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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1,741 to 1,800 of 6,773

Kernel-based Reconstruction of Graph Signals
Daniel Romero, Meng Ma, Georgios B. Giannakis
stat.MLcs.LGarXiv:1605.07174v12016
Compressed Sensing with Deep Image Prior and Learned Regularization
Dave Van Veen, Ajil Jalal, Mahdi Soltanolkotabi +3
stat.MLcs.ITcs.LGarXiv:1806.06438v42018
Schrödinger Bridges on Lie Group Manifolds for Probabilistic Intrinsic Generation
Shizhe Zhang, Mingyang Zhao, Lei Ma
stat.MLcs.AIcs.LGarXiv:2609.02196v12026
Anonymous Walk Embeddings
Sergey Ivanov, Evgeny Burnaev
cs.LGstat.MLarXiv:1805.11921v32018
Few-Shot Learning with Embedded Class Models and Shot-Free Meta Training
Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
cs.LGcs.CVstat.MLarXiv:1905.04398v22019
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting
Sergio Casas, Cole Gulino, Simon Suo +3
cs.CVcs.LGcs.ROarXiv:2007.12036v12020
Variational Bayesian Unlearning
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
cs.LGstat.MLarXiv:2010.12883v12020
Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors
Morteza Mardani, Gonzalo Mateos, Georgios B. Giannakis
stat.MLcs.ITcs.LGarXiv:1404.4667v12014
Certified Robustness to Label-Flipping Attacks via Randomized Smoothing
Elan Rosenfeld, Ezra Winston, Pradeep Ravikumar +1
cs.LGcs.AIcs.CRarXiv:2002.03018v42020
Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation
Iulian Vlad Serban, Tim Klinger, Gerald Tesauro +4
cs.CLcs.AIcs.LGarXiv:1606.00776v22016
A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements
Qinqing Zheng, John Lafferty
stat.MLcs.LGarXiv:1506.06081v32015
Imitation Learning from Imperfect Demonstration
Yueh-Hua Wu, Nontawat Charoenphakdee, Han Bao +2
cs.LGcs.AIstat.MLarXiv:1901.09387v32019
Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains
Aymeric Dieuleveut, Alain Durmus, Francis Bach
stat.MLmath.OCarXiv:1707.06386v22017
On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models
Erik Nijkamp, Mitch Hill, Tian Han +2
stat.MLcs.CVcs.LGarXiv:1903.12370v42019
Graph Normalizing Flows
Jenny Liu, Aviral Kumar, Jimmy Ba +2
cs.LGstat.MLarXiv:1905.13177v12019
Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model
Guodong Zhang, Lala Li, Zachary Nado +5
cs.LGstat.MLarXiv:1907.04164v22019
Learning with Feature-Dependent Label Noise: A Progressive Approach
Yikai Zhang, Songzhu Zheng, Pengxiang Wu +2
cs.LGcs.CVstat.AParXiv:2103.07756v32021
A New Convex Relaxation for Tensor Completion
Bernardino Romera-Paredes, Massimiliano Pontil
cs.LGmath.OCstat.MLarXiv:1307.4653v12013
Multiple Identifications in Multi-Armed Bandits
Sébastien Bubeck, Tengyao Wang, Nitin Viswanathan
cs.LGstat.MLarXiv:1205.3181v12012
Q-learning with Adjoint Matching
Qiyang Li, Sergey Levine
cs.LGcs.AIcs.ROarXiv:2601.14234v42026
Confidence Intervals for Policy Evaluation in Adaptive Experiments
Vitor Hadad, David A. Hirshberg, Ruohan Zhan +2
stat.MLcs.LGstat.MEarXiv:1911.02768v42019
Group Lasso with Overlaps: the Latent Group Lasso approach
Guillaume Obozinski, Laurent Jacob, Jean-Philippe Vert
stat.MLcs.LGarXiv:1110.0413v12011
The power of deeper networks for expressing natural functions
David Rolnick, Max Tegmark
cs.LGcs.NEstat.MLarXiv:1705.05502v22017
DeepArchitect: Automatically Designing and Training Deep Architectures
Renato Negrinho, Geoff Gordon
stat.MLcs.LGarXiv:1704.08792v12017
Personalized News Recommendation with Context Trees
Florent Garcin, Christos Dimitrakakis, Boi Faltings
cs.IRcs.LGstat.MLarXiv:1303.0665v22013
RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data
Yanbo Xu, Siddharth Biswal, Shriprasad R Deshpande +2
cs.LGstat.MLarXiv:1807.08820v12018
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
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries
Zhewei Yao, Amir Gholami, Qi Lei +2
cs.CVcs.LGstat.MLarXiv:1802.08241v42018
Real or Fake? Learning to Discriminate Machine from Human Generated Text
Anton Bakhtin, Sam Gross, Myle Ott +3
cs.LGcs.CLstat.MLarXiv:1906.03351v22019
Forecasting Corn Yield with Machine Learning Ensembles
Mohsen Shahhosseini, Guiping Hu, Sotirios V. Archontoulis
stat.APcs.LGstat.MLarXiv:2001.09055v22020
ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation
