Greedy Strategies for Convex Optimization Academic Article

abstract

• 2016, Springer-Verlag Italia. We investigate two greedy strategies for finding an approximation to the minimum of a convex function E defined on a Hilbert space H. We prove convergence rates for these algorithms under suitable conditions on the objective function E. These conditions involve the behavior of the modulus of smoothness and the modulus of uniform convexity of E.

authors

• Petrova, Guergana

published proceedings

• CALCOLO

author list (cited authors)

• Hao, N., & Petrova, G.

citation count

• 11

complete list of authors

• Hao, Nguyen||Petrova, Guergana

publication date

• March 2017

publisher

• Springer Nature  Publisher

published in

• Calcolo  Journal

keywords

• Convex Optimization
• Greedy Algorithms
• Rates Of Convergence

Digital Object Identifier (DOI)

• 10.1007/s10092-016-0183-2

URI

• https://hdl.handle.net/1969.1/151372

start page

• 207

end page

• 224

volume

• 54

issue

• 1

URL

• http://dx.doi.org/10.1007/s10092-016-0183-2