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Martin H.C. Law, Anil K. Jain, "Incremental Nonlinear Dimensionality Reduction by Manifold Learning," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 28, no. 3, pp. 377391, March, 2006.  
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@article{ 10.1109/TPAMI.2006.56, author = {Martin H.C. Law and Anil K. Jain}, title = {Incremental Nonlinear Dimensionality Reduction by Manifold Learning}, journal ={IEEE Transactions on Pattern Analysis and Machine Intelligence}, volume = {28}, number = {3}, issn = {01628828}, year = {2006}, pages = {377391}, doi = {http://doi.ieeecomputersociety.org/10.1109/TPAMI.2006.56}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Pattern Analysis and Machine Intelligence TI  Incremental Nonlinear Dimensionality Reduction by Manifold Learning IS  3 SN  01628828 SP377 EP391 EPD  377391 A1  Martin H.C. Law, A1  Anil K. Jain, PY  2006 KW  Incremental learning KW  dimensionality reduction KW  ISOMAP KW  manifold learning KW  unsupervised learning. VL  28 JA  IEEE Transactions on Pattern Analysis and Machine Intelligence ER   
[1] P. Baldi and K. Hornik, “Neural Networks and Principal Component Analysis: Learning from Examples without Local Minima,” Neural Networks, vol. 2, pp. 5358, 1989.
[2] M. Belkin and P. Niyogi, “Laplacian Eigenmaps for Dimensionality Reduction and Data Representation,” Neural Computation, vol. 15, no. 6, pp. 13731396, June 2003.
[3] Y. Bengio, J.F. Paiement, and P. Vincent, “OutofSample Extensions for LLE, Isomap, MDS, Eigenmaps, and Spectral Clustering,” Advances in Neural Information Processing Systems 16, MIT Press, 2004.
[4] M. Bernstein, V. de Silva, J. Langford, and J. Tenenbaum, “Graph Approximations to Geodesics on Embedded Manifolds,” technical report, Dept. of Psychology, Stanford Univ., 2000.
[5] A. Beygelzimer, S.M. Kakade, and J. Langford, “Cover Trees for Nearest Neighbor,” technical report, Univ. of Pennsylvania, 2005, http://www.cis.upenn.edu/~skakade/papers/ mlcover_tree.pdf.
[6] C.M. Bishop, M. Svensen, and C.K. I. Williams, “GTM: The Generative Topographic Mapping,” Neural Computation, vol. 10, pp. 215234, 1998.
[7] M. Brand, “Charting a Manifold,” Advances in Neural Information Processing Systems 15, pp. 961968, 2003.
[8] A. Brun, H.J. Park, H. Knutsson, and C.F. Westin, “Coloring of DTMRI Fiber Traces Using Laplacian Eigenmaps,” Proc. Ninth Int'l Conf. Computer Aided Systems Theory, vol. 2809, Feb. 2003.
[9] J. Bruske and G. Sommer, “Intrinsic Dimensionality Estimation with Optimally Topology Preserving Maps,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 5, pp. 572575, May 1998.
[10] F. Camastra and A. Vinciarelli, “Estimating the Intrinsic Dimension of Data with a FractalBased Method,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 24, no. 10, pp. 14041407, Oct. 2002.
[11] Y. Chang, C. Hu, and M.M. Turk, “Probabilistic Expression Analysis on Manifolds,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 520527, 2004.
[12] J. Costa and A.O. Hero, “Manifold Learning Using Euclidean KNearest Neighbor Graphs,” Proc. IEEE Int'l Conf. Acoustic Speech and Signal Processing, vol. 3, pp. 988991, 2004.
[13] T.F. Cox and M.A.A. Cox, Multidimensional Scaling. Chapman and Hall, 2001.
[14] V. de Silva and J.B. Tenenbaum, “Global versus Local Approaches to Nonlinear Dimensionality Reduction,” Advances in Neural Information Processing Systems 15, pp. 705712, 2003.
