Abstract. We study various ensemble methods for hybrid neural networks. The hybrid networks are composed of radial and projection units and are trained using a deterministic algori...
Sparsity-promoting L1-regularization has recently been succesfully used to learn the structure of undirected graphical models. In this paper, we apply this technique to learn the ...
Mark W. Schmidt, Alexandru Niculescu-Mizil, Kevin ...
In conventional tomography, the interior of an object is reconstructed from tomographic projections such as X-ray or electron microscope images. All the current reconstruction met...
Online Convex Programming (OCP) is a recently developed model of sequential decision-making in the presence of time-varying uncertainty. In this framework, a decisionmaker selects ...
Abstract. We present a Bayesian treatment of non-negative matrix factorization (NMF), based on a normal likelihood and exponential priors, and derive an efficient Gibbs sampler to ...