Maximum entropy inference and facial attractiveness

by Dr Miguel Ibàñez Berganza (Sapienza Università di Roma)

Monday 7 May 2018, 14:30 → 15:30 Europe/Rome

Aula 3 (Dipartimento di Fisica - Ed. E.Fermi)

Facial attractiveness has recently been subject of an intense research in the machine learning community, as a prototype of a cognitive phenomenon ruled by a complex set of "rules" difficult to infer. Most of the work so far is based on the supervised inference of (subject-averaged) numerical ratings assigned to natural facial images. We present a novel approach based on the unsupervised (maximum entropy) learning of different subject's preferences in the face-space. Interesting theoretical problems emerge in within this approach, as the maximum entropy inference of data with a-priori correlations and constraints, or the Bayesian model selection between different maximum entropy models...