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)

7,981 to 8,040 of 9,676

Policy-Gradient Algorithms Have No Guarantees of Convergence in Linear Quadratic Games
Eric Mazumdar, Lillian J. Ratliff, Michael I. Jordan +1
cs.LGstat.MLarXiv:1907.03712v22019
Detecting Spiky Corruption in Markov Decision Processes
Jason Mancuso, Tomasz Kisielewski, David Lindner +1
cs.LGstat.MLarXiv:1907.00452v12019
Deep Gamblers: Learning to Abstain with Portfolio Theory
Liu Ziyin, Zhikang Wang, Paul Pu Liang +3
cs.LGstat.MLarXiv:1907.00208v22019
Disentangling Adversarial Robustness and Generalization
David Stutz, Matthias Hein, Bernt Schiele
cs.CVcs.CRcs.LGarXiv:1812.00740v22018
Efficient and Modular Implicit Differentiation
Mathieu Blondel, Quentin Berthet, Marco Cuturi +5
cs.LGmath.NAstat.MLarXiv:2105.15183v52021
RL-finetuning LLMs from on- and off-policy data with a single algorithm
Yunhao Tang, Taco Cohen, David W. Zhang +2
cs.LGstat.MLarXiv:2503.19612v22025
Linear Latent Force Models using Gaussian Processes
Mauricio A. Álvarez, David Luengo, Neil D. Lawrence
stat.MLcs.AIarXiv:1107.2699v22011
Metrics for Multi-Class Classification: an Overview
Margherita Grandini, Enrico Bagli, Giorgio Visani
stat.MLcs.LGarXiv:2008.05756v12020
A Tensor Approach to Learning Mixed Membership Community Models
Anima Anandkumar, Rong Ge, Daniel Hsu +1
cs.LGcs.SIstat.MLarXiv:1302.2684v42013
Machine Learning at the Network Edge: A Survey
M. G. Sarwar Murshed, Christopher Murphy, Daqing Hou +3
cs.LGcs.CVcs.NIarXiv:1908.00080v42019
On the equivalence between graph isomorphism testing and function approximation with GNNs
Zhengdao Chen, Soledad Villar, Lei Chen +1
cs.LGstat.MLarXiv:1905.12560v22019
Graph Degree Linkage: Agglomerative Clustering on a Directed Graph
Wei Zhang, Xiaogang Wang, Deli Zhao +1
cs.CVcs.SIstat.MLarXiv:1208.5092v12012
Coresets for Clustering with Fairness Constraints
Lingxiao Huang, Shaofeng H. -C. Jiang, Nisheeth K. Vishnoi
cs.DScs.CGcs.LGarXiv:1906.08484v42019
Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization
Blake Woodworth, Jialei Wang, Adam Smith +2
math.OCcs.LGstat.MLarXiv:1805.10222v32018
Principled Training of Neural Networks with Direct Feedback Alignment
Julien Launay, Iacopo Poli, Florent Krzakala
stat.MLcs.LGcs.NEarXiv:1906.04554v12019
Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification
Shuangjie Xu, Yu Cheng, Kang Gu +3
cs.CVcs.LGstat.MLarXiv:1708.02286v22017
Geometric Scattering for Graph Data Analysis
Feng Gao, Guy Wolf, Matthew Hirn
cs.LGstat.MLarXiv:1810.03068v22018
Probabilistic FastText for Multi-Sense Word Embeddings
Ben Athiwaratkun, Andrew Gordon Wilson, Anima Anandkumar
cs.CLcs.AIcs.LGarXiv:1806.02901v12018
Few-Shot Learning with Graph Neural Networks
Victor Garcia, Joan Bruna
stat.MLcs.LGarXiv:1711.04043v32017
Evaluating Explanation Methods for Deep Learning in Security
Alexander Warnecke, Daniel Arp, Christian Wressnegger +1
cs.LGcs.CRstat.MLarXiv:1906.02108v42019
The Pitfalls of Simplicity Bias in Neural Networks
Harshay Shah, Kaustav Tamuly, Aditi Raghunathan +2
cs.LGcs.AIstat.MLarXiv:2006.07710v22020
Semi-supervised learning with max-margin graph cuts
Branislav Kveton, Michal Valko, Ali Rahimi +1
cs.LGstat.MLarXiv:2604.26818v12026
Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification
Han Bao, Masashi Sugiyama
cs.LGstat.MLarXiv:1905.12511v22019
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Kimin Lee, Michael Laskin, Aravind Srinivas +1
cs.LGcs.AIstat.MLarXiv:2007.04938v42020
Low-Rank Modeling and Its Applications in Image Analysis
Xiaowei Zhou, Can Yang, Hongyu Zhao +1
cs.CVcs.LGstat.MLarXiv:1401.3409v32014
Sampling using $SU(N)$ gauge equivariant flows
Denis Boyda, Gurtej Kanwar, Sébastien Racanière +5
hep-latcs.LGstat.MLarXiv:2008.05456v22020
Traceable Spectral Inference via Influence Functions: Efficient Data Attribution and Error Proxies for the Ariel Mission
Nikki Grens, Luís F. Simões, Kai Hou Yip +1
cs.LGastro-ph.IMstat.MLarXiv:2608.23458v12026
End to end learning and optimization on graphs
Bryan Wilder, Eric Ewing, Bistra Dilkina +1
cs.LGcs.SIstat.MLarXiv:1905.13732v32019
Ultrametric Fitting by Gradient Descent
Giovanni Chierchia, Benjamin Perret
cs.LGstat.MLarXiv:1905.10566v32019
