This paper proposes an efficient online method that trains a classifier with many conjunctive features. We employ kernel computation called kernel slicing, which explicitly consid...
Abstract. We show how the “Online Sparse Coding Neural Gas” algorithm can be applied to a more realistic model of the “Cocktail Party Problem”. We consider a setting where ...
The creation of language resources for less-resourced languages like the historical ones benefits from the exploitation of language-independent tools and methods developed over th...
We review the application of statistical mechanics methods to the study of online learning of a drifting concept in the limit of large systems. The model where a feed-forward netwo...
Recently, significant progress has been made on learning structured predictors via coordinated training algorithms such as conditional random fields and maximum margin Markov ne...