Dual Prediction-Correction Methods for Linearly Constrained Time-Varying Convex Programs

Devising efficient algorithms to solve continuously-varying strongly convex optimization programs is key in many applications, from control systems to signal processing and machine learning. In this context, solving means to find and track the optimizer trajectory of the continuously-varying convex...

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Bibliographic Details
Published in:	IEEE transactions on automatic control Vol. 64; no. 8; pp. 3355 - 3361
Main Author:	Simonetto, Andrea
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.08.2019 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Asymptotic methods Asymptotic properties Computational geometry Convergence Convex analysis Convex functions Convexity Cost function Dual ascent Error correction Iterative algorithms Iterative methods Machine learning parametric programming Prediction algorithms prediction–correction methods Signal processing Signal processing algorithms time-varying convex optimization Tracking errors Trajectory Trajectory optimization
ISSN:	0018-9286, 1558-2523
Online Access:	Get full text
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