao Ma, Yu Huang, Yuejie Chi +1
cs.LGcs.AImath.OCarXiv:2601.13474v12026
Quantitative Target Convergence and Uniform-in-Time Propagation of Chaos for Langevin-Regularized SVGD
Sayan Banerjee, Dohyeon Kim
stat.MLcs.LGmath.PRarXiv:2608.28827v12026
Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records
Zhengping Che, Yu Cheng, Shuangfei Zhai +2
cs.LGstat.MLarXiv:1709.01648v12017
Learn Beneficial Noise as Graph Augmentation
Siqi Huang, Yanchen Xu, Hongyuan Zhang +1
cs.LGstat.MLarXiv:2505.19024v12025
Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning
Jian Wu, Saul Toscano-Palmerin, Peter I. Frazier +1
cs.LGmath.OCstat.MEarXiv:1903.04703v12019
Distilling Policy Distillation
Wojciech Marian Czarnecki, Razvan Pascanu, Simon Osindero +3
cs.LGcs.AIstat.MLarXiv:1902.02186v12019
Physics-Guided Deep Neural Networks for Power Flow Analysis
Xinyue Hu, Haoji Hu, Saurabh Verma +1
cs.LGeess.SPstat.MLarXiv:2002.00097v22020
Gaussian Process Regression with a Student-t Likelihood
Pasi Jylänki, Jarno Vanhatalo, Aki Vehtari
stat.MLstat.MEarXiv:1106.4431v12011
Clustering Partially Observed Graphs via Convex Optimization
Yudong Chen, Ali Jalali, Sujay Sanghavi +1
cs.LGstat.MLarXiv:1104.4803v42011
Tensor Programs II: Neural Tangent Kernel for Any Architecture
Greg Yang
stat.MLcond-mat.dis-nncs.LGarXiv:2006.14548v42020
Group-Sparse Signal Denoising: Non-Convex Regularization, Convex Optimization
Po-Yu Chen, Ivan W. Selesnick
cs.CVcs.LGstat.MLarXiv:1308.5038v22013
Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems
Alinson S. Xavier, Feng Qiu, Shabbir Ahmed
math.OCcs.LGstat.MLarXiv:1902.01697v22019
On the Distribution of Penalized Maximum Likelihood Estimators: The LASSO, SCAD, and Thresholding
Benedikt M. Potscher, Hannes Leeb
math.STstat.MEstat.MLarXiv:0711.0660v22007
Sparse Matrix Inversion with Scaled Lasso
Tingni Sun, Cun-Hui Zhang
math.STstat.MLarXiv:1202.2723v22012
Consistent feature attribution for tree ensembles
Scott M. Lundberg, Su-In Lee
cs.AIcs.LGstat.MLarXiv:1706.06060v62017
Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells
Gengchen Mai, Krzysztof Janowicz, Bo Yan +3
cs.CVcs.AIcs.LGarXiv:2003.00824v12020
N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning
Anubhav Ashok, Nicholas Rhinehart, Fares Beainy +1
cs.LGstat.MLarXiv:1709.06030v22017
Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning
Cameron Voloshin, Hoang M. Le, Nan Jiang +1
cs.LGcs.AIcs.ROarXiv:1911.06854v32019
Subgraph Neural Networks
Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li +1
cs.LGcs.SIstat.MLarXiv:2006.10538v32020
Matrix Completion on Graphs
Vassilis Kalofolias, Xavier Bresson, Michael Bronstein +1
cs.LGstat.MLarXiv:1408.1717v32014
ProDiGe: PRioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples
Fantine Mordelet, Jean-Philippe Vert
q-bio.QMstat.MLarXiv:1106.0134v12011
Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient
Tianbao Yang, Lijun Zhang, Rong Jin +1
cs.LGmath.OCstat.MLarXiv:1605.04638v12016
Subspace Robust Wasserstein Distances
François-Pierre Paty, Marco Cuturi
cs.LGstat.MLarXiv:1901.08949v52019
Overlearning Reveals Sensitive Attributes
Congzheng Song, Vitaly Shmatikov
cs.LGcs.NEstat.MLarXiv:1905.11742v32019
Supervised Learning with Quantum-Inspired Tensor Networks
E. Miles Stoudenmire, David J. Schwab
stat.MLcond-mat.str-elcs.LGarXiv:1605.05775v22016
OptShrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage
Raj Rao Nadakuditi
math.STcs.ITstat.MLarXiv:1306.6042v42013
Support recovery without incoherence: A case for nonconvex regularization
Po-Ling Loh, Martin J. Wainwright
math.STcs.ITstat.MLarXiv:1412.5632v12014
The Price of Fair PCA: One Extra Dimension
Samira Samadi, Uthaipon Tantipongpipat, Jamie Morgenstern +2
cs.LGstat.MLarXiv:1811.00103v12018
Linear Contextual Bandits with Knapsacks
Shipra Agrawal, Nikhil R. Devanur
cs.LGmath.OCstat.MLarXiv:1507.06738v22015
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization
Jelena Diakonikolas, Constantinos Daskalakis, Michael I. Jordan
math.OCcs.DScs.LGarXiv:2011.00364v22020
Spectral bandits
Tomáš Kocák, Rémi Munos, Branislav Kveton +2
stat.MLcs.AIcs.LGarXiv:2604.25272v12026
Multi-Head Self Attention is a Parameter Identification Mechanism
W. Ross Morrow
cs.LGstat.MLarXiv:2609.01231v12026
Variable Selection for Feature-Based Newsvendor
Zhaoliang Yuan, Jie Wang
stat.MLcs.LGarXiv:2609.01544v12026
The Optimal Sample Complexity of Multiclass and List Learning
Chirag Pabbaraju
cs.LGstat.MLarXiv:2604.24749v42026
MuonEq: Balancing Before Orthogonalization with Lightweight Equilibration
Da Chang, Qiankun Shi, Lvgang Zhang +5
cs.LGstat.MLarXiv:2603.28254v22026
A Deep Learning Interpretable Classifier for Diabetic Retinopathy Disease Grading
Jordi de la Torre, Aida Valls, Domenec Puig
cs.LGcs.CVstat.MLarXiv:1712.08107v12017
Diffusion Models for Video Prediction and Infilling
Tobias Höppe, Arash Mehrjou, Stefan Bauer +2
cs.CVcs.LGstat.MLarXiv:2206.07696v32022
Patent Claim Generation by Fine-Tuning OpenAI GPT-2
Jieh-Sheng Lee, Jieh Hsiang
cs.CLcs.LGstat.MLarXiv:1907.02052v12019
Tensor principal component analysis via sum-of-squares proofs
Samuel B. Hopkins, Jonathan Shi, David Steurer
cs.LGcs.CCcs.DSarXiv:1507.03269v12015
There Will Be a Scientific Theory of Deep Learning
Jamie Simon, Daniel Kunin, Alexander Atanasov +11
stat.MLcs.LGarXiv:2604.21691v12026
Uniform Statistical Convergence of Empirical Sinkhorn Potentials with Exponential and Polynomial Dependence on the Regularization Parameter
Denis Belomestny
stat.MLcs.LGmath.OCarXiv:2608.29152v12026
Understanding State Preferences With Text As Data: Introducing the UN General Debate Corpus
Alexander Baturo, Niheer Dasandi, Slava J. Mikhaylov
cs.CLcs.AIstat.MLarXiv:1707.02774v12017

