Low-rank geometric mean metric learning

Mukul Bhutani; Pratik Jawanpuria; Hiroyuki Kasai; Bamdev Mishra

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arXiv · 1806.05454

Low-rank geometric mean metric learning

Mukul Bhutani·Pratik Jawanpuria·Hiroyuki Kasai·Bamdev Mishra

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Abstract

We propose a low-rank approach to learning a Mahalanobis metric from data. Inspired by the recent geometric mean metric learning (GMML) algorithm, we propose a low-rank variant of the algorithm. This allows to jointly learn a low-dimensional subspace where the data reside and the Mahalanobis metric that appropriately fits the data. Our results show that we compete effectively with GMML at lower ranks.

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Mukul Bhutani, Pratik Jawanpuria, Hiroyuki Kasai, Bamdev Mishra. 2018-06-14. Low-rank geometric mean metric learning. https://arxiv.org/abs/1806.05454

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