Parameterized Learnability of k-Juntas and Related Problems

  • Vikraman Arvind
  • Johannes Köbler
  • Wolfgang Lindner
Conference paper

DOI: 10.1007/978-3-540-75225-7_13

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4754)
Cite this paper as:
Arvind V., Köbler J., Lindner W. (2007) Parameterized Learnability of k-Juntas and Related Problems. In: Hutter M., Servedio R.A., Takimoto E. (eds) Algorithmic Learning Theory. ALT 2007. Lecture Notes in Computer Science, vol 4754. Springer, Berlin, Heidelberg

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.

Subject Classification

Learning theory computational complexity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Vikraman Arvind
    • 1
  • Johannes Köbler
    • 2
  • Wolfgang Lindner
    • 3
  1. 1.The Institute of Mathematical Sciences, Chennai 600 113India
  2. 2.Institut für Informatik, Humboldt Universität zu BerlinGermany
  3. 3.Sidonia Systems, Grubmühl 20, D-82131 StockdorfGermany

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