Web: http://arxiv.org/abs/2110.09455

June 16, 2022, 1:11 a.m. | Yannis Kalantidis, Carlos Lassance, Jon Almazan, Diane Larlus

cs.LG updates on arXiv.org arxiv.org

Dimensionality reduction methods are unsupervised approaches which learn
low-dimensional spaces where some properties of the initial space, typically
the notion of "neighborhood", are preserved. Such methods usually require
propagation on large k-NN graphs or complicated optimization solvers. On the
other hand, self-supervised learning approaches, typically used to learn
representations from scratch, rely on simple and more scalable frameworks for
learning. In this paper, we propose TLDR, a dimensionality reduction method for
generic input spaces that is porting the recent self-supervised …

arxiv cv dimensionality learning

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