Composite Self-Concordant Minimization
| Citations: | 7 - 5 self |
BibTeX
@MISC{Tran-dinh_compositeself-concordant,
author = {Quoc Tran-dinh and Anastasios Kyrillidis and Volkan Cevher},
title = {Composite Self-Concordant Minimization },
year = {}
}
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Abstract
We propose a variable metric framework for minimizing the sum of a self-concordant function and a possibly non-smooth convex function endowed with a computable proximal operator. We theoretically establish the convergence of our framework without relying on the usual Lipschitz gradient assumption on the smooth part. An important highlight of our work is a new set of analytic step-size selection and correction procedures based on the structure of the problem. We describe concrete algorithmic instances of our framework for several interesting large-scale applications and demonstrate them numerically on both synthetic and real data.
Keyphrases
composite self-concordant minimization important highlight correction procedure self-concordant function variable metric framework computable proximal operator real data usual lipschitz gradient assumption non-smooth convex function smooth part several interesting large-scale application concrete algorithmic instance new set analytic step-size selection
