Publications

Publications

[ Journal Papers | Conference Papers | Edited Books ]

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Journal Papers

    2017

  1. Y. Ma, X. Liang, J.T. Kwok. J. Li, X. Zhou, H. Zhang. Fast-solving quasi-optimal LS-S3VM based on an extended candidate set. IEEE Transactions on Neural Networks and Learning Systems, 2017.

  2. W. He, J.T. Kwok, J. Zhu, Y. Liu. A note on the unification of adaptive online learning. IEEE Transactions on Neural Networks and Learning Systems, 28(5): 1178-1191, February 2017.

    2015

  3. W. Bi, J.T. Kwok. Bayes-optimal hierarchical multilabel classification. IEEE Transactions on Knowledge and Data Engineering, 27(11): 2907-2918, November 2015.

  4. E.-L. Hu, J.T. Kwok. Scalable nonparametric low-rank kernel learning using block coordinate descent. IEEE Transactions on Neural Networks and Learning Systems, 26(9): 1927-1938, 2015.

  5. K. Zhang, L. Lan, J.T. Kwok, S. Vucetic, B. Parvin. Scaling up graph-based semi-supervised learning via prototype vector machines. IEEE Transactions on Neural Networks and Learning Systems, 26(3): 444-457, 2015.

  6. M. Li, W. Bi, J.T. Kwok, B. Lu. Large-scale Nystrom kernel matrix approximation using randomized SVD. IEEE Transactions on Neural Networks and Learning Systems, 26(1); 152-164, 2015.

    2014

  7. W. He, J.T. Kwok. Simple randomized algorithms for online learning with kernels. Neural Networks, 60: 17-24, 2014.

  8. W. Bi, J.T. Kwok. Mandatory leaf node prediction in hierarchical multilabel classification. IEEE Transactions on Neural Networks and Learning Systems, 25(12): 2275-2287, 2014.

    2013

  9. Y.-F. Li, I.W. Tsang, J.T. Kwok, Z.-H. Zhou. Convex and scalable weakly labeled SVMs. Journal of Machine Learning Research, 14(Jul):2151-2188, 2013.

    2012

  10. L.W. Zhong, J.T. Kwok. Efficient sparse modeling with automatic feature grouping. IEEE Transactions on Neural Networks and Learning Systems, 23(9): 1436-1447, September 2012.

  11. J. Zhao, P.L.H. Yu, J.T. Kwok. Bilinear probabilistic principal component analysis. IEEE Transactions on Neural Networks and Learning Systems (formerly called IEEE Transactions on Neural Networks), 23(3): 492-503, March 2012.

    2011

  12. S. Li, M. Tan, I.W. Tsang, J.T. Kwok. A hybrid PSO-BFGS strategy for global optimization of multimodal functions, IEEE Transactions on Systems, Man and Cybernetics (Part B), 41(4):1003-1014, August 2011.

  13. S.J. Pan, I.W. Tsang, J.T. Kwok, Q. Yang. Domain adaptation via transfer component analysis. IEEE Transactions on Neural Networks. 22(2): 199-210, Feb 2011.

    2010

  14. M. Zhao, S. Li, J.T. Kwok. Text detection in images using sparse representation with discriminative dictionaries. Image and Vision Computing. 28(12): 1590-1599, Dec 2010.

  15. K. Zhang, J.T. Kwok. Clustered Nystrom method for large scale manifold learning and dimension reduction. IEEE Transactions on Neural Networks. 21(10): 1576-1587, Oct 2010.

  16. W. Zhong, W. Pan, J.T. Kwok, I.W. Tsang. Incorporating the loss function into discriminative clustering of structured outputs. IEEE Transactions on Neural Networks. 21(10): 1564-1575, Oct 2010.

  17. K. Zhang, J.T. Kwok. Simplifying mixture models through function approximation. IEEE Transactions on Neural Networks. 21(4): 644-658, April 2010.

    2009

  18. 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.

