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Normalized Online Learning     Normalized  Online Learning       2013/6/17
We introduce online learning algorithms which are independent of feature scales, proving regret bounds dependent on the ratio of scales existent in the data rather than the absolute scale. This has se...
In an online contract selection problem there is a seller which offers a set of contracts to sequentially arriving buyers whose types are drawn from an unknown distribution. If there exists a profitab...
We present methods for online linear optimization that take advantage of benign (as opposed to worst-case) sequences. Speci cally if the sequence encountered by the learner is described well by a know...

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