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)

8,341 to 8,400 of 9,690

A Brief Introduction to Machine Learning for Engineers
Osvaldo Simeone
cs.LGcs.ITstat.MLarXiv:1709.02840v32017
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation
James Townsend, Niklas Koep, Sebastian Weichwald
cs.MScs.LGmath.OCarXiv:1603.03236v42016
Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization
Qilong Wang, Jiangtao Xie, Wangmeng Zuo +2
cs.CVcs.AIstat.MLarXiv:1904.06836v22019
Finite Versus Infinite Neural Networks: an Empirical Study
Jaehoon Lee, Samuel S. Schoenholz, Jeffrey Pennington +4
cs.LGstat.MLarXiv:2007.15801v22020
Distillation of Discrete Diffusion through Dimensional Correlations
Satoshi Hayakawa, Yuhta Takida, Masaaki Imaizumi +2
cs.LGcs.NAmath.NAarXiv:2410.08709v42024
Estimating network edge probabilities by neighborhood smoothing
Yuan Zhang, Elizaveta Levina, Ji Zhu
stat.MLarXiv:1509.08588v32015
Feedback Recurrent Autoencoder for Video Compression
Adam Golinski, Reza Pourreza, Yang Yang +2
cs.LGcs.CVstat.MLarXiv:2004.04342v12020
KVCOMM: Online Cross-context KV-cache Communication for Efficient LLM-based Multi-agent Systems
Hancheng Ye, Zhengqi Gao, Mingyuan Ma +8
cs.MAcs.AIstat.MLarXiv:2510.12872v22025
E(n) Equivariant Normalizing Flows
Victor Garcia Satorras, Emiel Hoogeboom, Fabian B. Fuchs +2
cs.LGphysics.chem-phstat.MLarXiv:2105.09016v42021
SDECast: Probabilistic Weather Forecasting in Continuous Time with Neural SDEs
Maria Marchenko, Martin Andrae, Fredrik Lindsten +1
stat.MLcs.LGphysics.ao-pharXiv:2610.03313v12026
Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo
Markus Heinonen, Henrik Mannerström, Juho Rousu +2
stat.MLarXiv:1508.04319v12015
Neural source-filter-based waveform model for statistical parametric speech synthesis
Xin Wang, Shinji Takaki, Junichi Yamagishi
eess.AScs.SDstat.MLarXiv:1810.11946v42018
The limitation of neural nets for approximation and optimization
Tommaso Giovannelli, Oumaima Sohab, Luis Nunes Vicente
cs.LGmath.OCstat.MLarXiv:2311.12253v12023
Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming
Claudio Michaelis, Benjamin Mitzkus, Robert Geirhos +5
cs.CVcs.LGstat.MLarXiv:1907.07484v22019
On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators
Changyou Chen, Nan Ding, Lawrence Carin
stat.MLarXiv:1610.06665v12016
Feature Space Adaptation for Effortless Gaussian Process Flows
Thomas Cowperthwaite, Louis Sharrock, Lachlan Astfalck +1
stat.MLcs.LGstat.MEarXiv:2610.11459v12026
Orthogonal Random Features
Felix X. Yu, Ananda Theertha Suresh, Krzysztof Choromanski +2
cs.LGstat.MLarXiv:1610.09072v12016
Optimal Slice-Adaptive Tuning of Hybrid Slice Sampling
Trevor Campbell
stat.COcs.LGstat.MLarXiv:2609.08172v12026
Reconstructing Training Data from Trained Neural Networks
Niv Haim, Gal Vardi, Gilad Yehudai +2
cs.LGcs.CRcs.CVarXiv:2206.07758v32022
Modeling and Uncertainty Analysis of Groundwater Level Using Six Evolutionary Optimization Algorithms Hybridized with ANFIS, SVM, and ANN
Akram Seifi, Mohammad Ehteram, Vijay P. Singh +1
eess.SPcs.LGcs.NEarXiv:2006.16848v12020
Prediction-Powered Smoothing and Validation for Disaggregated AI Evaluation
Sho Kawano, Zehang Richard Li, Paul A. Parker
stat.MLcs.AIcs.LGarXiv:2609.20758v12026
Scalable Bayesian Optimization Using Deep Neural Networks
Jasper Snoek, Oren Rippel, Kevin Swersky +6
stat.MLarXiv:1502.05700v22015
Membership Leakage in Label-Only Exposures
Zheng Li, Yang Zhang
cs.LGcs.CRstat.MLarXiv:2007.15528v32020
Conformal Prediction for Spatially Dependent Data via Sequential Whitening
Ayush Baran Sen, Arkajyoti Saha
stat.MLcs.LGstat.AParXiv:2610.10168v12026
Exploring the Limits of Large Scale Pre-training
Samira Abnar, Mostafa Dehghani, Behnam Neyshabur +1
cs.LGcs.AIcs.CVarXiv:2110.02095v12021
Inferring Multi-Timescale Neural Dynamics with Switching Linear Dynamical Systems
Lulu Gong, Yongxu Zhang, Shreya Saxena
cs.LGeess.SPq-bio.NCarXiv:2610.01786v12026
Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE
Juntang Zhuang, Nicha Dvornek, Xiaoxiao Li +3
stat.MLcs.LGarXiv:2006.02493v12020
Music Transformer
Cheng-Zhi Anna Huang, Ashish Vaswani, Jakob Uszkoreit +7
cs.LGcs.SDeess.ASarXiv:1809.04281v32018
A New PAC-Bayesian Perspective on Domain Adaptation
Pascal Germain, Amaury Habrard, François Laviolette +1
stat.MLcs.LGarXiv:1506.04573v42015
Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis
Rudy Bunel, Matthew Hausknecht, Jacob Devlin +2
