Online Learning of Non-stationary Sequences
We consider an online learning scenario in which the learner can make predictions on the basis of a fixed set of experts. The performance of each expert may change over time in a manner unknown to the learner. We formulate a class of universal learning algorithms for this problem by expressing them...
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| Language: | en_US |
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2004
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| Online Access: | http://hdl.handle.net/1721.1/7107 |