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)

8,521 to 8,580 of 9,676

Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black-Scholes Partial Differential Equations
Julius Berner, Philipp Grohs, Arnulf Jentzen
cs.LGmath.NAstat.MLarXiv:1809.03062v32018
Policy Learning with Observational Data
Susan Athey, Stefan Wager
math.STcs.LGecon.EMarXiv:1702.02896v62017
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks
Georgios Kissas, Yibo Yang, Eileen Hwuang +3
cs.LGstat.MLarXiv:1905.04817v22019
Timer: Generative Pre-trained Transformers Are Large Time Series Models
Yong Liu, Haoran Zhang, Chenyu Li +3
cs.LGstat.MLarXiv:2402.02368v32024
Fairness without Demographics through Adversarially Reweighted Learning
Preethi Lahoti, Alex Beutel, Jilin Chen +5
cs.LGstat.MLarXiv:2006.13114v32020
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
Jesse Farebrother, Jordi Orbay, Quan Vuong +9
cs.LGcs.AIstat.MLarXiv:2403.03950v12024
Kernels for Vector-Valued Functions: a Review
Mauricio A. Alvarez, Lorenzo Rosasco, Neil D. Lawrence
stat.MLcs.AImath.STarXiv:1106.6251v22011
From Pixels to Torques: Policy Learning with Deep Dynamical Models
Niklas Wahlström, Thomas B. Schön, Marc Peter Deisenroth
stat.MLcs.LGcs.ROarXiv:1502.02251v32015
Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics
Amir Mosavi, Pedram Ghamisi, Yaser Faghan +1
q-fin.STcs.LGecon.GNarXiv:2004.01509v12020
Ridge Regression, Hubness, and Zero-Shot Learning
Yutaro Shigeto, Ikumi Suzuki, Kazuo Hara +2
cs.LGstat.MLarXiv:1507.00825v12015
Signature moments to characterize laws of stochastic processes
Ilya Chevyrev, Harald Oberhauser
math.STmath.PRstat.MLarXiv:1810.10971v22018
Learning Phase Competition for Traffic Signal Control
Guanjie Zheng, Yuanhao Xiong, Xinshi Zang +6
cs.LGcs.AIstat.MLarXiv:1905.04722v12019
Hallucinations are inevitable but can be made statistically negligible
Atsushi Suzuki, Yulan He, Feng Tian +1
cs.CLcs.FLcs.LGarXiv:2502.12187v32025
On the Mechanism and Dynamics of Modular Addition: Fourier Features, Lottery Ticket, and Grokking
Jianliang He, Leda Wang, Siyu Chen +1
cs.LGmath.OCstat.MLarXiv:2602.16849v12026
Reliable Chain-of-Thought via Prefix Consistency
Naoto Iwase, Yuki Ichihara, Mohammad Atif Quamar +1
stat.MLcs.CLcs.LGarXiv:2605.07654v12026
Vanilla Bayesian Optimization Performs Great in High Dimensions
Carl Hvarfner, Erik Orm Hellsten, Luigi Nardi
cs.LGstat.MLarXiv:2402.02229v52024
RayS: A Ray Searching Method for Hard-label Adversarial Attack
Jinghui Chen, Quanquan Gu
cs.LGcs.AIstat.MLarXiv:2006.12792v22020
Solving Empirical Risk Minimization in the Current Matrix Multiplication Time
Yin Tat Lee, Zhao Song, Qiuyi Zhang
cs.DScs.LGmath.OCarXiv:1905.04447v12019
Neural Program Repair by Jointly Learning to Localize and Repair
Marko Vasic, Aditya Kanade, Petros Maniatis +2
cs.LGstat.MLarXiv:1904.01720v12019
GP-VAE: Deep Probabilistic Time Series Imputation
Vincent Fortuin, Dmitry Baranchuk, Gunnar Rätsch +1
stat.MLcs.LGarXiv:1907.04155v52019
Variational Inference: A Review for Statisticians
David M. Blei, Alp Kucukelbir, Jon D. McAuliffe
stat.COcs.LGstat.MLarXiv:1601.00670v92016
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma, Tim Salimans, Max Welling
stat.MLcs.LGstat.COarXiv:1506.02557v22015
Randomized Sketches of Convex Programs with Sharp Guarantees
Mert Pilanci, Martin J. Wainwright
cs.ITcs.DSmath.OCarXiv:1404.7203v12014
Demystifying Orthogonal Monte Carlo and Beyond
Han Lin, Haoxian Chen, Tianyi Zhang +2
cs.LGstat.MLarXiv:2005.13590v12020
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models
Cassidy Laidlaw, Sahil Singla, Soheil Feizi
cs.LGcs.CVstat.MLarXiv:2006.12655v42020
Identifiability of Nonnegative Tensor Decompositions via Positive Scattering
Haoming Wang, Ming Yuan
stat.MLcs.LGmath.COarXiv:2609.11606v12026
Most Influential Subset Selection: Challenges, Promises, and Beyond
Yuzheng Hu, Pingbang Hu, Han Zhao +1
cs.LGstat.MLarXiv:2409.18153v22024
Compositional Generalization via Structural Identification in a Category-Theoretic Framework
Akihiro Maeda, Thomas Seiller, Yohei Oseki
cs.CLstat.MLarXiv:2608.26465v12026
Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting
Bing Yu, Haoteng Yin, Zhanxing Zhu
cs.LGstat.MLarXiv:1709.04875v42017
Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning
Ruiqi Zhang, Licong Lin, Yu Bai +1