[15] D. DeMers and G. Cottrell, “Nonlinear Dimensionality Reduction,” Advances in Neural Information Processing Systems 5, pp. 580587, 1993.
[16] C. Demetrescu and G.F. Italiano, “A New Approach to Dynamic All Pairs Shortest Paths,” J. ACM, vol. 51, no. 6, pp. 968992, Nov. 2004.
[17] D.L. Donoho and C. Grimes, “When Does Isomap Recover Natural Parameterization of Families of Articulated Images?” Technical Report 200227, Dept. of Statistics, Stanford Univ., Aug. 2002.
[18] R. Duda, P. Hart, and D. Stork, Pattern Classification, second ed. John Wiley and Sons, 2001.
[19] A. Elgammal and C.S. Lee, “Inferring 3D Body Pose from Silhouettes Using Activity Manifold Learning,” Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 681688, 2004.
[20] A. Elgammal and C.S. Lee, “Separating Style and Content on a Nonlinear Manifold,” Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, pp. 478489, 2004.
[21] C. Fowlkes, S. Belongie, F. Chung, and J. Malik, “Spectral Grouping Using the Nyström Method,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 26, no. 2, pp. 214225, Feb. 2004.
[22] G.H. Golub and C.F. Van Loan, Matrix Computations. Johns Hopkins Univ. Press, 1996.
[23] A. Hadid, O. Kouropteva, and M. Pietikainen, “Unsupervised Learning Using Locally Linear Embedding: Experiments in Face Pose Analysis,” Proc. 16th Int'l Conf. Pattern Recognition, pp. I: 111114, 2002.
[24] T. Hastie and W. Stuetzle, “Principal Curves,” J. Am. Statistical Assoc., vol. 84, pp. 502516, 1989.
[25] G.E. Hinton, P. Dayan, and M. Revow, “Modeling the Manifolds of Handwritten Digits,” IEEE Trans. Neural Networks, vol. 8, no. 1, pp. 6574, Jan. 1997.
[26] O. Jenkins and M. Mataric, “A SpatioTemporal Extension to ISOMAP Nonlinear Dimension Reduction,” Proc. 21st Int'l Conf. Machine Learning, 2004.
[27] B. Kégl, “Intrinsic Dimension Estimation Using Packing Numbers,” Advances in Neural Information Processing Systems 15, 2003.
[28] B. Kégl, A. Krzyzak, T. Linder, and K. Zeger, “Learning and Design of Principal Curves,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 3, pp. 281297, Mar. 2000.
[29] T. Kohonen, SelfOrganizing Maps, third ed. SpringerVerlag, 2001.
[30] M.H. Law, N. Zhang, and A.K. Jain, “Nonlinear Manifold Learning for Data Stream,” Proc. SIAM Int'l Conf. Data Mining, pp. 3344, 2004.
[31] E. Levina and P.J. Bickel, “Maximum Likelihood Estimation of Intrinsic Dimension,” Advances in Neural Information Processing Systems 17, 2005.
[32] S.Z. Li, R. Xiao, Z.Y. Li, and H.J. Zhang, “Nonlinear Mapping from MultiView Face Patterns to a Gaussian Distribution in a Low Dimensional Space,” Proc. IEEE ICCV Workshop Recognition, Analysis and Tracking of Faces and Gestures in RealTime Systems, 2001.
[33] X. Lu and A.K. Jain, “Ethnicity Identification from Face Images,” Proc. Int'l Soc. Optical Eng. (SPIE), vol. 5404, pp. 114123, 2004.
[34] J. Mao and A.K. Jain, “Artificial Neural Networks for Feature Extraction and Multivariate Data Projection,” IEEE Trans. Neural Networks, vol. 6, no. 2, pp. 296317, Mar. 1995.
