Publications related to Convergence without Convexity: Sampling, Optimization, and Games

Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models

Latent Gaussian models (LGMs) are widely used in statistics and machine learning. Bayesian inference in non-conjugate LGMs is difficult due to intractable integrals in- volving the Gaussian prior and non-conjugate likelihoods. Algorithms based on variation ...

Omni Press2013

To Convexify or Not? Regression with Clustering Penalties on Graphs

Volkan Cevher, Luca Baldassarre, Marwa El Halabi

We consider minimization problems that are compositions of convex functions of a vector

\x \in\reals^N

with submodular set functions of its support (i.e., indices of the non-zero coefficients of

\x

). Such problems are in general difficult for large

N

...

IEEE2013

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

Regularized Bundle Methods for Convex and Non-Convex Risks

Machine learning is most often cast as an optimization problem. Ideally, one expects a convex objective function to rely on efficient convex optimizers with nice guarantees such as no local optima. Yet, non-convexity is very frequent in practice and it may ...

2012

A survey and comparison of contemporary algorithms for computing the matrix geometric mean

In this paper we present a survey of various algorithms for computing matrix geometric means and derive new second-order optimization algorithms to compute the Karcher mean. These new algorithms are constructed using the standard definition of the Riemanni ...

2012

Container Terminal Management

Ilaria Vacca

This thesis deals with models and methods for large scale optimization problems; in particular, we focus on decision problems arising in the context of seaport container terminals for the efficient management of terminal operations. Large-scale optimizatio ...

EPFL2011

Tracking Multiple Objects under Global Appearance Constraints

Pascal Fua, François Fleuret, Jérôme Berclaz, Horesh Beny Ben Shitrit

In this paper, we show that tracking multiple people whose paths may intersect can be formulated as a convex global optimization problem. Our proposed framework is designed to exploit image appearance clues to prevent identity switches. Our ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Tracking Multiple People under Global Appearance Constraints

Pascal Fua, François Fleuret, Jérôme Berclaz, Horesh Beny Ben Shitrit

In this paper, we show that tracking multiple people whose paths may intersect can be formulated as a convex global optimization problem. Our proposed framework is designed to exploit image appearance cues to prevent identity switches. Our method is effect ...

Ieee Service Center, 445 Hoes Lane, Po Box 1331, Piscataway, Nj 08855-1331 Usa2011

Welfare-Maximizing Correlated Equilibria with an Application to Wireless Communication

Daniel Kuhn

The set of correlated equilibria is convex and contains all Nash equilibria as special cases. Thus, the social welfare-maximizing correlated equilibrium is amenable to convex analysis and offers social welfare that is at least as good as the games best pe ...

2011

A comparison of global optimisation algorithms with standard benchmark functions and real-world applications using EnergyPlus

Jérôme Henri Kämpf, Darren Robinson

There is an increasing interest in the use of computer algorithms to identify combinations of parameters which optimise the energy performance of buildings. For such problems, the objective function can be multi-modal and needs to be approximated numerical ...

Taylor & Francis2010

Convergence without Convexity: Sampling, Optimization, and Games

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Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models

To Convexify or Not? Regression with Clustering Penalties on Graphs

Coordination and Sampling in Distributed Constraint Optimization

Regularized Bundle Methods for Convex and Non-Convex Risks

A survey and comparison of contemporary algorithms for computing the matrix geometric mean

Container Terminal Management

Tracking Multiple Objects under Global Appearance Constraints

Tracking Multiple People under Global Appearance Constraints

Welfare-Maximizing Correlated Equilibria with an Application to Wireless Communication

A comparison of global optimisation algorithms with standard benchmark functions and real-world applications using EnergyPlus

Coordination and Sampling in Distributed Constraint Optimization

Regularized Bundle Methods for Convex and Non-Convex Risks

A survey and comparison of contemporary algorithms for computing the matrix geometric mean

Container Terminal Management

A comparison of global optimisation algorithms with standard benchmark functions and real-world applications using EnergyPlus

Tracking Multiple Objects under Global Appearance Constraints

Welfare-Maximizing Correlated Equilibria with an Application to Wireless Communication

To Convexify or Not? Regression with Clustering Penalties on Graphs

Tracking Multiple People under Global Appearance Constraints

Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models