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» Parallel matrix algorithms and applications
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133
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CVPR
2008
IEEE
16 years 6 months ago
Non-negative graph embedding
We introduce a general formulation, called non-negative graph embedding, for non-negative data decomposition by integrating the characteristics of both intrinsic and penalty graph...
Jianchao Yang, Shuicheng Yan, Yun Fu, Xuelong Li, ...
229
Voted
ICDE
2008
IEEE
139views Database» more  ICDE 2008»
16 years 5 months ago
Maintaining Connectivity in Dynamic Multimodal Network Models
Network data models are frequently used as a mechanism to describe the connectivity between spatial features in many emerging GIS applications (location-based services, transporta...
Petko Bakalov, Erik G. Hoel, Wee-Liang Heng, Vassi...
ICML
2007
IEEE
16 years 4 months ago
Full regularization path for sparse principal component analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
ICML
2006
IEEE
16 years 4 months ago
Constructing informative priors using transfer learning
Many applications of supervised learning require good generalization from limited labeled data. In the Bayesian setting, we can try to achieve this goal by using an informative pr...
Rajat Raina, Andrew Y. Ng, Daphne Koller
111
Voted
KDD
2006
ACM
136views Data Mining» more  KDD 2006»
16 years 4 months ago
Very sparse random projections
There has been considerable interest in random projections, an approximate algorithm for estimating distances between pairs of points in a high-dimensional vector space. Let A Rn...
Ping Li, Trevor Hastie, Kenneth Ward Church