On the Use of Second-Order Modifiers for Real-Time Optimization

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This paper proposes a Control by Interconnection design, for a class of constrained Port-Hamiltonian systems, which is based on an associated Model Predictive Control optimization problem. This associated optimization problem allows to consider both state ...

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One of the main goal of Artificial Intelligence is to develop models capable of providing valuable predictions in real-world environments. In particular, Machine Learning (ML) seeks to design such models by learning from examples coming from this same envi ...

Despite the high number of investments for data-based models in the expansion of Industry 4.0, too little effort has been made to ensure the maintenance of those models. In a data-streaming environment, data-based models are subject to concept drifts. A co ...

We consider the problem of provably finding a stationary point of a smooth function to be minimized on the variety of bounded-rank matrices. This turns out to be unexpectedly delicate. We trace the difficulty back to a geometric obstacle: On a nonsmooth se ...

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On the Use of Second-Order Modifiers for Real-Time Optimization

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A combined Control by Interconnection—Model Predictive Control design for constrained Port-Hamiltonian systems

Level-set-based Shape Optimization on Soft Magnetic Composites with Isotropy Constraint

Unmoderated molten salt reactors design optimisation for power stability

Predicting in Uncertain Environments: Methods for Robust Machine Learning

Data-based model maintenance in the era of industry 4.0: A methodology

Finding stationary points on bounded-rank matrices: a geometric hurdle and a smooth remedy

Dual Approach for Two-Stage Robust Nonlinear Optimization

Enhanced Solar-to-Fuel Efficiency of Ceria-Based Thermochemical Cycles via Integrated Electrochemical Oxygen Pumping

Construction of Fe3O4 bridged Pt/g-C3N4 heterostructure with enhanced solar to fuel conversion

Material removing tool and method for designing the same

Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems

Large-scale traffic signal control and multimodal network design

Towards Understanding Sharpness-Aware Minimization

Memory of Motion for Initializing Optimization in Robotics

On the advantages of P2P ML on mobile devices

Vehicle-to-Grid for Reliable Frequency Regulation