3 papers
cs.IT2026
A Comparative Study of MAP and LMMSE Estimators for Blind Inverse Problems
Nathan Buskulic, Luca Calatroni
Maximum-a-posteriori (MAP) approaches are an effective framework for inverse problems with known forward operators, particularly when combined with expressive priors and careful pa…
cs.LG2025
On the Sample Complexity of Learning for Blind Inverse Problems
Nathan Buskulic, Luca Calatroni, Lorenzo Rosasco +1
Blind inverse problems arise in many experimental settings where both the signal of interest and the forward operator are (partially) unknown. In this context, methods developed fo…
cs.NE2019
Maximizing Drift is Not Optimal for Solving OneMax
Nathan Buskulic, Carola Doerr
It may seem very intuitive that for the maximization of the OneMax problem $\OM(x):=\sum_{i=1}^n{x_i}$ the best that an elitist unary unbiased search algorithm can do is to store a…