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TNN
2011
107views more  TNN 2011»
13 years 2 months ago
Iterative Gaussianization: From ICA to Random Rotations
Abstract—Most signal processing problems involve the challenging task of multidimensional probability density function (PDF) estimation. In this paper, we propose a solution to t...
Valero Laparra, Gustavo Camps-Valls, Jesus Malo
ICANN
2005
Springer
14 years 1 months ago
The LCCP for Optimizing Kernel Parameters for SVM
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
Sabri Boughorbel, Jean-Philippe Tarel, Nozha Bouje...
ICASSP
2010
IEEE
13 years 7 months ago
Summarization- and learning-based approaches to information distillation
Information distillation is the task that aims to extract relevant passages of text from massive volumes of textual and audio sources, given a query. In this paper, we investigate...
Boriska Toth, Dilek Hakkani-Tür, Sibel Yaman
FTML
2008
185views more  FTML 2008»
13 years 7 months ago
Graphical Models, Exponential Families, and Variational Inference
The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate stat...
Martin J. Wainwright, Michael I. Jordan
TIT
1998
80views more  TIT 1998»
13 years 7 months ago
Structural Risk Minimization Over Data-Dependent Hierarchies
The paper introduces some generalizations of Vapnik’s method of structural risk minimisation (SRM). As well as making explicit some of the details on SRM, it provides a result t...
John Shawe-Taylor, Peter L. Bartlett, Robert C. Wi...