activity
20172021
most citedPoisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates

29 citations · 45 across the 5 of their papers we have counts for

collaborators
Showing math.STShow all

2 papers · 1 filter

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.ST2017

Analysis of -Laplacian Regularization in Semi-Supervised Learning

Dejan Slepčev, Matthew Thorpe

We investigate a family of regression problems in a semi-supervised setting. The task is to assign real-valued labels to a set of sample points, provided a small training subse…