This paper deals with the frequency domain properties of an ellipsoidal family of rational functions, i.e. a family of rational functions whose coefficients depend affinely on an ...
Graziano Chesi, Andrea Garulli, Alberto Tesi, Anto...
We consider the problem of learning density mixture models for classification. Traditional learning of mixtures for density estimation focuses on models that correctly represent t...
Template Attacks and the Stochastic Model provide advanced methods for side channel cryptanalysis that make use of `a-priori' knowledge gained from a profiling step. For a sys...
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
We present a novel framework for multi-label learning that explicitly addresses the challenge arising from the large number of classes and a small size of training data. The key a...