CFP: Novel Applications of Dimensionality Reduction

Call For Papers

Novel Applications of Dimensionality Reduction
http://www.seas.upenn.edu/~kilianw/nldrworkshop06

          Workshop held at the 20th Annual Conference
            on Neural Information Processing Systems
                          (NIPS 2006)

              Whistler, CANADA: December 8, 2006

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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...

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