3 papers
cs.LG2026
Learning Conditional Averages
Marco Bressan, Nataly Brukhim, Nicolo Cesa-Bianchi +4
We introduce the problem of learning conditional averages in the PAC framework. The learner receives a sample labeled by an unknown target concept from a known concept class, as in…
cs.LG2025
Efficient Algorithms for Learning and Compressing Monophonic Halfspaces in Graphs
Marco Bressan, Victor Chepoi, Emmanuel Esposito +1
Abstract notions of convexity over the vertices of a graph, and corresponding notions of halfspaces, have recently gained attention from the machine learning community. In this wor…
cs.LG2024
Of Dice and Games: A Theory of Generalized Boosting
Marco Bressan, Nataly Brukhim, Nicolò Cesa-Bianchi +4
Cost-sensitive loss functions are crucial in many real-world prediction problems, where different types of errors are penalized differently; for example, in medical diagnosis, a fa…