Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...
We initiate a new line of investigation into online property-preserving data reconstruction. Consider a dataset which is assumed to satisfy various (known) structural properties; e...
Nir Ailon, Bernard Chazelle, Seshadhri Comandur, D...
We propose a general method for estimating the distance between a compact subspace K of the space L1 ([0, 1]s ) of Lebesgue measurable functions defined on the hypercube [0, 1]s ,...
Background: The importance of stochasticity in cellular processes having low number of molecules has resulted in the development of stochastic models such as chemical master equat...
This paper investigates the use of Euclidean invariant features in a generalization of iterative closest point registration of range images. Pointwisecorrespondences are chosen as...