[35] A. Martinez and R. Benavente, “The AR Face Database,” Technical Report 24, Computer Vision Center, Univ. Alabama at Birmingham, 1998, http://rvl1.ecn.purdue.edu/~aleixaleix_face_DB. html .
[36] P. Narváez, K.Y. Siu, and H.Y. Tzeng, “New Dynamic Algorithms for Shortest Path Tree Computation,” IEEE/ACM Trans. Networking, vol. 8, no. 6, pp. 734746, Dec. 2000.
[37] P. Narváez, K.Y. Siu, and H.Y. Tzeng, “New Dynamic SPT Algorithm Based on a BallandString Model,” IEEE/ACM Trans. Networking, vol. 9, no. 6, pp. 706718, Dec. 2001.
[38] M. Niskanen and O. Silvén, “Comparison of Dimensionality Reduction Methods for Wood Surface Inspection,” Proc. Sixth Int'l Conf. Quality Control by Artificial Vision, pp. 178188, 2003.
[39] K. Pettis, T. Bailey, A.K. Jain, and R. Dubes, “An Intrinsic Dimensionality Estimator from NearNeighbor Information,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 1, no. 1, pp. 2536, Jan. 1979.
[40] S.T. Roweis, L.K. Saul, and G.E. Hinton, “Global Coordination of Local Linear Models,” Advances in Neural Information Processing Systems 14, pp. 889896, 2002.
[41] J.W. Sammon, “A Nonlinear Mapping for Data Structure Analysis,” IEEE Trans. Computers, vol. 18, no. 5, pp. 401409, May 1969.
[42] B. Schölkopf, A.J. Smola, and K.R. Müller, “Nonlinear Component Analysis as a Kernel Eigenvalue Problem,” Neural Computation, vol. 10, pp. 12991319, 1998.
[43] P.Y. Simard, D. Steinkraus, and J. Platt, “Best Practice for Convolutional Neural Networks Applied to Visual Document Analysis,” Proc. Int'l Conf. Document Analysis and Recogntion, pp. 958962, 2003.
[44] E. Sjöström, “Singular Value Computations for Toeplitz Matrices,” Licentiate thesis, 1996, http://www.mai.liu.se/~evlun/pub/liclic.html .
[45] A.J. Smola, S. Mika, B. Schölkopf, and R.C. Williamson, “Regularized Principal Manifolds,” J. Machine Learning Research, vol. 1, pp. 179209, June 2001.
[46] J.B. Tenenbaum, V. de Silva, and J.C. Langford, “A Global Geometric Framework for Nonlinear Dimensionality Reduction,” Science, vol. 290, pp. 23192323, 2000.
[47] R. Tibshirani, “Principal Curves Revisited,” Statistics and Computing, vol. 2, pp. 183190, 1992.
[48] J.J. Verbeek, N. Vlassis, and B. Krose, “Coordinating Principal Component Analyzers,” Proc. Int'l Conf. Artificial Neural Networks, pp. 914919, 2002.
[49] K.Q. Weinberger and L.K. Saul, “Unsupervised Learning of Image Manifolds by Semidefinite Programming,” Proc. IEEE CS Conf. Computer Vision and Pattern Recognition, vol. 2, pp. 988995, 2004.
[50] J. Weng, Y. Zhang, and W.S. Hwang, “Candid CovarianceFree Incremental Principal Component Analysis,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 8, pp. 10341040, Aug. 2003.
[51] M.H. Yang, “Face Recognition Using Extended Isomap,” Proc. IEEE Int'l Conf. Image Processing, pp. II: 117120, 2002.
[52] H. Zha and Z. Zhang, “Isometric Embedding and Continuum Isomap,” Proc. 20th Int'l Conf. Machine Learning, 2003.
[53] J. Zhang, S.Z. Li, and J. Wang, “Nearest Manifold Approach for Face Recognition,” Proc. Sixth Int'l Conf. Automatic Face and Gesture Recognition, May 2004.