Title
Parameterized Learnability of k-Juntas and Related Problems
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
2007
10.1007/978-3-540-75225-7_13
ALT
Keywords
Field
DocType
parameterized learnability,related problems,pac model,complete problem,improper equivalence query,parameterized complexity,general result,computational complexity,learning theory
Parameterized complexity,Learning theory,Computer science,Oracle,Theoretical computer science,Equivalence (measure theory),Artificial intelligence,Learnability,Machine learning,Computational complexity theory
Conference
Volume
ISSN
Citations 
4754
0302-9743
3
PageRank 
References 
Authors
0.45
20
3
Name
Order
Citations
PageRank
Vikraman Arvind129638.18
Johannes Köbler258046.51
Wolfgang Lindner3707.89