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131
Voted
NIPS
2003
15 years 5 months ago
2003
What happens to the optimal interpretation of noisy data when there exists more than one equally plausible interpretation of the data? In a Bayesian model-learning framework the a...
158
Voted
CVPR
2012
IEEE
13 years 6 months ago
2012
IEEE
We describe a method for learning steerable deformable part models. Our models exploit the fact that part templates can be written as linear filter banks. We demonstrate that one...
114
Voted
NECO
2002
15 years 3 months ago
2002
A Bayesian ensemble learning method is introduced for unsupervised extraction of dynamic processes from noisy data. The data are assumed to be generated by an unknown nonlinear ma...
180
Voted
JMLR
2012
13 years 6 months ago
2012
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
150
Voted
ICML
2007
IEEE
16 years 4 months ago
2007
IEEE
In many prediction tasks, selecting relevant features is essential for achieving good generalization performance. Most feature selection algorithms consider all features to be a p...