Publications

Publications

[ Journal Papers | Conference Papers | Edited Books ]

c)200x IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from IEEE.

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

Journal Papers

    2010

  1. K. Zhang, J.T. Kwok. Simplifying mixture models through function approximation. To appear in IEEE Transactions on Neural Networks.

    2009

  2. B. Mak, T.-C. Lai, I.W. Tsang, J.T. Kwok. Maximum penalized likelihood kernel regression for fast adaptation. IEEE Transactions on Audio, Speech and Language Processing. 17(7): 1372-1381, September 2009.

  3. M. Hu, Y. Chen, J.T. Kwok. Building sparse multi-kernel SVM classifiers. IEEE Transactions on Neural Networks, 20(5): 827-839, May 2009.

  4. K. Zhang, I.W. Tsang, J.T. Kwok. Maximum margin clustering made practical. IEEE Transactions on Neural Networks. 20(4): 583-596, Apr 2009.

  5. K. Zhang, J.T. Kwok. Density-weighted Nystrom method for computing large kernel eigen-systems. Neural Computation. 21(1): 121-146, Jan 2009.

    2008

  6. X. Xie, S. Yan, J. Kwok, and T.S. Huang. Matrix-variate factor analysis and its applications. IEEE Transactions on Neural Networks. 19(10): 1821-1826, Oct 2008.

  7. I.W. Tsang, A. Kocsor, J.T. Kwok. Large-scale maximum margin discriminant analysis using core vector machines. IEEE Transactions on Neural Networks. 19(4): 610-624, Apr 2008.

  8. Z. Zhang, D.Y. Yeung, J.T. Kwok, E.Y. Chang. Sliced coordinate analysis for effective dimension reduction and nonlinear extensions. Journal of Computational and Graphical Statistics. 17(1): 225-242, Mar 2008.

    2007

  9. Z. Zhang, J.T. Kwok, D.Y. Yeung. Surrogate maximization/minimization algorithms and extensions. Machine Learning, 69(1): 1-33, Oct 2007.

  10. F. Wang, J. Wang, C. Zhang, J.T. Kwok. Face recognition using spectral features. Pattern Recognition, 40(10): 2786-2797, Oct 2007.

  11. J. Park, D. Kang, J. Kim, J.T. Kwok, I.W. Tsang. SVDD-based pattern de-noising. Neural Computation, 19(7): 1919-1938, July 2007.

  12. J.T. Kwok, I.W. Tsang, J.M. Zurada. A class of single-class minimax probability machines for novelty detection. IEEE Transactions on Neural Networks, 18(3): 778-785, May 2007.

    2006

  13. I.W. Tsang, J.T. Kwok, J.M. Zurada. Generalized core vector machines. IEEE Transactions on Neural Networks, 17(5):1126-1140, Sept 2006. (abstract)

  14. J.J. Pan, J.T. Kwok, Q. Yang, Y. Chen. Multidimensional vector regression for accurate and low-cost location estimation in pervasive computing. IEEE Transactions on Knowledge and Data Engineering, 18(9): 1181-1193, Sept 2006. (abstract)

  15. H. Zhao, P.C. Yuen, J.T. Kwok. Incremental principal component analysis and its application for face recognition. IEEE Transactions on Systems, Man and Cybernetics (Part B), 36(4):873-886, August 2006. (abstract)

  16. B. Mak, R. Hsiao, S. Ho, J.T. Kwok. Embedded kernel eigenvoice speaker adaptation and its implication to reference speaker weighting. IEEE Transactions on Speech and Audio Processing 14(4):1267-1280, July 2006. (abstract)

  17. Z. Zhang, J.T. Kwok, D.-Y. Yeung. Model-based transductive learning of the kernel matrix. Machine Learning, 63(1):69-101, Apr 2006. (abstract)

  18. I.W. Tsang, J.T. Kwok. Efficient hyperkernel learning using second-order cone programming. IEEE Transactions on Neural Networks, 17(1):48-58, Jan 2006. (abstract)

    2005

  19. B. Mak, J.T. Kwok, S. Ho. Kernel eigenvoice speaker adaptation. IEEE Transactions on Speech and Audio Processing, 13(5):984-992, Sept 2005. (abstract)

  20. I.W. Tsang, J.T. Kwok, P.-M. Cheung. Core vector machines: Fast SVM training on very large data sets. Journal of Machine Learning Research, 6(Apr):363-392, 2005. (abstract, code)
    • Authors' Reply to the "Comments on the Core Vector Machines: Fast SVM Training on Very Large Data Set"

