Design of deterministic optimization algorithms with inexact information

2 settimane fa

Italia Università degli Studi della Campania A tempo pieno

Organisation/Company: Università degli Studi della Campania

Research Field: Mathematics

Researcher Profile: Recognised Researcher (R2), Leading Researcher (R4), First Stage Researcher (R1), Established Researcher (R3)

Country: Italy

Application Deadline: 25 Nov 2024 - 23:59 (UTC)

Type of Contract: To be defined

Job Status: Not Applicable

Is the job funded through the EU Research Framework Programme? Not funded by a EU programme

Is the Job related to staff position within a Research Infrastructure? No

Offer Description

The project involves designing first-order algorithms for large-scale minimization with linear or constrained constraints on variables, focusing mainly on step length rules based on variable metric techniques. The idea is to scale the different gradient components to faithfully capture the geometry of the problem. Another strategy to be analyzed is to dynamically alternate different rules, particularly Barzilai Borwein and its variants with limited memory algorithms, as the iterative process progresses. Finally, the design of efficient strategies that can make up for the inexactness of the first-order information will be considered: this is a major problem in several applications because of the need to preserve the convergence properties of the methods under the assumption of inexactness of the available information.

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