data mining

Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining - 2022-10-04

Mikhail Moshkov, Professor, Applied Mathematics and Computational Science

Oct 4, 12:00 - 13:00

B9 L2 R2322

Dynamic programming combinatorial optimization data mining

Dynamic programming is an efficient technique to solve optimization problems. It is based on decomposing the initial problem into simpler ones and solving these sub-problems beginning from the simplest ones. A conventional dynamic programming algorithm returns an optimal object from a given set of objects.

New Book "Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining" of Professor Moshkov and His Former Students is Published by Springer

1 min read · Mon, Jul 9 2018

machine learning knowledge discovery data mining combinatorial optimization

A new book - "Extensions of Dynamic Programming for Combinatorial Optimization and Data Mining" by Hassan AbouEisha, Talha Amin, Igor Chikalov, Shahid Hussain, and Mikhail Moshkov - was recently published by Springer.

Mikhail Moshkov

Professor, Applied Mathematics and Computational Science

machine learning data mining discrete optimization algorithmic complexity

Professor Moshkov specializes in various areas of discrete applied mathematics, theoretical computer science and operations research. He is the author or co-author of more than 200 research publications, including 10 books published by Springer.