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cs.LG2025
An entropy-optimal path to humble AI
Davide Bassetti, Lukáš Pospíšil, Michael Groom +2
Progress of AI has led to very successful, but by no means humble models and tools, especially regarding (i) the huge and further exploding costs and resources they demand, and (ii…
cs.LG2025
Fast, close, non-singular and property-preserving approximations of entropic measures
Illia Horenko, Davide Bassetti, Lukáš Pospíšil
Entropic measures like Shannon entropy (SE), its quantum mechanical analogue von Neumann entropy, and Kullback-Leibler divergence (KL) are key components in many tools used in phys…
cs.LG2023
Gauge-optimal approximate learning for small data classification problems
Edoardo Vecchi, Davide Bassetti, Fabio Graziato +2
Small data learning problems are characterized by a significant discrepancy between the limited amount of response variable observations and the large feature space dimension. In t…