LADE Seminar

Romina Wild (SISSA)

Title: Selecting and weighting informative features automatically with Differentiable Information Imbalance


Feature selection is a common practice in many applications and tends to come with attached uncertainties such as: What is the best dimensionality of a reduced feature space in order to retain maximum information? How can one correct for different units of measure? What is the optimal relative scaling of importance between features? To solve these questions, we extend Information Imbalance, an effective statistic to rank information content between feature spaces, to its differentiable form. This Differentiable Information Imbalance is used as a loss function to optimize relative feature weights, simultaneously per- forming unit alignment and relative importance scaling. The same method can generate sparse solutions. The optimal size of a reduced space is conveniently found by considering the change in the Differentiable Information Imbalance as a function of the number of non-zero features.

Apr 17, 2024 11:30 AM — 12:30 PM
LADE Seminar
Sala Riunioni RIT, Area Science Park
Località Padriciano 99, Trieste, 34149
Area Science Park - RIT
Area Science Park - RIT
Research Institute

The Institute of Research and Innovation Technology (RIT) at Area Science Park carries out cutting-edge research and provides services and consulting to public and private-sector users through its three laboratories equipped with state-of-the-art technology.