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» Regularization Methods for Additive Models
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NIPS
2007
15 years 1 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
CVPR
2012
IEEE
13 years 2 months ago
Locality-constrained and spatially regularized coding for scene categorization
Improving coding and spatial pooling for bag-of-words based feature design have gained a lot of attention in recent works addressing object recognition and scene classification. ...
Aymen Shabou, Hervé Le Borgne
IPMI
2005
Springer
16 years 18 days ago
Fiber Tracking in q-Ball Fields Using Regularized Particle Trajectories
Abstract. Most of the approaches dedicated to fiber tracking from diffusionweighted MR data rely on a tensor model. However, the tensor model can only resolve a single fiber orient...
Muriel Perrin, Cyril Poupon, Yann Cointepas, Berna...
ICPR
2008
IEEE
16 years 29 days ago
Bregman distance to L1 regularized logistic regression
In this work we investigate the relationship between Bregman distances and regularized Logistic Regression model. We present a detailed study of Bregman Distance minimization, a f...
Mithun Das Gupta, Thomas S. Huang
CIKM
2008
Springer
15 years 1 months ago
Linear time membership in a class of regular expressions with interleaving and counting
The extension of Regular Expressions (REs) with an interleaving (shuffle) operator has been proposed in many occasions, since it would be crucial to deal with unordered data. Howe...
Giorgio Ghelli, Dario Colazzo, Carlo Sartiani