Poster

On the Consistency of Quick Shift

Heinrich Jiang

Keywords: Clustering Learning Theory Unsupervised Learning Density Estimation

2017 Poster

[ Paper]

Abstract

Quick Shift is a popular mode-seeking and clustering algorithm. We present finite sample statistical consistency guarantees for Quick Shift on mode and cluster recovery under mild distributional assumptions. We then apply our results to construct a consistent modal regression algorithm.

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