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12/02/2020
An algorithm for non-convex off-the-grid sparse spike estimation with a minimum separation constraint
Theoretical results show that sparse off-the-grid spikes can be estimate...
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09/18/2020
The basins of attraction of the global minimizers of non-convex inverse problems with low-dimensional models in infinite dimension
Non-convex methods for linear inverse problems with low-dimensional mode...
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04/17/2020
Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling
We provide statistical learning guarantees for two unsupervised learning...
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11/29/2018
The basins of attraction of the global minimizers of the non-convex sparse spikes estimation problem
The sparse spike estimation problem consists in estimating a number of o...
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06/21/2018
Is the 1-norm the best convex sparse regularization?
The 1-norm is a good convex regularization for the recovery of sparse ve...
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03/02/2018
Optimality of 1-norm regularization among weighted 1-norms for sparse recovery: a case study on how to find optimal regularizations
The 1-norm was proven to be a good convex regularizer for the recovery o...
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06/22/2017
Compressive Statistical Learning with Random Feature Moments
We describe a general framework --compressive statistical learning-- for...
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10/27/2016
Compressive K-means
The Lloyd-Max algorithm is a classical approach to perform K-means clust...
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09/30/2016