Concept

Elastic net regularization

Publications associées (144)

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On Regularized Reconstruction of Vector Fields

Michaël Unser, Pouya Dehghani Tafti

In this paper, we give a general characterization of regularization functionals for vector field reconstruction, based on the requirement that the said functionals satisfy certain geometric invariance properties with respect to transformations of the coord ...

IEEE2011

A Wearable Gaze Tracking System for Children in Unconstrained Environments

Aude Billard, Basilio Noris, Jean-Baptiste Keller

We present here a head-mounted gaze tracking system for the study of visual behavior in unconstrained environments. The system is designed both for adults and for infants as young as 1 year of age. The system uses two CCD cameras to record a very wide fiel ...

2011

Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning

Jie Luo

Many state-of-the-art approaches for Multi Kernel Learning (MKL) struggle at finding a compromise between performance, sparsity of the solution and speed of the optimization process. In this paper we look at the MKL problem at the same time from a learning ...

2011

Ultra-Fast Optimization Algorithm for Sparse Multi Kernel Learning

Jie Luo

Idiap2011

On multivariate calibration with unlabeled data

Dominique Bonvin, Michael Amrhein, Pamandeep Singh Gujral

In principal component regression (PCR) and partial least-squares regression (PLSR), the use of unlabeled data, in addition to labeled data, helps stabilize the latent subspaces in the calibration step, typically leading to a lower prediction error. A non- ...

Wiley-Blackwell2011

Regularized Interpolation for Noisy Images

Michaël Unser, Philippe Thévenaz, Sathish Ramani

Interpolation is the means by which a continuously defined model is fit to discrete data samples. When the data samples are exempt of noise, it seems desirable to build the model by fitting them exactly. In medical imaging, where quality is of paramount im ...

IEEE2010

An Efficient Numerical Method for General

Michaël Unser, Jean-Charles Baritaux, Kai Hassler

Reconstruction algorithms for fluorescence tomography have to address two crucial issues : 1) the ill-posedness of the reconstruction problem, 2) the large scale of numerical problems arising from imaging of 3-D samples. Our contribution is the design and ...

IEEE2010

Joint reconstruction of correlated images from compressed linear measurements

Pascal Frossard, Vijayaraghavan Thirumalai

This paper proposes a joint reconstruction algorithm for compressed correlated images that are given under the form of linear measurements. We first propose a geometry based model in order to describe the correlation between visual information in pairs of ...

2010

Geodesic Active Fields - A Geometric Framework for Image Registration

Jean-Philippe Thiran, Xavier Bresson, Dominique Zosso

In this paper we present a novel geometric framework called geodesic active fields for general image registration. In image registration, one looks for the underlying deformation field that best maps one image onto another. This is a classic ill-posed inve ...

Amer Inst Physics, 2 Huntington Quadrangle, Ste 1No1 D, Melville, Ny 11747-4501 Usa2010

Approximating Parameterized Convex Optimization Problems.

Martin Jaggi

We extend Clarkson's framework by considering parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an ε-approximate solution (and a corresponding ε-coreset) ...

2010