Minimal regret state estimation of time-varying systems

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Minimal regret state estimation of time-varying systems

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Integer Linear Programming for Unsupervised Training Set Selection in Molecular Machine Learning

First and Zeroth-Order Implementations of the Regularized Newton Method with Lazy Approximated Hessians

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Estimation and control under uncertainty with application to power systems

Distributed Adaptive Learning Under Communication Constraints

A Continuous-Domain Solution for Computed Tomography with Hessian Total-Variation Regularization

OASIS: Optimisation-based Activity Scheduling with Integrated Simultaneous choice dimensions

Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraints

Learning of Continuous and Piecewise-Linear Functions With Hessian Total-Variation Regularization

Experimental data-driven model predictive control of a hospital HVAC system during regular use