6533b82cfe1ef96bd128fe81

RESEARCH PRODUCT

Scaling Up a Metric Learning Algorithm for Image Recognition and Representation

Francesc J. FerriAdrian Perez-suay

subject

Clustering high-dimensional dataSet (abstract data type)Range (mathematics)LandmarkMetric (mathematics)Landmark pointRepresentation (mathematics)AlgorithmFacial recognition systemMathematics

description

Maximally Collapsing Metric Learning is a recently proposed algorithm to estimate a metric matrix from labelled data. The purpose of this work is to extend this approach by considering a set of landmark points which can in principle reduce the cost per iteration in one order of magnitude. The proposal is in fact a generalized version of the original algorithm that can be applied to larger amounts of higher dimensional data. Exhaustive experimentation shows that very similar behavior at a lower cost is obtained for a wide range of the number of landmark points used.

yearjournalcountryeditionlanguage
2008-01-01
https://doi.org/10.1007/978-3-540-89646-3_58