A Bernstein-type Inequality for Some Mixing Processes and Dynamical Systems with an Application to Learning

13 January 2015

H. Hang

Ingo Steinwart

ArXiv (abs)PDF HTML

Papers citing "A Bernstein-type Inequality for Some Mixing Processes and Dynamical Systems with an Application to Learning"

26 / 26 papers shown

Discrimination-free Insurance Pricing with Privatized Sensitive Attributes

306

16 Apr 2025

Meta-Posterior Consistency for the Bayesian Inference of Metastable System

Zachary P Adams

Sayan Mukherjee

283

03 Aug 2024

Neural Network Approximation for Pessimistic Offline Reinforcement Learning

Yuling Jiao

307

19 Dec 2023

Statistical Spatially Inhomogeneous Diffusion Inference

249

10 Dec 2023

On the Connection between

L_p

and Risk Consistency and its Implications on Regularized Kernel MethodsJournal of machine learning research (JMLR), 2023

Hannes Köhler

317

27 Mar 2023

Mixed moving average field guided learning for spatio-temporal dataElectronic Journal of Statistics (EJS), 2023

386

02 Jan 2023

Statistical learning for

ψ

-weakly dependent processes

Mamadou Lamine Diop

William Kengne

274

30 Sep 2022

Bernstein-type Inequalities and Nonparametric Estimation under Near-Epoch DependenceJournal of Econometrics (JE), 2022

Zihao Yuan

Martin Spindler

325

24 Aug 2022

Nyström Regularization for Time Series ForecastingJournal of machine learning research (JMLR), 2021

296

13 Nov 2021

A Bernstein-type Inequality for High Dimensional Linear Processes with Applications to Robust Estimation of Time Series Regressions

Linbo Liu

Danna Zhang

AI4TS

331

21 Sep 2021

Under-bagging Nearest Neighbors for Imbalanced ClassificationJournal of machine learning research (JMLR), 2021

364

01 Sep 2021

The Bootstrap for Dynamical Systems

Kasun Fernando

Nan Zou

179

19 Aug 2021

A Kernel Two-sample Test for Dynamical Systems

Dominik Baumann

Thomas Seel

335

23 Apr 2020

Kernel Autocovariance Operators of Stationary Processes: Estimation and ConvergenceJournal of machine learning research (JMLR), 2020

272

02 Apr 2020

Aggregation of Multiple KnockoffsInternational Conference on Machine Learning (ICML), 2020

Tuan-Binh Nguyen

Jérôme-Alexis Chevalier

Bertrand Thirion

Sylvain Arlot

469

21 Feb 2020

Distributed Learning with Dependent SamplesIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020

Zirui Sun

Shao-Bo Lin

357

10 Feb 2020

Best-scored Random Forest Classification

H. Hang

Xiaoyu Liu

Ingo Steinwart

163

27 May 2019

Gibbs posterior convergence and the thermodynamic formalism

K. Mcgoff

S. Mukherjee

A. Nobel

309

24 Jan 2019

Structure learning via unstructured kernel-based M-regression

Xin He

Yeheng Ge

Xingdong Feng

368

03 Jan 2019

Recovery guarantees for polynomial approximation from dependent data with outliers

201

25 Nov 2018

Exponential inequalities for nonstationary Markov Chains

Pierre Alquier

P. Doukhan

Xiequan Fan

355

27 Aug 2018

Concentration of weakly dependent Banach-valued sums and applications to statistical learning methods

Gilles Blanchard

O. Zadorozhnyi

197

05 Dec 2017

Empirical risk minimization and complexity of dynamical models

K. Mcgoff

A. Nobel

318

18 Nov 2016

Kernel Density Estimation for Dynamical SystemsJournal of machine learning research (JMLR), 2016

282

13 Jul 2016

Learning theory estimates with observations from general stationary stochastic processes

189

10 May 2016

Variational analysis of inference from dynamical systems

K. Mcgoff

A. Nobel

398

19 Jan 2016