3 papers
cs.LG2026
Generalization of Gibbs and Langevin Monte Carlo Algorithms in the Interpolation Regime
Andreas Maurer, Erfan Mirzaei, Massimiliano Pontil
This paper provides data-dependent bounds on the expected error of the Gibbs algorithm in the overparameterized interpolation regime, where low training errors are also obtained fo…
cs.LG2025
Generalization of the Gibbs algorithm with high probability at low temperatures
Andreas Maurer
The paper gives a bound on the generalization error of the Gibbs algorithm, which recovers known data-independent bounds for the high temperature range and extends to the low-tempe…
cs.LG2024
Generalization of Hamiltonian algorithms
Andreas Maurer
The paper proves generalization results for a class of stochastic learning algorithms. The method applies whenever the algorithm generates an absolutely continuous distribution rel…