Online prediction under submodular constraints

Daiki Suehiro, Kohei Hatano, Shuji Kijima, Eiji Takimoto, Kiyohito Nagano

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

26 Citations (Scopus)


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
Number of pages15
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


Other23rd International Conference on Algorithmic Learning Theory, ALT 2012

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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