Global Optimization via Schrödinger–Föllmer Diffusion-Reference-Cited by-同舟云学术

Global Optimization via Schrödinger–Föllmer Diffusion

Published:2023-09-28 Issue:5 Volume:61 Page:2953-2980
ISSN:0363-0129
Container-title:SIAM Journal on Control and Optimization
language:en
Short-container-title:SIAM J. Control Optim.

Author:

Dai Yin¹,Jiao Yuling²,Kang Lican³,Lu Xiliang⁴,Yang Jerry Zhijian²^ORCID

Affiliation:

1. School of Mathematics and Statistics, Wuhan University, Wuhan, 430072, People’s Republic of China.

2. School of Mathematics and Statistics, and Hubei Key Laboratory of Computational Science, Wuhan University, Wuhan, 430072, People’s Republic of China.

3. School of Mathematics and Statistics, Wuhan University, Wuhan, 430072, People’s Republic of China, and Cardiovascular and Metabolic Disorders Program, Duke-NUS Medical School, 169857, Singapore.

4. Corresponding author. School of Mathematics and Statistics, and Hubei Key Laboratory of Computational Science, Wuhan University, Wuhan, 430072, People’s Republic of China.

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Society for Industrial & Applied Mathematics (SIAM)

Subject

Applied Mathematics,Control and Optimization

Reference44 articles.

1. Rate of convergence for ergodic continuous Markov processes: Lyapunov versus Poincaré

2. Analysis and Geometry of Markov Diffusion Operators

3. On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case

4. Coupling and convergence for Hamiltonian Monte Carlo

5. A consensus-based global optimization method for high dimensional machine learning problems

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