Structured weight-based prediction algorithms

Akira Maruoka, Eiji Takimoto

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Reviewing structured weight-based prediction algorithms (SWP for short) due to Takimoto, Maruoka and Vovk, we present underlying design methods for constructing a variety of on-line prediction algorithms based on the SWP. In particular, we shown how the typical expert model where the experts are considered to be arranged on one layer can be generalized to the case where they are laid on a tree structure so that the expert model can be applied to search for the best pruning in a straightforward fashion through dynamic programming scheme.

Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 9th International Conference, ALT 1998, Proceedings
EditorsMichael M. Richter, Rolf Wiehagen, Carl H. Smith, Thomas Zeugmann
PublisherSpringer Verlag
Pages127-142
Number of pages16
ISBN (Print)354065013X, 9783540650133
Publication statusPublished - Jan 1 1998
Externally publishedYes
Event9th International Conference on Algorithmic Learning Theory, ALT 1998 - Otzenhausen, Germany
Duration: Oct 8 1998Oct 10 1998

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1501
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other9th International Conference on Algorithmic Learning Theory, ALT 1998
CountryGermany
CityOtzenhausen
Period10/8/9810/10/98

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Maruoka, A., & Takimoto, E. (1998). Structured weight-based prediction algorithms. In M. M. Richter, R. Wiehagen, C. H. Smith, & T. Zeugmann (Eds.), Algorithmic Learning Theory - 9th International Conference, ALT 1998, Proceedings (pp. 127-142). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1501). Springer Verlag.