On Russian Roulette Estimates for Bayesian Inference with Doubly-Intractable Likelihoods
Anne-Marie Lyne, Mark Girolami, Yves Atchadé +2
stat.MEstat.COstat.MLarXiv:1306.4032v42013
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
Cold Case: The Lost MNIST Digits
Chhavi Yadav, Léon Bottou
cs.LGcs.CVstat.MLarXiv:1905.10498v22019
Batch Normalization is a Cause of Adversarial Vulnerability
Angus Galloway, Anna Golubeva, Thomas Tanay +2
cs.LGstat.MLarXiv:1905.02161v22019
Real-time Power System State Estimation and Forecasting via Deep Neural Networks
Liang Zhang, Gang Wang, Georgios B. Giannakis
cs.LGstat.MLarXiv:1811.06146v22018
An elementary introduction to information geometry
Frank Nielsen
cs.LGcs.ITstat.MLarXiv:1808.08271v22018
Deep Factors for Forecasting
Yuyang Wang, Alex Smola, Danielle C. Maddix +3
stat.MLcs.LGarXiv:1905.12417v12019
Deep Bayesian Inversion
Jonas Adler, Ozan Öktem
stat.MLcs.LGmath.STarXiv:1811.05910v12018
Linear Exponential Quadratic Gaussian Covariance Steering
Chiran B. Cherian, Yasemin Isik, Abhishek Halder
math.OCcs.AIcs.LGarXiv:2609.12463v12026
Strategies for Pre-training Graph Neural Networks
Weihua Hu, Bowen Liu, Joseph Gomes +4
cs.LGstat.MLarXiv:1905.12265v32019
Reinforcement Learning for Relation Classification from Noisy Data
Jun Feng, Minlie Huang, Li Zhao +2
cs.IRcs.LGstat.MLarXiv:1808.08013v12018
A Survey on Practical Applications of Multi-Armed and Contextual Bandits
Djallel Bouneffouf, Irina Rish
cs.LGstat.MLarXiv:1904.10040v12019
Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers
Aaron Griffith, Andrew Pomerance, Daniel J. Gauthier
cs.LGnlin.CDstat.MLarXiv:1910.00659v22019
Jigsaw-CRL: Recovering Global Latent Causal Order from Fragmented Multi-Client Interventions
Haijie Xu, Chen Zhang
stat.MLcs.LGarXiv:2608.28991v12026
Brenier Meets Adversarial Training: Optimal Transport Geometry for Robust Learning
Alireza Abdollahpoorrostam, Ehsan Sharifian, Buse Şen +2
cs.LGmath.OCstat.MLarXiv:2609.31363v12026
Transfer Learning under High-dimensional Generalized Linear Models
Ye Tian, Yang Feng
stat.MLcs.LGstat.MEarXiv:2105.14328v42021
Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates
Yuchen Zhang, John C. Duchi, Martin J. Wainwright
math.STcs.LGstat.MLarXiv:1305.5029v22013
Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)
John Gideon, Melvin G McInnis, Emily Mower Provost
cs.LGcs.SDeess.ASarXiv:1903.12094v22019
Measuring abstract reasoning in neural networks
David G. T. Barrett, Felix Hill, Adam Santoro +2
cs.LGstat.MLarXiv:1807.04225v12018
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
Po-Ling Loh, Martin J. Wainwright
math.STcs.ITstat.MLarXiv:1305.2436v22013
Elements of Sequential Monte Carlo
Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön
stat.MLcs.LGstat.COarXiv:1903.04797v32019
Nash Learning from Human Feedback
Rémi Munos, Michal Valko, Daniele Calandriello +14
stat.MLcs.AIcs.GTarXiv:2312.00886v42023
Exploring Interpretable LSTM Neural Networks over Multi-Variable Data
Tian Guo, Tao Lin, Nino Antulov-Fantulin
cs.LGstat.MLarXiv:1905.12034v12019
Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction
Filipe de Avila Belbute-Peres, Thomas D. Economon, J. Zico Kolter
cs.LGphysics.comp-phstat.MLarXiv:2007.04439v32020
Neural Fine-Gray: Monotonic neural networks for competing risks
Vincent Jeanselme, Chang Ho Yoon, Brian Tom +1
cs.LGcs.AIstat.MLarXiv:2305.06703v12023
Rethinking the Value of Labels for Improving Class-Imbalanced Learning
Yuzhe Yang, Zhi Xu
cs.LGcs.CVstat.MLarXiv:2006.07529v22020
Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts
Bertrand Charpentier, Daniel Zügner, Stephan Günnemann
cs.LGstat.MLarXiv:2006.09239v22020
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
Yifan Wu, Ezra Winston, Divyansh Kaushik +1
cs.LGstat.MLarXiv:1903.01689v22019
Gotta Go Fast When Generating Data with Score-Based Models
Alexia Jolicoeur-Martineau, Ke Li, Rémi Piché-Taillefer +2
cs.LGcs.CVmath.OCarXiv:2105.14080v12021
Counterfactual Risk Assessments, Evaluation, and Fairness
Amanda Coston, Alan Mishler, Edward H. Kennedy +1
stat.MLcs.CYcs.LGarXiv:1909.00066v32019
Learning Good State and Action Representations via Tensor Decomposition
Chengzhuo Ni, Yaqi Duan, Munther Dahleh +2
stat.MLcs.LGarXiv:2105.01136v22021

