Academic Journal

The Proximal Alternating Direction Method of Multipliers in the Nonconvex Setting: Convergence Analysis and Rates: Convergence analysis and rates

Bibliographic Details
Title: The Proximal Alternating Direction Method of Multipliers in the Nonconvex Setting: Convergence Analysis and Rates: Convergence analysis and rates
Authors: Radu Ioan Boţ, Dang-Khoa Nguyen
Source: Mathematics of Operations Research. 45:682-712
Publication Status: Preprint
Publisher Information: Institute for Operations Research and the Management Sciences (INFORMS), 2020.
Publication Year: 2020
Subject Terms: 101016 Optimisation, NONSMOOTH, 0211 other engineering and technologies, Convergence rates, 02 engineering and technology, proximal splitting algorithms, convergence analysis, SPLITTING ALGORITHM, 47H05, 65K05, 90C26, Convergence analysis, Kurdyka-Lojasiewicz property, FOS: Mathematics, Mathematics - Numerical Analysis, Lojasiewicz exponent, Mathematics - Optimization and Control, Proximal splitting algorithms, SUM, alternating direction method of multipliers, Variable metric, Numerical Analysis (math.NA), Kurdyka-Łojasiewicz property, Łojasiewicz exponent, Alternating direction method of multipliers, nonconvex complexly structured optimization problems, variable metric, Optimization and Control (math.OC), convergence rates, MINIMIZATION, POINTS, 101016 Optimierung, Nonconvex complexly structured optimization problems
Description: We propose two numerical algorithms in the fully nonconvex setting for the minimization of the sum of a smooth function and the composition of a nonsmooth function with a linear operator. The iterative schemes are formulated in the spirit of the proximal alternating direction method of multipliers and its linearized variant, respectively. The proximal terms are introduced via variable metrics, a fact that allows us to derive new proximal splitting algorithms for nonconvex structured optimization problems, as particular instances of the general schemes. Under mild conditions on the sequence of variable metrics and by assuming that a regularization of the associated augmented Lagrangian has the Kurdyka–Łojasiewicz property, we prove that the iterates converge to a Karush–Kuhn–Tucker point of the objective function. By assuming that the augmented Lagrangian has the Łojasiewicz property, we also derive convergence rates for both the augmented Lagrangian and the iterates.
Document Type: Article
Language: English
ISSN: 1526-5471
0364-765X
DOI: 10.1287/moor.2019.1008
DOI: 10.48550/arxiv.1801.01994
Access URL: http://arxiv.org/pdf/1801.01994
http://arxiv.org/abs/1801.01994
https://ucrisportal.univie.ac.at/de/publications/e526ce94-59b7-48e9-9406-221df3dcb56a
https://doi.org/10.1287/moor.2019.1008
https://pubsonline.informs.org/doi/10.1287/moor.2019.1008
https://dblp.uni-trier.de/db/journals/mor/mor45.html#BotN20
https://ideas.repec.org/a/inm/ormoor/v45y2020i2p682-712.html
http://ui.adsabs.harvard.edu/abs/2018arXiv180101994I/abstract
Rights: arXiv Non-Exclusive Distribution
Accession Number: edsair.doi.dedup.....b7ddf6dbd94d9512ce06445dbdea4d5a
Database: OpenAIRE
Description
ISSN:15265471
0364765X
DOI:10.1287/moor.2019.1008