148 search results - page 6 / 30 » DiscLDA: Discriminative Learning for Dimensionality Reductio... |
SDM
2012
SIAM
11 years 10 months ago
2012
SIAM
To date, many active learning techniques have been developed for acquiring labels when training data is limited. However, an important aspect of the problem has often been neglect...
AAAI
2010
13 years 4 months ago
2010
Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...
SIAMMAX
2010
13 years 2 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...
KDD
2006
ACM
14 years 8 months ago
2006
ACM
Linear and Quadratic Discriminant Analysis have been used widely in many areas of data mining, machine learning, and bioinformatics. Friedman proposed a compromise between Linear ...
ECCV
2004
Springer
14 years 9 months ago
2004
Springer
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...