EXTENSIONS OF DYNAMIC PROGRAMMING FOR COMBINATORIAL OPTIMIZATION

Speaker(s)

Mikhail Moshkov

Affiliation

KAUST

Date

June 6, 2014, 3:45 p.m.

Room

room 5440

Seminar

Research Seminar of the Logic Group: Approximate reasoning in data mining

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The aim of usual Dynamic Programming (DP) is to find an optimal object from a finite set of objects. We consider extensions of DP which allow us (i) to describe the set of optimal objects, (ii) to count the number of these objects, (iii) to make sequential optimization relative to different criteria, (iv) to find the set of Pareto optimal points for two criteria, and (v) to describe relationships between two criteria.  The areas of applications include discrete optimization, fault diagnosis, complexity of algorithms, machine learning, and knowledge representation.

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