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Learning-Based Compressive Subsampling

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic, Yen-Huan Li, Luca Baldassarre, Baran Gözcü

The problem of recovering a structured signal

\mathbf{x} \in \mathbb{C}^p

from a set of dimensionality-reduced linear measurements

\mathbf{b} = \mathbf {A}\mathbf {x}

arises in a variety of applications, such as medical imaging, spectroscopy, Fourier o ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Baran Gözcü

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Scalable Learning-Based Sampling Optimization For Compressive Dynamic MRI

Data-driven Measurement Designs for Magnetic Resonance Imaging

Rethinking Sampling in Parallel MRI: A Data-Driven Approach

Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI

Learning-Based Compressive MRI

Learning-based subsampling

Learning-Based Compressive Subsampling

A Primal-dual Framework For Mixtures Of Regularisers

Metric Learning with Rank and Sparsity Constraints

Manifold Sparse Beamforming

Data-driven Measurement Designs for Magnetic Resonance Imaging

Scalable Learning-Based Sampling Optimization For Compressive Dynamic MRI

Rethinking Sampling in Parallel MRI: A Data-Driven Approach

Scalable Learning-Based Sampling Optimization for Compressive Dynamic MRI

Learning-Based Compressive MRI

Learning-Based Compressive Subsampling

A Primal-dual Framework For Mixtures Of Regularisers

Metric Learning with Rank and Sparsity Constraints

Manifold Sparse Beamforming

Learning-based subsampling