Sorting by decision trees with hypotheses (extended abstract)

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Type
Conference Paper
Authors
Azad, Mohammad cc
Chikalov, Igor cc
Hussain, Shahid cc
Moshkov, Mikhail cc
KAUST Department
Applied Mathematics and Computational Science Program
Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
Extensions of Dynamic Programming, Machine Learning and Discrete Optimization Research Group
Date
2021-01-01
Permanent link to this record
http://hdl.handle.net/10754/672122

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Abstract
In this paper, we consider decision trees that use both queries based on one attribute each and queries based on hypotheses about values of all attributes. Such decision trees are similar to ones studied in exact learning, where not only membership but also equivalence queries are allowed. For n = 3,..., 6, we compare decision trees based on various combinations of attributes and hypotheses for sorting n pairwise different elements from linearly ordered set.
Sponsors
Research reported in this publication was supported by King Abdullah University of Science and Technology (KAUST). The authors are indebted to the anonymous reviewers for interesting comments.
Publisher
CEUR-WS
Conference/Event name
29th International Workshop on Concurrency, Specification and Programming, CS and P 2021
Collections
Conference Papers; Applied Mathematics and Computational Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division