cs.LGcs.AIcs.CLarXiv:2404.05868v22024
A vector-contraction inequality for Rademacher complexities
Andreas Maurer
cs.LGstat.MLarXiv:1605.00251v12016
Tight Prediction Intervals Using Expanded Interval Minimization
Dongqi Su, Ying Yin Ting, Jason Ansel
cs.LGstat.MLarXiv:1806.11222v12018
Online Optimization : Competing with Dynamic Comparators
Ali Jadbabaie, Alexander Rakhlin, Shahin Shahrampour +1
cs.LGmath.OCstat.MLarXiv:1501.06225v12015
NSML: Meet the MLaaS platform with a real-world case study
Hanjoo Kim, Minkyu Kim, Dongjoo Seo +9
cs.DCcs.LGstat.MLarXiv:1810.09957v12018
CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients
Dani Kiyasseh, Tingting Zhu, David A. Clifton
cs.LGeess.SPstat.MLarXiv:2005.13249v32020
Learning to Optimize
Ke Li, Jitendra Malik
cs.LGcs.AImath.OCarXiv:1606.01885v12016
Stress-Testing Dynamical and Generative Downscaling Using Subseasonal Extreme Precipitation Forecasts
Mauricio Lima, Marika Koukoula, Romain Pilon +4
physics.comp-phphysics.geo-phstat.MLarXiv:2609.11696v12026
Assumption-lean logistic regression with missing covariates
Jyotishka Ray Choudhury, Kabir Aladin Verchand, Richard J. Samworth +1
stat.MLcs.ITcs.LGarXiv:2610.07292v12026
Convolutional-network models to predict wall-bounded turbulence from wall quantities
L. Guastoni, A. Güemes, A. Ianiro +4
physics.flu-dynphysics.comp-phstat.MLarXiv:2006.12483v12020
Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation
Xinyu Chen, Mengying Lei, Nicolas Saunier +1
cs.LGstat.MLarXiv:2104.14936v12021
Multi-Head Self Attention is a Parameter Identification Mechanism
W. Ross Morrow
cs.LGstat.MLarXiv:2609.01231v12026
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics
Yuchen Zhang, Percy Liang, Moses Charikar
cs.LGmath.OCstat.MLarXiv:1702.05575v32017
Tensor Network Moral Graph Recovery of Discrete Probability Distributions
Á. Troyano Olivas, Chi-Hang Fred Fung, Hans H. Brunner +2
stat.MLcs.ITcs.LGarXiv:2609.09258v12026
Predicting Path Failure In Time-Evolving Graphs
Jia Li, Zhichao Han, Hong Cheng +4
cs.LGstat.MLarXiv:1905.03994v22019
Fairness Without Demographics in Repeated Loss Minimization
Tatsunori B. Hashimoto, Megha Srivastava, Hongseok Namkoong +1
stat.MLcs.LGarXiv:1806.08010v22018
Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes
Chen-Yu Wei, Mehdi Jafarnia-Jahromi, Haipeng Luo +2
cs.LGcs.AIstat.MLarXiv:1910.07072v22019
PHYRE: A New Benchmark for Physical Reasoning
Anton Bakhtin, Laurens van der Maaten, Justin Johnson +2
cs.LGcs.AIstat.MLarXiv:1908.05656v12019
Random Hazard Forests
Hemant Ishwaran, Eileen M. Hsich, Udaya B. Kogalur +1
stat.MLcs.LGstat.MEarXiv:2608.21597v12026
Energy-based Generative Adversarial Network
Junbo Zhao, Michael Mathieu, Yann LeCun
cs.LGstat.MLarXiv:1609.03126v42016
Copula Active Subspaces I: A Score-Covariance Method for Reduced-Order Non-Gaussian Density Estimation
Joshua Chen, Peter Jan van Leeuwen
stat.MEstat.COstat.MLarXiv:2609.36142v22026
Sparse DNNs with Improved Adversarial Robustness
Yiwen Guo, Chao Zhang, Changshui Zhang +1
cs.LGcs.CRcs.CVarXiv:1810.09619v22018
Learning to Cover Locally: Graph Neural Combinatorial Optimization under a Hard Information Horizon
Johannes F. Loevenich, Thies Moehlenhof, Laurin Holz +3
stat.MLcs.AIcs.LGarXiv:2610.00422v12026
Predicting Expressive Speaking Style From Text In End-To-End Speech Synthesis
Daisy Stanton, Yuxuan Wang, RJ Skerry-Ryan
cs.CLcs.LGcs.SDarXiv:1808.01410v12018
Unsupervised Domain Adaptation via Regularized Conditional Alignment
Safa Cicek, Stefano Soatto
cs.LGcs.CVstat.MLarXiv:1905.10885v12019
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
Gen Li, Yuting Wei, Yuejie Chi +1
cs.LGcs.ITmath.OCarXiv:2005.12900v82020
Pyro: Deep Universal Probabilistic Programming
Eli Bingham, Jonathan P. Chen, Martin Jankowiak +7
cs.LGcs.PLstat.MLarXiv:1810.09538v12018
Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform
Zhenyu Zhao, Radhika Anand, Mallory Wang
stat.MLcs.LGarXiv:1908.05376v12019
Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality
Rui Gao
cs.LGmath.PRstat.MLarXiv:2009.04382v32020
Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization
Noam Razin, Sadhika Malladi, Adithya Bhaskar +3
cs.LGcs.AIcs.CLarXiv:2410.08847v42024
Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning
Qiang Ma, Suwen Ge, Danyang He +2
cs.LGstat.MLarXiv:1911.04936v12019

