A Working Set Algorithm for Accelerating the Relevance Vector Machine

David Ben-Shimon, Armin Shmilovici

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


The runtime complexity of the Relevance Vector Machine (RVM) is which makes it too expensive for moderately sized machine learning problems. We propose a working set algorithm which reduces the runtime complexity to O(N2). Experiments verify the viability of the method for classification benchmark problemsץ
Original languageEnglish
Title of host publicationProceedings of the 10th International Conference on Information Processing and Management of Uncertainty in Knowledge Based Systems (IPMU'2006), Proceedings Poster Sessions pp. 56-59, Paris, France, July 2-7
StatePublished - 2006


  • Machine Learning
  • Data Mining
  • The Relevance Vector Machine
  • Working Set


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