We propose a method to find the Lq mean of a set of symmetric positive-definite (SPD) matrices, for 1≤q ≤2. Given a set of points, the Lq mean is defined as a point for which the sum of q-th power of distances to all the given points is minimum. The
AbstractWe give a constructive proof of a theorem of Marshall and Olkin that any real symmetric posi...
AbstractWe define a new average – termed the resolvent average – for positive semidefinite matrices....
International audienceThe estimation of means of data points lying on the Riemannian manifold of sym...
Symmetric positive definite (SPD) matrices have become fundamental computational objects in many area...
In this article we introduce a new family of power means for m positive definite matrices, called Ré...
We explore the connection between two problems that have arisen independently in the signal processi...
When computing an average of positive definite (PD) matrices, the preservation of additional matrix ...
Indefinite symmetric matrices that are estimates of positive definite population matrices occur in a...
Indefinite symmetric matrices that are estimates of positive definite population matrices occur in a...
Indefinite symmetric matrices that are estimates of positive definite population matrices occur in a...
International audienceWe explore the connection between two problems that have arisen independently ...
AbstractWe define a new family of matrix means {Pt(ω;A)}t∈[−1,1], where ω and A vary over all positi...
© 2016 Society for Industrial and Applied Mathematics. When one computes an average of positive defi...
We define a new average — termed the resolvent average — for positive semidefinite matrices. For pos...
International audienceEstimating means of data points lying on the Riemannian manifold of symmetric ...
AbstractWe give a constructive proof of a theorem of Marshall and Olkin that any real symmetric posi...
AbstractWe define a new average – termed the resolvent average – for positive semidefinite matrices....
International audienceThe estimation of means of data points lying on the Riemannian manifold of sym...
Symmetric positive definite (SPD) matrices have become fundamental computational objects in many area...
In this article we introduce a new family of power means for m positive definite matrices, called Ré...
We explore the connection between two problems that have arisen independently in the signal processi...
When computing an average of positive definite (PD) matrices, the preservation of additional matrix ...
Indefinite symmetric matrices that are estimates of positive definite population matrices occur in a...
Indefinite symmetric matrices that are estimates of positive definite population matrices occur in a...
Indefinite symmetric matrices that are estimates of positive definite population matrices occur in a...
International audienceWe explore the connection between two problems that have arisen independently ...
AbstractWe define a new family of matrix means {Pt(ω;A)}t∈[−1,1], where ω and A vary over all positi...
© 2016 Society for Industrial and Applied Mathematics. When one computes an average of positive defi...
We define a new average — termed the resolvent average — for positive semidefinite matrices. For pos...
International audienceEstimating means of data points lying on the Riemannian manifold of symmetric ...
AbstractWe give a constructive proof of a theorem of Marshall and Olkin that any real symmetric posi...
AbstractWe define a new average – termed the resolvent average – for positive semidefinite matrices....
International audienceThe estimation of means of data points lying on the Riemannian manifold of sym...
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