Sebastian Trimpe

We propose tests for general functionals of conditional distributions (including the two-sample test) with finite-sample guarantees and dependent data thanks to generalizations of time-uniform uncertainty bounds for kernel ridge regression.

We introduce BayeSQP, a novel black-box optimization algorithm that combines sequential quadratic programming with Bayesian optimization for high-dimensional constrained problems..