Publications related to Compressed sensing

Graph learning under sparsity priors

Graph signals offer a very generic and natural representation for data that lives on networks or irregular structures. The actual data structure is however often unknown a priori but can sometimes be estimated from the knowledge of the application domain. ...

Ieee2017

Fast Computation Of Spectral Projectors Of Banded Matrices

Daniel Kressner, Ana Susnjara

We consider the approximate computation of spectral projectors for symmetric banded matrices. While this problem has received considerable attention, especially in the context of linear scaling electronic structure methods, the presence of small relative s ...

Siam Publications2017

Gaussian versus Sparse Stochastic Processes

Julien René Pierre Fageot

Although our work lies in the field of random processes, this thesis was originally motivated by signal processing applications, mainly the stochastic modeling of sparse signals. We develop a mathematical study of the innovation model, under which a signal ...

EPFL2017

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Kyong Hwan Jin

While the recent theory of compressed sensing provides an opportunity to overcome the Nyquist limit in recovering sparse signals, a solution approach usually takes the form of an inverse problem of an unknown signal, which is crucially dependent on specifi ...

IEEE2017

Sparse inverse problems for Fourier imaging

Anna Auria Rasclosa

Many natural images have low intrinsic dimension (a.k.a. sparse), meaning that they can be represented with very few coefficients when expressed in an adequate domain. The recent theory of Compressed Sensing exploits this property offering a powerful frame ...

EPFL2017

Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework

Volkan Cevher, Jonathan Mark Scarlett

The support recovery problem consists of determining a sparse subset of a set of variables that is relevant in generating a set of observations, and arises in a diverse range of settings, such as compressive sensing, subset selection in regression, and gro ...

Institute of Electrical and Electronics Engineers2017

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Volkan Cevher, Mikhail Kapralov, Jonathan Mark Scarlett, Amir Zandieh

The problem of approximately computing the

k

dominant Fourier coefficients of a vector

X

quickly, and using few samples in time domain, is known as the Sparse Fourier Transform (sparse FFT) problem. A long line of work on the sparse FFT has resulted in ...

2017

Face Recognition in Real-world Images

Sabine Süsstrunk, Radhakrishna Achanta, Xavier Philippe Marie Fontaine

Face recognition systems are designed to handle well-aligned images captured under controlled situations. However real-world images present varying orientations, expressions, and illumination conditions. Traditional face recognition algorithms perform poor ...

Ieee2017

Efficient Inversion of Multiple-Scattering Model for Optical Diffraction Tomography

Michaël Unser, Thanh-An Michel Pham, Emmanuel Emilien Louis Soubies

Optical diffraction tomography relies on solving an inverse scattering problem governed by the wave equation. Classical reconstruction algorithms are based on linear approximations of the forward model (Born or Rytov), which limits their applicability to t ...

2017

Sparse Pronunciation Codes for Perceptual Phonetic Information Assessment

Hervé Bourlard, Milos Cernak, Afsaneh Asaei, Dhananjay Ram

Speech is a complex signal produced by a highly constrained articulation machinery. Neuro and psycholinguistic theories assert that speech can be decomposed into molecules of structured atoms. Although characterization of the atoms is controversial, the ex ...

2017

Compressed sensing

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Graph learning under sparsity priors

Fast Computation Of Spectral Projectors Of Banded Matrices

Gaussian versus Sparse Stochastic Processes

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Sparse inverse problems for Fourier imaging

Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Face Recognition in Real-world Images

Efficient Inversion of Multiple-Scattering Model for Optical Diffraction Tomography

Sparse Pronunciation Codes for Perceptual Phonetic Information Assessment

Limits on Support Recovery With Probabilistic Models: An Information-Theoretic Framework

Graph learning under sparsity priors

Sparse inverse problems for Fourier imaging

Fast Computation Of Spectral Projectors Of Banded Matrices

Gaussian versus Sparse Stochastic Processes

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

An Adaptive Sublinear-Time Block Sparse Fourier Transform

Sparse Pronunciation Codes for Perceptual Phonetic Information Assessment

Face Recognition in Real-world Images

Efficient Inversion of Multiple-Scattering Model for Optical Diffraction Tomography