Convex Optimization on Banach Spaces Academic Article

abstract

• 2015, SFoCM. Greedy algorithms which use only function evaluations are applied to convex optimization in a general Banach space (Formula presented.). Along with algorithms that use exact evaluations, algorithms with approximate evaluations are treated. A priori upper bounds for the convergence rate of the proposed algorithms are given. These bounds depend on the smoothness of the objective function and the sparsity or compressibility (with respect to a given dictionary) of a point in (Formula presented.) where the minimum is attained.

authors

• Devore, Ronald

published proceedings

• FOUNDATIONS OF COMPUTATIONAL MATHEMATICS

author list (cited authors)

• DeVore, R. A., & Temlyakov, V. N.

citation count

• 13

complete list of authors

• DeVore, RA||Temlyakov, VN

publication date

• April 2016

publisher

• Springer Nature  Publisher

published in

• Foundations of Computational Mathematics  Journal

keywords

• Approximate Evaluation
• Banach Space
• Convergence Rate
• Greedy
• Optimization
• Sparse

Digital Object Identifier (DOI)

• 10.1007/s10208-015-9248-x

start page

• 369

end page

• 394

volume

• 16

issue

• 2

URL

• http%3A%2F%2Fdx.doi.org%2F10.1007%2Fs10208-015-9248-x