Cover Image

Convergence guarantees for forward gradient descent in the linear regression model

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bos, Thijs, Schmidt-Hieber, Johannes
Format:	Preprint
Published:	2023
Subjects:	Statistics Theory Neural and Evolutionary Computing Primary: 62L20, secondary: 62J05
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Improving the Convergence Rates of Forward Gradient Descent with Repeated Sampling
by: Dexheimer, Niklas, et al.
Published: (2024)

A supervised deep learning method for nonparametric density estimation
by: Bos, Thijs, et al.
Published: (2023)

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

Even naive trees are consistent
by: Föge, Nico, et al.
Published: (2024)

The empirical copula process in high dimensions: Stute's representation and applications
by: Bücher, Axel, et al.
Published: (2024)

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

Goodness-of-fit testing from observations with multiplicative measurement error
by: Johannes, Jan, et al.
Published: (2025)

Azadkia-Chatterjee's dependence coefficient for infinite dimensional data
by: Hörmann, Siegfried, et al.
Published: (2024)

General linear hypothesis testing of high-dimensional mean vectors with unequal covariance matrices based on random integration
by: Cao, Mingxiang, et al.
Published: (2024)

A General (Non-Markovian) Framework for Covariate Adaptive Randomization: Achieving Balance While Eliminating the Shift
by: Fang, Hengjia, et al.
Published: (2026)

CBARA: Covariate-Balanced-and-Adjusted Response-Adaptive Randomization
by: Fang, Hengjia, et al.
Published: (2026)

Frontiers to the learning of nonparametric hidden Markov models
by: Abraham, Kweku, et al.
Published: (2023)

Dimension free ridge regression
by: Cheng, Chen, et al.
Published: (2022)

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

Empirical tail dependence functions in high dimensions: uniform linearizations and inference
by: Bücher, Axel, et al.
Published: (2026)

Integrated empirical measures and generalizations of classical goodness-of-fit statistics
by: Hwang, Hsien-Kuei, et al.
Published: (2024)

Lower bounds for the trade-off between bias and mean absolute deviation
by: Derumigny, Alexis, et al.
Published: (2023)

Linear methods for non-linear inverse problems
by: Koers, Geerten, et al.
Published: (2024)

Online jump and kink detection in segmented linear regression: Statistical optimality meets computational efficiency
by: Hüselitz, Annika, et al.
Published: (2025)

Improved performance guarantees for Tukey's median
by: Minsker, Stanislav, et al.
Published: (2024)

Statistical inference for rough volatility: Central limit theorems
by: Chong, Carsten, et al.
Published: (2022)

Uniform-over-dimension convergence with application to location tests for high-dimensional data
by: Chowdhury, Joydeep, et al.
Published: (2024)

Sparse maximum likelihood estimation for regression models
by: Tsao, Min
Published: (2024)

Generative Modelling via Quantile Regression
by: Schmidt-Hieber, Johannes, et al.
Published: (2024)

A Bayesian approach to functional regression: theory and computation
by: Berrendero, José R., et al.
Published: (2023)

Adaptive estimation for nonparametric circular regression with errors in variables
by: Nguyen, Tien Dat, et al.
Published: (2025)

Estimation of trace functionals and spectral measures of covariance operators in Gaussian models
by: Koltchinskii, Vladimir
Published: (2024)

Implicit vs. explicit regularization for high-dimensional gradient descent
by: Stark, Thomas, et al.
Published: (2025)

Semi-supervised linear regression with missing covariates
by: Risebrow, Benedict M., et al.
Published: (2026)

A nonparametric test for elliptical distribution based on kernel embedding of probabilities
by: Tang, Yin, et al.
Published: (2023)

Huber means on Riemannian manifolds
by: Lee, Jongmin, et al.
Published: (2024)

An exploration of sequential Bayesian variable selection -- A comment on García-Donato et al. (2025). "Model uncertainty and missing data: An objective Bayesian perspective"
by: Arnold, Sebastian, et al.
Published: (2025)

A novel statistical approach to analyze image classification
by: Chen, Juntong, et al.
Published: (2022)

Generalized Linear Spectral Statistics of High-dimensional Sample Covariance Matrices and Its Applications
by: Hu, Yanlin, et al.
Published: (2024)

On Second order correctness of Bootstrap in Logistic Regression
by: Das, Debraj, et al.
Published: (2020)

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

A Lower Bound for Estimating Fréchet Means
by: Hundrieser, Shayan, et al.
Published: (2024)

Subordinated Wright-Fisher Priors
by: Judd, Nathan A., et al.
Published: (2026)

High-dimensional linear regression inference via $\ell^2$ weak convergence
by: Fujimori, Kou, et al.
Published: (2026)

Harris recurrent Markov chains and nonlinear monotone cointegrated models
by: Bertail, Patrice, et al.
Published: (2024)