5 papers
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…
EM++: A parameter learning framework for stochastic switching systems
Renzi Wang, Alexander Bodard, Mathijs Schuurmans +1
This paper proposes a general switching dynamical system model, and a custom majorization-minimization-based algorithm EM++ for identifying its parameters. For certain families of…
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…
Risk-Sensitive Model Predictive Control for Interaction-Aware Planning -- A Sequential Convexification Algorithm
Renzi Wang, Mathijs Schuurmans, Panagiotis Patrinos
This paper considers risk-sensitive model predictive control for stochastic systems with a decision-dependent distribution. This class of systems is commonly found in human-robot i…
Optimal Intraday Power Trading for Single-Price Balancing Markets: An Adaptive Risk-Averse Strategy using Mixture Models
Robin Bruneel, Mathijs Schuurmans, Panagiotis Patrinos
Efficient markets are characterised by profit-driven participants continuously refining their positions towards the latest insights. Margins for profit generation are generally sma…