Wednesday, 16:15 - 16:40 h, Room: H 2036


Sahar Karimi
CGSO for convex problems with polyhedral constraints

Coauthor: Stephen Vavasis


We have proposed CGSO (Conjugate Gradient with Subspace Optimization) as an extension to Nemirovski-Yudin's algorithm. CGSO is a conjugate gradient type algorithm that benefits from the optimal complexity bound Nemirovski-Yudin's algorithm achieves for the class of unconstrained convex problems. In this talk, we discuss CGSO for convex problems with polyhedral constraints. We study the theoretical properties as well as the practical performance of CGSO for this class of problems.


Talk 3 of the invited session Wed.3.H 2036
"First-derivative methods in convex optimization" [...]
Cluster 4
"Conic programming" [...]


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