Machine Learning (stat)

Analysis of the Generalization Error: Empirical Risk Minimization over Deep Artificial Neural Networks Overcomes the Curse of Dimensionality in the Numerical Approximation of Black-Scholes Partial Differential Equations

Policy Learning with Observational Data

Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks

Timer: Generative Pre-trained Transformers Are Large Time Series Models

Fairness without Demographics through Adversarially Reweighted Learning

Stop Regressing: Training Value Functions via Classification for Scalable Deep RL

Kernels for Vector-Valued Functions: a Review

From Pixels to Torques: Policy Learning with Deep Dynamical Models

Comprehensive Review of Deep Reinforcement Learning Methods and Applications in Economics

Ridge Regression, Hubness, and Zero-Shot Learning

Signature moments to characterize laws of stochastic processes

Learning Phase Competition for Traffic Signal Control

Hallucinations are inevitable but can be made statistically negligible

On the Mechanism and Dynamics of Modular Addition: Fourier Features, Lottery Ticket, and Grokking

Reliable Chain-of-Thought via Prefix Consistency

Vanilla Bayesian Optimization Performs Great in High Dimensions

RayS: A Ray Searching Method for Hard-label Adversarial Attack

Solving Empirical Risk Minimization in the Current Matrix Multiplication Time

Neural Program Repair by Jointly Learning to Localize and Repair

GP-VAE: Deep Probabilistic Time Series Imputation

Variational Inference: A Review for Statisticians

Variational Dropout and the Local Reparameterization Trick

Randomized Sketches of Convex Programs with Sharp Guarantees

Demystifying Orthogonal Monte Carlo and Beyond

Perceptual Adversarial Robustness: Defense Against Unseen Threat Models

Identifiability of Nonnegative Tensor Decompositions via Positive Scattering

Most Influential Subset Selection: Challenges, Promises, and Beyond

Compositional Generalization via Structural Identification in a Category-Theoretic Framework

Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting

Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning

A vector-contraction inequality for Rademacher complexities

Tight Prediction Intervals Using Expanded Interval Minimization

Online Optimization : Competing with Dynamic Comparators

NSML: Meet the MLaaS platform with a real-world case study

CLOCS: Contrastive Learning of Cardiac Signals Across Space, Time, and Patients

Learning to Optimize

Stress-Testing Dynamical and Generative Downscaling Using Subseasonal Extreme Precipitation Forecasts

Assumption-lean logistic regression with missing covariates

Convolutional-network models to predict wall-bounded turbulence from wall quantities

Low-Rank Autoregressive Tensor Completion for Spatiotemporal Traffic Data Imputation

Multi-Head Self Attention is a Parameter Identification Mechanism

A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics

Tensor Network Moral Graph Recovery of Discrete Probability Distributions

Predicting Path Failure In Time-Evolving Graphs

Fairness Without Demographics in Repeated Loss Minimization

Model-free Reinforcement Learning in Infinite-horizon Average-reward Markov Decision Processes

PHYRE: A New Benchmark for Physical Reasoning

Random Hazard Forests

Energy-based Generative Adversarial Network

Copula Active Subspaces I: A Score-Covariance Method for Reduced-Order Non-Gaussian Density Estimation

Sparse DNNs with Improved Adversarial Robustness

Learning to Cover Locally: Graph Neural Combinatorial Optimization under a Hard Information Horizon

Predicting Expressive Speaking Style From Text In End-To-End Speech Synthesis

Unsupervised Domain Adaptation via Regularized Conditional Alignment

Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model

Pyro: Deep Universal Probabilistic Programming

Maximum Relevance and Minimum Redundancy Feature Selection Methods for a Marketing Machine Learning Platform

Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality

Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization

Combinatorial Optimization by Graph Pointer Networks and Hierarchical Reinforcement Learning