Adaptive manifold learning

Advances in Neural Information Processing Systems

Volumn , Issue , 2005, Pages

  Wang, Jing ^a   Zhang, Zhenyue ^a   Zha, Hongyuan ^b  

^a ZHEJIANG UNIVERSITY   (China)

^b The Pennsylvania State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING ALGORITHMS; PATTERN RECOGNITION;

ADAPTIVE SELECTION; HIGH DIMENSIONAL SPACES; LOCAL GEOMETRIC STRUCTURES; LOW-DIMENSIONAL MANIFOLDS; MANIFOLD LEARNING; MANIFOLD LEARNING ALGORITHM; SAMPLING DENSITIES; SYNTHETIC DATASETS;

CURVE FITTING;

EID: 84898976138     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. M. Brand. Charting a manifold. Advances in Neural Information Processing Systems, 15, MIT Press, 2003.
2. D. Donoho and C. Grimes. Hessian Eigenmaps: new tools for nonlinear dimensionality reduction. Proceedings of National Academy of Science, 5591-5596, 2003.
3. S. Roweis and L. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, 290: 2323-2326, 2000.
4. L. Saul and S. Roweis. Think globally, fit locally: unsupervised learning of nonlinear manifolds. Journal of Machine Learning Research, 4:119-155, 2003.
5. E. Teh and S. Roweis. Automatic Alignment of Local Representations. Advances in Neural Information Processing Systems, 15, MIT Press, 2003.
6. J. Tenenbaum, V. De Silva and J. Langford. A global geometric framework for nonlinear dimension reduction. Science, 290:2319-2323, 2000.
7. Z. Zhang and H. Zha. Principal Manifolds and Nonlinear Dimensionality Reduction via Tangent Space Alignment. SIAM J. Scientific Computing, 26:313-338, 2004.
8. J. Wang, Z. Zhang and H. Zha. Adaptive Manifold Learning. Technical Report CSE- 04-21, Dept. CSE, Pennsylvania State University, 2004.