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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

Best, worst and average case

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Integration of a Real-Time Node for Magnetic Perturbations Signal Analysis in the Distributed Digital Control System of the TCV Tokamak

Jump-Penalized Least Absolute Values Estimation of Scalar or Circle-Valued Signals

Control-Quality Driven Design of Embedded Control Systems with Stability Guarantees

Synthesizing efficient systems in probabilistic environments

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From Acoustic Room Reconstruction to SLAM

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On convergence and performance certification of a continuous-time economic model predictive control scheme with time-varying performance index

Learning-Based Compressive Subsampling

Robustness of classifiers: from adversarial to random noise

Jump-Penalized Least Absolute Values Estimation of Scalar or Circle-Valued Signals

Synthesizing efficient systems in probabilistic environments

Worst-case execution time analysis for many-core architectures with NoC

Control-Quality Driven Design of Embedded Control Systems with Stability Guarantees

On convergence and performance certification of a continuous-time economic model predictive control scheme with time-varying performance index

SHAPE: Linear-Time Camera Pose Estimation With Quadratic Error-Decay

From Acoustic Room Reconstruction to SLAM

Learning-Based Compressive Subsampling

Robustness of classifiers: from adversarial to random noise

Integration of a Real-Time Node for Magnetic Perturbations Signal Analysis in the Distributed Digital Control System of the TCV Tokamak