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» Modeling High-Dimensional Index Structures using Sampling
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KDD
2009
ACM
191views Data Mining» more  KDD 2009»
15 years 11 months ago
Efficient methods for topic model inference on streaming document collections
Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
Limin Yao, David M. Mimno, Andrew McCallum
BMCBI
2011
14 years 6 months ago
RAIphy: Phylogenetic classification of metagenomics samples using iterative refinement of relative abundance index profiles
Background: Computational analysis of metagenomes requires the taxonomical assignment of the genome contigs assembled from DNA reads of environmental samples. Because of the diver...
Ozkan U. Nalbantoglu, Samuel F. Way, Steven H. Hin...
NIPS
1997
15 years 12 days ago
EM Algorithms for PCA and SPCA
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
Sam T. Roweis
95
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APPROX
2008
Springer
119views Algorithms» more  APPROX 2008»
15 years 1 months ago
The Complexity of Distinguishing Markov Random Fields
Abstract. Markov random fields are often used to model high dimensional distributions in a number of applied areas. A number of recent papers have studied the problem of reconstruc...
Andrej Bogdanov, Elchanan Mossel, Salil P. Vadhan
ICCV
2011
IEEE
14 years 2 months ago
Outdoor Human Motion Capture using Inverse Kinematics and von Mises-Fisher Sampling
Human motion capturing (HMC) from multiview image sequences constitutes an extremely difficult problem due to depth and orientation ambiguities and the high dimensionality of the s...
Gerard Pons-Moll, Andreas Baak, Juergen Gall, Laur...