49 search results - page 2 / 10 » Factorized Orthogonal Latent Spaces |
NECO
1998
13 years 5 months ago
1998
Latent variable models represent the probability density of data in a space of several dimensions in terms of a smaller number of latent, or hidden, variables. A familiar example ...
CIKM
2010
Springer
13 years 3 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
2004
IEEE
14 years 6 months ago
2004
IEEE
We describe a class of causal, discrete latent variable models called Multiple Multiplicative Factor models (MMFs). A data vector is represented in the latent space as a vector of...
SCHOLARPEDIA
2008
13 years 4 months ago
2008
A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higher-order structure in the association of terms with documents (&q...
SIGIR
2005
ACM
13 years 11 months ago
2005
ACM
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...