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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7,141 to 7,200 of 9,713

Combating Label Noise in Deep Learning Using Abstention
Sunil Thulasidasan, Tanmoy Bhattacharya, Jeff Bilmes +2
stat.MLcs.LGarXiv:1905.10964v22019
Balanced Policy Evaluation and Learning
Nathan Kallus
stat.MLcs.LGmath.OCarXiv:1705.07384v22017
A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems
Anthony Corso, Robert J. Moss, Mark Koren +2
cs.LGcs.AIeess.SYarXiv:2005.02979v32020
Inference via low-dimensional couplings
Alessio Spantini, Daniele Bigoni, Youssef Marzouk
stat.MEstat.COstat.MLarXiv:1703.06131v42017
Variational Diffusion Models
Diederik P. Kingma, Tim Salimans, Ben Poole +1
cs.LGstat.MLarXiv:2107.00630v62021
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks
Yibo Yang, Paris Perdikaris
stat.MLcs.LGphysics.comp-pharXiv:1811.04026v12018
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
Jinxin Zhou, Xiao Li, Tianyu Ding +3
cs.LGcs.AIcs.ITarXiv:2203.01238v22022
Inductive Representation Learning on Temporal Graphs
Da Xu, Chuanwei Ruan, Evren Korpeoglu +2
cs.LGstat.MLarXiv:2002.07962v12020
T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction
Ling Zhao, Yujiao Song, Chao Zhang +5
cs.LGstat.MLarXiv:1811.05320v32018
SmoothGrad: removing noise by adding noise
Daniel Smilkov, Nikhil Thorat, Been Kim +2
cs.LGcs.CVstat.MLarXiv:1706.03825v12017
Variational Autoencoders Pursue PCA Directions (by Accident)
Michal Rolinek, Dominik Zietlow, Georg Martius
cs.LGcs.CVstat.MLarXiv:1812.06775v22018
On Context-Dependent Clustering of Bandits
Claudio Gentile, Shuai Li, Purushottam Kar +3
cs.LGcs.AIcs.IRarXiv:1608.03544v22016
Rank-One Signal Recovery in Sparse Wishart Noise
Preben Forer, Urte Adomaityte, Pierpaolo Vivo
cond-mat.dis-nncond-mat.stat-mechmath-pharXiv:2609.28163v12026
Explainable Reinforcement Learning: A Survey
Erika Puiutta, Eric MSP Veith
cs.LGstat.MLarXiv:2005.06247v12020
Neural Networks can Learn Representations with Gradient Descent
Alex Damian, Jason D. Lee, Mahdi Soltanolkotabi
cs.LGcs.ITstat.MLarXiv:2206.15144v12022
Do RNN and LSTM have Long Memory?
Jingyu Zhao, Feiqing Huang, Jia Lv +4
stat.MLcs.LGarXiv:2006.03860v22020
An Empirical Study of Rich Subgroup Fairness for Machine Learning
Michael Kearns, Seth Neel, Aaron Roth +1
cs.LGstat.MLarXiv:1808.08166v12018
Learning to Optimize under Non-Stationarity
Wang Chi Cheung, David Simchi-Levi, Ruihao Zhu
cs.LGstat.MLarXiv:1810.03024v62018
Certified Data Removal from Machine Learning Models
Chuan Guo, Tom Goldstein, Awni Hannun +1
cs.LGstat.MLarXiv:1911.03030v62019
Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction
Huaxiu Yao, Fei Wu, Jintao Ke +6
cs.LGstat.MLarXiv:1802.08714v22018
Modular Networks: Learning to Decompose Neural Computation
Louis Kirsch, Julius Kunze, David Barber
cs.LGcs.AIstat.MLarXiv:1811.05249v12018
Thompson Sampling: An Asymptotically Optimal Finite Time Analysis
Emilie Kaufmann, Nathaniel Korda, Rémi Munos
stat.MLcs.LGarXiv:1205.4217v22012
Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs
Mingyang Chen, Wen Zhang, Wei Zhang +2
cs.CLstat.MLarXiv:1909.01515v12019
Neural Optimizer Search with Reinforcement Learning
Irwan Bello, Barret Zoph, Vijay Vasudevan +1
cs.AIcs.LGstat.MLarXiv:1709.07417v22017
Transferability of Spectral Graph Convolutional Neural Networks
Ron Levie, Wei Huang, Lorenzo Bucci +2
cs.LGstat.MLarXiv:1907.12972v32019
When Machine Unlearning Jeopardizes Privacy
Min Chen, Zhikun Zhang, Tianhao Wang +3
cs.CRcs.LGstat.MLarXiv:2005.02205v22020
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits
Alekh Agarwal, Daniel Hsu, Satyen Kale +3
cs.LGstat.MLarXiv:1402.0555v22014
Stability and Generalization of Straight-Through Estimators for Training Two-Layer Quantized Neural Networks
Yiming Ying
cs.LGstat.MLarXiv:2609.06430v12026
Parameter Estimation for Unnormalized Discrete Models via Empirically Localized Deformed Bregman Divergence
Takashi Takenouchi
stat.MLcs.LGarXiv:2609.30713v12026
Towards High Resolution Video Generation with Progressive Growing of Sliced Wasserstein GANs
Dinesh Acharya, Zhiwu Huang, Danda Pani Paudel +1
cs.CVcs.AIstat.MLarXiv:1810.02419v22018
Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation
Kexuan Shi, Hanxuan Li, Zeju Qiu +3
