Publications related to CoCoA: A General Framework for Communication-Efficient Distributed Optimization

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

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

A Signal Processing Approach to Generalized 1-D Total Variation

Dimitri Nestor Alice Van De Ville, Fikret Isik Karahanoglu, Ilker Bayram

Total variation (TV) is a powerful method that brings great benefit for edge-preserving regularization. Despite being widely employed in image processing, it has restricted applicability for 1-D signal processing since piecewise-constant signals form a rat ...

Institute of Electrical and Electronics Engineers2011

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

Framework for explicit drift correction in multivariate calibration models

Dominique Bonvin, Michael Amrhein, Pamandeep Singh Gujral

Latent-variable calibrations using principal component regression and partial least-squares regression are often compromised by drift such as systematic disturbances and offsets. This paper presents a two-step framework that facilitates the evaluation and ...

Wiley-Blackwell2010

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

On a doubly nonlinear diffusion model of chemotaxis with prevention of overcrowding

Ricardo Esteban Ruiz Baier

This paper addresses the existence and regularity of weak solutions for a fully parabolic model of chemotaxis, with prevention of overcrowding, that degenerates in a two-sided fashion, including an extra nonlinearity represented by a p-Laplacian diffusion ...

Wiley-Blackwell2009

Parametric B-Spline Snakes on Distance Maps—Application to Segmentation of Histology Images

Michaël Unser, Philippe Thévenaz, François Aguet, Chandra Sekhar Seelamantula

We construct parametric active contours (snakes) for outlining cells in histology images. These snakes are defined in terms of cubic B-spline basis functions. We use a steerable ridge detector for obtaining a reliable map of the cell boundaries. Using the ...

EURASIP2008

Regularized Robust Filters for Time-Varying Uncertain Discrete-Time Systems

Ali H. Sayed

This note develops robust filters for time-varying uncertain discrete-time systems. The developed filters are based on a data regularization solution and they enforce a minimum state-error variance property. Simulation results confirm their superior perfor ...

IEEE2004

Regularized Robust Estimators for Time Varying Uncertain Discrete-Time Systems

Ali H. Sayed

This paper addresses the issue of robust filtering for time varying uncertain discrete time systems. The proposed robust filters are based on a regularized least-squares formulation and guarantee minimum state error variances. Simulation results indicate t ...

2003

The analysis of kernel ridge regression learning algorithm.

Alexei Pozdnoukhov

The paper presents Kernel Ridge Regression, a nonlinear extension of the well known statistical model of ridge regression. New insights on the method are also presented. In particular, the connection between ridge regression and local translation-invariant ...

IDIAP2002

CoCoA: A General Framework for Communication-Efficient Distributed Optimization

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Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

A Signal Processing Approach to Generalized 1-D Total Variation

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

Framework for explicit drift correction in multivariate calibration models

Nonideal sampling and regularized interpolation of noisy data

On a doubly nonlinear diffusion model of chemotaxis with prevention of overcrowding

Parametric B-Spline Snakes on Distance Maps—Application to Segmentation of Histology Images

Regularized Robust Filters for Time-Varying Uncertain Discrete-Time Systems

Regularized Robust Estimators for Time Varying Uncertain Discrete-Time Systems

The analysis of kernel ridge regression learning algorithm.

A Signal Processing Approach to Generalized 1-D Total Variation

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

Combinatorial Selection and Least Absolute Shrinkage via the CLASH Algorithm

Framework for explicit drift correction in multivariate calibration models

Nonideal sampling and regularized interpolation of noisy data

The analysis of kernel ridge regression learning algorithm.

Regularized Robust Filters for Time-Varying Uncertain Discrete-Time Systems

Parametric B-Spline Snakes on Distance Maps—Application to Segmentation of Histology Images

Regularized Robust Estimators for Time Varying Uncertain Discrete-Time Systems

On a doubly nonlinear diffusion model of chemotaxis with prevention of overcrowding