    2004 and before

  21. J.T. Kwok, I.W. Tsang. The pre-image problem in kernel methods. IEEE Transactions on Neural Networks, 15(6):1517-1525, Nov 2004. (abstract, code)

  22. S. Li, J.T. Kwok, I.W. Tsang, Y. Wang. Fusing images with different focuses using support vector machines. IEEE Transactions on Neural Networks, 15(6):1555-1561, Nov 2004. (abstract)

  23. V. Cheng, C.-H. Li, J.T. Kwok, C.-K. Li. Dissimilarity learning for nominal data. Pattern Recognition, 37(7):1471-1477, July 2004. (abstract)

  24. S. Li, J.T. Kwok, H. Zhu, Y. Wang. Texture classification using support vector machines. Pattern Recognition, 36(12):2883-2893, Dec 2003. (abstract)

  25. J.T. Kwok, I.W. Tsang. Linear dependency between epsilon and the input noise in epsilon-support vector regression. IEEE Transactions on Neural Networks, 14(3):544-553, May 2003. (abstract)

  26. K.W. Cheung, J.T. Kwok, M.H. Law, K.C. Tsui. Mining customer product ratings for personalized marketing. Decision Support Systems, 35(2): 231-243, May 2003. (abstract)

  27. S. Li, J.T. Kwok, Y. Wang. Multifocus image fusion using artificial neural networks. Pattern Recognition Letters, 23(8): 985-997, June 2002. (abstract)

  28. S. Li, J.T. Kwok, Y. Wang. Using the discrete wavelet frame transform to merge Landsat TM and SPOT panchromatic images. Information Fusion, 3(1):17-23, March, 2002. (abstract)

  29. S. Li, J.T. Kwok, Y. Wang. Combination of images with diverse focuses using the spatial frequency. Information Fusion, 2(3):169-176, September 2001. (abstract)

  30. J.T. Kwok. The evidence framework applied to support vector machines. IEEE Transactions on Neural Networks, 11(5):1162-1173, September 2000. (abstract)

  31. J.T. Kwok. Moderating the outputs of support vector machine classifiers. IEEE Transactions on Neural Networks, 10(5):1018-1031, September 1999. (abstract)

  32. T.Y. Kwok, D.Y. Yeung. Objective functions for training new hidden units in constructive neural networks. IEEE Transactions on Neural Networks, 8(5):1131-1148, September 1997.

  33. T.Y. Kwok, D.Y. Yeung. Constructive algorithms for structure learning in feedforward neural networks for regression problems. IEEE Transactions on Neural Networks, 8(3):630-645, May 1997.

  34. T.Y. Kwok, D.Y. Yeung. Use of bias term in projection pursuit learning improves approximation and convergence properties. IEEE Transactions on Neural Networks, 7(5):1168-1183, September 1996.

  35. T.Y. Kwok, D.Y. Yeung. Improving the approximation and convergence capabilities of projection pursuit learning. Neural Processing Letters, 2(3):20-25, May 1995.

Conference Papers

    2010

  1. M. Li, J.T. Kwok, B. Lu. Online multiple instance learning with no regret. To appear in the International Conference on Computer Vision and Pattern Recognition (CVPR), San Francisco, CA, USA, June 2010.

  2. W. Yang, J.T. Kwok, B. Lu. Spectral and semidefinite relaxations of the CLUHSIC algorithm. To appear in the SIAM International Conference on Data Mining (SDM), Columbus, Ohio, USA, Apr 2010.

    2009

  3. C. Hu, J.T. Kwok, W. Pan. Accelerated gradient methods for stochastic optimization and online learning. Neural Information Processing Systems (NIPS), Vancouver, Canada, December 2009.

  4. X. Chen, W. Pan, J.T. Kwok, J. Carbonell. Accelerated gradient method for multi-task sparse learning problem. Proceedings of the International Conference on Data Mining (ICDM), Miami, Florida, USA, December 2009.

  5. B. Zhao, J.T. Kwok, C. Zhang. Maximum margin clustering with multivariate loss function. Proceedings of the International Conference on Data Mining (ICDM), Miami, Florida, USA, December 2009.

  6. Y.-F. Li, J.T. Kwok, I.W. Tsang, Z.-H. Zhou. A convex method for locating regions of interest with multi-instance learning. Proceedings of the European Conference on Machine Learning (ECML), Bled, Slovenia, September 2009.

