Approximating Hessian matrices using Bayesian inference: a new approach for quasi-Newton methods in stochastic optimization
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Publication:6661113
DOI10.1080/10556788.2024.2339226MaRDI QIDQ6661113
A. G. Carlon, R. Tempone, L. F. R. Espath
Publication date: 10 January 2025
Published in: Optimization Methods \& Software (Search for Journal in Brave)
Bayesian inference (62F15) Numerical optimization and variational techniques (65K10) Stochastic programming (90C15)
Cites Work
- Title not available (Why is that?)
- A stochastic quasi-Newton method for large-scale optimization
- Minimizing finite sums with the stochastic average gradient
- SGD-QN: careful quasi-Newton stochastic gradient descent
- On the Use of Stochastic Hessian Information in Optimization Methods for Machine Learning
- Quasi-Newton Methods, Motivation and Theory
- Optimization Methods for Large-Scale Machine Learning
- A Noise-Tolerant Quasi-Newton Algorithm for Unconstrained Optimization
- Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization
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