Central limit theorems for stochastic gradient descent with averaging for stable manifolds
From MaRDI portal
Publication:6164916
DOI10.1214/23-ejp947arXiv1912.09187OpenAlexW2995406725WikidataQ121684527 ScholiaQ121684527MaRDI QIDQ6164916
Sebastian Kassing, Steffen Dereich
Publication date: 4 July 2023
Published in: Electronic Journal of Probability (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1912.09187
Monte Carlo methods (65C05) Discrete-time Markov processes on general state spaces (60J05) Stochastic approximation (62L20)
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Stochastic approximation revisited
- Stochastic algorithms
- Existence, uniqueness and regularity of the projection onto differentiable manifolds
- General multilevel adaptations for stochastic approximation algorithms. II: CLTs
- Resolution of singularities and geometric proofs of the Łojasiewicz inequalities
- Lower error bounds for the stochastic gradient descent optimization algorithm: sharp convergence rates for slowly and fast decaying learning rates
- Hölder and locally Hölder Continuous Functions, and Open Sets of Class C^k, C^{k,lambda}
- On Stochastic Approximation Methods
- Acceleration of Stochastic Approximation by Averaging
- Nonlinear orthogonal projection
- Global Minima of Overparameterized Neural Networks
- Stable Convergence and Stable Limit Theorems
- On Dvoretzky's Stochastic Approximation Theorem
- Asymptotic Distribution of Stochastic Approximation Procedures
- A Stochastic Approximation Method
- Approximation Methods which Converge with Probability one
- On a Stochastic Approximation Method
- Central limit theorems for stochastic gradient descent with averaging for stable manifolds
This page was built for publication: Central limit theorems for stochastic gradient descent with averaging for stable manifolds