
Robust Certification for Laplace Learning on Geometric Graphs
Graph Laplacian (GL)based semisupervised learning is one of the most u...
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A Linear Transportation L^p Distance for Pattern Recognition
The transportation L^p distance, denoted TL^p, has been proposed as a ge...
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Machine learning for COVID19 detection and prognostication using chest radiographs and CT scans: a systematic methodological review
Background: Machine learning methods offer great potential for fast and ...
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Poisson Learning: Graph Based SemiSupervised Learning At Very Low Label Rates
We propose a new framework, called Poisson learning, for graph based sem...
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Rates of Convergence for Laplacian SemiSupervised Learning with Low Labeling Rates
We study graphbased Laplacian semisupervised learning at low labeling ...
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From graph cuts to isoperimetric inequalities: Convergence rates of Cheeger cuts on data clouds
In this work we study statistical properties of graphbased clustering a...
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PDEInspired Algorithms for SemiSupervised Learning on Point Clouds
Given a data set and a subset of labels the problem of semisupervised l...
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Large Data and Zero Noise Limits of GraphBased SemiSupervised Learning Algorithms
Scalings in which the graph Laplacian approaches a differential operator...
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Analysis of pLaplacian Regularization in SemiSupervised Learning
We investigate a family of regression problems in a semisupervised sett...
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A Transportation L^p Distance for Signal Analysis
Transport based distances, such as the Wasserstein distance and earth mo...
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Transportbased analysis, modeling, and learning from signal and data distributions
Transportbased techniques for signal and data analysis have received in...
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Matthew Thorpe
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