Call For Papers
Novel Applications of Dimensionality Reduction
http://www.seas.upenn.edu/
Workshop held at the 20th Annual Conference
on Neural Information Processing Systems
(NIPS 2006)
Whistler, CANADA: December 8, 2006
Dimensionality reduction is an important research topic in machine learning that is motivated by several needs, including data visualization and representation, discovering meaningful underlying structures, reducing computational complexity, and improving accuracy by avoiding overfitting due to data sparsity...