764 search results - page 8 / 153 » Maximum-Margin Matrix Factorization |
SDM
2012
SIAM
11 years 10 months ago
2012
SIAM
Finding latent factors of the data using matrix factorizations is a tried-and-tested approach in data mining. But finding shared factors over multiple matrices is more novel prob...
CIKM
2010
Springer
13 years 7 months ago
2010
Springer
Matrix factorization methods are among the most common techniques for detecting latent components in data. Popular examples include the Singular Value Decomposition or Nonnegative...
ICML
2010
IEEE
13 years 9 months ago
2010
IEEE
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
WWW
2010
ACM
14 years 3 months ago
2010
ACM
The Web abounds with dyadic data that keeps increasing by every single second. Previous work has repeatedly shown the usefulness of extracting the interaction structure inside dya...
JMLR
2010
13 years 6 months ago
2010
Sparse coding—that is, modelling data vectors as sparse linear combinations of basis elements—is widely used in machine learning, neuroscience, signal processing, and statisti...