cs.LGstat.MLarXiv:1805.04276v22018
Nonparametric Hypothesis Testing of High-dimensional Clustering With Application to Single-cell RNA Data
Yifan Dai, Di Wu, Yufeng Liu
stat.MEstat.APstat.COarXiv:2609.05683v12026
Motifs in Temporal Networks
Ashwin Paranjape, Austin R. Benson, Jure Leskovec
cs.SIphysics.soc-phstat.MLarXiv:1612.09259v12016
ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots
Michael Ahn, Henry Zhu, Kristian Hartikainen +4
cs.ROcs.LGstat.MLarXiv:1909.11639v32019
Merging Belief Propagation and the Mean Field Approximation: A Free Energy Approach
Erwin Riegler, Gunvor Elisabeth Kirkelund, Carles Navarro Manchón +2
cs.ITmath.ITstat.MLarXiv:1112.0467v32011
Amortized Planning with Large-Scale Transformers: A Case Study on Chess
Anian Ruoss, Grégoire Delétang, Sourabh Medapati +7
cs.LGcs.AIstat.MLarXiv:2402.04494v22024
Actionable Recourse in Linear Classification
Berk Ustun, Alexander Spangher, Yang Liu
stat.MLcs.LGarXiv:1809.06514v22018
In-context Learning of Single-index Targets: Comparing Kernel and Feature Learners
Haotian Gu, Yizhou Xu, Lenka Zdeborová
cs.LGcond-mat.dis-nnstat.MLarXiv:2610.01712v12026
Linear Mode Connectivity and the Lottery Ticket Hypothesis
Jonathan Frankle, Gintare Karolina Dziugaite, Daniel M. Roy +1
cs.LGcs.NEstat.MLarXiv:1912.05671v42019
Analysis of Nystrom method with sequential ridge leverage scores
Daniele Calandriello, Alessandro Lazaric, Michal Valko
cs.LGstat.MLarXiv:2604.20077v12026
Which Neural Net Architectures Give Rise To Exploding and Vanishing Gradients?
Boris Hanin
stat.MLcs.LGmath.PRarXiv:1801.03744v32018
Flora: Low-Rank Adapters Are Secretly Gradient Compressors
Yongchang Hao, Yanshuai Cao, Lili Mou
cs.LGcs.AIstat.MLarXiv:2402.03293v22024
Smoothing proximal gradient method for general structured sparse regression
Xi Chen, Qihang Lin, Seyoung Kim +2
stat.MLcs.LGmath.OCarXiv:1005.4717v42010
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization
Dan Hendrycks, Steven Basart, Norman Mu +10
cs.CVcs.LGstat.MLarXiv:2006.16241v32020
The Role of Uncertainty in Assessing the Fairness of Machine Learning Models
Francesca Panero, Ernst C. Wit, Marco Scutari
stat.MLcs.LGstat.MEarXiv:2609.07959v12026
A PAC-Bayesian bound for Lifelong Learning
Anastasia Pentina, Christoph H. Lampert
stat.MLcs.LGarXiv:1311.2838v22013
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin Liu, Juho Lee, Minseop Park +4
cs.LGcs.CVcs.NEarXiv:1805.10002v52018
When to use parametric models in reinforcement learning?
Hado van Hasselt, Matteo Hessel, John Aslanides
cs.LGcs.AIstat.MLarXiv:1906.05243v12019
Fast Differentiable Sorting and Ranking
Mathieu Blondel, Olivier Teboul, Quentin Berthet +1
stat.MLcs.LGarXiv:2002.08871v22020
Structured Nonconvex and Nonsmooth Optimization: Algorithms and Iteration Complexity Analysis
Bo Jiang, Tianyi Lin, Shiqian Ma +1
math.OCcs.LGstat.MLarXiv:1605.02408v52016
Shampoo: Preconditioned Stochastic Tensor Optimization
Vineet Gupta, Tomer Koren, Yoram Singer
cs.LGmath.OCstat.MLarXiv:1802.09568v22018
Provable Sparse Tensor Decomposition
Will Wei Sun, Junwei Lu, Han Liu +1
stat.MLarXiv:1502.01425v32015
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference
Shumao Zhang, Pengchuan Zhang, Thomas Y. Hou
stat.MLcs.CVcs.LGarXiv:2105.05489v12021
Exponential concentration in quantum kernel methods
Supanut Thanasilp, Samson Wang, M. Cerezo +1
quant-phcs.LGstat.MLarXiv:2208.11060v22022
Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering
Chong You, Chun-Guang Li, Daniel P. Robinson +1
cs.LGcs.CVstat.MLarXiv:1605.02633v12016
BDgraph: An R Package for Bayesian Structure Learning in Graphical Models
Reza Mohammadi, Ernst C. Wit
stat.MLarXiv:1501.05108v62015
Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions
Luyang Fang, Xiaowei Yu, Jiazhang Cai +23
cs.CLcs.LGstat.MLarXiv:2504.14772v22025
Flower: A Friendly Federated Learning Research Framework
Daniel J. Beutel, Taner Topal, Akhil Mathur +8
cs.LGcs.CVstat.MLarXiv:2007.14390v52020
Testing Robustness Against Unforeseen Adversaries
Max Kaufmann, Daniel Kang, Yi Sun +9
cs.LGcs.CRcs.CVarXiv:1908.08016v42019
Max-Sliced Wasserstein Distance and its use for GANs
Ishan Deshpande, Yuan-Ting Hu, Ruoyu Sun +6
cs.LGcs.CVstat.MLarXiv:1904.05877v22019
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models
Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang
cs.LGstat.MLarXiv:1909.11299v22019

