Quadratic Growth Conditions and Uniqueness of Optimal Solution to Lasso

Autor: Yunier Bello-Cruz, Guoyin Li, Tran Thai An Nghia
Rok vydání: 2022
Předmět:
Zdroj: Journal of Optimization Theory and Applications. 194:167-190
ISSN: 1573-2878
0022-3239
DOI: 10.1007/s10957-022-02013-2
Popis: In the previous paper Bello-Cruz et al. (J Optim Theory Appl 188:378–401, 2021), we showed that the quadratic growth condition plays a key role in obtaining Q-linear convergence of the widely used forward–backward splitting method with Beck–Teboulle’s line search. In this paper, we analyze the property of quadratic growth condition via second-order variational analysis for various structured optimization problems that arise in machine learning and signal processing. This includes, for example, the Poisson linear inverse problem as well as the $$\ell _1$$ ℓ 1 -regularized optimization problems. As a by-product of this approach, we also obtain several full characterizations for the uniqueness of optimal solution to Lasso problem, which complements and extends recent important results in this direction.
Databáze: OpenAIRE
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