We study a method of optimal data-driven aggregation of classifiers in a convex combination and establish tight upper bounds on its excess risk with respect to a convex loss funct...
We describe a way of using multiple different types of similarity relationship to learn a low-dimensional embedding of a dataset. Our method chooses different, possibly overlappin...
We present a semi-parametric latent variable model based technique for density modelling, dimensionality reduction and visualization. Unlike previous methods, we estimate the late...
: In this paper, we propose a technique to design Fuzzy Inference Systems (FIS) of Mamdani type with transparency constraints. The technique is based on our Crisp Double Clustering...
Giovanna Castellano, Anna Maria Fanelli, Corrado M...
We introduce a new type of Self-Organizing Map (SOM) to navigate in the Semantic Space of large text collections. We propose a "hyperbolic SOM" (HSOM) based on a regular...