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91
Voted
NIPS
2004
14 years 11 months ago
2004
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
111
Voted
SSPR
2010
Springer
14 years 8 months ago
2010
Springer
Mixture models have been widely used for data clustering. However, commonly used mixture models are generally of a parametric form (e.g., mixture of Gaussian distributions or GMM),...
74
Voted
FTML
2010
14 years 8 months ago
2010
We give a tutorial overview of several geometric methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the da...
89
Voted
ICDM
2010
IEEE
14 years 7 months ago
2010
IEEE
Abstract--Most well-known discriminative clustering models, such as spectral clustering (SC) and maximum margin clustering (MMC), are non-Bayesian. Moreover, they merely considered...
ICCV
2009
IEEE
16 years 3 months ago
2009
IEEE
We propose an unconventional but highly effective approach
to robust fitting of multiple structures by using statistical
learning concepts. We design a novel Mercer kernel
for t...