  7. S.J. Pan, I.W. Tsang, J.T. Kwok, Q. Yang. Domain adaptation via transfer component analysis. Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence (IJCAI), Pasadena, California, USA, July 2009.

  8. B. Zhao, J.T. Kwok, F. Wang, C. Zhang. Unsupervised maximum margin feature selection with manifold regularization. Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR), Miami, FL, USA, June 2009.

  9. K. Zhang, J.T. Kwok, B. Parvin. Prototype vector machine for large scale semi-supervised learning. Proceedings of the Twenty-Sixth International Conference on Machine Learning (ICML), Montreal, Canada. June 2009.

  10. Y.-F. Li, J.T. Kwok, Z.-H. Zhou. Semi-supervised learning using label mean. Proceedings of the Twenty-Sixth International Conference on Machine Learning (ICML), Montreal, Canada. June 2009.

  11. B. Zhao, J.T. Kwok, C. Zhang. Multiple kernel clustering. Proceedings of the SIAM International Conference on Data Mining (SDM). Sparks, Nevada, April 2009.

  12. Y.-F. Li, I.W. Tsang, J.T. Kwok, Z.-H. Zhou. Tighter and convex maximum margin clustering. Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics (AISTATS). Clearwater Beach, Florida, USA, April 2009.

    13. 2008

  13. S.J. Pan, J.T. Kwok, Q. Yang. Transfer learning via dimensionality reduction. Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (AAAI), Chicago, Illinois, USA. July 2008.

  14. S.J. Pan, D. Shen, Q. Yang, J.T. Kwok. Transferring localization models across space. the Twenty-Third Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), Chicago, Illinois, USA. July 2008.

  15. K. Zhang, I.W. Tsang, J.T. Kwok. Improved Nystrom low rank approximation and error analysis. Proceedings of the Twenty-Fifth International Conference on Machine Learning (ICML), Helsinki, Finland. July 2008.

    2007

  16. S.J. Pan, J.T. Kwok, Q. Yang, J. Pan. Adaptive localization in a dynamic WiFi environment through multi-view learning. Proceedings of the Twenty-Second AAAI Conference on Artificial Intelligence (AAAI), pp.1108-1113, Vancouver, British Columbia, Canada. July 2007.

  17. I.W. Tsang, A. Kocsor, J.T. Kwok. Simpler core vector machines with enclosing balls. Proceedings of the Twenty-Fourth International Conference on Machine Learning (ICML), pp.911-918, Corvallis, Oregon, USA, June 2007.

  18. K. Zhang, I.W. Tsang, J.T. Kwok. Maximum margin clustering made practical. Proceedings of the Twenty-Fourth International Conference on Machine Learning (ICML), pp.1119-1126, Corvallis, Oregon, USA, June 2007.

  19. J.T. Kwok, P.-M. Cheung. Marginalized multi-instance kernels. Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI), pp.901-906, Hyderabad, India, January 2007.

  20. I.W. Tsang, J.T. Kwok. Ensembles of partially trained SVMs with multiplicative updates. Proceedings of the Twentieth International Joint Conference on Artificial Intelligence (IJCAI), pp.1089-1094, Hyderabad, India, January 2007.

    2006

  21. I.W. Tsang, J.T. Kwok. Large-scale sparsified manifold regularization. Neural Information Processing Systems (NIPS), Vancouver, Canada, December 2006. [oral]

  22. K. Zhang, J.T. Kwok. Simplifying mixture models through function approximation. Neural Information Processing Systems (NIPS), Vancouver, Canada, December 2006.

  23. S. Li, C. Liao, J.T. Kwok. Gene feature extraction using T-test statistics and kernel partial least squares. Proceedings of the International Conference on Neural Information Processing (ICONIP), pp.11-20, Hong Kong, October 2006.

  24. I.W. Tsang, A. Kocsor, J.T. Kwok. Diversified SVM ensembles for large data sets. Proceedings of the European Conference on Machine Learning (ECML), pp.792-800, Berlin, Germany, September 2006.

  25. I.W. Tsang, A. Kocsor, J.T. Kwok. Efficient kernel feature extraction for massive data sets. Proceedings of the International Conference on Knowledge Discovery and Data Mining (KDD), pp.724-729, Philadelphia, PA, USA, August 2006.

  26. S. Li, J. Peng, J.T. Kwok, J. Zhang. Multimodal registration using the discrete wavelet frame transform. Proceedings of the International Conference on Pattern Recognition (ICPR), pp.877-880, Hong Kong, China, August 2006.

