In this paper, we develop a novel online algorithm based on the Sequential Monte Carlo (SMC) samplers framework for posterior inference in Dirichlet Process Mixtures (DPM) (DelMor...
Whereas before 2006 it appears that deep multilayer neural networks were not successfully trained, since then several algorithms have been shown to successfully train them, with e...
The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...
Dimensionality reduction is an important pre-processing step in many applications. Linear discriminant analysis (LDA) is a classical statistical approach for supervised dimensiona...
Policy search is a method for approximately solving an optimal control problem by performing a parametric optimization search in a given class of parameterized policies. In order ...