Top-k lists: Models and Algorithms
neural information processing systems(2018)
摘要
The classic Mallows model is a widely-used tool to realize distributions on permutations. Motivated by common practical situations, in this paper, we generalize Mallows to model distributions on topk lists by using a suitable distance measure between topk lists. Unlike many earlier work, our model is both analytically tractable and computationally efficient. We demonstrate this by studying two basic problems in this model, namely, sampling and reconstruction, from both algorithmic and practical points of view.
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