An approach to build a multi-class classifier is proposed in this paper. This approach consists of a derivation to show under which loss function an optimal classifier can be obtai...
Abstract. The protein family classification problem, which consists of determining the family memberships of given unknown protein sequences, is very important for a biologist for ...
We describe a novel inference algorithm for sparse Bayesian PCA with a zero-norm prior on the model parameters. Bayesian inference is very challenging in probabilistic models of t...
Recently popularized randomized methods for principal component analysis (PCA) efficiently and reliably produce nearly optimal accuracy -- even on parallel processors -- unlike the...
We introduce a semi-supervised learning estimator which tends to the first kernel principal component as the number of labeled points vanishes. We show application of the proposed...
Leonardo Angelini, Daniele Marinazzo, Mario Pellic...