Deterministic annealing for clustering: Tutorial and computational aspects

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The deterministic annealing (DA) method, used for the solution of several nonconvex problems, offers the ability to avoid shallow local minima of a given cost surface and the ability to minimize the cost function even when there are many local minima. The method is established in a probabilistic framework through basic information-theoretic techniques such as maximum entropy and random coding. It arises naturally in the context of statistical mechanics by the emulation of a physical process whereby a solid is slowly cooled and at zero temperature assumes its minimum energy configuration. In this paper, we first present some background material on the DA method and its connections to statistical physics and rate-distortion theory. A computational complexity analysis is then presented for a given temperature schedule. The case study focuses on the geometric cooling law T(t) = ρT (t-1); 0 < ρ < 1, where T(t) is the temperature at time t.

Original languageEnglish (US)
Title of host publicationACC 2015 - 2015 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)9781479986842
StatePublished - Jul 28 2015
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Conference2015 American Control Conference, ACC 2015
Country/TerritoryUnited States

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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