  27. I.W. Tsang, J.T. Kwok. Learning the kernel in Mahalanobis one-class support vector machines. Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp.1169-1175, Vancouver, Canada, July 2006.

  28. S. Li, C. Liao, J.T. Kwok. Wavelet-based feature extraction for microarray data classification. Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp.5028-5033, Vancouver, Canada, July 2006.

  29. K. Chen, B.-L. Lu, J.T. Kwok. Efficient classification of multi-label and imbalanced data using Min-Max modular classifiers. Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp.1770-1775, Vancouver, Canada, July 2006.

  30. P.-M. Cheung, J.T. Kwok. A regularization framework for multiple-instance learning. Proceedings of the Twenty-Third International Conference on Machine Learning (ICML), vol 3, pp.193-200, Pittsburgh, USA, June 2006. (abstract) (data)

  31. J. Dai, S. Yan, X. Tang, J.T. Kwok. Locally adaptive classification piloted by uncertainty. Proceedings of the Twenty-Third International Conference on Machine Learning (ICML), pp.225-232, Pittsburgh, USA, June 2006. (abstract)

  32. K. Zhang, J.T. Kwok. Block-quantized kernel matrix for fast spectral embedding. Proceedings of the Twenty-Third International Conference on Machine Learning (ICML), pp.1097-1104, Pittsburgh, USA, June 2006. (abstract)

  33. K. Zhang, J.T. Kwok. Fitting kernel density estimators using divide-and-conquer. ECCV Workshop on Computation Intensive Methods for Computer Vision, Graz, Austria, May 2006.

  34. K. Zhang, J.T. Kwok, M. Tang. Accelerated convergence using dynamic mean shift. Proceedings of the European Conference on Computer Vision (ECCV), pp.257-268, Graz, Austria, May 2006. (abstract)

  35. I.W. Tsang, J.T. Kwok, B. Mak, K. Zhang, J.J. Pan. Fast speaker adaption via maximum penalized likelihood kernel regression. Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP), vol 1, pp.997-1000, Toulouse, France, May 2006. (abstract)

  36. J. Park, D. Kang, J.T. Kwok, S.-W. Lee, B.-W. Hwang, S.-W. Lee. Facial image reconstruction by SVDD-based pattern de-noising. Proceedings of the International Conference on Biometrics (ICB), pp.129-135, Hong Kong, Jan 2006. (abstract)

    2005

  37. K.-F.S. Wong, I.W. Tsang, V. Cheung, S.-H.G. Chan, J.T. Kwok. Position estimation for wireless sensor networks. Proceedings of the IEEE Global Telecommunications Conference (GLOBECOM), pp.2772-2776, St. Louis, MO, USA, Nov 2005. (abstract)

  38. I.W. Tsang, J.T. Kwok, K.T. Lai. Core vector regression for very large regression problems. Proceedings of the Twenty-Second International Conference on Machine Learning (ICML), pp.913-920, Bonn, Germany, August 2005. (abstract)

  39. J.J. Pan, J.T. Kwok, Q. Yang, Y. Chen. Accurate and low-cost location estmation using kernels. Proceedings of the Nineteenth International Joint Conference on Artificial Intelligence (IJCAI), pp.1366-1371, Edinburgh, Scotland, July 2005. (abstract)

  40. I.W. Tsang, P.-M. Cheung, J.T. Kwok. Kernel relevant component analysis for distance metric learning. Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp.954-959, Montreal, Canada, July 2005. (abstract)

  41. J. Park, D. Kang, J. Kim, J.T. Kwok, I.W. Tsang. Pattern de-noising based on support vector data description. Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp.949-953, Montreal, Canada, July 2005. (abstract)

  42. J. Wang, J.T. Kwok, H.C. Shen, L. Quan. Data-dependent kernels for small-scale, high-dimensional data classification. Proceedings of International Joint Conference on Neural Networks (IJCNN), pp.102-107, Montreal, Canada, July 2005. (abstract)

  43. K. Zhang, M. Tang, J.T. Kwok. Applying neighborhood consistency for fast clustering and kernel density estimation. Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR), pp.1001-1007, San Diego, CA, USA, June 2005. (abstract)

  44. I.W. Tsang, J.T. Kwok, P.-M. Cheung. Very large SVM training using core vector machines. Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics (AISTATS), Barbados, January 2005. (abstract)

    2004 and before

  45. H. Zhao, P.C. Yuen, J.T. Kwok, J. Yang. Incremental PCA-based face recognition. Proceedings of the International Conference on Control, Automation, Robotics and Vision (ICARCV), Kunming, China, December 2004.

