Type
ArticleAuthors
Moshkov, Mikhail
KAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionApplied Mathematics and Computational Science Program
Extensions of Dynamic Programming, Machine Learning and Discrete Optimization Research Group
Date
2010-12-01Permanent link to this record
http://hdl.handle.net/10754/561592
Metadata
Show full item recordAbstract
An approximate algorithm for minimization of weighted depth of decision trees is considered. A bound on accuracy of this algorithm is obtained which is unimprovable in general case. Under some natural assumptions on the class NP, the considered algorithm is close (from the point of view of accuracy) to best polynomial approximate algorithms for minimization of weighted depth of decision trees.Sponsors
This work was partially supported by the KAUST-Stanford AEA program. The author is greatly indebted to the anonymous reviewer for helpful comments and suggestions.Publisher
IOS PressJournal
Fundamenta Informaticaeae974a485f413a2113503eed53cd6c53
10.3233/FI-2010-350