Yizheng Huang, Wenjun Zeng, Aditi Kumaresan +1
cs.LGcs.AIstat.MLarXiv:2604.23099v22026
wd1: Weighted Policy Optimization for Reasoning in Diffusion Language Models
Xiaohang Tang, Rares Dolga, Sangwoong Yoon +1
cs.LGcs.AIstat.MLarXiv:2507.08838v22025
Conditional Gradient Algorithms for Norm-Regularized Smooth Convex Optimization
Zaid Harchaoui, Anatoli Juditsky, Arkadi Nemirovski
math.OCstat.COstat.MLarXiv:1302.2325v42013
Learning ReLUs via Gradient Descent
Mahdi Soltanolkotabi
cs.LGcs.ITmath.OCarXiv:1705.04591v22017
Neural Rough Differential Equations for Long Time Series
James Morrill, Cristopher Salvi, Patrick Kidger +2
cs.LGcs.AImath.DSarXiv:2009.08295v42020
On the Reliable Detection of Concept Drift from Streaming Unlabeled Data
Tegjyot Singh Sethi, Mehmed Kantardzic
stat.MLcs.AIcs.LGarXiv:1704.00023v12017
iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making
Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum
cs.LGcs.IRstat.MLarXiv:1806.01059v22018
Unsupervised Control Through Non-Parametric Discriminative Rewards
David Warde-Farley, Tom Van de Wiele, Tejas Kulkarni +3
cs.LGcs.AIstat.MLarXiv:1811.11359v12018
Contrastive learning, multi-view redundancy, and linear models
Christopher Tosh, Akshay Krishnamurthy, Daniel Hsu
cs.LGstat.MLarXiv:2008.10150v22020
Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs
Lei Cai, Zhengzhang Chen, Chen Luo +4
cs.LGcs.SIstat.MLarXiv:2005.07427v22020
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings
Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt +4
cs.LGcs.AIstat.MLarXiv:2007.14175v22020
Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach
Dohyung Park, Anastasios Kyrillidis, Constantine Caramanis +1
stat.MLcs.ITcs.LGarXiv:1609.03240v22016
FedGAN: Federated Generative Adversarial Networks for Distributed Data
Mohammad Rasouli, Tao Sun, Ram Rajagopal
cs.LGcs.CVcs.MAarXiv:2006.07228v22020
Do RNN and LSTM have Long Memory?
Jingyu Zhao, Feiqing Huang, Jia Lv +4
stat.MLcs.LGarXiv:2006.03860v22020
Generalisation error in learning with random features and the hidden manifold model
Federica Gerace, Bruno Loureiro, Florent Krzakala +2
math.STcs.LGmath.PRarXiv:2002.09339v22020
Learning Linear-Quadratic Regulators Efficiently with only $\sqrt{T}$ Regret
Alon Cohen, Tomer Koren, Yishay Mansour
cs.LGstat.MLarXiv:1902.06223v22019
Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints
Chaoqi Wang, Yibo Jiang, Chenghao Yang +2
cs.LGcs.AIstat.MLarXiv:2309.16240v12023
Deep Neural Network Fingerprinting by Conferrable Adversarial Examples
Nils Lukas, Yuxuan Zhang, Florian Kerschbaum
cs.LGcs.CRstat.MLarXiv:1912.00888v42019
Variational Gaussian Process State-Space Models
Roger Frigola, Yutian Chen, Carl E. Rasmussen
cs.LGcs.ROeess.SYarXiv:1406.4905v22014
Verdict Instability of OOD Scores under Reference Resampling
Donghoon Lee, Shinjin Kang
cs.LGstat.MLarXiv:2609.00691v12026
Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals
Andrew Cotter, Heinrich Jiang, Serena Wang +4
cs.LGcs.AIcs.GTarXiv:1809.04198v12018
Explainable $k$-Means and $k$-Medians Clustering
Sanjoy Dasgupta, Nave Frost, Michal Moshkovitz +1
cs.LGcs.CGcs.DSarXiv:2002.12538v22020
Follow the Leader If You Can, Hedge If You Must
Steven de Rooij, Tim van Erven, Peter D. Grünwald +1
cs.LGstat.MLarXiv:1301.0534v22013
Structured Bayesian Pruning via Log-Normal Multiplicative Noise
Kirill Neklyudov, Dmitry Molchanov, Arsenii Ashukha +1
stat.MLarXiv:1705.07283v22017
Curriculum Loss: Robust Learning and Generalization against Label Corruption
Yueming Lyu, Ivor W. Tsang
cs.LGstat.MLarXiv:1905.10045v32019
k-Space Deep Learning for Accelerated MRI
Yoseob Han, Leonard Sunwoo, Jong Chul Ye
cs.CVcs.LGstat.MLarXiv:1805.03779v32018
Muon Optimizes Under Spectral Norm Constraints
Lizhang Chen, Jonathan Li, Qiang Liu
cs.LGmath.OCstat.MLarXiv:2506.15054v22025
Distilled One-Shot Federated Learning
Yanlin Zhou, George Pu, Xiyao Ma +2
cs.LGcs.AIstat.MLarXiv:2009.07999v32020
Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment
Audrey Huang, Adam Block, Qinghua Liu +3
cs.AIcs.LGstat.MLarXiv:2503.21878v22025
Message-Aware Graph Attention Networks for Large-Scale Multi-Robot Path Planning
Qingbiao Li, Weizhe Lin, Zhe Liu +1
cs.ROcs.DCcs.LGarXiv:2011.13219v22020

