most citedRates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates

4 citations · 4 across the 2 of their papers we have counts for

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2 papers

math.ST2020★ 4 cited

Rates of Convergence for Laplacian Semi-Supervised Learning with Low Labeling Rates

Jeff Calder, Dejan Slepčev, Matthew Thorpe

We study graph-based Laplacian semi-supervised learning at low labeling rates. Laplacian learning uses harmonic extension on a graph to propagate labels. At very low label rates, L…

math.ST2015

Convergence of the -Means Minimization Problem using -Convergence

Matthew Thorpe, Florian Theil, Adam M. Johansen +1

The -means method is an iterative clustering algorithm which associates each observation with one of clusters. It traditionally employs cluster centers in the same space as…