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PR
2010
129views more  PR 2010»
13 years 7 months ago
Parsimonious reduction of Gaussian mixture models with a variational-Bayes approach
Aggregating statistical representations of classes is an important task for current trends in scaling up learning and recognition, or for addressing them in distributed infrastruc...
Pierrick Bruneau, Marc Gelgon, Fabien Picarougne
ISDA
2010
IEEE
13 years 6 months ago
Self-adaptive Gaussian mixture models for real-time video segmentation and background subtraction
The usage of Gaussian mixture models for video segmentation has been widely adopted. However, the main difficulty arises in choosing the best model complexity. High complex models ...
Nicola Greggio, Alexandre Bernardino, Cecilia Lasc...
JMLR
2010
155views more  JMLR 2010»
13 years 7 months ago
Approximate Tree Kernels
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...
NIPS
2004
13 years 10 months ago
Assignment of Multiplicative Mixtures in Natural Images
In the analysis of natural images, Gaussian scale mixtures (GSM) have been used to account for the statistics of filter responses, and to inspire hierarchical cortical representat...
Odelia Schwartz, Terrence J. Sejnowski, Peter Daya...
ICPR
2010
IEEE
13 years 7 months ago
Variational Mixture of Experts for Classification with Applications to Landmine Detection
Abstract--In this paper, we (1) provide a complete framework for classification using Variational Mixture of Experts (VME); (2) derive the variational lower bound; and (3) apply th...
Seniha Esen Yuksel, Paul D. Gader