16 search results - page 2 / 4 » Extracting Principal Components from Pseudo-random Data by U... |
BMCBI
2010
13 years 5 months ago
2010
Background: Nonnegative Matrix Factorization (NMF) is an unsupervised learning technique that has been applied successfully in several fields, including signal processing, face re...
ESANN
2006
13 years 7 months ago
2006
Random Forests were introduced by Breiman for feature (variable) selection and improved predictions for decision tree models. The resulting model is often superior to AdaBoost and ...
NIPS
1997
13 years 7 months ago
1997
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
SIGIR
2003
ACM
13 years 11 months ago
2003
ACM
The ability to find tables and extract information from them is a necessary component of data mining, question answering, and other information retrieval tasks. Documents often c...
ICPR
2006
IEEE
14 years 6 months ago
2006
IEEE
This paper describes a new motion based feature extraction technique for speaker identification using orientation estimation in 2D manifolds. The motion is estimated by computing ...