Mathematical Advances in Manifold Learning
نویسنده
چکیده
Manifold learning has recently gained a lot of interest by machine learning practitioners. Here we provide a mathematically rigorous treatment of some of the techniques in unsupervised learning in context of manifolds. We will study the problems of dimension reduction and density estimation and present some recent results in terms of fast convergence rates when the data lie on a manifold.
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تاریخ انتشار 2008