Machine Learning (stat)

Policy-Gradient Algorithms Have No Guarantees of Convergence in Linear Quadratic Games

Detecting Spiky Corruption in Markov Decision Processes

Deep Gamblers: Learning to Abstain with Portfolio Theory

Disentangling Adversarial Robustness and Generalization

Efficient and Modular Implicit Differentiation

RL-finetuning LLMs from on- and off-policy data with a single algorithm

Linear Latent Force Models using Gaussian Processes

Metrics for Multi-Class Classification: an Overview

A Tensor Approach to Learning Mixed Membership Community Models

Machine Learning at the Network Edge: A Survey

On the equivalence between graph isomorphism testing and function approximation with GNNs

Graph Degree Linkage: Agglomerative Clustering on a Directed Graph

Coresets for Clustering with Fairness Constraints

Graph Oracle Models, Lower Bounds, and Gaps for Parallel Stochastic Optimization

Principled Training of Neural Networks with Direct Feedback Alignment

Jointly Attentive Spatial-Temporal Pooling Networks for Video-based Person Re-Identification

Geometric Scattering for Graph Data Analysis

Probabilistic FastText for Multi-Sense Word Embeddings

Few-Shot Learning with Graph Neural Networks

Evaluating Explanation Methods for Deep Learning in Security

The Pitfalls of Simplicity Bias in Neural Networks

Semi-supervised learning with max-margin graph cuts

Calibrated Surrogate Maximization of Linear-fractional Utility in Binary Classification

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning

Low-Rank Modeling and Its Applications in Image Analysis

Sampling using $SU(N)$ gauge equivariant flows

Traceable Spectral Inference via Influence Functions: Efficient Data Attribution and Error Proxies for the Ariel Mission

End to end learning and optimization on graphs

Ultrametric Fitting by Gradient Descent

On Russian Roulette Estimates for Bayesian Inference with Doubly-Intractable Likelihoods

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

Cold Case: The Lost MNIST Digits

Batch Normalization is a Cause of Adversarial Vulnerability

Real-time Power System State Estimation and Forecasting via Deep Neural Networks

An elementary introduction to information geometry

Deep Factors for Forecasting

Deep Bayesian Inversion

Linear Exponential Quadratic Gaussian Covariance Steering

Strategies for Pre-training Graph Neural Networks

Reinforcement Learning for Relation Classification from Noisy Data

A Survey on Practical Applications of Multi-Armed and Contextual Bandits

Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computers

Jigsaw-CRL: Recovering Global Latent Causal Order from Fragmented Multi-Client Interventions

Brenier Meets Adversarial Training: Optimal Transport Geometry for Robust Learning

Transfer Learning under High-dimensional Generalized Linear Models

Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates

Improving Cross-Corpus Speech Emotion Recognition with Adversarial Discriminative Domain Generalization (ADDoG)

Measuring abstract reasoning in neural networks

Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima

Elements of Sequential Monte Carlo

Nash Learning from Human Feedback

Exploring Interpretable LSTM Neural Networks over Multi-Variable Data

Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction

Neural Fine-Gray: Monotonic neural networks for competing risks

Rethinking the Value of Labels for Improving Class-Imbalanced Learning

Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts

Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment

Gotta Go Fast When Generating Data with Score-Based Models

Counterfactual Risk Assessments, Evaluation, and Fairness

Learning Good State and Action Representations via Tensor Decomposition