The problem of minimizing the rank of a matrix subject to linear equality constraints arises in applications in machine learning, dimensionality reduction, and control theory, and...
Given a sample from a probability measure with support on a submanifold in Euclidean space one can construct a neighborhood graph which can be seen as an approximation of the subm...
Matthias Hein, Jean-Yves Audibert, Ulrike von Luxb...
Gaussian fields (GF) have recently received considerable attention for dimension reduction and semi-supervised classification. In this paper we show how the GF framework can be us...
Many clustering algorithms only find one clustering solution. However, data can often be grouped and interpreted in many different ways. This is particularly true in the high-dim...
Abstract-- Motion planning of deformable objects is challenging due to the high degrees-of-freedom inherent in deformation as well as the computational cost of producing physically...