A Distance Metric Learning Model Based On Variational Information Bottleneck

arXiv:2403.02794v1 Announce Type: cross
Abstract: In recent years, personalized recommendation technology has flourished and become one of the hot research directions. The matrix factorization model and the metric learning model which proposed successively have been widely studied and applied. The latter uses the Euclidean distance instead of the dot product used by the former to measure the latent space vector. While avoiding the shortcomings of the dot product, the assumption of Euclidean distance is neglected, resulting in limited recommendation quality …

abstract arxiv become cs.ai cs.ir cs.lg factorization hot information matrix personalized product recommendation research technology the matrix type