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25 April 2024

» arxiv » 1510.0490

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On the rate analysis of inexact augmented Lagrangian schemes for convex optimization problems with misspecified constraints
H. Ahmadi ; N. S. Aybat ; U. V. Shanbhag ;
Date:	2 Oct 2015
Abstract:	We consider a misspecified optimization problem that requires minimizing of a convex function f (x;q) in x over a constraint set represented by h(x;q)<=0, where q* is an unknown (or misspecified) vector of parameters. Suppose q* is learnt by a distinct process that generates a sequence of estimators q_k, each of which is an increasingly accurate approximation of q. We develop a constant joint first order augmented Lagrangian scheme for computing x while simultaneously learning q. Numerical results based on a portfolio optimization problem with a misspecified covariance matrix support the findings.
Source:	arXiv, 1510.0490
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