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Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent

Abstract : A fundamental concept in statistics is the concept of Fréchet sample mean. While its computation is a simple task in Euclidian space, the same does not hold for less structured spaces such as the space of graphs, where concepts of distance or mid-point can be hard to compute. We present some work in progress regarding new distance measures and new algorithms to compute the Fréchet mean in the space of Graphs.
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https://hal-normandie-univ.archives-ouvertes.fr/hal-02895832
Contributor : Nicolas Boria <>
Submitted on : Friday, July 10, 2020 - 10:26:43 AM
Last modification on : Wednesday, October 14, 2020 - 4:01:21 AM

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  • HAL Id : hal-02895832, version 1

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Nicolas Boria, Benjamin Negrevergne, Florian Yger. Fréchet Mean Computation in Graph Space through Projected Block Gradient Descent. ESANN 2020, 2020, Bruges, France. ⟨hal-02895832⟩

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