10 search results - page 2 / 2 » Convergence rate of dimension reduction in Bose-Einstein con... |
SIAMMAX
2010
12 years 11 months ago
2010
Linear Discriminant Analysis (LDA) is one of the most popular approaches for feature extraction and dimension reduction to overcome the curse of the dimensionality of the high-dime...
SIGGRAPH
1996
ACM
13 years 8 months ago
1996
ACM
Antialiased pixel values are often computed as the mean of N point samples. Using uniformly distributed random samples, the central limit theorem predicts a variance of the mean o...
JMLR
2010
12 years 11 months ago
2010
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
ICDM
2008
IEEE
13 years 11 months ago
2008
IEEE
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...
ICML
2004
IEEE
14 years 5 months ago
2004
IEEE
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...