activity
20162026
most citedEmbedded nonlinear model predictive control for obstacle avoidance using PANOC

100 citations · 114 across the 30 of their papers we have counts for

collaborators

51 papers

math.OC20261 cited

Active learning-based Bayesian optimization in the realm of copper slag-blended cement systems

Debadri Som, Rayna Maheshwari, Mathijs Schuurmans +2

Accelerated mix design optimization is critical for deploying low-carbon supplementary cementitious materials (SCMs) because traditional experimental approaches require extensive t…

math.OC2026

Newton methods beyond Hessian Lipschitz continuity: A nonlinear preconditioning approach

Alexander Bodard, Panagiotis Patrinos

Newton-type methods are typically analyzed under Lipschitz continuity of the Hessian, an assumption that can fail for objectives with higher-order or polynomial growth. We introduc…

math.OC2026

Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives

Konstantinos Oikonomidis, Jan Quan, Kimon Antonakopoulos +3

In this work, we develop proximal preconditioned gradient methods with a focus on spectral gradient methods providing a proximal extension to the Muon and Scion optimizers. We intr…

math.OC2026

Parametric Nonconvex Optimization via Convex Surrogates

Renzi Wang, Panagiotis Patrinos, Alberto Bemporad

This paper presents a novel learning-based approach to construct a surrogate problem that approximates a given parametric nonconvex optimization problem. The surrogate function is…

math.OC2025

Probabilistic Safety under Arbitrary Disturbance Distributions using Piecewise-Affine Control Barrier Functions

Matisse Teuwen, Mathijs Schuurmans, Panagiotis Patrinos

We propose a simple safety filter design for stochastic discrete-time systems based on piecewise affine probabilistic control barrier functions, providing an appealing balance betw…

math.OC2025

Scaled relative graphs for pairs of operators beyond classical monotonicity

Jan Quan, Alexander Bodard, Konstantinos Oikonomidis +1

We introduce a generalization of the scaled relative graph (SRG) to pairs of operators, enabling the visualization of their relative incremental properties. This novel SRG framewor…