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- Ben Jeuris
- 2012

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 Riemannian Hessian. The survey includes the ALM list of desired properties for a geometric mean, the analytical… (More)

- Ben Jeuris, Raf Vandebril
- SIAM J. Matrix Analysis Applications
- 2016

When computing an average of positive definite (PD) matrices, the preservation of additional matrix structure is desirable for interpretations in applications. An interesting and widely present structure is that of PD Toeplitz matrices, which we endow with a geometry originating in signal processing theory. As an averaging operation, we consider the… (More)

- Pooya Zakeri, Ben Jeuris, Raf Vandebril, Yves Moreau
- Bioinformatics
- 2014

MOTIVATION
Various approaches based on features extracted from protein sequences and often machine learning methods have been used in the prediction of protein folds. Finding an efficient technique for integrating these different protein features has received increasing attention. In particular, kernel methods are an interesting class of techniques for… (More)

- Ben Jeuris, Raf Vandebril
- GSI
- 2013

- Marnix Van Daele, Stefan Vandewalle, +37 authors D. Hollevoet
- 2012

s at ICCAM 2012 Multi-Step Skipping Methods with Modified Search Direction for Unconstrained Optimization Nudrat Aamir Department of Mathematical Sciences, University of Essex Wivenhoe Park, Colchester, Essex, CO4 3SQ United Kingdom naamir@essex.ac.uk Joint work with: John A. Ford When dealing with unconstrained non-linear optimization problems using… (More)

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