Optimization for Data-Driven Learning and Control

Usman A. Khan, Waheed U. Bajwa, Angelia Nedic, Michael G. Rabbat, Ali H. Sayed

Research output: Contribution to journalReview articlepeer-review

8 Scopus citations

Abstract

The special issue of Proceedings of the IEEE November 2020 provides a comprehensive overview of modern optimization tools and methods for the purposes of data-driven learning and control. The special issue brings together world-renowned experts from the areas of signal processing, control, optimization, and machine learning, who have contributed a total of 12 articles to this issue. These articles should be accessible to readers with different technical backgrounds, summarize the state-of-the-art theoretical and algorithmic advances in optimization for data-driven learning and control, and they elaborate on the implications of these advances in many real-world applications. Another highlight of these articles is their ability to connect their technical results to real-world applications for the benefit of the diverse readership of this special issue.

Original languageEnglish (US)
Article number9241498
Pages (from-to)1863-1868
Number of pages6
JournalProceedings of the IEEE
Volume108
Issue number11
DOIs
StatePublished - Nov 2020

ASJC Scopus subject areas

  • General Computer Science
  • Electrical and Electronic Engineering

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