Parameter estimation for manifold learning, through density estimation

Proceedings of the 2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing, MLSP 2006

Volumn , Issue , 2006, Pages 211-216

  Vasiloglou, Nikolaos ^a   Gray, Alexander G ^a   Anderson, David V ^a  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BANDWIDTH; COMPUTATIONAL METHODS; LEARNING ALGORITHMS; PARAMETER ESTIMATION; PROBLEM SOLVING; STATISTICAL METHODS;

AUTOMATIC BANDWIDTH; KERNEL PARAMETER ESTIMATION; NONPARAMETRIC STATISTICAL THEORY ESTIMATION;

LEARNING SYSTEMS;

EID: 38949138425     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MLSP.2006.275550     Document Type: Conference Paper

References (7)

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2. Mikhail Belkin, "Problems of learning on manifolds," in PhD Thesis, University of Chicago, 2003.
3. [31 R. Jenssen, D. Erdogmus, JC Principe, and T. Eltoft, "The Laplacian PDF Distance: A Cost Function for Clustering in a Kernel Feature Space," Advances in Neural Information Processing Systems, vol. 17, pp. 625-632.
4. B.W.Silverman, Density Estimation for Statistics and Data Analysis, CRC Publications, 1998.
5. M. Girolami and N. Computation, "Orthogonal Series Density Estimation and the Kernel Eigenvalue Problem," Neural Computation, vol. 14, pp. 669-688, 2002.
6. Cvetkovic Dragos, Spectra of graphs : theory and application, Academic Press, 1980.
7. A. Gray and A.W. Moore, "N-Body problems in statistical learning," Advances in Neural Information Processing Systems, vol. 13, 2001.