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TNN
2010
216views Management» more  TNN 2010»
13 years 3 months ago
Simplifying mixture models through function approximation
Finite mixture model is a powerful tool in many statistical learning problems. In this paper, we propose a general, structure-preserving approach to reduce its model complexity, w...
Kai Zhang, James T. Kwok
ICPR
2008
IEEE
14 years 9 months ago
K-means clustering of proportional data using L1 distance
We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
CVPR
2009
IEEE
14 years 12 days ago
Nonnegative Matrix Factorization with Earth Mover's Distance metric
Nonnegative Matrix Factorization (NMF) approximates a given data matrix as a product of two low rank nonnegative matrices, usually by minimizing the L2 or the KL distance between ...
Roman Sandler, Michael Lindenbaum
CORR
2011
Springer
214views Education» more  CORR 2011»
13 years 8 days ago
K-Median Clustering, Model-Based Compressive Sensing, and Sparse Recovery for Earth Mover Distance
We initiate the study of sparse recovery problems under the Earth-Mover Distance (EMD). Specifically, we design a distribution over m × n matrices A such that for any x, given A...
Piotr Indyk, Eric Price
CORR
2004
Springer
168views Education» more  CORR 2004»
13 years 8 months ago
Estimating Genome Reversal Distance by Genetic Algorithm
Sorting by reversals is an important problem in inferring the evolutionary relationship between two genomes. The problem of sorting unsigned permutation has been proven to be NP-ha...
Andy Auyeung, Ajith Abraham