cs.LGstat.MLarXiv:2605.12492v12026
Learning Latent Dynamics for Planning from Pixels
Danijar Hafner, Timothy Lillicrap, Ian Fischer +4
cs.LGcs.AIstat.MLarXiv:1811.04551v52018
Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data
Charles H. Martin, Tongsu, Peng +1
cs.LGphysics.data-anstat.MLarXiv:2002.06716v22020
Multi-Task Reinforcement Learning with Soft Modularization
Ruihan Yang, Huazhe Xu, Yi Wu +1
cs.LGcs.AIcs.ROarXiv:2003.13661v22020
Smooth Exploration for Robotic Reinforcement Learning
Antonin Raffin, Jens Kober, Freek Stulp
cs.LGcs.ROstat.MLarXiv:2005.05719v22020
OpenTag: Open Attribute Value Extraction from Product Profiles [Deep Learning, Active Learning, Named Entity Recognition]
Guineng Zheng, Subhabrata Mukherjee, Xin Luna Dong +1
cs.CLcs.AIcs.IRarXiv:1806.01264v22018
Quality-Diversity Optimization: a novel branch of stochastic optimization
Konstantinos Chatzilygeroudis, Antoine Cully, Vassilis Vassiliades +1
cs.NEcs.LGmath.OCarXiv:2012.04322v22020
Transferable Graph Metanetworks
Yuxin Ma, Adir Dayan, Yam Eitan +2
stat.MLcs.LGarXiv:2610.00420v12026
Reliably Learning the ReLU in Polynomial Time
Surbhi Goel, Varun Kanade, Adam Klivans +1
cs.LGcs.CCstat.MLarXiv:1611.10258v12016
iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making
Preethi Lahoti, Krishna P. Gummadi, Gerhard Weikum
cs.LGcs.IRstat.MLarXiv:1806.01059v22018
Meta-Q-Learning
Rasool Fakoor, Pratik Chaudhari, Stefano Soatto +1
cs.LGstat.MLarXiv:1910.00125v22019
Copula Transformations for Data-Consistent Inversion
Troy Butler, Tianyi Jiang, João Silva +2
stat.MLmath.OCmath.PRarXiv:2609.02832v12026
RACE: Residual-Aware Test-Time Adaptation for Neighbor-Rich Time-Series Foundation Model Forecasting
Hao-Nan Shi, Tong Wu, Chen-Cong Sun +3
cs.LGstat.MLarXiv:2610.00405v12026
FAER: Auditable Utility-Aligned Trajectory Replay for Language Model Post-Training
Miaobo Hu, Shuhao Hu, Xiaobo Guo +5
cs.LGcs.AIcs.CLarXiv:2610.00385v12026
Verdict Instability of OOD Scores under Reference Resampling
Donghoon Lee, Shinjin Kang
cs.LGstat.MLarXiv:2609.00691v12026
Flexible statistical inference for mechanistic models of neural dynamics
Jan-Matthis Lueckmann, Pedro J. Goncalves, Giacomo Bassetto +3
stat.MLarXiv:1711.01861v12017
Adversarial Distributional Training for Robust Deep Learning
Yinpeng Dong, Zhijie Deng, Tianyu Pang +2
cs.LGcs.CRstat.MLarXiv:2002.05999v22020
Learning Scheduling Algorithms for Data Processing Clusters
Hongzi Mao, Malte Schwarzkopf, Shaileshh Bojja Venkatakrishnan +2
cs.LGstat.MLarXiv:1810.01963v42018
Larger Datasets Can Be Repeated More: A Theoretical Analysis of Multi-Epoch Scaling in Linear Regression
Tingkai Yan, Haodong Wen, Binghui Li +3
cs.LGstat.MLarXiv:2511.13421v22025
Deep Learning COVID-19 Features on CXR using Limited Training Data Sets
Yujin Oh, Sangjoon Park, Jong Chul Ye
eess.IVcs.CVcs.LGarXiv:2004.05758v22020
Batch size-invariance for policy optimization
Jacob Hilton, Karl Cobbe, John Schulman
cs.LGstat.MLarXiv:2110.00641v32021
Robust Spectral Compressed Sensing via Structured Matrix Completion
Yuxin Chen, Yuejie Chi
cs.ITeess.SYmath.NAarXiv:1304.8126v52013
Optimizer Benchmarking Needs to Account for Hyperparameter Tuning
Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels +2
cs.LGstat.MLarXiv:1910.11758v42019
FedSplit: An algorithmic framework for fast federated optimization
Reese Pathak, Martin J. Wainwright
cs.LGmath.OCstat.MLarXiv:2005.05238v12020
An Axiomatic Definition of Hierarchical Clustering
Ery Arias-Castro, Elizabeth Coda
stat.MLcs.LGmath.STarXiv:2407.03574v12024
Self-Distillation Amplifies Regularization in Hilbert Space
Hossein Mobahi, Mehrdad Farajtabar, Peter L. Bartlett
cs.LGstat.MLarXiv:2002.05715v32020
An ensemble-based system for automatic screening of diabetic retinopathy
Balint Antal, Andras Hajdu
cs.CVcs.LGstat.AParXiv:1410.8576v12014
Neural Sampling with Reweighted Normalizing Flows via the Wasserstein--Fisher--Rao JKO Scheme
Chenguang Duan, Johannes Hertrich, Gabriele Steidl
math.NAcs.LGcs.NAarXiv:2610.10278v12026
Nonparametric inference of interaction laws in systems of agents from trajectory data
Fei Lu, Mauro Maggioni, Sui Tang +1
cs.LGstat.MLarXiv:1812.06003v42018
Retrieval-Augmented Reinforcement Learning
Anirudh Goyal, Abram L. Friesen, Andrea Banino +13
cs.LGstat.MLarXiv:2202.08417v42022

