Title
Parameterized learnability of juntas
Abstract
We study the parameterized complexity of learning k-juntas and some variations of juntas. We show the hardness of learning k-juntas and subclasses of k-juntas in the PAC model by reductions from a W[2]-complete problem. On the other hand, as a consequence of a more general result, we show that k-juntas are exactly learnable with improper equivalence queries and access to a W[P] oracle.
Year
DOI
Venue
2009
10.1016/j.tcs.2009.07.003
Theor. Comput. Sci.
Keywords
DocType
Volume
Computational complexity,PAC model,complete problem,improper equivalence query,parameterized complexity,Parameterized learnability,Learning theory,general result
Journal
410
Issue
ISSN
Citations 
47-49
Theoretical Computer Science
3
PageRank 
References 
Authors
0.37
20
3
Name
Order
Citations
PageRank
V. Arvind1524.34
Johannes Köbler258046.51
Wolfgang Lindner3707.89