Publications related to Ridge regression

Orientation invariant and non-parametric Axon Diameter Distribution mapping using PGSE and regularized discrete linear modeling

Jean-Philippe Thiran, David Paul Roger Romascano, Alessandro Daducci, Muhamed Barakovic, Anna Auria Rasclosa, Tim Bjørn Dyrby

Axon Diameter Distributions (ADDs) change during brain development and are altered in several brain pathologies. Mapping ADDs non-invasively using dMRI could provide a useful biomarker, but existing methods are either parametric, orientation dependent, sur ...

2017

A FUNCTIONAL FRAMEWORK FOR ULTRASOUND IMAGING

Paul Hurley, Matthieu Martin Jean-André Simeoni

Delay-And-Sum (DAS), the state-of-art in ultrasound imaging, is known to be sub-optimal, resulting in low resolution and contrast. Most proposed improvements involve ad-hoc re-weighting, or hit computational bottlenecks given real-time requirements. This p ...

2017

Method and apparatus for wireless validation

Serge Vaudenay, Handan Kilinç Alper

A wireless validation method between an first apparatus and a second apparatus comprising the following steps of communicating between the first apparatus and the second apparatus for agreeing in a protected way on a common symmetric key and performing a s ...

2017

Comparing molecules and solids across structural and alchemical space

Michele Ceriotti, Sandip De

Evaluating the (dis)similarity of crystalline, disordered and molecular compounds is a critical step in the development of algorithms to navigate automatically the configuration space of complex materials. For instance, a structural similarity metric is cr ...

Royal Society of Chemistry2016

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Michaël Unser, Julien René Pierre Fageot, Harshit Gupta

We present a theoretical analysis and comparison of the effect of

ℓ _{ 1 }

versus

ℓ _{ 2 }

regularization for the resolution of ill-posed linear inverse and/or compressed sensing problems. Our formulation covers the most general setting where the s ...

IEEE2016

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

Emrah Bostan

We propose new regularization models to solve inverse problems encountered in biomedical imaging applications. In formulating mathematical schemes, we base our approach on the sparse signal processing principles that have emerged as a central paradigm in t ...

EPFL2016

Diffusion stochastic optimization with non-smooth regularizers

Ali H. Sayed, Stefan Vlaski

We develop an effective distributed strategy for seeking the Pareto solution of an aggregate cost consisting of regularized risks. The focus is on stochastic optimization problems where each risk function is expressed as the expectation of some loss functi ...

IEEE2016

A Study on Estimating the Next Failure Time of Compressor Equipment in an Offshore Plant

Jongho Shin, Sangje Cho

The offshore plant equipment usually has a long life cycle. During its O&M (Operation and Maintenance) phase, since the accidental occurrence of offshore plant equipment causes catastrophic damage, it is necessary to make more efforts for managing critical ...

Hindawi Limited2016

Group-Sparse Model Selection: Hardness and Relaxations

Volkan Cevher, Anastasios Kyrillidis, Luca Baldassarre, Nirav Bhan

Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. The main promise of these models is the recovery of ``interpretable" signals along with ...

Institute of Electrical and Electronics Engineers2016

Morphological component analysis for sparse regularization in plane wave imaging

Jean-Philippe Thiran, Yves Wiaux, Dimitris Perdios, Eric Bezzam, Rafael Eduardo Carrillo Rangel, Marcel Arditi, Adrien Georges Jean Besson

Classical ultrasound image reconstruction mainly relies on the well-known delay-and-sum (DAS) beamforming for its simplicity and real-time capability. Sparse regularization methods propose an alternative to DAS which lead to a better inversion of the ill-p ...

Ieee2016

Ridge regression

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Orientation invariant and non-parametric Axon Diameter Distribution mapping using PGSE and regularized discrete linear modeling

A FUNCTIONAL FRAMEWORK FOR ULTRASOUND IMAGING

Method and apparatus for wireless validation

Comparing molecules and solids across structural and alchemical space

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

Diffusion stochastic optimization with non-smooth regularizers

A Study on Estimating the Next Failure Time of Compressor Equipment in an Offshore Plant

Group-Sparse Model Selection: Hardness and Relaxations

Morphological component analysis for sparse regularization in plane wave imaging

Sparsity-Based Data Reconstruction Models for Biomedical Imaging

A Study on Estimating the Next Failure Time of Compressor Equipment in an Offshore Plant

Orientation invariant and non-parametric Axon Diameter Distribution mapping using PGSE and regularized discrete linear modeling

A FUNCTIONAL FRAMEWORK FOR ULTRASOUND IMAGING

Comparing molecules and solids across structural and alchemical space

Group-Sparse Model Selection: Hardness and Relaxations

Morphological component analysis for sparse regularization in plane wave imaging

Method and apparatus for wireless validation

Representer Theorems for Sparsity-Promoting $ ℓ _{ 1 } $ Regularization

Diffusion stochastic optimization with non-smooth regularizers