We propose a family of learning algorithms based on a new form of regularization that allows us to exploit the geometry of the marginal distribution. We focus on a semi-supervised...
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
We describe a new class of utility-maximization scheduling problem with precedence constraints, the disconnected staged scheduling problem (DSSP). DSSP is a nonpreemptive multipro...
Eric Anderson, Dirk Beyer 0002, Kamalika Chaudhuri...
Optimal path queries are queries to obtain an optimal path specified by a given criterion of optimality. There have been many studies to give efficient algorithms for classes of o...