We present an algorithm for finding an ssparse vector x that minimizes the squareerror y - x 2 where satisfies the restricted isometry property (RIP), with isometric constant 2s ...
Large margin learning of Continuous Density HMMs with a partially labeled dataset has been extensively studied in the speech and handwriting recognition fields. Yet due to the non...
In the paper we propose a new type of regularization procedure for training sparse Bayesian methods for classification. Transforming Hessian matrix of log-likelihood function to d...
We present an efficient method for maximizing energy functions with first and second order potentials, suitable for MAP labeling estimation problems that arise in undirected graph...
We present a novel algorithm for computing a training set consistent subset for the nearest neighbor decision rule. The algorithm, called FCNN rule, has some desirable properties....