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Showing 1 to 2 of 2 for “"Diverse Subset Selection"”.
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Representation learning for non-sequential data
… First, we formulate a new method for performing diverse subset selection using a neural set function approximation method. This method relies on the deep sets idea, which says that any set function s(X) has a universal approximator of the form f([sigma]x[xi]X [phi](x)). Second, we design a new …
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Scalable Inference Algorithms for Determinantal Point Processes
… (DPPs) are probability distributions on subsets of a collection of points that tend to generate diverse configurations of points. This feature makes them suitable as a probabilistic model of diversity. Recently this idea has been exploited extensively in subset selection problems, where …