Publications related to Dictionary preconditioning for greedy algorithms

Learned Compressive Representations for Single-Photon 3D Imaging

Edoardo Charbon, Claudio Bruschini, Andrei Ardelean, Mohit Gupta

Single-photon 3D cameras can record the time-of-arrival of billions of photons per second with picosecond accuracy. One common approach to summarize the photon data stream is to build a per-pixel timestamp histogram, resulting in a 3D histogram tensor that ...

Ieee Computer Soc2023

Sub-Matrix Factorization for Real-Time Vote Prediction

Patrick Thiran, Matthias Grossglauser, Victor Kristof

We address the problem of predicting aggregate vote outcomes (e.g., national) from partial outcomes (e.g., regional) that are revealed sequentially. We combine matrix factorization techniques and generalized linear models (GLMs) to obtain a flexible, effic ...

2020

Convex Optimization Approaches for Blind Sensor Calibration using Sparsity

Rémi Gribonval, Gilles Puy

We investigate a compressive sensing framework in which the sensors introduce a distortion to the measurements in the form of unknown gains. We focus on blind calibration, using measures performed on multiple unknown (but sparse) signals and formulate the ...

Institute of Electrical and Electronics Engineers2014

Jump-Sparse and Sparse Recovery Using Potts Functionals

Martin Kurt Storath

We recover jump-sparse and sparse signals from blurred incomplete data corrupted by (possibly non-Gaussian) noise using inverse Potts energy functionals. We obtain analytical results (existence of minimizers, complexity) on inverse Potts functionals and pr ...

Ieee-Inst Electrical Electronics Engineers Inc2014

LAYOUT ASSESSMENT METHOD AND SYSTEM

Frank Grégoire Jean de Morsier, Virginia Estellers Casas, Nathalie Casati, Maria Gabrani

Candidate layout patterns can be assessed using a sparse pattern dictionary of known design layout patterns by determining sparse coefficients for each candidate pattern, reconstructing the respective candidate pattern, and determining reconstruction error ...

U.S. Patent and Trademark Office; U.S. DEPARTMENT OF COMMERCE2013

A geometric framework for registration of sparse images

Pascal Frossard, Alhussein Fawzi

We examine the problem of image registration when images have a sparse representation in a dictionary of geometric features. We propose a novel algorithm for aligning images by pairing their sparse components. We show numerically that this algorithm works ...

2013

Image registration with sparse approximations in parametric dictionaries

Pascal Frossard, Alhussein Fawzi

We examine in this paper the problem of image registration from the new perspective where images are given by sparse approximations in parametric dictionaries of geometric functions. We propose a registration algorithm that looks for an estimate of the glo ...

2013

Hard Thresholding with Norm Constraints

Volkan Cevher, Gilles Puy, Anastasios Kyrillidis

We introduce a new sparse recovery paradigm, called Normed Pursuits, where efficient algorithms from combinatorial and convex optimization interface for interpretable and model-based solutions. Synthetic and real data experiments illustrate that Normed Pur ...

Ieee2012

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding

Pascal Frossard, Pierre Vandergheynst, Adel Rahmoune

This paper introduces a novel algorithm for sparse approximation in redundant dictionaries called the M-term pursuit (MTP). This algorithm decomposes a signal into a linear combination of atoms that are selected in order to represent the main signal compon ...

Institute of Electrical and Electronics Engineers2012

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Volkan Cevher, Anastasios Kyrillidis

The least absolute shrinkage and selection operator (LASSO) for linear regression exploits the geometric interplay of the

\ell_2

-data error objective and the

\ell_1

-norm constraint to arbitrarily select sparse models. Guiding this uninformed selection ...

IEEE2012

Dictionary preconditioning for greedy algorithms

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Learned Compressive Representations for Single-Photon 3D Imaging

Sub-Matrix Factorization for Real-Time Vote Prediction

Convex Optimization Approaches for Blind Sensor Calibration using Sparsity

Jump-Sparse and Sparse Recovery Using Potts Functionals

LAYOUT ASSESSMENT METHOD AND SYSTEM

A geometric framework for registration of sparse images

Image registration with sparse approximations in parametric dictionaries

Hard Thresholding with Norm Constraints

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Convex Optimization Approaches for Blind Sensor Calibration using Sparsity

Learned Compressive Representations for Single-Photon 3D Imaging

Sub-Matrix Factorization for Real-Time Vote Prediction

LAYOUT ASSESSMENT METHOD AND SYSTEM

Hard Thresholding with Norm Constraints

Sparse Approximation Using M-Term Pursuit and Application in Image and Video Coding

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Jump-Sparse and Sparse Recovery Using Potts Functionals

A geometric framework for registration of sparse images

Image registration with sparse approximations in parametric dictionaries