: This paper addresses the sparse data problem in the linear regression model, namely the number of variables is significantly larger than the number of the data points for regress...
We consider the problem of correcting the posterior marginal approximations computed by expectation propagation and Laplace approximation in latent Gaussian models and propose cor...
We present an approach to high-level shape editing that adapts the structure of the shape while maintaining its global characteristics. Our main contribution is a new algebraic mo...
Martin Bokeloh, Michael Wand, Hans-Peter Seidel, V...
Recent successful techniques for the efficient simulation of largescale interconnect models rely on the sparsification of the inverse of the inductance matrix L. While there are...
Hong Li, Venkataramanan Balakrishnan, Cheng-Kok Ko...
The success of NASA’s Mars Exploration Rovers has demonstrated the important benefits that mobility adds to planetary exploration. Very soon, mission requirements will impose t...
Ioannis M. Rekleitis, Jean-Luc Bedwani, Sebastien ...