Fast Manifold Learning

Fast Manifold Learning

A Workshop on Scalable Algorithms for Nonlinear Dimension Reduction

Fast Manifold Learning will be held April 14-15 at the College of William & Mary in Williamsburg, VA. Participation is by invitation; however, we may have room for a few extra people. Please contact the organizers, Michael Trosset and Carey Priebe, if you are interested in attending.

Information

Attendees

Schedule

Travel

Accommodations

Meals

Presentations

Neighbourhood Component Analysis, by Sam Roweis, University of Toronto.
State-of-the-art Methods and Software for Solving Large Hermitian Eigenvalue Problems, by Andreas Stathopoulos, College of William & Mary.
Non-Euclidean Multidimensional Scaling, by Jeffrey Solka, Naval Surface Warfare Center.

Sponsors
Fast Manifold Learning is sponsored by the ASA Section on Statistical Computing, the Interface Foundation of North America, the Office of Naval Research, the William & Mary Research Institute, and AlgoTek.