Publications related to Scalable Convex Optimization Methods for Semidefinite Programming

Global Optimization for Image Restoration in Optical/IR Interferometry

Many image reconstruction algorithms have been proposed to cope with optical/IR interferometric data. A first difficulty is to deal with the sparsity of the data and the uneven u-v coverage. This is usually overcome by imposing a priori constraints to the ...

SPIE2016

Parallelizing Query Optimization on Shared-Nothing Architectures

Christoph Koch, Immanuel Trummer

Data processing systems offer an ever increasing degree of parallelism on the levels of cores, CPUs, and processing nodes. Query optimization must exploit high degrees of parallelism in order not to gradually become the bottleneck of query evaluation. We s ...

Assoc Computing Machinery2016

Optimized Distributed Hyperparameter Search and Simulation for Lung Texture Classification in CT Using Hadoop

Adrien Raphaël Depeursinge

Many medical image analysis tasks require complex learning strategies to reach a quality of image-based decision support that is sufficient in clinical practice. The analysis of medical texture in tomographic images, for example of lung tissue, is no excep ...

2016

Sparse Representation of Signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Ambrogio Fasoli, Duccio Testa, Patrick Blanchard, Jonathan Bryan Lister, Theodoros Panis, Mattia Albergante

Efficient, real-time and automated data analysis is one of the key elements for achieving scientific success in complex engineering and physical systems, of which two examples are the JET and ITER tokamaks. One problem which is common to these fields is t ...

IOP2016

Sparse representation of signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Ambrogio Fasoli, Duccio Testa, Patrick Blanchard, Jonathan Bryan Lister, Theodoros Panis, Mattia Albergante

Efficient, real-time and automated data analysis is one of the key elements for achieving scientific success in complex engineering and physical systems, of which two examples are the JET and ITER tokamaks. One problem which is common to these fields is th ...

2016

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Michaël Unser, Martin Kurt Storath

We consider

L ^{ 1 }

-TV regularization of univariate signals with values on the real line or on the unit circle. While the real data space leads to a convex optimization problem, the problem is nonconvex for circle-valued data. In this paper, we deriv ...

SIAM2016

Memetic Viability Evolution for Constrained Optimization

Dario Floreano, Andrea Maesani, Giovanni Iacca

The performance of evolutionary algorithms can be heavily undermined when constraints limit the feasible areas of the search space. For instance, while Covariance Matrix Adapta- tion Evolution Strategy is one of the most efficient algorithms for unconstrai ...

Institute of Electrical and Electronics Engineers2016

Global Optimization on an Interval

Thomas Alois Weber

This paper provides expressions for the largest and smallest solution of a global optimization problem using an adjoint variable which represents the available one-sided improvements up to the interval “horizon”. Interpreting the problem in terms of optima ...

2016

Demand-based discrete optimization

Michel Bierlaire, Shadi Sharif Azadeh

We propose a methodological framework to include a wide variety of discrete choice models in (mixed) integer optimization problems. We succeed in obtaining a specification that is linear in the decision variables, allowing to use exact methods to solve the ...

2016

Scampi: a robust approximate message-passing framework for compressive imaging

Florent Gérard Krzakala, Jean François Emmanuel Barbier

Reconstruction of images from noisy linear measurements is a core problem in image processing, for which convex optimization methods based on total variation (TV) minimization have been the long-standing state-of-the-art. We present an alternative probabil ...

Iop Publishing Ltd2016

Scalable Convex Optimization Methods for Semidefinite Programming

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Global Optimization for Image Restoration in Optical/IR Interferometry

Parallelizing Query Optimization on Shared-Nothing Architectures

Optimized Distributed Hyperparameter Search and Simulation for Lung Texture Classification in CT Using Hadoop

Sparse Representation of Signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Sparse representation of signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Memetic Viability Evolution for Constrained Optimization

Global Optimization on an Interval

Demand-based discrete optimization

Scampi: a robust approximate message-passing framework for compressive imaging

Exact Algorithms for $ L ^{ 1 } $ -TV Regularization of Real-Valued or Circle-Valued Signals

Global Optimization for Image Restoration in Optical/IR Interferometry

Parallelizing Query Optimization on Shared-Nothing Architectures

Optimized Distributed Hyperparameter Search and Simulation for Lung Texture Classification in CT Using Hadoop

Sparse Representation of Signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Sparse representation of signals: from astrophysics to real-time data analysis for fusion plasmas and system optimization analysis for ITER and TCV

Memetic Viability Evolution for Constrained Optimization

Scampi: a robust approximate message-passing framework for compressive imaging

Global Optimization on an Interval

Demand-based discrete optimization