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

A Primal-Dual Reconstruction Algorithm for Fluorescence and Bioluminescence Tomography

We introduce a new primal-dual reconstruction algorithm for fluorescence and bioluminescence tomography. As often in optical tomography, image reconstruction is performed by optimizing a multi-term convex cost function. Current reconstruction methods emplo ...

IEEE2011

Comparison of Gradient Estimation Methods for Real-time Optimization

Dominique Bonvin, Grégory François

Various real-time optimization techniques proceed by controlling the gradient to zero. These methods primarily differ in the way the gradient is estimated. This paper compares various gradient estimation methods. It is argued that methods with model-based ...

Elsevier2011

Simultaneous Point Matching and 3D Deformable Surface Reconstruction

Pascal Fua, Appu Shaji, Aydin Varol

It has been shown that the 3D shape of a deformable surface in an image can be recovered by establishing correspondences between that image and a reference one in which the shape is known. These matches can then be used to set-up a convex optimization prob ...

Ieee Computer Soc Press, Customer Service Center, Po Box 3014, 10662 Los Vaqueros Circle, Los Alamitos, Ca 90720-1264 Usa2010

An Optimal Algorithm for Reconstructing Images from Binary Measurements

Martin Vetterli, Luciano Sbaiz, Yue Lu, Feng Yang

We have studied a camera with a very large number of binary pixels referred to as the gigavision camera or the gigapixel digital film camera. Potential advantages of this new camera design include improved dynamic range, thanks to its logarithmic sensor re ...

2010

An optimal first-order solver for the TV-$L_1$ optical flow problem

Pierre Vandergheynst, Gilles Puy, Emmanuel D'Angelo

In this study, we address the problem of computing efficiently a dense optical flow between two images under a total variation (TV) regularization and an

L_1

norm data fidelity constraint using a variational method. We build upon Nesterov's framework for ...

2010

Design of tensegrity structures using parametric analysis and stochastic search

Ian Smith, Landolf-Giosef-Anastasios Rhode-Barbarigos, Himanshu Jain

Tensegrity structures are lightweight structures composed of cables in tension and struts in compression. Since tensegrity systems exhibit geometrically nonlinear behavior, finding optimal structural designs is difficult. This paper focuses on the use of s ...

Springer Verlag2010

Iterative Learning Control Using Stochastic Approximation Theory with Application to a Mechatronic System

Alireza Karimi, Mark Edward John Butcher

In this paper it is shown how Stochastic Approximation theory can be used to derive and analyse well-known Iterative Learning Control algorithms for linear systems. The Stochastic Approximation theory gives conditions that, when satisfied, ensure almost su ...

Springer2010

Heuristics for Distributed Pseudo-tree Regeneration

Jonas Helfer

The goal of this project is to develop a new heuristic for pseudo-tree regeneration in S-DPOP. S-DPOP is a version of DPOP which should show performance improvements when resolving problems after small changes. Examples of such problems are: tracking movin ...

2010

Geometry-aware analysis of high-dimensional visual information sets

Effrosyni Kokiopoulou

Over the past few decades we have been experiencing a data explosion; massive amounts of data are increasingly collected and multimedia databases, such as YouTube and Flickr, are rapidly expanding. At the same time rapid technological advancements in mobil ...

EPFL2009

Modifier-adaptation methodology for real-time optimization

Alejandro Gabriel Marchetti

The process industries are characterized by a large number of continuously operating plants, for which optimal operation is of economic importance. However, optimal operation is particularly difficult to achieve when the process model used in the optimizat ...

EPFL2009

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

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A Primal-Dual Reconstruction Algorithm for Fluorescence and Bioluminescence Tomography

Comparison of Gradient Estimation Methods for Real-time Optimization

Simultaneous Point Matching and 3D Deformable Surface Reconstruction

An Optimal Algorithm for Reconstructing Images from Binary Measurements

An optimal first-order solver for the TV-$L_1$ optical flow problem

Design of tensegrity structures using parametric analysis and stochastic search

Iterative Learning Control Using Stochastic Approximation Theory with Application to a Mechatronic System

Heuristics for Distributed Pseudo-tree Regeneration

Geometry-aware analysis of high-dimensional visual information sets

Modifier-adaptation methodology for real-time optimization

Modifier-adaptation methodology for real-time optimization

A Primal-Dual Reconstruction Algorithm for Fluorescence and Bioluminescence Tomography

Comparison of Gradient Estimation Methods for Real-time Optimization

Simultaneous Point Matching and 3D Deformable Surface Reconstruction

An Optimal Algorithm for Reconstructing Images from Binary Measurements

Design of tensegrity structures using parametric analysis and stochastic search

An optimal first-order solver for the TV-$L_1$ optical flow problem

Iterative Learning Control Using Stochastic Approximation Theory with Application to a Mechatronic System

Heuristics for Distributed Pseudo-tree Regeneration

Geometry-aware analysis of high-dimensional visual information sets