Baptiste Abélès

Online-to-PAC generalization bounds under graph-mixing dependencies

Traditional generalization results in statistical learning require a training data set made of independently drawn examples. Most of the recent efforts to relax this independence assumption have considered either purely temporal (mixing) dependencies, or graph-dependencies, where non-adjacent vertic…