Xuất bản mới
Cấn Văn Hảo, Naoki Kubota, Shuta Nakajima, Lipschitz-Type Estimate for the Frog Model with Bernoulli Initial Configuration, Mathematical Physics, Analysis and Geometry, Volume 28, article number 1, (2025) (SCI-E, Scopus) .
Đoàn Thái Sơn, Phan Thị Hương, Peter E. Kloeden, Theta-scheme for solving Caputo fractional differential equations, Electronic Journal of Differential Equations, Vol. 2025 (2025), No. 05, pp. 1-13 (SCI-E, Scopus) .
Đinh Sĩ Tiệp, Guo Feng, Nguyễn Hồng Đức, Phạm Tiến Sơn, Computation of the Łojasiewicz exponents of real bivariate analytic functions, Manuscripta Mathematica . Volume 176, 1 (2025) (SCI-E, Scopus) .

Subgradient Methods in Infinite Dimensional Hilbert Spaces

Người báo cáo: Hong-Kun Xu (Hangzhou Dianzi University, China)


Thời gian: 930-10h30 Thứ Tư, ngày 19/7/2013

Địa điểm: Phòng 612, nhà A6

Tóm tắt: Subgradient methods, introduced by Shor and developed by Albert, Iusem, Nesterov, Polyak, Soloov, and many others, are used to solve nondifferentiable optimization problems. The major differences from the gradient descent methods (or projection-gradient methods) for differentiable optimization problems lie in the selection manners of the step-sizes. For instance, constant step-sizes for differen-tiable objective functions no longer work for nondifferentiable objective functions; for the latter case, diminishing step-sizes must however be adopted. In this talk, we will first review some existing projected subgradient methods and the main purpose is to discuss weak and strong convergence of projected subgradient methods in an infinite-dimensional Hilbert space. Some regularization techniques for strong convergence of projected subgradient methods will particu-larly be presented. Extension to the proximal-subgradient method for minimizing the sum of two nondifferentiable convex functions will also be discussed.