We propose a linear-quadratic (LQ) control problem of streamflow discharge by optimizing
an infinite-dimensional jump-driven stochastic differential equation (SDE). Our SDE is a …

As robotic systems continue to address emerging issues in areas such as logistics, mobility,
manufacturing, and disaster response, it is increasingly important to rapidly generate safe …

Shape constraints, such as non-negativity, monotonicity, convexity or supermodularity, play
a key role in various applications of machine learning and statistics. However, incorporating …

Hilbertian kernel methods and their positive semidefinite kernels have been extensively
used in various fields of applied mathematics and machine learning, owing to their several …

A supremum-of-quadratics representation for a class of extended real valued barrier
functions is developed and applied in the context of solving a continuous time linear …

In this letter, we address the problem of improving the feasible domain of the solution of a
decentralized control framework for coordinating connected and automated vehicles (CAVs) …

It is often said that control and estimation problems are in duality. Recently, in (Aubin-
Frankowski, 2021), we found new reproducing kernels in Linear-Quadratic optimal control …

The Linear Quadratic Regulator (LQR), which is arguably the most classical problem in
control theory, was recently related to kernel methods in [1] for finite dimensional systems …

In this study, we provide an interpretation of the dual differential Riccati equation of Linear-
Quadratic (LQ) optimal control problems. Adopting a novel viewpoint, we show that LQ …

Handling an infinite number of inequality constraints in infinite-dimensional spaces occurs in
many fields, from global optimization to optimal transport. These problems have been …