Machine Learning (stat)

A Brief Introduction to Machine Learning for Engineers

Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation

Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization

Finite Versus Infinite Neural Networks: an Empirical Study

Distillation of Discrete Diffusion through Dimensional Correlations

Estimating network edge probabilities by neighborhood smoothing

Feedback Recurrent Autoencoder for Video Compression

KVCOMM: Online Cross-context KV-cache Communication for Efficient LLM-based Multi-agent Systems

E(n) Equivariant Normalizing Flows

SDECast: Probabilistic Weather Forecasting in Continuous Time with Neural SDEs

Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo

Neural source-filter-based waveform model for statistical parametric speech synthesis

The limitation of neural nets for approximation and optimization

Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming

On the Convergence of Stochastic Gradient MCMC Algorithms with High-Order Integrators

Feature Space Adaptation for Effortless Gaussian Process Flows

Orthogonal Random Features

Optimal Slice-Adaptive Tuning of Hybrid Slice Sampling

Reconstructing Training Data from Trained Neural Networks

Modeling and Uncertainty Analysis of Groundwater Level Using Six Evolutionary Optimization Algorithms Hybridized with ANFIS, SVM, and ANN

Prediction-Powered Smoothing and Validation for Disaggregated AI Evaluation

Scalable Bayesian Optimization Using Deep Neural Networks

Membership Leakage in Label-Only Exposures

Conformal Prediction for Spatially Dependent Data via Sequential Whitening

Exploring the Limits of Large Scale Pre-training

Inferring Multi-Timescale Neural Dynamics with Switching Linear Dynamical Systems

Adaptive Checkpoint Adjoint Method for Gradient Estimation in Neural ODE

Music Transformer

A New PAC-Bayesian Perspective on Domain Adaptation

Leveraging Grammar and Reinforcement Learning for Neural Program Synthesis

Nonparametric Hypothesis Testing of High-dimensional Clustering With Application to Single-cell RNA Data

Motifs in Temporal Networks

ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots

Merging Belief Propagation and the Mean Field Approximation: A Free Energy Approach

Amortized Planning with Large-Scale Transformers: A Case Study on Chess

Actionable Recourse in Linear Classification

In-context Learning of Single-index Targets: Comparing Kernel and Feature Learners

Linear Mode Connectivity and the Lottery Ticket Hypothesis

Analysis of Nystrom method with sequential ridge leverage scores

Which Neural Net Architectures Give Rise To Exploding and Vanishing Gradients?

Flora: Low-Rank Adapters Are Secretly Gradient Compressors

Smoothing proximal gradient method for general structured sparse regression

The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization

The Role of Uncertainty in Assessing the Fairness of Machine Learning Models

A PAC-Bayesian bound for Lifelong Learning

Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning

When to use parametric models in reinforcement learning?

Fast Differentiable Sorting and Ranking

Structured Nonconvex and Nonsmooth Optimization: Algorithms and Iteration Complexity Analysis

Shampoo: Preconditioned Stochastic Tensor Optimization

Provable Sparse Tensor Decomposition

Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference

Exponential concentration in quantum kernel methods

Oracle Based Active Set Algorithm for Scalable Elastic Net Subspace Clustering

BDgraph: An R Package for Bayesian Structure Learning in Graphical Models

Knowledge Distillation and Dataset Distillation of Large Language Models: Emerging Trends, Challenges, and Future Directions

Flower: A Friendly Federated Learning Research Framework

Testing Robustness Against Unforeseen Adversaries

Max-Sliced Wasserstein Distance and its use for GANs

Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models