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

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

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

    2008

  22. 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.

  23. 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.

  24. 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

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

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

  27. 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.

  28. 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

  29. 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)

  30. 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)

  31. 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)

  32. 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)

  33. 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)

  34. 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

  35. 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)

  36. 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

  37. 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)

  38. 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)

  39. 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)

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

  41. 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)

  42. 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)

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

  44. 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)

  45. 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)

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

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

  48. 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.

  49. 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.

  50. 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.

  51. 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

    2017

  1. H. Zhao, Q. Yao, J.T. Kwok, D.L. Lee. Collaborative filtering with social local models. Proceedings of the International Conference on Data Mining (ICDM), New Orleans, USA, November 2017.

  2. Q. Yao, J.T. Kwok, F. Gao, W. Chen, T.-Y. Liu. Efficient inexact proximal gradient algorithm for nonconvex problems. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Melbourne, Australia, August 2017.

  3. S. Zheng, J.T. Kwok. Follow the moving leader in deep learning. Proceedings of the International Conference on Machine Learning (ICML), Sydney, Australia, August 2017.

  4. Y. Wang, J.T. Kwok, Q. Yao, L.M. Ni. Zero-shot learning with a partial set of observed attributes. Proceedings of the International Joint Conference on Neural Networks (IJCNN), Anchorage, Alaska, USA, May 2017.

  5. L. Hou, Q. Yao, J.T. Kwok. Loss-aware binarization of deep networks. Proceedings of the International Conference on Representation Learning (ICLR), Toulon, France, Apr 2017.

  6. X. Guo, Q. Yao, J.T. Kwok. Efficient sparse low-rank tensor completion using Frank-Wolfe algorithm. Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI), San Francisco, California USA, Feb 2017.

    2016

  7. X. Guo, J.T. Kwok. Aggregating crowdsourced ordinal labels via Bayesian clustering. Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML-PKDD), Riva del Garda, Italy, Sept 2016.

  8. S. Zheng, J.T. Kwok. Fast-and-light stochastic ADMM. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), New York, NY, USA, Jul 2016.

  9. Q. Yao, J.T. Kwok. Greedy learning of generalized low-rank models. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), New York, NY, USA, Jul 2016.

  10. Q. Yao, J.T. Kwok. Efficient learning with a family of nonconvex regularizers by redistributing nonconvexity. Proceedings of the International Conference on Machine Learning (ICML), New York, NY, USA, Jun 2016.

  11. S. Zheng, R. Zhang, J.T. Kwok. Fast nonsmooth regularized risk minimization with continuation. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), pp.2393-2399, Phoenix, AZ, USA, Feb 2016.

  12. R. Zhang, S. Zheng, J.T. Kwok. Asynchronous distributed semi-stochastic gradient optimization. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), pp.2323-2329, Phoenix, AZ, USA, Feb 2016.

  13. L. Hou, J.T. Kwok, J.M. Zurada. Efficient learning of timeseries shapelets. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), pp.1209-1215, Phoenix, AZ, USA, Feb 2016.

  14. Y.-F. Li, J.T. Kwok, Z.-H. Zhou. Towards safe semi-supervised learning for multivariate performance measures. Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI), pp.1816-1822, Phoenix, AZ, USA, Feb 2016.

    2015

  15. K. Fan, Z. Wang, J. Beck, J.T. Kwok, K. Heller. Fast second order stochastic backpropagation for variational inference. Neural Information Processing Systems (NIPS), Montreal, Canada, Dec 2015.

  16. Q. Yao, J.T. Kwok, L.W. Zhong. Fast low-rank matrix learning with nonconvex regularization. Proceedings of the International Conference on Data Mining (ICDM), Atlantic City, NJ, USA, Nov 2015.

  17. Q. Yao, J.T. Kwok. Accelerated inexact soft-impute for fast large-scale matrix completion. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Buenos Aires, Argentina, Jul 2015.

