Manifolds of Shape via Gaussian Process Latent Variable Models
Professor Andrea Sgarro, University of Trieste
Abstract: Back in 1967 the Croat linguist. Muljacic had used a fuzzy generalization of the Hamming distance between binary strings to classify Romance languages. In 1956 Cl. Shannon had introduced the notion of codeword distinguishability in zero-error information theory. Distance and distinguishability are subtly different notions, even if, with distances as those usually met in coding theory (with the exception of zero-error information theory, which is definitely non-metric), the need for string distinguishabilities evaporates, since the distinguishability turns out to be an obvious and trivial function of the distance. Fuzzy Hamming distinguishabilities derived from Muljacic distances, instead, are not that trivial, and must be considered explicitly. They are quite easy to compute, however, and we show how they could be applied in coding theory to channels with erasures and blurs. The new tool of fuzzy Hamming distinguishability appears to be quite promising to extend Muljacic approach from linguistic classification to linguistic evolution.
Bio: Andrea Sgarro is full professor of Theoretical Computer Science at the University of Trieste. His research interests include information theory and codes, cryptography, bioinformatics, soft computing, management of incomplete knowledge and computational linguistics. He is responsible for the scientific section of the Circolo della Cultura e delle Arti of Trieste, and is quite active in scientific communication: his books Secret Codes, Mondadori, and Cryptography, Muzzio, for the first time have introduced cryptology to an Italian-speaking audience. In his free time he enjoys languages, of which he speaks a dozen with varying degrees of competence, and plays the one-keyed transverse baroque flute.