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Structured Sparsity Models for Multiparty Speech Recovery from Reverberant Recordings
Afsaneh Asaei, Mohammad Golbabaee, Hervé Bourlard +1
We tackle the multi-party speech recovery problem through modeling the acoustic of the reverberant chambers. Our approach exploits structured sparsity models to perform room modeli…
Sparse projections onto the simplex
Anastasios Kyrillidis, Stephen Becker, Volkan Cevher and +1
Most learning methods with rank or sparsity constraints use convex relaxations, which lead to optimization with the nuclear norm or the -norm. However, several important le…
Sublinear Time, Approximate Model-based Sparse Recovery For All
Anastasios Kyrillidis, Volkan Cevher
We describe a probabilistic, {\it sublinear} runtime, measurement-optimal system for model-based sparse recovery problems through dimensionality reducing, {\em dense} random matric…
Matrix Recipes for Hard Thresholding Methods
Anastasios Kyrillidis, Volkan Cevher
In this paper, we present and analyze a new set of low-rank recovery algorithms for linear inverse problems within the class of hard thresholding methods. We provide strategies on…
Matrix ALPS: Accelerated Low Rank and Sparse Matrix Reconstruction
Anastasios Kyrillidis, Volkan Cevher
We propose Matrix ALPS for recovering a sparse plus low-rank decomposition of a matrix given its corrupted and incomplete linear measurements. Our approach is a first-order project…
Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm
Anastasios Kyrillidis, Volkan Cevher
The least absolute shrinkage and selection operator (LASSO) for linear regression exploits the geometric interplay of the -data error objective and the -norm constr…