148 search results - page 11 / 30 » DiscLDA: Discriminative Learning for Dimensionality Reductio... |
PAA
2008
13 years 7 months ago
2008
This paper proposes a method of finding a discriminative linear transformation that enhances the data's degree of conformance to the compactness hypothesis and its inverse. Th...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
In machine learning problems with tens of thousands of features and only dozens or hundreds of independent training examples, dimensionality reduction is essential for good learni...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
Dimensionality reduction is an important pre-processing step for many applications. Linear Discriminant Analysis (LDA) is one of the well known methods for supervised dimensionali...
ICML
2005
IEEE
14 years 8 months ago
2005
IEEE
Linear discriminant analysis (LDA) has been an active topic of research during the last century. However, the existing algorithms have several limitations when applied to visual d...
ICIP
2010
IEEE
13 years 5 months ago
2010
IEEE
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...