Publications associées à Iterative Learning Control Using Stochastic Approximation Theory with Application to a Mechatronic System

The $ L ^{ 1 } $ -Potts Functional for Robust Jump-Sparse Reconstruction

We investigate the nonsmooth and nonconvex

L ^{ 1 }

-Potts functional in discrete and continuous time. We show Γ-convergence of discrete

L ^{ 1 }

-Potts functionals toward their continuous counterpart and obtain a convergence statement for the corr ...

SIAM2015

The L-1-Potts Functional For Robust Jump-Sparse Reconstruction

Martin Kurt Storath

We investigate the nonsmooth and nonconvex L-1-Potts functional in discrete and continuous time. We show Gamma-convergence of discrete L-1-Potts functionals toward their continuous counterpart and obtain a convergence statement for the corresponding minimi ...

Siam Publications2015

A New Convergence Proof For The Higher-Order Power Method And Generalizations

André Uschmajew

A proof for the point-wise convergence of the factors in the higher-order power method for tensors towards a critical point is given. It is obtained by applying established results from the theory of Lojasiewicz inequalities to the equivalent, unconstraine ...

Yokohama Publ2015

Stable blow up dynamics for energy supercritical wave equations

Roland Donninger

We study the semilinear wave equation

\displaystyle \partial _t^2 \psi -\Delta \psi =\vert\psi \vert^{p-1}\psi

for

p > 3

with radial data in three spatial dimensions. There exists an explicit solution which blows up at

t=T>0

given by $\displaystyl ...

American Mathematical Society2014

Approximation theorems in metric spaces and functionals strictly subordinated to convergent series

Some new results are presented concerning the search and approximation of solutions of equations in metric spaces using functionals strictly subordinated to a convergent series and functionals compatible with a convergent series. These classes of functiona ...

Elsevier2014

PREDIcT: Towards Predicting the Runtime of Large Scale Iterative Analytics

Anastasia Ailamaki, Adrian Daniel Popescu

Machine learning algorithms are widely used today for analytical tasks such as data cleaning, data categorization, or data filtering. At the same time, the rise of social media motivates recent uptake in large scale graph processing. Both categories of alg ...

2013

Towards Predicting the Runtime of Iterative Analytics with PREDIcT

Anastasia Ailamaki, Adrian Daniel Popescu

Machine learning algorithms are widely used today for analytical tasks such as data cleaning, data categorization, or data filtering. At the same time, the rise of social media motivates recent uptake in large scale graph processing. Both categories of alg ...

EPFL2013

Using the interface Peclet number to select the maximum simulation interface width in phase-field solidification modelling

Jonathan Dantzig

This study investigates the use of interface Peclet number P = w/(D-l/V-tip), to determine the interface width (w) used in phase-field simulations, where D-l is the liquid diffusivity and V-tip is the tip velocity. The maximum simulation interface width (w ...

Elsevier2013

Gaze Evidence for Different Activities in Program Understanding

Pierre Dillenbourg, Patrick Jermann, Kshitij Sharma, Marc-Antoine Nüssli

We present an empirical study that illustrates the potential of dual eye-tracking to detect successful understanding and social processes during pair programming. The gaze of forty pairs of programmers was recorded during a program understanding task. An a ...

2012

Use of Learned Dictionaries in Tomographic Reconstruction

Martin Vetterli, Ivana Jovanovic, Vincent Etter

We study the use and impact of a dictionary in a tomographic reconstruction setup. First, we build two different dictionaries: one using a set of bases functions (Discrete Cosine Transform), and the other that is learned using patches extracted from traini ...

Spie-Int Soc Optical Engineering, Po Box 10, Bellingham, Wa 98227-0010 Usa2011

Iterative Learning Control Using Stochastic Approximation Theory with Application to a Mechatronic System

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The $ L ^{ 1 } $ -Potts Functional for Robust Jump-Sparse Reconstruction

The L-1-Potts Functional For Robust Jump-Sparse Reconstruction

A New Convergence Proof For The Higher-Order Power Method And Generalizations

Stable blow up dynamics for energy supercritical wave equations

Approximation theorems in metric spaces and functionals strictly subordinated to convergent series

PREDIcT: Towards Predicting the Runtime of Large Scale Iterative Analytics

Towards Predicting the Runtime of Iterative Analytics with PREDIcT

Using the interface Peclet number to select the maximum simulation interface width in phase-field solidification modelling

Gaze Evidence for Different Activities in Program Understanding

Use of Learned Dictionaries in Tomographic Reconstruction

A New Convergence Proof For The Higher-Order Power Method And Generalizations

The L-1-Potts Functional For Robust Jump-Sparse Reconstruction

The $ L ^{ 1 } $ -Potts Functional for Robust Jump-Sparse Reconstruction

Stable blow up dynamics for energy supercritical wave equations

Approximation theorems in metric spaces and functionals strictly subordinated to convergent series

Use of Learned Dictionaries in Tomographic Reconstruction

Using the interface Peclet number to select the maximum simulation interface width in phase-field solidification modelling

Gaze Evidence for Different Activities in Program Understanding

PREDIcT: Towards Predicting the Runtime of Large Scale Iterative Analytics

Towards Predicting the Runtime of Iterative Analytics with PREDIcT