Différences
Ci-dessous, les différences entre deux révisions de la page.
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recherche:projets:faust2020 [2020/04/29 19:29] equemene créée |
recherche:projets:faust2020 [2020/04/29 19:31] (Version actuelle) equemene [Flexible Approximate MUlti-layer Sparse Transforms (FAµST)] |
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| ====== Flexible Approximate MUlti-layer Sparse Transforms (FAµST) ====== | ====== Flexible Approximate MUlti-layer Sparse Transforms (FAµST) ====== | ||
| - | {{:recherche:projets:faust.png?250 |}} **IXXI, ENS-Lyon ** : Hakim Hadj-Djilani\\ | + | {{:recherche:projets:faust.png?100 |}} **IXXI, ENS-Lyon ** : Hakim Hadj-Djilani\\ |
| **Centre Blaise Pascal :** Emmanuel Quémener | **Centre Blaise Pascal :** Emmanuel Quémener | ||
| - | The FAµST toolbox provides algorithms and data structures to decompose a given dense matrix into a product of sparse matrices in order to reduce its computational complexity (both for storage and manipulation). FaµST can be used to | + | The FAµST toolbox provides algorithms and data structures to decompose a given dense matrix into a product of sparse matrices in order to reduce its computational complexity (both for storage and manipulation). FaµST can be used to : |
| * speedup / reduce the memory footprint of iterative algorithms commonly used for solving high dimensional linear inverse problems. | * speedup / reduce the memory footprint of iterative algorithms commonly used for solving high dimensional linear inverse problems. | ||
| - | * learn dictionaries with an intrinsically efficient implementation | + | * learn dictionaries with an intrinsically efficient implementation |
| - | * compute (approximate) fast Fourier transforms on graphs. | + | * compute (approximate) fast Fourier transforms on graphs. |
| A C++ implementation (versions 2.x), including Matlab and Python wrappers, is available under an Inria licence. | A C++ implementation (versions 2.x), including Matlab and Python wrappers, is available under an Inria licence. | ||