Manifold Learning and Its Applications
Papers from the 2009 AAAI Fall Symposium
Richard Souvenir Program Chair
Technical Report FS-09-04. Published by The AAAI Press, Menlo Park, California
This technical report is also available in book and CD format.
Contents
Sparse Geodesic Paths
Mark A. Davenport, Richard G. Baraniuk
Interactive Learning Using Manifold Geometry
Eric Eaton, Gary Holness, Daniel McFarlane
MiPPS: A Generative Model for Multi-Manifold Clustering
Oluwasanmi Koyejo, Joydeep Ghosh
Multiscale Estimation of Intrinsic Dimensionality of Data Sets
Anna V. Little, Yoon-Mo Jung, Mauro Maggioni
Learning Topology of Curves with Application to Clustering
Hossein Mobahi, Shankar Rao, Yi Ma
Robust Laplacian Eigenmaps Using Global Information
Shounak Roychowdhury
Mesh Segmentation Using Laplacian Eigenvectors and Gaussian Mixtures
Avinash Sharma, Radu Patrice Horaud, David Knossow, Etienne von Lavante
Semi-Supervised Learning Using Sparse Eigenfunction Bases
Kaushik Sinha, Mikhail Belkin
Sensor Map Discovery for Developing Robots
Jeremy Stober, Lewis Fishgold, Benjamin Kuipers
Illumination Invariant Face Recognition on Nonlinear Manifolds
Birkan Tunc, Muhittin Gökmen
A General Framework for Manifold Alignment
Chang Wang, Sridhar Mahadevan
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