Publications related to Augmented Lagrangian Methods for Provable and Scalable Machine Learning

A heuristic for nonlinear global optimization

Michel Bierlaire, Michaël Clément Louis Ghislain Thémans, Nicolas Zufferey

We propose a new heuristic for nonlinear global optimization combining a variable neighbourhood search framework with a modified trust-region algorithm as local search. The proposed method presents the capability to prematurely interrupt the local search i ...

2008

A Unified Framework for Joint Sink Mobility and Routing to Increase the Lifetime of Wireless Sensor Networks

Jean-Pierre Hubaux, Jun Luo

The longevity of wireless sensor networks is a major issue that impacts the application of such networks. While communication protocols are striving to save energy by acting on sensor nodes, recent results show that network lifetime can be prolonged by fur ...

2008

Temperature Control of High Performance Multicore Platforms Using Convex Optimization

Giovanni De Micheli, David Atienza Alonso, Luca Benini, Srinivasan Murali

With technology advances, the number of cores integrated on a chip and their speed of operation is increasing. This, in turn is leading to a significant increase in chip temperature. Temperature gradi- ents and hot-spots not only affect the performance of ...

2008

Some Recovery Conditions for Basis Learning by L1-Minimization

Rémi Gribonval, Karin Schnass

Many recent works have shown that if a given signal admits a sufficiently sparse representation in a given dictionary, then this representation is recovered by several standard optimization algorithms, in particular the convex

\ell^1

minimization approac ...

2008

Two-stage column generation and applications in container terminal management

Michel Bierlaire, Matteo Salani, Ilaria Vacca

Seaport container terminals are source of many interesting large-scale optimization problems, which arise in the management of operations at several decision levels. In this paper we firstly illustrate a recently proposed framework, called two-stage column ...

2008

Two-stage column generation and applications in container terminal management

Michel Bierlaire, Matteo Salani, Ilaria Vacca

Seaport container terminals are source of many interesting large-scale optimization problems, which arise in the management of operations at several decision levels. In this paper we firstly illustrate a recently proposed framework, called two-stage column ...

2008

Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks

Ali H. Sayed

Cognitive radio technology has been proposed to improve spectrum efficiency by having the cognitive radios act as secondary users to opportunistically access under-utilized frequency bands. Spectrum sensing, as a key enabling functionality in cognitive rad ...

IEEE2008

Identifying physical properties of deformable objects by using particle filters

Charles Baur, Oussama Khatib

This paper presents a new approach for estimating physical properties of deformable models from experimental measurements. In contrast to most previous work, we introduce a new method based on particle filters which identifies the different stiffness prope ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2008

Numerical methods and models relevant to transportation applications

Michaël Clément Louis Ghislain Thémans

In this thesis, we focus on standard classes of problems in numerical optimization: unconstrained nonlinear optimization as well as systems of nonlinear equations. More precisely, we consider two types of unconstrained nonlinear optimization problems. On t ...

EPFL2007

A Unified Framework for Max-Min and Min-Max Fairness with Applications

Jean-Yves Le Boudec

Max-min fairness is widely used in various areas of networking. In every case where it is used, there is a proof of existence and one or several algorithms for computing it; in most, but not all cases, they are based on the notion of bottlenecks. In spite ...

2007

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

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A heuristic for nonlinear global optimization

A Unified Framework for Joint Sink Mobility and Routing to Increase the Lifetime of Wireless Sensor Networks

Temperature Control of High Performance Multicore Platforms Using Convex Optimization

Some Recovery Conditions for Basis Learning by L1-Minimization

Two-stage column generation and applications in container terminal management

Two-stage column generation and applications in container terminal management

Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks

Identifying physical properties of deformable objects by using particle filters

Numerical methods and models relevant to transportation applications

A Unified Framework for Max-Min and Min-Max Fairness with Applications

A heuristic for nonlinear global optimization

A Unified Framework for Joint Sink Mobility and Routing to Increase the Lifetime of Wireless Sensor Networks

Some Recovery Conditions for Basis Learning by L1-Minimization

Temperature Control of High Performance Multicore Platforms Using Convex Optimization

Numerical methods and models relevant to transportation applications

Identifying physical properties of deformable objects by using particle filters

Two-stage column generation and applications in container terminal management

Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks

A Unified Framework for Max-Min and Min-Max Fairness with Applications

Two-stage column generation and applications in container terminal management