Nonnegative Matrix Factorization with the β-Divergence”
نویسندگان
چکیده
The equivalence can be formalized as follows: For a particular c in (21), there is a corresponding δ > 0 in the optimization in (A-1). We focus on `1-ARD where f(x) = ‖x‖1. Then the objective is concave in H. One natural way to solve (A-1) iteratively is to use an MM procedure by upper bounding the objective function with its tangent (first-order Taylor expansion) at the current iterate H. This yields the following convex program
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تاریخ انتشار 2012