Block-Coordinate Gradient Descent Method for
โ Scribed by P. Tseng; S. Yun
- Publisher
- Springer
- Year
- 2008
- Tongue
- English
- Weight
- 506 KB
- Volume
- 140
- Category
- Article
- ISSN
- 0022-3239
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๐ SIMILAR VOLUMES
We consider the problem of minimizing the sum of a smooth function and a separable convex function. This problem includes as special cases bound-constrained optimization and smooth optimization with 1 -regularization. We propose a (block) coordinate gradient descent method for solving this class of
In this paper, we propose two new hybrid nonlinear conjugate gradient methods, which produce sufficient descent search direction at every iteration. This property depends neither on the line search used nor on the convexity of the objective function. Under suitable conditions, we prove that the prop