Publication

Modifier-adaptation methodology for real-time optimization

Publications associées (424)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Adaptation in Stochastic Algorithms: From Nonsmooth Optimization to Min-Max Problems and Beyond

Ahmet Alacaoglu

Stochastic gradient descent (SGD) and randomized coordinate descent (RCD) are two of the workhorses for training modern automated decision systems. Intriguingly, convergence properties of these methods are not well-established as we move away from the spec ...

EPFL2021

ON THE DESIGN AND OPTIMIZATION OF WIDE ANGLE DIFFRACTIVE OPTICAL ELEMENTS

Dong Cheon Kim

Diffractive optical elements (DOEs) which consist of microstructure surface relief permit the generation of the spatial distribution of light beams by using a single element. Due to their compact size, design flexibility, and mass productivity, they are us ...

EPFL2021

Geometric optimization of dielectric elastomer electrodes for dynamic applications

Herbert Shea, Bekir Aksoy, Emil Yan Garnell

Dielectric elastomers are soft actuators, made of an elastomer membrane sandwiched by compliant electrodes. Because of their high energy density and quick response, they are well suited for dynamic applications such as loudspeakers. Thanks to progress in t ...

ELSEVIER SCI LTD2021

Algebraic and Boolean Optimization Methods for AQFP Superconducting Circuits

Giovanni De Micheli, Eleonora Testa, Heinz Riener, Siang-Yun Lee

Adiabatic quantum-flux-parametron (AQFP) circuits are a family of superconducting electronic (SCE) circuits that have recently gained growing interest due to their low-energy consumption, and may serve as alternative technology to overcome the down-scalin ...

Association for Computing Machinery2021

Turning PathFinder Upside -Down: 1-4,xploring FPGA Switch -Blocks by Negotiating Switch Presence

Paolo Ienne, Stefan Nikolic

Automated switch-block exploration gains in importance as technology scaling brings more emphasis on the physical constraints, making it insufficient to rely on abstract measures of routability alone. In this work, we take an approach that significantly di ...

IEEE COMPUTER SOC2021

The role of PDE-based parameterization techniques in gradient-based IGA shape optimization applications

This paper proposes a shape optimization algorithm based on the principles of Isogeometric Analysis (IGA) in which the parameterization of the geometry enters the problem formulation as an additional PDE-constraint. Inspired by the isoparametric principle ...

2021

Convergence of adaptive algorithms for constrained weakly convex optimization

Volkan Cevher, Ahmet Alacaoglu, Yurii Malitskyi

We analyze the adaptive first order algorithm AMSGrad, for solving a constrained stochastic optimization problem with a weakly convex objective. We prove the

\tilde O(t^{-1/2})

rate of convergence for the squared norm of the gradient of Moreau envelope, ...

2021

Modifier Adaptation as a Feedback Control Scheme

Dominique Bonvin, Alejandro Gabriel Marchetti, Sean Costello

As a real-time optimization technique, modifier adaptation (MA) has gained much significance in recent years. This is mainly due to the fact that MA can deal explicitly with structural plant-model mismatch and unknown disturbances. MA is an iterative techn ...

AMER CHEMICAL SOC2020

Real-time optimization of load sharing for gas compressors in the presence of uncertainty

Dominique Bonvin, Timm Faulwasser, Alejandro Gabriel Marchetti, Predrag Milosavljevic

This paper investigates the problem of load-sharing optimization of gas compressors in the presence of uncertainty. The objective is to operate a set of compressor units in an energy-efficient way, while at the same time meeting a varying load demand. The ...

ELSEVIER SCI LTD2020

Estimation of discrete choice models with hybrid stochastic adaptive batch size algorithms

Michel Bierlaire, Timothy Michael Hillel, Virginie Janine Camille Lurkin, Gael Lederrey

The emergence of Big Data has enabled new research perspectives in the discrete choice community. While the techniques to estimate Machine Learning models on a massive amount of data are well established, these have not yet been fully explored for the esti ...

2020

Convergence of adaptive algorithms for constrained weakly convex optimization

Volkan Cevher, Ahmet Alacaoglu, Yurii Malitskyi

We analyze the adaptive first order algorithm AMSGrad, for solving a constrained stochastic optimization problem with a weakly convex objective. We prove the

\tilde O(t^{-1/2})

rate of convergence for the squared norm of the gradient of Moreau envelope, ...

2021