The convex geometry of linear inverse problems
V Chandrasekaran, B Recht, PA Parrilo… - Foundations of …, 2012 - Springer
In applications throughout science and engineering one is often faced with the challenge of
solving an ill-posed inverse problem, where the number of available measurements is …
solving an ill-posed inverse problem, where the number of available measurements is …
Computational drug repositioning using low-rank matrix approximation and randomized algorithms
Motivation Computational drug repositioning is an important and efficient approach towards
identifying novel treatments for diseases in drug discovery. The emergence of large-scale …
identifying novel treatments for diseases in drug discovery. The emergence of large-scale …
Beyond Nyquist: Efficient sampling of sparse bandlimited signals
Wideband analog signals push contemporary analog-to-digital conversion (ADC) systems to
their performance limits. In many applications, however, sampling at the Nyquist rate is …
their performance limits. In many applications, however, sampling at the Nyquist rate is …
Signal recovery from incomplete and inaccurate measurements via regularized orthogonal matching pursuit
D Needell, R Vershynin - IEEE Journal of selected topics in …, 2010 - ieeexplore.ieee.org
We demonstrate a simple greedy algorithm that can reliably recover a vector v¿¿ d from
incomplete and inaccurate measurements x=¿ v+ e. Here,¿ is a N xd measurement matrix …
incomplete and inaccurate measurements x=¿ v+ e. Here,¿ is a N xd measurement matrix …
Augmented Lagrangian method, dual methods, and split Bregman iteration for ROF, vectorial TV, and high order models
C Wu, XC Tai - SIAM Journal on Imaging Sciences, 2010 - SIAM
In image processing, the Rudin–Osher–Fatemi (ROF) model [L. Rudin, S. Osher, and E.
Fatemi, Phys. D, 60 (1992), pp. 259–268] based on total variation (TV) minimization has …
Fatemi, Phys. D, 60 (1992), pp. 259–268] based on total variation (TV) minimization has …
A fast algorithm for edge-preserving variational multichannel image restoration
Variational models with \ell_1-norm based regularization, in particular total variation (TV)
and its variants, have long been known to offer superior image restoration quality, but …
and its variants, have long been known to offer superior image restoration quality, but …
[PDF][PDF] Fast linearized Bregman iteration for compressive sensing and sparse denoising
We propose and analyze an extremely fast, efficient, and simple method for solving the
problem: min {u1: Au= f, u∈ Rn}. This method was first described in [J. Darbon and S. Osher …
problem: min {u1: Au= f, u∈ Rn}. This method was first described in [J. Darbon and S. Osher …
A fast algorithm for Euler's elastica model using augmented Lagrangian method
Minimization of functionals related to Euler's elastica energy has a wide range of
applications in computer vision and image processing. A high order nonlinear partial …
applications in computer vision and image processing. A high order nonlinear partial …
Augmented Lagrangian method, dual methods and split Bregman iteration for ROF model
XC Tai, C Wu - International conference on scale space and …, 2009 - Springer
In the recent decades the ROF model (total variation (TV) minimization) has made great
successes in image restoration due to its good edge-preserving property. However, the non …
successes in image restoration due to its good edge-preserving property. However, the non …
[PDF][PDF] Augmented Lagrangian method for total variation restoration with non-quadratic fidelity
Recently augmented Lagrangian method has been successfully applied to image
restoration. We extend the method to total variation (TV) restoration models with non …
restoration. We extend the method to total variation (TV) restoration models with non …