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» An overview of clustering methods
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91
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NIPS
2007
15 years 1 months ago
Expectation Maximization and Posterior Constraints
The expectation maximization (EM) algorithm is a widely used maximum likelihood estimation procedure for statistical models when the values of some of the variables in the model a...
João Graça, Kuzman Ganchev, Ben Task...
111
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SDM
2007
SIAM
118views Data Mining» more  SDM 2007»
15 years 1 months ago
On Privacy-Preservation of Text and Sparse Binary Data with Sketches
In recent years, privacy preserving data mining has become very important because of the proliferation of large amounts of data on the internet. Many data sets are inherently high...
Charu C. Aggarwal, Philip S. Yu
104
Voted
VMV
2008
120views Visualization» more  VMV 2008»
15 years 1 months ago
Thinning Mesh Animations
Three-dimensional animation sequences are often represented by a discrete set of compatible triangle meshes. In order to create the illusion of a smooth motion, a sequence usually...
Tim Winkler, Jens Drieseberg, Kai Hormann, Alexand...
123
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PDCN
2004
15 years 1 months ago
Caching large files by using P2P based client-cluster for web proxy cache
Many web cache systems and policies have been proposed. These studies, however, consider large sized objects less useful than small sized objects for the performance and evict the...
Kyungbaek Kim, Daeyeon Park
109
Voted
ACL
1998
15 years 1 months ago
Dialogue Act Tagging with Transformation-Based Learning
For the task of recognizing dialogue acts, we are applying the Transformation-Based Learning (TBL) machine learning algorithm. To circumvent a sparse data problem, we extract valu...
Ken Samuel, Sandra Carberry, K. Vijay-Shanker