Machine Learning (stat)

Kernel-based Reconstruction of Graph Signals

Compressed Sensing with Deep Image Prior and Learned Regularization

Schrödinger Bridges on Lie Group Manifolds for Probabilistic Intrinsic Generation

Anonymous Walk Embeddings

Few-Shot Learning with Embedded Class Models and Shot-Free Meta Training

Implicit Latent Variable Model for Scene-Consistent Motion Forecasting

Variational Bayesian Unlearning

Subspace Learning and Imputation for Streaming Big Data Matrices and Tensors

Certified Robustness to Label-Flipping Attacks via Randomized Smoothing

Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation

A Convergent Gradient Descent Algorithm for Rank Minimization and Semidefinite Programming from Random Linear Measurements

Imitation Learning from Imperfect Demonstration

Bridging the Gap between Constant Step Size Stochastic Gradient Descent and Markov Chains

On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models

Graph Normalizing Flows

Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model

Learning with Feature-Dependent Label Noise: A Progressive Approach

A New Convex Relaxation for Tensor Completion

Multiple Identifications in Multi-Armed Bandits

Q-learning with Adjoint Matching

Confidence Intervals for Policy Evaluation in Adaptive Experiments

Group Lasso with Overlaps: the Latent Group Lasso approach

The power of deeper networks for expressing natural functions

DeepArchitect: Automatically Designing and Training Deep Architectures

Personalized News Recommendation with Context Trees

RAIM: Recurrent Attentive and Intensive Model of Multimodal Patient Monitoring Data

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

Hessian-based Analysis of Large Batch Training and Robustness to Adversaries

Real or Fake? Learning to Discriminate Machine from Human Generated Text

Forecasting Corn Yield with Machine Learning Ensembles

ProEval: Proactive Failure Discovery and Efficient Performance Estimation for Generative AI Evaluation

wd1: Weighted Policy Optimization for Reasoning in Diffusion Language Models

Conditional Gradient Algorithms for Norm-Regularized Smooth Convex Optimization

Learning ReLUs via Gradient Descent

Neural Rough Differential Equations for Long Time Series

On the Reliable Detection of Concept Drift from Streaming Unlabeled Data

iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making

Unsupervised Control Through Non-Parametric Discriminative Rewards

Contrastive learning, multi-view redundancy, and linear models

Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs

PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings

Non-square matrix sensing without spurious local minima via the Burer-Monteiro approach

FedGAN: Federated Generative Adversarial Networks for Distributed Data

Do RNN and LSTM have Long Memory?

Generalisation error in learning with random features and the hidden manifold model

Learning Linear-Quadratic Regulators Efficiently with only $\sqrt{T}$ Regret

Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints

Deep Neural Network Fingerprinting by Conferrable Adversarial Examples

Variational Gaussian Process State-Space Models

Verdict Instability of OOD Scores under Reference Resampling

Optimization with Non-Differentiable Constraints with Applications to Fairness, Recall, Churn, and Other Goals

Explainable $k$-Means and $k$-Medians Clustering

Follow the Leader If You Can, Hedge If You Must

Structured Bayesian Pruning via Log-Normal Multiplicative Noise

Curriculum Loss: Robust Learning and Generalization against Label Corruption

k-Space Deep Learning for Accelerated MRI

Muon Optimizes Under Spectral Norm Constraints

Distilled One-Shot Federated Learning

Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment

Message-Aware Graph Attention Networks for Large-Scale Multi-Robot Path Planning