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Computer-Assisted Design of Accelerated Composite Optimization Methods: OptISTA
The accelerated composite optimization method FISTA (Beck, Teboulle 2009) is suboptimal, and we present a new method OptISTA that improves upon it by a factor of 2. The performance estimation problem (PEP) has recently been introduced as a new computer-assisted paradigm for designing optimal first-o...
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Published in: | arXiv.org 2024-09 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | The accelerated composite optimization method FISTA (Beck, Teboulle 2009) is suboptimal, and we present a new method OptISTA that improves upon it by a factor of 2. The performance estimation problem (PEP) has recently been introduced as a new computer-assisted paradigm for designing optimal first-order methods, but the methodology was largely limited to unconstrained optimization with a single function. In this work, we present a novel double-function stepsize-optimization PEP methodology that poses the optimization over fixed-step first-order methods for composite optimization as a finite-dimensional nonconvex QCQP, which can be practically solved through spatial branch-and-bound algorithms, and use it to design the exact optimal method OptISTA for the composite optimization setup. We then establish the exact optimality of OptISTA with a novel lower-bound construction that extends the semi-interpolated zero-chain construction (Drori, Taylor 2022) to the double-function setup of composite optimization. By establishing exact optimality, our work concludes the search for the fastest first-order methods for the proximal, projected-gradient, and proximal-gradient setups. |
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ISSN: | 2331-8422 |