# Moving Up the Cluster Tree with the Gradient Flow

@inproceedings{AriasCastro2021MovingUT, title={Moving Up the Cluster Tree with the Gradient Flow}, author={Ery Arias-Castro and Wanli Qiao}, year={2021} }

The paper establishes a strong correspondence between two important clustering approaches that emerged in the 1970’s: clustering by level sets or cluster tree as proposed by Hartigan and clustering by gradient lines or gradient flow as proposed by Fukunaga and Hostetler. We do so by showing that we can move up the cluster tree by following the gradient ascent flow.

## One Citation

Fitting a Multi-modal Density by Dynamic Programming

- Computer Science, Mathematics
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A dynamic programming approach to solving the problem of tipping a probability density function when it is constrained to have a given number of modal intervals by providing several data-driven ways for selecting it.

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