  46. S. Li, J.T. Kwok. Text extraction using edge detection and morphological dilation. Proceedings of the International Symposium on Intelligent Multimedia, Video and Speech Processing, Hong Kong, China, October 2004.

  47. B. Mak, S. Ho, J.T. Kwok. Speedup of kernel eigenvoice speaker adaptation by embedded kernel PCA. Proceedings of the International Conference on Spoken Language Processing (INTERSPEECH-ICSLP), vol 4, pp.2913-2916, Jeju, Korea, October 2004. (abstract)

  48. I.W. Tsang, J.T. Kwok. Efficient hyperkernel learning using second-order cone programming. Proceedings of the European Conference on Machine Learning (ECML), pp.453-464, Pisa, Italy, September 2004. (abstract)

  49. Z. Zhang, K.L. Chan, J.T. Kwok, D.-Y. Yeung. Bayesian inference on principal component analysis using reversible jump Markov chain Monte Carlo. Proceedings of the Nineteenth National Conference on Artificial Intelligence (AAAI), pp.372-377, San Jose, California, USA, July 2004. (abstract)

  50. C.S. Chu, I.W. Tsang, J.T. Kwok. Scaling up support vector data description by using core-sets. Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp.425-430, Budapest, Hungary, July 2004. (abstract)

  51. Z. Zhang, J.T. Kwok, D.-Y. Yeung. Surrogate maximization/minimization algorithms for AdaBoost and the logistic regression model. Proceedings of the Twenty-First International Conference on Machine Learning (ICML), pp.927-934, Banff, Alberta, Canada, July 2004. (abstract)

  52. Z. Zhang, D.-Y. Yeung, J.T. Kwok. Bayesian inference for transductive learning of kernel matrix using the Tanner-Wong data augmentation algorithm. Proceedings of the Twenty-First International Conference on Machine Learning (ICML), pp.935-942, Banff, Alberta, Canada, July 2004. (abstract)

  53. B. Mak, J.T. Kwok, S. Ho. Investigation of various composite kernels for kernel eigenvoice speaker adaptation. Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP), vol 1, pp.325-328, Montreal, Canada, May 2004. (abstract)

  54. J.T. Kwok, B. Mak, S. Ho. Eigenvoice speaker adaptation via composite kernel principal component analysis. Advances in Neural Information Processing Systems 16 (NIPS), S. Thrun, L. Saul and B. Schoelkopf, Eds. MIT Press, Cambridge, MA, 2004. (abstract) (slides)

  55. J.T. Kwok, I.W. Tsang. The pre-image problem in kernel methods. Proceedings of the Twentieth International Conference on Machine Learning (ICML), pp.408-415, Washington, D.C., USA, August 2003. (abstract) (slides)

  56. J.T. Kwok, I.W. Tsang. Learning with idealized kernels. Proceedings of the Twentieth International Conference on Machine Learning (ICML), pp.400-407, Washington, D.C., USA, August 2003. (abstract) (slides)

  57. Z. Zhang, J.T. Kwok, D.Y. Yeung. Parametric distance metric learning with label information. Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI), pp.1450-1452, Acapulco, Mexico, August 2003. (abstract)

  58. I.W. Tsang, J.T. Kwok. Distance metric learning with kernels. Proceedings of the International Conference on Artificial Neural Networks (ICANN), pp.126-129, Istanbul, Turkey, June 2003. (abstract)

  59. J.T. Kwok, H. Zhao. Incremental eigen decomposition. Proceedings of the International Conference on Artificial Neural Networks (ICANN), pp.270-273, Istanbul, Turkey, June 2003. (abstract)

  60. J.T. Kwok, I.W. Tsang. Finding the pre-images in kernel principal component analysis. 6th Annual Workshop On Kernel Machines, NIPS, Whistler, Canada, December 2002. (abstract)

  61. S. Li, J.T. Kwok, Y. Wang. Fusing images with multiple focuses using support vector machines. Proceedings of the International Conference on Artificial Neural Networks (ICANN), pp.405-410, Madrid, Spain, August 2002. (abstract)

  62. H. Zhu, J.T. Kwok, L. Qu. Improving de-noising by coefficient de-noising and dyadic wavelet transform. Proceedings of the International Conference on Pattern Recognition (ICPR), pp.272-276, Quebec City, Canada, August 2002. (abstract)

