Resilient monotone submodular function maximization

Resilient monotone submodular function maximization

In this paper, we focus on applications in machine learning, optimization, and control that call for the resilient selection of a few elements, e.g. features, sensors, or leaders, against a number of adversarial denial-of-service attacks or failures. In general, such resilient optimization problems...

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Bibliographic Details
Main Authors: Tzoumas, Vasileios (Author), Gatsis, Konstantinos (Author), Jadbabaie, Ali (Author), Pappas, George J. (Author), Jadbabaie-Moghadam, Ali (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Civil and Environmental Engineering (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor), MIT Sociotechnical Systems Research Center (Contributor)
Format: Article
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE), 2018-09-11T19:30:02Z.
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