In this paper we study adaptive and non-adaptive exact learning of Juntas from membership queries. We use new techniques to find new bounds, narrow some of the gaps between the lower bounds and upper bounds and find new deterministic and randomized algorithms with small query and time complexities. Some of the bounds are tight in the sense that finding better ones either gives a breakthrough result in some long-standing combinatorial open problem or needs a new technique that is beyond the existing ones.
CITATION STYLE
Bshouty, N. H., & Costa, A. (2016). Exact learning of Juntas from membership queries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9925 LNAI, pp. 115–129). Springer Verlag. https://doi.org/10.1007/978-3-319-46379-7_8
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