Mixture of Gaussians (MoG) model is a useful tool in statistical learning. In many learning processes that are based on mixture models, computational requirements are very demandin...
Jacob Goldberger, Hayit Greenspan, Jeremie Dreyfus...
Although modern control theories have been successfully applied to solve a variety of problems, they are often mathematically and physically too specific to describe and analyze t...
Abstract— The sparsification of the reluctance matrix L−1 (where L denotes the usual inductance matrix L) has been widely used in several recent investigations to make the pro...
Hong Li, Venkataramanan Balakrishnan, Cheng-Kok Ko...
The urban transit routing problem (UTRP) is NP-Hard and involves devising routes for public transport systems. It is a highly complex multiply constrained problem and the evaluati...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...