Piecewise-Linear Manifolds for Deep Metric Learning

arXiv:2403.14977v1 Announce Type: cross
Abstract: Unsupervised deep metric learning (UDML) focuses on learning a semantic representation space using only unlabeled data. This challenging problem requires accurately estimating the similarity between data points, which is used to supervise a deep network. For this purpose, we propose to model the high-dimensional data manifold using a piecewise-linear approximation, with each low-dimensional linear piece approximating the data manifold in a small neighborhood of a point. These neighborhoods are used to estimate similarity between data …

abstract arxiv cs.ai cs.cv cs.lg data eess.iv linear manifold network representation semantic space type unsupervised