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Statistical Learning Guarantees for Compressive Clustering and
  Compressive Mixture Modeling
v1v2v3 (latest)

Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling

Mathematical Statistics and Learning (MSL), 2020
17 April 2020
Rémi Gribonval
Gilles Blanchard
Nicolas Keriven
Y. Traonmilin
ArXiv (abs)PDFHTML

Papers citing "Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling"

7 / 7 papers shown
Effective regions and kernels in continuous sparse regularisation, with application to sketched mixtures
Effective regions and kernels in continuous sparse regularisation, with application to sketched mixtures
Yohann De Castro
Rémi Gribonval
Nicolas Jouvin
187
0
0
11 Jul 2025
Compressive Recovery of Sparse Precision Matrices
Compressive Recovery of Sparse Precision Matrices
Titouan Vayer
Etienne Lasalle
Rémi Gribonval
Paulo Gonçalves
287
1
0
08 Nov 2023
Batch-less stochastic gradient descent for compressive learning of deep
  regularization for image denoising
Batch-less stochastic gradient descent for compressive learning of deep regularization for image denoisingJournal of Mathematical Imaging and Vision (JMIV), 2023
Hui Shi
Yann Traonmilin
Jean-François Aujol
185
1
0
02 Oct 2023
Approximation speed of quantized vs. unquantized ReLU neural networks
  and beyond
Approximation speed of quantized vs. unquantized ReLU neural networks and beyondIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2022
Antoine Gonon
Nicolas Brisebarre
Rémi Gribonval
E. Riccietti
173
8
0
24 May 2022
Mean Nyström Embeddings for Adaptive Compressive Learning
Mean Nyström Embeddings for Adaptive Compressive LearningInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2021
Antoine Chatalic
Luigi Carratino
Ernesto De Vito
Lorenzo Rosasco
211
8
0
21 Oct 2021
Asymmetric compressive learning guarantees with applications to
  quantized sketches
Asymmetric compressive learning guarantees with applications to quantized sketchesIEEE Transactions on Signal Processing (IEEE TSP), 2021
V. Schellekens
Laurent Jacques
129
1
0
20 Apr 2021
Compressive Statistical Learning with Random Feature Moments
Compressive Statistical Learning with Random Feature Moments
Rémi Gribonval
Gilles Blanchard
Nicolas Keriven
Y. Traonmilin
360
54
0
22 Jun 2017
1
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