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Model Adequacy for Real-Time Optimization

Publications associées (296)

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Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning

Jie Luo

Many state-of-the-art approaches for Multi Kernel Learning (MKL) struggle at finding a compromise between performance, sparsity of the solution and speed of the optimization process. In this paper we look at the MKL problem at the same time from a learning ...

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Modifier Adaptation for Run-to-Run Optimization of Transient Processes

Dominique Bonvin, Grégory François, Sean Costello

Dynamic optimization can be used to determine optimal input profiles for dynamic processes. Due to plant-model mismatch and disturbances, the optimal inputs determined through model-based optimization will, in general, not be optimal for the plant. Modifie ...

2011

Free Form Deformation Techniques for 3D Shape Optimization Problems

Anwar Koshakji

The purpose of this work is to analyse and study an efficient parametrization technique for a 3D shape optimization problem. After a brief review of the techniques and approaches already available in literature, we choose to use the Free Form Deformation p ...

2011

Browsing Catalogue Graphs: Content Caching Supercharged!!

We consider a generic scenario of content browsing where a client is presented with a catalogue of items of interest. Upon the selection of an item from a page of the catalogue, the client can choose the next item to browse from a list of related items pre ...

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Analysis of the economic criteria used in energy efficiency optimization of industrial systems

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A previous study, of Wenk, 2011, showed, in the case of a simple heat exchanger model, inconsistencies between optimization results with different investment decision criteria. As a result, a deep analysis of the state of the art in financial decision maki ...

2011

Distributed Constraint Optimization under Stochastic Uncertainty

Boi Faltings, Thomas Léauté

In many real-life optimization problems involving multiple agents, the rewards are not necessarily known exactly in advance, but rather depend on sources of exogenous uncertainty. For instance, delivery companies might have to coordinate to choose who shou ...

2011

Uncertainty Feature Optimization: an implicit paradigm for problems with noisy data

Michel Bierlaire, Matteo Salani, Niklaus Eggenberg

Optimization problems with noisy data solved using stochastic programming or robust optimization approaches require the explicit characterization of an uncertainty set U that models the nature of the noise. Such approaches depend on the modeling of the unc ...

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Multi-objective optimization of regenerator placement using Constraint Programming

Sébastien Rumley, Christian Gaumier

In translucent optical networks, connections bypass most intermediate nodes transparently. However, their signal quality is affected by the traveled distance and/or the bypass operations. Hence, they might require optical-electrical-optical conversions at ...

2011

On Variable Density Compressive Sampling

Pierre Vandergheynst, Yves Wiaux, Gilles Puy

We advocate an optimization procedure for variable density sampling in the context of compressed sensing. In this perspective, we introduce a minimization problem for the coherence between the sparsity and sensing bases, whose solution provides an optimize ...

Institute of Electrical and Electronics Engineers2011

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Michaël Unser, Philippe Thévenaz, Ricard Delgado Gonzalo

We propose an active contour (a.k.a. snake) that takes the shape of an ellipse. Its evolution is driven by surface terms made of two contributions: the integral of the data over an inner ellipse, counterbalanced by the integral of the data over an outer el ...

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