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103
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ICML
2010
IEEE
15 years 1 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
148
Voted
ECCV
2006
Springer
16 years 2 months ago
2006
Springer
Since it is hard to handcraft the prior knowledge in a shape detection framework, machine learning methods are preferred to exploit the expert annotation of the target shape in a d...
89
Voted
ICML
2008
IEEE
16 years 1 months ago
2008
IEEE
Canonical Correlation Analysis (CCA) is a well-known technique for finding the correlations between two sets of multi-dimensional variables. It projects both sets of variables int...
134
Voted
ICML
2006
IEEE
16 years 1 months ago
2006
IEEE
Latent Dirichlet allocation (LDA) and other related topic models are increasingly popular tools for summarization and manifold discovery in discrete data. However, LDA does not ca...
98
Voted
ICML
2006
IEEE
16 years 1 months ago
2006
IEEE
Recently, a very appealing approach was proposed to compute the entire solution path for support vector classification (SVC) with very low extra computational cost. This approach ...