Online prediction under submodular constraints

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

16 Citations (Scopus)

Abstract

We consider an online prediction problem of combinatorial concepts where each combinatorial concept is represented as a vertex of a polyhedron described by a submodular function (base polyhedron). In general, there are exponentially many vertices in the base polyhedron. We propose polynomial time algorithms with regret bounds. In particular, for cardinality-based submodular functions, we give O(n 2)-time algorithms.

Original languageEnglish
Title of host publicationAlgorithmic Learning Theory - 23rd International Conference, ALT 2012, Proceedings
Pages260-274
Number of pages15
DOIs
Publication statusPublished - 2012
Event23rd International Conference on Algorithmic Learning Theory, ALT 2012 - Lyon, France
Duration: Oct 29 2012Oct 31 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7568 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other23rd International Conference on Algorithmic Learning Theory, ALT 2012
CountryFrance
CityLyon
Period10/29/1210/31/12

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Suehiro, D., Hatano, K., Kijima, S., Takimoto, E., & Nagano, K. (2012). Online prediction under submodular constraints. In Algorithmic Learning Theory - 23rd International Conference, ALT 2012, Proceedings (pp. 260-274). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7568 LNAI). https://doi.org/10.1007/978-3-642-34106-9_22