3 papers
cs.LG2025
Scalable Decision Focused Learning via Online Trainable Surrogates
Gaetano Signorelli, Michele Lombardi
Decision support systems often rely on solving complex optimization problems that may require to estimate uncertain parameters beforehand. Recent studies have shown how using tradi…
cs.LG2025
Interlocking-free Selective Rationalization Through Genetic-based Learning
Federico Ruggeri, Gaetano Signorelli
A popular end-to-end architecture for selective rationalization is the select-then-predict pipeline, comprising a generator to extract highlights fed to a predictor. Such a coopera…
cs.LG2025
Constrained Machine Learning Through Hyperspherical Representation
Gaetano Signorelli, Michele Lombardi
The problem of ensuring constraints satisfaction on the output of machine learning models is critical for many applications, especially in safety-critical domains. Modern approache…