  63. M.H. Law, J.T. Kwok. Applying the Bayesian evidence framework to nu-support vector regression. Proceedings of the Twelfth European Conference on Machine Learning (ECML), pp.312-323, Freiburg, Germany, September 2001. (abstract)

  64. J.T. Kwok. Linear dependency between epsilon and the input noise in epsilon-support vector regression. Proceedings of the International Conference on Artificial Neural Networks (ICANN), pp.405-410, Vienna, Austria, August 2001. (abstract) (@ Springer-Verlag)

  65. M.H. Law, J.T. Kwok. Bayesian support vector regression. Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics (AISTATS), pp.239-244, Key West, Florida, USA, January 2001. (abstract)

  66. M.H. Law, J.T. Kwok. Rival penalized competitive learning for model-based sequence clustering. Proceedings of the International Conference on Pattern Recognition (ICPR), vol 2, pp.195-198, Barcelona, Spain, September 2000. (abstract)

  67. J.J. Liu, J.T. Kwok. An extended genetic rule induction algorithm. Proceedings of the Congress on Evolutionary Computation (CEC), pp.458-463, La Jolla, California, USA, July 2000. (abstract)

  68. W.K. Cheung, J.T. Kwok, M.H. Law, K.C. Tsui. Mining customer preference ratings for product recommendation using the support vector machine and the latent class model. Proceedings of the Second International Conference on Data Mining Methods and Databases for Engineering, Finance and Other Fields, pp.601-610, Cambridge, UK, July 2000. (abstract)

  69. J.T. Kwok. Moderating the outputs of support vector machine classifiers. Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp.943-948, Washington, DC, USA, July 1999. (abstract)

  70. J.T. Kwok. Integrating the evidence framework and the support vector machine. Proceedings of the European Symposium on Artificial Neural Networks (ESANN), pp.177-182, Bruges, Belgium, April 1999. (abstract)

  71. J.T. Kwok. Automated text categorization using support vector machine. Proceedings of the International Conference on Neural Information Processing (ICONIP), pp.347-351, Kitakyushu, Japan, October 1998. (abstract)

  72. J.T. Kwok. Support vector mixture for classification and regression problems. Proceedings of the International Conference on Pattern Recognition (ICPR), pp.255-258, Brisbane, Australia, August 1998. (abstract)

  73. T.Y. Kwok, D.Y. Yeung. Reference priors for neural networks: Laplace versus Gaussian. Proceedings of the International Conference on Neural Information Processing (ICONIP), pp.109-114, Hong Kong, September 1996.

  74. T.Y. Kwok, D.Y. Yeung. Bayesian regularization in constructive neural networks. Proceedings of the International Conference on Artificial Neural Networks (ICANN), pp.557-562, Bochum, Germany, July 1996.

  75. T.Y. Kwok, D.Y. Yeung. Efficient cross-validation for feedforward neural networks. Proceedings of the IEEE International Conference on Neural Networks (ICNN), Perth, Western Australia, November 1995.

  76. T.Y. Kwok, D.Y. Yeung. Improving the approximation and convergence capabilities of projection pursuit learning. Proceedings of the International Conference on Artificial Neural Networks (ICANN), pp.197-202, Paris, France, October 1995.

  77. T.Y. Kwok, D.Y. Yeung. Constructive neural networks: Some practical considerations. Proceedings of the IEEE International Conference on Neural Networks (ICNN), pp.198-203, Orlando, Florida, USA, June 1994.

  78. T.Y. Kwok, D.Y. Yeung. A theoretically sound learning algorithm for constructive neural networks. Proceedings of the IEEE International Symposium on Speech, Image Processing and Neural Networks, pp.389-392, Hong Kong, April 1994.

  79. T.Y. Kwok, D.Y. Yeung. Experimental analysis of input weight freezing in constructive neural networks. Proceedings of the IEEE International Conference on Neural Networks (ICNN), pp.511-516, San Francisco, California, USA, March 1993.

Edited Books

    2008

  1. N. da Vitoria Lobo, T. Kasparis, F. Roli, J.T. Kwok, M. Georgiopoulos, G.C. Anagnostopoulos, M. Loog (Eds.): Structural, Syntactic, and Statistical Pattern Recognition, Joint IAPR International Workshops, SSPR & SPR 2008. Springer, December 2008.

    2. 2006

  2. D.Y. Yeung, J.T. Kwok, A. Fred, F. Roli, D. de Ridder (eds.). Structural, Syntactic and Statistical Pattern Recognition: Joint IAPR International Workshops, SSPR 2006 and SPR 2006. Springer, August 2006.