We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...
In this paper, we address the problem of database selection for XML document collections, that is, given a set of collections and a user query, how to rank the collections based o...
Abstract. Trained support vector machines (SVMs) have a slow runtime classification speed if the classification problem is noisy and the sample data set is large. Approximating the...
—In this paper we look at the problem of accurately reconstructing distributed signals through the collection of a small number of samples at a data gathering point. The techniqu...
Riccardo Masiero, Giorgio Quer, Daniele Munaretto,...
We consider approximate pattern matching in natural language text. We use the words of the text as the alphabet, instead of the characters as in traditional string matching approac...