Publications related to Saddle-to-Saddle Dynamics in Diagonal Linear Networks

Towards More Accurate and Efficient Beamformed Radio Interferometry Imaging

The Square Kilometre Array (SKA) will form the largest radio telescope ever built, generating on the order of one terabyte of data per second. To reduce the data flow sent to the central processor, hierarchical designs have been proposed: the data is prima ...

2015

Multitask diffusion LMS with sparsity-based regularization

Ali H. Sayed, Roula Nassif

In this work, a diffusion-type algorithm is proposed to solve multitask estimation problems where each cluster of nodes is interested in estimating its own optimum parameter vector in a distributed manner. The approach relies on minimizing a global mean-sq ...

IEEE2015

Fast Process Variation Analysis in Nano-Scaled Technologies Using Column-Wise Sparse Parameter Selection

Giovanni De Micheli, Pierre-Emmanuel Julien Marc Gaillardon, Majid Yazdani, Hassan Ghasemzadeh Mohammadi

With growing concern about process variation in deeply nano-scaled technologies, parameterized device and circuit modeling is becoming very important for design and verification. However, the high dimensionality of parameter space is a serious modeling cha ...

2014

Compressible distributions for high-dimensional statistics

Volkan Cevher, Rémi Gribonval

We develop a principled way of identifying probability distributions whose independent and identically distributed realizations are compressible, i.e., can be well approximated as sparse. We focus on Gaussian compressed sensing, an example of underdetermin ...

Institute of Mathematical Statistics2012

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

Fast Geodesic Active Fields for Image Registration based on Splitting and Augmented Lagrangian Approaches

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso

In this paper we present an efficient numerical scheme for the recently introduced Geodesic Active Fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, data-te ...

2011

Joint registration and super-resolution with omnidirectional images

Pascal Frossard, Zafer Arican

This paper addresses the reconstruction of high resolution omnidirectional images from multiple low resolution images with inexact registration. When omnidirectional images from low resolution vision sensors can be uniquely mapped on the 2-sphere, such a r ...

Institute of Electrical and Electronics Engineers2011

Nonideal sampling and regularized interpolation of noisy data

Sathish Ramani

Conventional sampling (Shannon's sampling formulation and its approximation-theoretic counterparts) and interpolation theories provide effective solutions to the problem of reconstructing a signal from its samples, but they are primarily restricted to the ...

EPFL2009

Joint registration and super-resolution with omnidirectional images

Pascal Frossard, Zafer Arican

This paper addresses the reconstruction of high resolution omnidirectional images from multiple low resolution images with inexact registration. When omnidirectional images from low resolution vision sensors can be uniquely mapped on the 2-sphere, such a r ...

2009

Nonideal Sampling and Regularization Theory

Michaël Unser, Dimitri Nestor Alice Van De Ville, Thierry Blu, Sathish Ramani

Shannon's sampling theory and its variants provide effective solutions to the problem of reconstructing a signal from its samples in some “shift-invariant” space, which may or may not be bandlimited. In this paper, we present some further justification for ...

IEEE2008

Saddle-to-Saddle Dynamics in Diagonal Linear Networks

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Towards More Accurate and Efficient Beamformed Radio Interferometry Imaging

Multitask diffusion LMS with sparsity-based regularization

Fast Process Variation Analysis in Nano-Scaled Technologies Using Column-Wise Sparse Parameter Selection

Compressible distributions for high-dimensional statistics

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Fast Geodesic Active Fields for Image Registration based on Splitting and Augmented Lagrangian Approaches

Joint registration and super-resolution with omnidirectional images

Nonideal sampling and regularized interpolation of noisy data

Joint registration and super-resolution with omnidirectional images

Nonideal Sampling and Regularization Theory

Compressible distributions for high-dimensional statistics

Nonideal sampling and regularized interpolation of noisy data

Fast Geodesic Active Fields for Image Registration based on Splitting and Augmented Lagrangian Approaches

Multitask diffusion LMS with sparsity-based regularization

Nonideal Sampling and Regularization Theory

Towards More Accurate and Efficient Beamformed Radio Interferometry Imaging

Fast Process Variation Analysis in Nano-Scaled Technologies Using Column-Wise Sparse Parameter Selection

Joint registration and super-resolution with omnidirectional images

Joint registration and super-resolution with omnidirectional images

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm