Cover Image

Empirical Risk Minimization as Parameter Choice Rule for General Linear Regularization Methods

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Housen, Werner, Frank
Format:	Preprint
Published:	2017
Subjects:	Numerical Analysis Statistics Theory Primary 62G05, Secondary 62G20, 65J22, 65J20
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

L^1 data fitting for Inverse Problems yields optimal rates of convergence in case of discretized white Gaussian noise
by: Bätz, Kristina, et al.
Published: (2025)

Maximum a posteriori testing in statistical inverse problems
by: Kretschmann, Remo, et al.
Published: (2024)

Convergence analysis of Tikhonov regularization for non-linear statistical inverse learning problems
by: Rastogi, Abhishake, et al.
Published: (2019)

Hybrid ABBA-GMRES for Unmatched Backprojectors in Large Scale X-Ray Computerized Tomography
by: Bentley, Ryan, et al.
Published: (2026)

Least squares approximations in linear statistical inverse learning problems
by: Helin, Tapio
Published: (2022)

On regularized polynomial functional regression
by: Holzleitner, Markus, et al.
Published: (2023)

Optimal regularized hypothesis testing in statistical inverse problems
by: Kretschmann, Remo, et al.
Published: (2022)

Spectral Regularized Kernel Two-Sample Tests
by: Hagrass, Omar, et al.
Published: (2022)

Spectral Regularized Kernel Goodness-of-Fit Tests
by: Hagrass, Omar, et al.
Published: (2023)

A Scalable Sequential Framework for Dynamic Inverse Problems via Model Parameter Estimation
by: Keating, Aryeh, et al.
Published: (2026)

Early stopping for conjugate gradients in statistical inverse problems
by: Hucker, Laura, et al.
Published: (2024)

Minimax Optimal Kernel Two-Sample Tests with Random Features
by: Mukherjee, Soumya, et al.
Published: (2025)

Minimax Optimal Goodness-of-Fit Testing with Kernel Stein Discrepancy
by: Hagrass, Omar, et al.
Published: (2024)

Non-asymptotic error estimates for the Laplace approximation in Bayesian inverse problems
by: Helin, Tapio, et al.
Published: (2020)

Are minimizers of the Onsager-Machlup functional strong posterior modes?
by: Kretschmann, Remo
Published: (2022)

Berry-Esseen Bounds and Moderate Deviations for Catoni-Type Robust Estimation
by: Cai, Zhijun, et al.
Published: (2026)

On Learning the Optimal Regularization Parameter in Inverse Problems
by: Rodriguez, Jonathan Chirinos, et al.
Published: (2023)

A multilevel sketch-and-solve method for overdetermined least squares problems
by: Haas, Irina-Beatrice, et al.
Published: (2026)

Dictionary-based model reduction for state estimation
by: Nouy, Anthony, et al.
Published: (2023)

Error bounds for some approximate posterior measures in Bayesian inference
by: Lie, Han Cheng, et al.
Published: (2019)

Model-free filtering in high dimensions via projection and score-based diffusions
by: Christensen, Sören, et al.
Published: (2025)

Bernstein-von Mises Theorem for Sparse Generalized Linear Model
by: Li, Hanqing, et al.
Published: (2026)

Amortized Energy-Based Bayesian Inference
by: Kaveh, Hojjat, et al.
Published: (2026)

Transfer Learning for Functional Mean Estimation: Phase Transition and Adaptive Algorithms
by: Cai, T. Tony, et al.
Published: (2024)

Automatic Debiased Machine Learning via Riesz Regression
by: Chernozhukov, Victor, et al.
Published: (2021)

A short tour of operator learning theory: Convergence rates, statistical limits, and open questions
by: Brugiapaglia, Simone, et al.
Published: (2026)

Convergence Analysis of regularised Nyström method for Functional Linear Regression
by: Gupta, Naveen, et al.
Published: (2024)

Volatility estimation from a view point of entropy
by: Akahori, Jirô, et al.
Published: (2024)

Uniform convergence of kernel averages under fixed design with heterogeneous dependent data
by: Matsuoka, Danilo Hiroshi, et al.
Published: (2026)

A hypothesis test for the domain of attraction of a random variable
by: Olivero, Héctor, et al.
Published: (2022)

Error Bounds for Importance Sampling with Estimated Proposal Distributions
by: Aeckerle-Willems, Cathrine, et al.
Published: (2026)

How should we aggregate ratings? Accounting for personal rating scales via Wasserstein barycenters
by: Raban, Daniel
Published: (2024)

Estimating hazard rates from $δ$-records in discrete distributions
by: Alcalde, Martín, et al.
Published: (2025)

Large sample behavior of the least trimmed squares estimator
by: Zuo, Yijun
Published: (2022)

Convergence of stochastic gradient descent schemes for Lojasiewicz-landscapes
by: Dereich, Steffen, et al.
Published: (2021)

Global polynomial-time estimation in statistical nonlinear inverse problems via generalized stability
by: Wang, Sven
Published: (2026)

Adaptive Nonparametric Estimation via Kernel Transport on Group Orbits: Oracle Inequalities and Minimax Rates
by: Nembe, Jocelyn
Published: (2025)

An effective estimation of multivariate density functions using extended-beta kernels with Bayesian adaptive bandwidths
by: Somé, Sobom M., et al.
Published: (2025)

Nonparametric Bayesian inference for stochastic processes with piecewise constant priors
by: Belomestny, Denis, et al.
Published: (2023)

Nonparametric Inference on Dose-Response Curves Without the Positivity Condition
by: Zhang, Yikun, et al.
Published: (2024)