Machine Learning (stat)

On the Connection Between Adversarial Robustness and Saliency Map Interpretability

Quasi-Monte Carlo Feature Maps for Shift-Invariant Kernels

Approximation by Combinations of ReLU and Squared ReLU Ridge Functions with $ \ell^1 $ and $ \ell^0 $ Controls

Smart "Predict, then Optimize"

From Predictive to Prescriptive Analytics

Bias-Reduced Uncertainty Estimation for Deep Neural Classifiers

Pessimistic Model-based Offline Reinforcement Learning under Partial Coverage

Notes on Computational Hardness of Hypothesis Testing: Predictions using the Low-Degree Likelihood Ratio

Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs

Power-SMC: Low-Latency Sequence-Level Power Sampling for Training-Free LLM Reasoning

DELTA: DEep Learning Transfer using Feature Map with Attention for Convolutional Networks

Deep learning observables in computational fluid dynamics

Geometric Mean Metric Learning

Reliable and Explainable Machine Learning Methods for Accelerated Material Discovery

Reinforcement Learning with Quantum Variational Circuits

Building Damage Detection in Satellite Imagery Using Convolutional Neural Networks

Deriving Neural Scaling Laws from the statistics of natural language

The information geometry of product-reference discrete diffusion: Interaction growth complexity and optimal scheduling

Preconditioning Benefits of Spectral Orthogonalization in Muon

Quantitative Target Convergence and Uniform-in-Time Propagation of Chaos for Langevin-Regularized SVGD

Boosting Deep Learning Risk Prediction with Generative Adversarial Networks for Electronic Health Records

Learn Beneficial Noise as Graph Augmentation

Practical Multi-fidelity Bayesian Optimization for Hyperparameter Tuning

Distilling Policy Distillation

Physics-Guided Deep Neural Networks for Power Flow Analysis

Gaussian Process Regression with a Student-t Likelihood

Clustering Partially Observed Graphs via Convex Optimization

Tensor Programs II: Neural Tangent Kernel for Any Architecture

Group-Sparse Signal Denoising: Non-Convex Regularization, Convex Optimization

Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems

On the Distribution of Penalized Maximum Likelihood Estimators: The LASSO, SCAD, and Thresholding

Sparse Matrix Inversion with Scaled Lasso

Consistent feature attribution for tree ensembles

Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells

N2N Learning: Network to Network Compression via Policy Gradient Reinforcement Learning

Empirical Study of Off-Policy Policy Evaluation for Reinforcement Learning

Subgraph Neural Networks

Matrix Completion on Graphs

ProDiGe: PRioritization Of Disease Genes with multitask machine learning from positive and unlabeled examples

Tracking Slowly Moving Clairvoyant: Optimal Dynamic Regret of Online Learning with True and Noisy Gradient

Subspace Robust Wasserstein Distances

Overlearning Reveals Sensitive Attributes

Supervised Learning with Quantum-Inspired Tensor Networks

OptShrink: An algorithm for improved low-rank signal matrix denoising by optimal, data-driven singular value shrinkage

Support recovery without incoherence: A case for nonconvex regularization

The Price of Fair PCA: One Extra Dimension

Linear Contextual Bandits with Knapsacks

Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization

Spectral bandits

Multi-Head Self Attention is a Parameter Identification Mechanism

Variable Selection for Feature-Based Newsvendor

The Optimal Sample Complexity of Multiclass and List Learning

MuonEq: Balancing Before Orthogonalization with Lightweight Equilibration

A Deep Learning Interpretable Classifier for Diabetic Retinopathy Disease Grading

Diffusion Models for Video Prediction and Infilling

Patent Claim Generation by Fine-Tuning OpenAI GPT-2

Tensor principal component analysis via sum-of-squares proofs

There Will Be a Scientific Theory of Deep Learning

Uniform Statistical Convergence of Empirical Sinkhorn Potentials with Exponential and Polynomial Dependence on the Regularization Parameter

Understanding State Preferences With Text As Data: Introducing the UN General Debate Corpus