Publications related to Quantization Design for Distributed Optimization

Splitting Methods for Distributed Optimization and Control

This thesis contributes towards the design and analysis of fast and distributed optimization algorithms based on splitting techniques, such as proximal gradient methods or alternation minimization algorithms, with the application of solving model predictiv ...

EPFL2016

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

Quantization Design for Distributed Optimization

Colin Neil Jones, Ye Pu, Melanie Nicole Zeilinger

We consider the problem of solving a distributed optimization problem using a distributed computing platform, where the communication in the network is limited: each node can only communicate with its neighbours and the channel has a limited data-rate. A c ...

2015

Quantization Design for Unconstrained Distributed Optimization

Colin Neil Jones, Ye Pu, Melanie Nicole Zeilinger

We consider an unconstrained distributed optimization problem and assume that the bit rate of the communication in the network is limited. We propose a distributed optimization algorithm with an iteratively refining quantization design, which bounds the qu ...

2015

Directional Real-Time Optimization Applied to a Kite-Control Simulation Benchmark

Dominique Bonvin, Grégory François, Sean Costello

This paper applies a novel two-layer optimizing control scheme to a kite-control benchmark problem. The upper layer is a recent real-time optimization algorithm, called Directional Modifier Adaptation, which represents a variation of the popular Modifier A ...

IEEE2015

Learning of Closed-Loop Motion Control

Jonas Buchli, Farbod Farshidian

Learning motion control as a unified process of designing the reference trajectory and the controller is one of the most challenging problems in robotics. The complexity of the problem prevents most of the existing optimization algorithms from giving satis ...

2014

Path-following gradient-based decomposition algorithms for separable convex optimization

Quoc Tran Dinh

A new decomposition optimization algorithm, called path-following gradient-based decomposition, is proposed to solve separable convex optimization problems. Unlike path-following Newton methods considered in the literature, this algorithm does not require ...

Springer Verlag2014

A Branch-and-Price Algorithm to Solve the Integrated Berth Allocation and Yard Assignment Problem in Bulk Ports

Michel Bierlaire, Tomas Robenek, Nitish Umang

In this research, two crucial optimization problems of berth allocation and yard assignment in the context of bulk ports are studied. We discuss how these problems are interrelated and can be combined and solved as a single large scale optimization problem ...

Elsevier Science Bv2014

Geometric Variational Models for Inverse Problems in Imaging

Virginia Estellers Casas

This dissertation develops geometric variational models for different inverse problems in imaging that are ill-posed, designing at the same time efficient numerical algorithms to compute their solutions. Variational methods solve inverse problems by the fo ...

EPFL2013

Coordination and Sampling in Distributed Constraint Optimization

Brammert Ottens

The Distributed Constraint Optimization (DCOP) framework can be used to model a wide range of optimization problems that are inherently distributed. A distributed optimization problem can be viewed as a problem distributed over a set of agents, where agent ...

EPFL2012

Quantization Design for Distributed Optimization

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Splitting Methods for Distributed Optimization and Control

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

Quantization Design for Distributed Optimization

Quantization Design for Unconstrained Distributed Optimization

Directional Real-Time Optimization Applied to a Kite-Control Simulation Benchmark

Learning of Closed-Loop Motion Control

Path-following gradient-based decomposition algorithms for separable convex optimization

A Branch-and-Price Algorithm to Solve the Integrated Berth Allocation and Yard Assignment Problem in Bulk Ports

Geometric Variational Models for Inverse Problems in Imaging

Coordination and Sampling in Distributed Constraint Optimization

Splitting Methods for Distributed Optimization and Control

A Branch-and-Price Algorithm to Solve the Integrated Berth Allocation and Yard Assignment Problem in Bulk Ports

Directional Real-Time Optimization Applied to a Kite-Control Simulation Benchmark

Coordination and Sampling in Distributed Constraint Optimization

Geometric Variational Models for Inverse Problems in Imaging

Quantization Design for Unconstrained Distributed Optimization

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

Learning of Closed-Loop Motion Control

Path-following gradient-based decomposition algorithms for separable convex optimization

Quantization Design for Distributed Optimization