3 citations · 4 across the 5 of their papers we have counts for
5 papers
Manifold learning: what, how, and why
Marina Meilă, Hanyu Zhang
Manifold learning (ML), known also as non-linear dimension reduction, is a set of methods to find the low dimensional structure of data. Dimension reduction for large, high dimensi…
Dictionary-based Manifold Learning
Hanyu Zhang, Samson Koelle, Marina Meila
We propose a paradigm for interpretable Manifold Learning for scientific data analysis, whereby we parametrize a manifold with smooth functions from a scientist-provided dictio…
The Parametric Stability of Well-separated Spherical Gaussian Mixtures
Hanyu Zhang, Marina Meila
We quantify the parameter stability of a spherical Gaussian Mixture Model (sGMM) under small perturbations in distribution space. Namely, we derive the first explicit bound to show…
Distribution free optimality intervals for clustering
Marina Meilă, Hanyu Zhang
We address the problem of validating the ouput of clustering algorithms. Given data and a partition of these data into clusters, when can we say tha…
Manifold Coordinates with Physical Meaning
Samson Koelle, Hanyu Zhang, Marina Meila +1
Manifold embedding algorithms map high-dimensional data down to coordinates in a much lower-dimensional space. One of the aims of dimension reduction is to find intrinsic coordinat…