Machine Learning (stat)

Combating Label Noise in Deep Learning Using Abstention

Balanced Policy Evaluation and Learning

A Survey of Algorithms for Black-Box Safety Validation of Cyber-Physical Systems

Inference via low-dimensional couplings

Variational Diffusion Models

Adversarial Uncertainty Quantification in Physics-Informed Neural Networks

On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features

Inductive Representation Learning on Temporal Graphs

T-GCN: A Temporal Graph ConvolutionalNetwork for Traffic Prediction

SmoothGrad: removing noise by adding noise

Variational Autoencoders Pursue PCA Directions (by Accident)

On Context-Dependent Clustering of Bandits

Rank-One Signal Recovery in Sparse Wishart Noise

Explainable Reinforcement Learning: A Survey

Neural Networks can Learn Representations with Gradient Descent

Do RNN and LSTM have Long Memory?

An Empirical Study of Rich Subgroup Fairness for Machine Learning

Learning to Optimize under Non-Stationarity

Certified Data Removal from Machine Learning Models

Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction

Modular Networks: Learning to Decompose Neural Computation

Thompson Sampling: An Asymptotically Optimal Finite Time Analysis

Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs

Neural Optimizer Search with Reinforcement Learning

Transferability of Spectral Graph Convolutional Neural Networks

When Machine Unlearning Jeopardizes Privacy

Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits

Stability and Generalization of Straight-Through Estimators for Training Two-Layer Quantized Neural Networks

Parameter Estimation for Unnormalized Discrete Models via Empirically Localized Deformed Bregman Divergence

Towards High Resolution Video Generation with Progressive Growing of Sliced Wasserstein GANs

Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation

Learning Latent Dynamics for Planning from Pixels

Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data

Multi-Task Reinforcement Learning with Soft Modularization

Smooth Exploration for Robotic Reinforcement Learning

OpenTag: Open Attribute Value Extraction from Product Profiles [Deep Learning, Active Learning, Named Entity Recognition]

Quality-Diversity Optimization: a novel branch of stochastic optimization

Transferable Graph Metanetworks

Reliably Learning the ReLU in Polynomial Time

iFair: Learning Individually Fair Data Representations for Algorithmic Decision Making

Meta-Q-Learning

Copula Transformations for Data-Consistent Inversion

RACE: Residual-Aware Test-Time Adaptation for Neighbor-Rich Time-Series Foundation Model Forecasting

FAER: Auditable Utility-Aligned Trajectory Replay for Language Model Post-Training

Verdict Instability of OOD Scores under Reference Resampling

Flexible statistical inference for mechanistic models of neural dynamics

Adversarial Distributional Training for Robust Deep Learning

Learning Scheduling Algorithms for Data Processing Clusters

Larger Datasets Can Be Repeated More: A Theoretical Analysis of Multi-Epoch Scaling in Linear Regression

Deep Learning COVID-19 Features on CXR using Limited Training Data Sets

Batch size-invariance for policy optimization

Robust Spectral Compressed Sensing via Structured Matrix Completion

Optimizer Benchmarking Needs to Account for Hyperparameter Tuning

FedSplit: An algorithmic framework for fast federated optimization

An Axiomatic Definition of Hierarchical Clustering

Self-Distillation Amplifies Regularization in Hilbert Space

An ensemble-based system for automatic screening of diabetic retinopathy

Neural Sampling with Reweighted Normalizing Flows via the Wasserstein--Fisher--Rao JKO Scheme

Nonparametric inference of interaction laws in systems of agents from trajectory data

Retrieval-Augmented Reinforcement Learning