Publications associées à Multi-party Speech Recovery Exploiting Structured Sparsity Models

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Estimation Error of the Constrained Lasso

Volkan Cevher, Yen-Huan Li, Ya-Ping Hsieh, Nissim Zerbib

This paper presents a non-asymptotic upper bound for the estimation error of the constrained lasso, under the high-dimensional (

n \ll p

) setting. In contrast to existing results, the error bound in this paper is sharp, is valid when the parameter to be e ...

2016

Multi-party Speech Recovery Exploiting Structured Sparsity Models

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Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization

‪Stochastic Control-A Moment Approach to Sparse Control Design‬

Estimation Error of the Constrained Lasso

Signal structure: from manifolds to molecules and structured sparsity

On Compressibility of Neural Network phonological Features for Low Bit Rate Speech Coding

Structured Sparsity Models for Reverberant Speech Separation

Jump-Sparse and Sparse Recovery Using Potts Functionals

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

A geometric framework for registration of sparse images

Image registration with sparse approximations in parametric dictionaries

‪Stochastic Control-A Moment Approach to Sparse Control Design‬

Sparse Gammatone Signal Model Predicts Perceived Noise Intrusiveness

On Compressibility of Neural Network phonological Features for Low Bit Rate Speech Coding

Structured Sparsity Models for Reverberant Speech Separation

Jump-Sparse and Sparse Recovery Using Potts Functionals

Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization

Image registration with sparse approximations in parametric dictionaries

Signal structure: from manifolds to molecules and structured sparsity

A geometric framework for registration of sparse images

Estimation Error of the Constrained Lasso