Collaborative Ranking for Local Preferences Supplement
نویسندگان
چکیده
We assume that the hypothesis class is based on the set of low-rank matrices. Given a low-rank matrix M , let gM ∈ F be the associated hypothesis, where gM (u, i) = Mu,i. Throughout the paper, we abuse notation and use gM and M interchangeably. We assume that data is generated with respect to D, which is an unknown probability distribution over the sample space X , and we let E denote expectation. Then, the generalization error of hypothesis M is E (u,C,i)∼D LM (u,C, i), which is the quantity we bound
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تاریخ انتشار 2014