Learning Sparse Additive Models with Interactions in High Dimensions
نویسندگان
چکیده
A function f : R → R is referred to as a SparseAdditive Model (SPAM), if it is of the formf(x) =∑l∈S φl(xl), where S ⊂ [d], |S| d.Assuming φl’s and S to be unknown, the prob-lem of estimating f from its samples has beenstudied extensively. In this work, we consider ageneralized SPAM, allowing for second order in-teraction terms. For someS1 ⊂ [d],S2 ⊂([d]2),the function f is assumed to be of the form:
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تاریخ انتشار 2016