Using manifold structure for partially labelled classification

Advances in Neural Information Processing Systems

Volumn , Issue , 2003, Pages

  Belkin, Mikhail ^a   Niyogi, Partha ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); TEXT PROCESSING;

ALGORITHMIC FRAMEWORK; CLASSIFICATION ACCURACY; CLASSIFICATION FUNCTIONS; HIGH DIMENSIONAL SPACES; LABELED AND UNLABELED DATA; LAPLACE-BELTRAMI OPERATOR; MANIFOLD STRUCTURES; TEXT CLASSIFICATION;

ALGORITHMS;

EID: 84898946656     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. M. Belkin, P. Niyogi, Laplacian Eigenmaps for Dimensionality Reduction and Data Representation, Technical Report, TR-2002-01, Department of Computer Science, The University of Chicago, 2002.
2. A. Blum, S. Chawla, Learning from Labeled and Unlabeled Data using Graph Mincuts, ICML, 2001,
3. Fan R. K. Chung, Spectral Graph Theory, Regional Conference Series in Mathematics, number 92, 1997
4. K. Nigam, A.K. McCallum, S. Thrun, T. Mitchell, Text Classification from Labeled in Unlabeled Data, Machine Learning 39(2/3), 2000,
5. S. Rosenberg, The Laplacian on a Riemmannian Manifold, Cambridge University Press, 1997,
6. Sam T. Roweis, Lawrence K. Saul, Nonlinear Dimensionality Reduction by Locally Linear Embedding, Science, vol 290, 22 December 2000,
7. Martin Szummer, Tommi Jaakkola, Partially labeled classification with Markov random walks, Neural Information Processing Systems (NIPS) 2001, vol 14.,
8. Joshua B. Tenenbaum, Vin de Silva, John C. Langford, A Global Geometric Framework for Nonlinear Dimensionality Reduction, Science, Vol 290, 22 December 2000,