Model Selection in Exploration

author: John Langford, Microsoft Research
published: Jan. 25, 2012,   recorded: December 2011,   views: 4053


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I will discuss model selection in 4 settings: {Selective Sampling, Partial Feedback} x {Agnostic,Realizable}. In selective sampling, you choose on which examples to acquire a label. In partial feedback, you choose on which label (or action) to discover a reward (or loss). In the agnostic setting, your goal is simply competing a set of predictors. In the realizable setting, one of your predictors is perfect, for varying definitions of perfect.

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