Metadata
Abstract
We introduce and analyse the almost sure convergence of a new stochastic algorithm for the global minimization of Morse functions on compact Riemannian manifolds. This diffusion process is called fraudulent because it requires the knowledge of minimal value of the function to minimize. Its investigation is nevertheless important, since in particular it appears as the limit behavior of non-fraudulent and time-inhomogeneous swarm mean-field algorithms used in global optimization.
References
[BMV24] Swarm gradient dynamics for global optimization: the density case, Math. Program., Volume 205 (2024) no. 1-2, pp. 661-701 | MR | DOI | Zbl
[CLN06] Hamilton’s Ricci flow, Graduate Studies in Mathematics, 77, American Mathematical Society, 2006 | Zbl
[EK86] Markov processes. Characterization and convergence, Wiley Series in Probability and Statistics, John Wiley & Sons, 1986 | DOI | MR | Zbl
[HKS89] Asymptotics of the spectral gap with applications to the theory of simulated annealing, J. Funct. Anal., Volume 83 (1989) no. 2, pp. 333-347 | MR | DOI | Zbl
[IW89] Stochastic differential equations and diffusion processes, North-Holland Mathematical Library, 24, North-Holland; Kodansha Ltd., 1989 | MR | Zbl
[LG15] Bessel processes, the Brownian snake and super-Brownian motion, Séminaire de Probabilités XLVII, Springer, 2015, pp. 89-105 | DOI | Zbl
[LTE19] Stochastic modified equations and dynamics of stochastic gradient algorithms. I: Mathematical foundations, J. Mach. Learn. Res., Volume 20 (2019), 40, 47 pages | MR | Zbl
[MZLU22] Power-Law Escape Rate of SGD, Proceedings of the 39th International Conference on Machine Learning (Chaudhuri, Kamalika; Jegelka, Stefanie; Song, Le; Szepesvari, Csaba; Niu, Gang; Sabato, Sivan, eds.) (Proceedings of Machine Learning Research), Volume 162, PMLR (2022), pp. 15959-15975
[RY99] Continuous martingales and Brownian motion, Grundlehren der Mathematischen Wissenschaften, 293, Springer, 1999 | Zbl | DOI | MR
[Sil86] Density estimation for statistics and data analysis, Monographs on Statistics and Applied Probability, CRC Press, 1986 | MR | Zbl
[SV97] Multidimensional diffusion processes, Classics in Mathematics, Springer, 1997 | MR | Zbl
[Woj24] Stochastic gradient descent with noise of machine learning type. II: Continuous time analysis, J. Nonlinear Sci., Volume 34 (2024) no. 1, 16, 45 pages | MR | DOI | Zbl
[WWS22] The alignment property of SGD noise and how it helps select flat minima. A stability analysis, NeurIPS 2022 (Koyejo, Sanmi; Mohamed, S.; Agarwal, Alekh; Belgrave, Danielle; Cho, Kyunghyun; Oh, Alice H., eds.) (Advances in Neural Information Processing), Volume 35, Curran Associates, Inc. (2022), pp. 4680-4693