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ICML
2009
IEEE
16 years 8 months ago
Large-scale deep unsupervised learning using graphics processors
The promise of unsupervised learning methods lies in their potential to use vast amounts of unlabeled data to learn complex, highly nonlinear models with millions of free paramete...
Rajat Raina, Anand Madhavan, Andrew Y. Ng
ICML
2005
IEEE
16 years 8 months ago
Learning first-order probabilistic models with combining rules
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
Sriraam Natarajan, Prasad Tadepalli, Eric Altendor...
ICML
2004
IEEE
16 years 8 months ago
Generalized low rank approximations of matrices
The problem of computing low rank approximations of matrices is considered. The novel aspect of our approach is that the low rank approximations are on a collection of matrices. W...
Jieping Ye
WWW
2007
ACM
16 years 7 months ago
Determining the user intent of web search engine queries
Determining the user intent of Web searches is a difficult problem due to the sparse data available concerning the searcher. In this paper, we examine a method to determine the us...
Bernard J. Jansen, Danielle L. Booth, Amanda Spink
WWW
2006
ACM
16 years 7 months ago
Large-scale text categorization by batch mode active learning
Large-scale text categorization is an important research topic for Web data mining. One of the challenges in large-scale text categorization is how to reduce the amount of human e...
Steven C. H. Hoi, Rong Jin, Michael R. Lyu
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