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 International workshop on advances in Regularization, Optimization, Kernel methods and Support vector machines: theory and applications

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Ramla2010
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Ramla2010


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International workshop on advances in Regularization, Optimization, Kernel methods and Support vector machines: theory and applications Empty
MessageSujet: International workshop on advances in Regularization, Optimization, Kernel methods and Support vector machines: theory and applications   International workshop on advances in Regularization, Optimization, Kernel methods and Support vector machines: theory and applications Icon_minitimeLun 18 Fév 2013 - 19:55





LieuLeuven, Belgique
Résumé One
area of high impact both in theory and applications is kernel methods
and support vector machines. Optimization problems, learning and
representations of models are key ingredients in these methods. On the
other hand considerable progress has also been made on regularization of
parametric models, including methods for compressed sensing and
sparsity, where convex optimization plays a prominent role. The aim of
ROKS-2013 is to provide a multi-disciplinary forum where researchers of
different communities can meet, to find new synergies along these areas,
both at the level of theory and applications.
Sujets The
scope includes but is not limited to: - Regularization: L2, L1, Lp,
lasso, group lasso, elastic net, spectral regularization, nuclear norm,
others - Support vector machines, least squares support vector machines,
kernel methods, gaussian processes and graphical models - Lagrange
duality, Fenchel duality, estimation in Hilbert spaces, reproducing
kernel Hilbert spaces, Banach spaces, operator splitting - Optimization
formulations, optimization algorithms - Supervised, unsupervised,
semi-supervised learning, inductive and transductive learning -
Multi-task learning, multiple kernel learning, choice of kernel
functions, manifold learning - Prior knowledge incorporation -
Approximation theory, learning theory, statistics - Matrix and tensor
completion, learning with tensors - Feature selection, structure
detection, regularization paths, model selection - Sparsity and
interpretability - On-line learning and optimization - Applications in
machine learning, computational intelligence, pattern analysis, system
identification, signal processing, networks, datamining, others -
Software
Page web http://www.esat.kuleuven.be/sista/ROKS2013
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International workshop on advances in Regularization, Optimization, Kernel methods and Support vector machines: theory and applications
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