14 citations · 15 across the 3 of their papers we have counts for
3 papers
Seeing is Believing: Belief-Space Planning with Foundation Models as Uncertainty Estimators
Linfeng Zhao, Willie McClinton, Aidan Curtis +4
Generalizable robotic mobile manipulation in open-world environments poses significant challenges due to long horizons, complex goals, and partial observability. A promising approa…
Functional Risk Minimization
Ferran Alet, Clement Gehring, Tomás Lozano-Pérez +3
The field of Machine Learning has changed significantly since the 1970s. However, its most basic principle, Empirical Risk Minimization (ERM), remains unchanged. We propose Functio…
Generalization in Machine Learning via Analytical Learning Theory
Kenji Kawaguchi, Yoshua Bengio, Vikas Verma +1
This paper introduces a novel measure-theoretic theory for machine learning that does not require statistical assumptions. Based on this theory, a new regularization method in deep…