[1] J. X. Dong, A. Krzyzak, C. Y. Suen, A fast SVM training algorithm. International workshop on Pattern Recognition with Support Vector Machines. S.-W. Lee and A. Verri (Eds.): Springer Lecture Notes in Computer Science LNCS 2388, pp. 53-67, Niagara Falls, Canada, August 10, 2002.

[2] S.B. Cho and J. H. Kim, ``Combining multiple neural network by fuzzy integral for robust classification," *IEEE Trans. Systems, Man and Cybernetics*, vol. 25, no. 2, pp. 380--384, 1995

[3] S. W. Lee, ``Multilayer cluster neural network for totally unconstrained handwritten numeral recognition," *Neural Networks*, vol. 8, no. 5, pp. 783--792, 1995

[4] J. X. Dong, A. Krzyzak. and C. Y. Suen, Local Learning Framework for Handwritten Character Recognition. *Engineering Applications of Artificial Intelligence*, vol. 15, Issue 2, pp. 151--159, April 2002.

[5] J. X. Dong, A. Krzyzak, and C. Y. Suen, "Fast SVM Training Algorithm with Decomposition on Very Large Datasets," *IEEE Transactions on Pattern Analysis and Machine Intelligence*, vol. 27, no. 4, pp. 603--618, April 2005.

[6] Cheng-Lin Liu, Kazuki Nakashima, Hiroshi Sako and Hiromichi Fujisawa, "Handwritten Digit Recognition Using State-of-the-art Techniques,"*Proceedings of the eighth International Workshop on Frontiers in Handwriting Recognition*, pp. 320--325, Niagara-on-the lake, Canada. August 6--8, 2002

[7] P. Simard, Y. LeCun, and J. Denker, "Tangent prop -- a formalism for specifying selected invariance in an adaptive network," in *Advances in Neural Information Processing Systems*, J.E. Moody, S.J. Hanson, and R. P. Lippmann, Eds., vol. 4, Morgan Kaufmann, San Mateo, CA, 1993

[8] Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R.E. Howard, W. Hubbard, and L.J. Jackel, "Backpropagation applied to handwritten zip code recognition," *Neural Computation*, vol. 1, pp. 541--551, 1989

[9] B.E. Boser, I.M. Guyon, and V.N. Vapnik, "A training algorithm for optimal margin classifiers," in *Proceedings of the 5th Annual ACM Workshop on Computational Learning Theory*, D. Haussler, Ed., pp. 144--152, ACM Press, Pittsburg, PA, 1992.

[10] B. Scholkopf, C.J.C. Burges, and V. Vapnik, "Extracting support data for a given task," in *Proceedings, First International Conference on Knowledge Discovery and Data Mining*, U.M. Fayyad and R. Uthurusamy, Eds., pp. 252--257, AAAI Press, Menlo Park, CA, 1995

[11] L. Bottou and V. Vapnik, "Local Learning algorithm," *Neural Computation*, Vol. 4, no. 6, pp. 888--901, 1992

[12] B. Scholkopf, Support Vector Learning, Ph.D. thesis, R. Oldenbourg Verlag, Munchen., Technical University of Berlin, 1997

[13] H. Drucker, R. Schapire, and P. Simard, "Boosting performance in neural network," *International Journal of Pattern Recognition and Artificial Intelligence*, vol. 7, no. 4, pp. 705--719, 1993

[14] B. Scholkopf, C.J.C. Burges, and V. Vapnik, "Incorporating invariances in support vector learning machines," in *Artificial Neural Network-ICANN'96*, C. von der malsburg, W. von Seelen, J.C. Vorbruggen, and B. Sendhoff, Eds., vol. 1112, pp. 47--52, Springer Lecture notes in Computer Science, Berlin, 1996.

[15] J. Bromley and E. Sackinger, "Neural-network and k-nearest-neighbor classifiers," Tech. Rep. 11359--910819-16TM, AT&T, 1991

[16] Jian-xiong Dong, Statistical Results of Human Performance on USPS database. Report. CENPARMI, Concordia University, October 2001. ( Labelling date file of four subjects. USPS images for test set.)

[17] Y. LeCun, L.D. Jackel, L. Bottou, J.S. Denker, H. Drucker, I. Guyon, U.A. Muller, E. Sackinger, P. Simard, and V.N. Vapnik, "Comparison of learning algorithms for handwritten digit recognition," in *Proc. Int'l Conf. Artificial Neural Networks*, pp. 53--60, Paris, 1995

[18] C.J.C. Burges and B. Scholkopf, "Improving the accuracy and speed of support vector learning machines," in *Advances in Neural Information Processing Systems*, M. Mozer, M. Jordan, and T. Petsche, Eds., vol. 9, pp. 375--381, MIT Press, Cambridge, MA, 1997.

[19] B. Scholkopf, P. Simard, and V. Vapnik, "Prior knowledge in support vector kernels," in *Advances in Neural Information Processing Systems*, M. Jordan, M. Kearns, and S. Solla, Eds., vol. 10, pp. 640--646, MIT Press, Cambridge, MA, 1998.

[20] D. DeCoste and B. Scholkopf, "Training invariant support vector machines," *Machine Learning*, vol. 46,no. 1-3, pp. 161--190, 2002

[21] J. X. Dong, Speed and accuracy: large-scale machine learning algorithms and their applications. Ph.D. thesis. Department of Computer Science, Concordia University, Montreal, 2003

[22] J. X. Dong, C. Y. Suen and A. Krzyzak, A fast parallel optimization for training support vector machine. Technical Report, CENPARMI, Concordia University, October, 2002.

[23] L.N. Teow and K.F. Loe, Robust vision-based features and classification schemes for off-line handwritten digit recognition. Pattern Recognition, vol. 35, pp. 2355--2364, 2002.

[24] T. Joachims, Making large-scale SVM Learning Practical. Advances in Kernel Methods-Support Vector Learning, B.Scholkopf and C. Burges and A. Smola (eds.), MIT Press, 1999. Svm-light is available from http://svmlight.joachims.org/

[25] Chih-Chung Chang and Chih-Jen Lin, Training nu-Support Vector Classifiers Theory and Algorithms. Neural Computation, vol. 13, pp. 1443--1471, 2001. Libsvm is available from http://www.csie.ntu.edu.tw/~cjlin/libsvm/

[26] S.S. Keerthi, S.K. Shevade, C. Bhattacharyya and K.R.K. Murthy, Improvements to Platt's SMO algorithm for SVM classifier design, Technical Report CD-99-14, Control Division, Dept. of Mechanical Engineering, National University of Singapore, 1999. see electronic version from the web: http://guppy.mpe.nus.edu.sg/~mpessk/publications.shtml

[27] Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner, Gradient-based learning applied to document recognition. Proceedings of the IEEE, vol. 86, No. 11, pp. 2278--2324, November 1998

[28] D. Keysers, R. Paredes, H. Ney, and E. Vidal, Combination of Tangent Vectors and Local Representation for Handwritten Digit Recognition. In SPR2002, International Workshop on Statistical Pattern Recognition, Windsor, Ontario, Canada, Volume LNCS 2396 of Lecture Notes in Computer Science, Springer-Vertag, pp. 538--547, Aug. 2002.

[29] J.X. Dong, A. Krzyzak and C.Y. Suen, "Algorithms of Fast Evaluations based on Subspace Projection," *Proceedings of IEEE International Joint Conference on Neural Network* (IJCNN'05), Montreal, Quebec, July 31-August 4, 2005.