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A Coordinate Gradient Descent Method for Structured Nonsmooth Optimization

Name: A Coordinate Gradient Descent Method for Structured Nonsmooth Optimization
Brand: VDM Verlag Dr. Müller
SKU: 9783836478601
Price: 181.43 PLN
Availability: InStock

Theory and Applications

Autor: Sangwoon Yun

Język:

Oprawa: Miękka

Wydawca: VDM Verlag Dr. Müller

Dostępność: Dostępna u dostawcy

Wysyłamy za 5-8 dni

181.43 zł

Nonsmooth optimization problems are generally considered to be more difficult than smooth problems....

Informacje o książce

Autor

Sangwoon Yun

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2010

strony

112

EAN

9783836478601

Enbook ID

07161550

Wydawca

VDM Verlag Dr. Müller

Waga

168

Wymiary

150 x 220 x 6

Pełny opis

Nonsmooth optimization problems are generally considered to be more difficult than smooth problems. Yet, there is an important class of nonsmooth problems that lie in between. In this book, we consider the problem of minimizing the sum of a smooth function and a (block separable) convex function with or without linear constraints. This problem includes as special cases bound-constrained optimization, smooth optimization with L_1-regularization, and linearly constrained smooth optimization such as a large-scale quadratic programming problem arising in the training of support vector machines. We propose a block coordinate gradient descent method for solving this class of structured nonsmooth problems. The method is simple, highly parallelizable, and suited for large-scale applications in signal/image denoising, regression, and data mining/classification. We establish global convergence and, under a local Lipschitzian error bound assumption, local linear rate of convergence for this method. Our numerical experiences suggest that our method is effective in practice. This book is helpful to the people who are interested in solving large-scale optimization problems.