283
click to vote
ICML
16 years 7 months ago
2004 IEEE 
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
218
click to vote
ICML
16 years 7 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...
211
click to vote
ICML
16 years 12 days ago
2004 IEEE
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
210
click to vote
ICML
16 years 7 months ago
2004 IEEE 
In many application domains there is a large amount of unlabeled data but only a very limited amount of labeled training data. One general approach that has been explored for util...
210
click to vote
ICML
16 years 12 days ago
2004 IEEE
LASSO (Least Absolute Shrinkage and Selection Operator) is a useful tool to achieve the shrinkage and variable selection simultaneously. Since LASSO uses the L1 penalty, the optim...
|
Machine Learning