Orbel Wolsey Award 2014

Nicolas BoumalNicolas Boumal has a master degree in mathematical engineering from the Ecole polytechnique de Louvain. He graduated in 2010 with summa cum laude. In 2010 he became a FNRS fellow and joined the department of mathematical engineering (part of the ICTEAM) and begun a PhD under the supervision of Pierre-Antoine Absil and Vincent Blondel.

His works focus mainly on applications of optimization methods on manifolds (for which he develop the toolbox called Manopt) to solve computational problems. His initial research in that area was about the design and analysis of numerical algorithms for curve fitting on manifolds, which he started during his master thesis. More recently, he has been working on low-rank matrix completion and synchronization of rotations.

Bamdev MishraBamdev Mishra holds a master degree in Electrical Engineering from the Indian Institute of Technology, Bombay. He graduated in 2010. Then he begun a PhD in Engineering at the Montefiore Institute (ULG).
His research focus mainly on the application of manifold optimization techniques to large-scale convex optimization problems whose expected or desired solutions have low rank. He focuses specifically on convex relaxations of large-scale rank-constrained problems encountered in machine learning, data reduction and bioinformatics.

ManOpt – A Matlab toolbox for optimization on manifolds

Optimization on manifolds is a rapidly developing branch of nonlinear optimization. Its focus is on problems where the smooth geometry of the search space can be leveraged to design efficient numerical algorithms. Optimization on manifolds is well-suited to deal with rank and orthogonality constraints, in particular. Such structured constraints appear pervasively in operations research applications, notably in large-scale data processing and estimation problems. The Manopt toolbox is a user-friendly, documented piece of software dedicated to simplify experimenting with state of the art Riemannian optimization algorithms.

Strong points

The decision of the Jury has been motivated by the following qualities:

  • Applicability: there exists many useful applications that may require ManOpt to be solved
  • High quality: The code and documentation are of a great quality
  • Availability: The toolbox can be used by everyone using Matlab
  • Broad audience: The aim of ManOpt is to be used outside strict practitioner of Manifold optimization
  • Communication: The web site and all documents are very clear
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