Adaptive Online Prediction Using Weighted Windows
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概要
- 論文の詳細を見る
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.
- （社）電子情報通信学会の論文
- 2011-10-01
著者
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Takimoto Eiji
Department Of Informatics Kyushu University
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Takeda Masayuki
Department Of Biochemistry And Engineering Faculty Of Engineering Tohoku University
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Yoshida Shin-ichi
Ntt West
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HATANO Kohei
Department of Informatics, Kyushu University
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Hatano Kohei
Department Of Informatics Kyushu University
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