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ALT
2003
Springer
14 years 1 months ago
Kernel Trick Embedded Gaussian Mixture Model
In this paper, we present a kernel trick embedded Gaussian Mixture Model (GMM), called kernel GMM. The basic idea is to embed kernel trick into EM algorithm and deduce a parameter ...
Jingdong Wang, Jianguo Lee, Changshui Zhang
ICDM
2008
IEEE
193views Data Mining» more  ICDM 2008»
13 years 11 months ago
Multiplicative Mixture Models for Overlapping Clustering
The problem of overlapping clustering, where a point is allowed to belong to multiple clusters, is becoming increasingly important in a variety of applications. In this paper, we ...
Qiang Fu, Arindam Banerjee
JMLR
2010
206views more  JMLR 2010»
12 years 11 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
IWANN
2005
Springer
13 years 10 months ago
Manifold Constrained Finite Gaussian Mixtures
In many practical applications, the data is organized along a manifold of lower dimension than the dimension of the embedding space. This additional information can be used when le...
Cédric Archambeau, Michel Verleysen
CVPR
2012
IEEE
11 years 7 months ago
Image categorization using Fisher kernels of non-iid image models
The bag-of-words (BoW) model treats images as an unordered set of local regions and represents them by visual word histograms. Implicitly, regions are assumed to be identically an...
Ramazan Gokberk Cinbis, Jakob J. Verbeek, Cordelia...