29 citations · 79 across the 18 of their papers we have counts for
4 papers · 1 filter
A Linear Transportation Distance for Pattern Recognition
Oliver M. Crook, Mihai Cucuringu, Tim Hurst +3
The transportation distance, denoted , has been proposed as a generalisation of Wasserstein distances motivated by the property that it…
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…
Poisson Learning: Graph Based Semi-Supervised Learning At Very Low Label Rates
Jeff Calder, Brendan Cook, Matthew Thorpe +1
We propose a new framework, called Poisson learning, for graph based semi-supervised learning at very low label rates. Poisson learning is motivated by the need to address the dege…
From graph cuts to isoperimetric inequalities: Convergence rates of Cheeger cuts on data clouds
Nicolas Garcia Trillos, Ryan Murray, Matthew Thorpe
In this work we study statistical properties of graph-based clustering algorithms that rely on the optimization of balanced graph cuts, the main example being the optimization of C…