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» Dimensionality Reduction of Clustered Data Sets
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WWW
2008
ACM
14 years 9 months ago
Computable social patterns from sparse sensor data
We present a computational framework to automatically discover high-order temporal social patterns from very noisy and sparse location data. We introduce the concept of social foo...
Dinh Q. Phung, Brett Adams, Svetha Venkatesh
ICML
2006
IEEE
14 years 9 months ago
Local distance preservation in the GP-LVM through back constraints
The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
Joaquin Quiñonero Candela, Neil D. Lawrence
NAACL
2004
13 years 10 months ago
Name Tagging with Word Clusters and Discriminative Training
We present a technique for augmenting annotated training data with hierarchical word clusters that are automatically derived from a large unannotated corpus. Cluster membership is...
Scott Miller, Jethran Guinness, Alex Zamanian
SIGIR
2004
ACM
14 years 2 months ago
Document clustering via adaptive subspace iteration
Document clustering has long been an important problem in information retrieval. In this paper, we present a new clustering algorithm ASI1, which uses explicitly modeling of the s...
Tao Li, Sheng Ma, Mitsunori Ogihara
NIPS
2007
13 years 10 months ago
Random Projections for Manifold Learning
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
Chinmay Hegde, Michael B. Wakin, Richard G. Barani...