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Publications associées (197)

Data reconciliation of steam networks in refineries and petrochemical sites

Laurent Gabriel Félix Alexandre Stéphane Bungener

Process knowledge is the key factor in establishing quality energy efficiency and integration solutions. Without process knowledge, engineers run the risk of oversizing, undersizing or creating non-feasible and potentially dangerous solutions. Resulting ac ...

2015

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

Barrier Smoothing for Nonsmooth Convex Minimization

Volkan Cevher, Quoc Tran Dinh, Yen-Huan Li

This paper proposes a smoothing technique for nonsmooth convex minimization using self-concordant barriers. To illustrate the main ideas, we compare our technique and the proximity smoothing approach (Nesterov2005) via the classical gradient method on both ...

Ieee2014

Constrained convex minimization via model-based excessive gap

Volkan Cevher, Quoc Tran Dinh

We introduce a model-based excessive gap technique to analyze first-order primal- dual methods for constrained convex minimization. As a result, we construct new primal-dual methods with optimal convergence rates on the objective residual and the primal fe ...

2014

A Convex Solution to Disparity Estimation from Light Fields via the Primal-Dual Method

Pierre Vandergheynst, Mahdad Hosseini Kamal

We present a novel approach to the reconstruction of depth from light field data. Our method uses dictionary representations and group sparsity constraints to derive a convex formulation. Although our solution results in an increase of the problem dimensio ...

2014

A Primal-Dual Algorithmic Framework for Constrained Convex Minimization

Volkan Cevher, Quoc Tran Dinh

We present a primal-dual algorithmic framework to obtain approximate solutions to a prototypical constrained convex optimization problem, and rigorously characterize how common structural assumptions affect the numerical efficiency. Our main analysis techn ...

2014

Constrained Reachability and Trajectory Generation for Flat Systems

Timm Faulwasser

We consider the problem of trajectory generation for constrained differentially flat systems. Based on the topological properties of the set of admissible steady state values of a flat output we derive conditions which allow for an a priori verification of ...

Pergamon-Elsevier Science Ltd2014

Scalable sparse covariance estimation via self-concordance

Volkan Cevher, Quoc Tran Dinh, Anastasios Kyrillidis, Rabeeh Karimi Mahabadi

We consider the class of convex minimization problems, composed of a self-concordant function, such as the logdet metric, a convex data fidelity term h and, a regularizing -- possibly non-smooth -- function g. This type of problems have recently attracted ...

2014

An inexact proximal path-following algorithm for constrained convex minimization

Volkan Cevher, Quoc Tran Dinh, Anastasios Kyrillidis

Many scientific and engineering applications feature large-scale non-smooth convex minimization problems over convex sets. In this paper, we address an important instance of this broad class where we assume that the non-smooth objective is equipped with a ...

Siam Publications2014

LP-Based Algorithms for Capacitated Facility Location

Ola Nils Anders Svensson, Hyung Chan An

Linear programming has played a key role in the study of algorithms for combinatorial optimization problems. In the field of approximation algorithms, this is well illustrated by the uncapacitated facility location problem. A variety of algorithmic methodo ...

IEEE2014

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