We consider the problem of labeling a partially labeled graph. This setting may arise in a number of situations from survey sampling to information retrieval to pattern recognition...
We describe and demonstrate an algorithm that takes as input an unorganized set of points fx1; : : : ; xng IR3 on or near an unknown manifold M, and produces as output a simplicia...
Hugues Hoppe, Tony DeRose, Tom Duchamp, John Alan ...
This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...
Dimensionality reduction is a much-studied task in machine learning in which high-dimensional data is mapped, possibly via a non-linear transformation, onto a low-dimensional mani...
We propose a framework to extend Markov random walks (Szummer and Jaakkola, 2001) to a continuum of points. In this framework, the transition probability between two points is the...