Adaptive online prediction using weighted windows

Shin Ichi Yoshida, Kohei Hatano, Eiji Takimoto, Masayuki Takeda

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


We propose online prediction algorithms for data streams whose characteristics might change over time. Our algorithms are applications of online learning with experts. In particular, our algorithms combine base predictors over sliding windows with different length as experts. As a result, our algorithms are guaranteed to be competitive with the base predictor with the best fixed-length sliding window in hindsight.

Original languageEnglish
Pages (from-to)1917-1923
Number of pages7
JournalIEICE Transactions on Information and Systems
Issue number10
Publication statusPublished - Oct 2011

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence


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