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The derivatives of the SEDS optimization cost function and constraints with respect to the learning parameters

Related publications (40)

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Disparity and Optical Flow Partitioning Using Extended Potts Priors

Martin Kurt Storath

This paper addresses the problems of disparity and optical flow partitioning based on the brightness invariance assumption. We investigate new variational approaches to these problems with Potts priors and possibly box constraints. For the optical flow par ...

IMA2015

Rotor Design Optimization for a Reaction Sphere Actuator

Yves Perriard, Leopoldo Rossini

This paper presents the rotor design optimization for a reaction sphere (RS) actuator. The RS is a permanent-magnet synchronous spherical actuator whose rotor is magnetically levitated and can be accelerated about any desired axis. The RS is composed of an ...

Institute of Electrical and Electronics Engineers2014

Statistical analysis of optimal energy and security controls under different sources of uncertainties

Mokhtar Bozorg, Omid Alizadeh Mousavi

The management of uncertainties is a challenging task for reliable and secure operation of power systems. The uncertainties come from multiple sources, including the forecast errors of wind power and load, the forced outage of generating units, loss of tra ...

IEEE2014

Equivalence between Neighboring-Extremal Control and Self-Optimizing Control for the Steady-State Optimization of Dynamical Systems

Dominique Bonvin, Grégory François

The problem of steering a dynamical system toward optimal steady-state performance is considered. For this purpose, a static optimization problem can be formulated and solved. However, because of uncertainty, the optimal steady-state inputs can rarely be a ...

American Chemical Society2014

Extended Reverse Convex Programming: An Active-Set Approach to Global Optimization

Gene Bunin

Reverse convex programming (RCP) represents an important class of global optimization problems consisting of concave cost and inequality constraint functions. While useful in many practical scenarios due to the frequent appearance of concave models, a more ...

Springer Verlag2013

Model Adequacy for Real-Time Optimization

Dominique Bonvin

Optimization is important in science and engineering as a way of finding ”optimal” situations, designs or operating conditions. Optimization is typically performed on the basis of a mathematical model of the process under investigation. In practice, optimi ...

2012

Real-Time Optimization in the Presence of Uncertainty

Dominique Bonvin

This presentation discusses real-time optimization (RTO) strategies for improving process performance in the presence of uncertainty in the form of plant-model mismatch, drifts and disturbances. RTO typically uses a plant model to compute optimal inputs. I ...

2012

Energy system design under uncertainty

Matthias Dubuis

The current context leads energy system design to very demanding objectives, due to their variety. Indeed, despite an increasing energy demand, environment indicators are becoming always more important. So that for a given service, emission (and then assoc ...

EPFL2012

Numerical Simulation and Optimization of the Alumina Distribution in an Aluminium Electrolysis Pot

Thomas Hofer

This thesis is about the numerical simulation and optimization of the alumina repartition in the bath of an aluminium electrolysis pot. A mathematical model is set up which contains the feeding of alumina particles to the bath, the dissolution of the parti ...

EPFL2011

Real-Time Optimization  in the Presence of Uncertainty

Dominique Bonvin

2011