  18. Y. Huang, J.T. Kwok. Collaborative filtering via co-factorization of individuals and groups. Proceedings of the International Joint Conference on Neural Networks (IJCNN), Killarney, Ireland, UK, Jul 2015.

  19. Q. Yao, J.T. Kwok. Colorization by patch-based local low-rank matrix completion. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), Austin, Texas, USA, Jan 2015.

    2014

  20. S. Zheng, J.T. Kwok. Accurate integration of aerosol predictions by smoothing on a manifold. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), Quebec City, Canada, July 2014.

  21. L.W. Zhong, J.T. Kwok. Gradient descent method with proximal average for nonconvex and composite regularization. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), Quebec City, Canada, July 2014.

  22. W. Bi, J.T. Kwok. Multilabel classification with label correlations and missing labels. Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), Quebec City, Canada, July 2014.

  23. W. Bi, L. Wang, J.T. Kwok, Z. Tu. Learning to predict from crowdsourced data. Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), Quebec City, Canada, July 2014.

  24. R. Zhang, J.T. Kwok. Asynchronous distributed ADMM for consensus optimization. Proceedings of the International Conference on Machine Learning (ICML), Beijing, China, June 2014.

  25. L.W. Zhong, J.T. Kwok. Fast stochastic alternating direction method of multipliers. Proceedings of the International Conference on Machine Learning (ICML), Beijing, China, June 2014.

  26. L.W. Zhong, J.T. Kwok. Accelerated stochastic gradient method for composite regularization. Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), Reykjavik, Iceland, April 2014.

    2013

  27. L.W. Zhong, J.T. Kwok. Efficient learning for models with DAG-structured parameter constraints. Proceedings of the International Conference on Data Mining (ICDM), Dallas, Texas, USA, December 2013.

  28. E. Hu, J.T. Kwok. Flexible nonparametric kernel learning with different loss functions. Proceedings of the International Conference on Neural Information Processing (ICONIP), Daegu, Korea, Nov 2013.

  29. L.W. Zhong, J.T. Kwok. Accurate probability calibration for multiple classifiers. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, July 2013.

  30. E.-L. Hu, J.T. Kwok. Efficient kernel learning from side information using ADMM. Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), Beijing, China, July 2013.

  31. W. Bi, J.T. Kwok. Efficient multi-label classification with many labels. Proceedings of the International Conference on Machine Learning (ICML), Atlanta, Georgia, USA, June 2013.

  32. K. Zhang, V.W. Zheng, Q. Wang, J.T. Kwok, Q. Yang, I. Marsic. Covariate shift in Hilbert space: A solution via surrogate kernels. Proceedings of the International Conference on Machine Learning (ICML), Atlanta, Georgia, USA, June 2013.

    2012

  33. W. Bi, J.T. Kwok. Hierarchical multilabel classification with minimum Bayes risk. Proceedings of the International Conference on Data Mining (ICDM), Brussels, Belgium, December 2012.

  34. W. Bi, J.T. Kwok. Mandatory leaf node prediction in hierarchical multilabel classification. Neural Information Processing Systems (NIPS), Lake Tahoe, CA, USA, December 2012.

  35. L.W. Zhong, J.T. Kwok. Convex multitask learning with flexible task clusters. Proceedings of the Twenty-Nineth International Conference on Machine Learning (ICML), Edinburgh, Scotland, June 2012.

    2011

  36. W. Pan, J.T. Kwok. Structured clustering with automatic kernel adaptation. Proceedings of the International Joint Conference on Neural Networks (IJCNN), San Jose, CA, USA, July 2011.

  37. L.W. Zhong, J.T. Kwok. Efficient sparse modeling with automatic feature grouping. Proceedings of the Twenty-Eighth International Conference on Machine Learning (ICML), Bellevue, WA, USA, June 2011.

  38. W. Bi, J.T. Kwok. Multi-label classification on tree- and DAG-structured hierarchies. Proceedings of the Twenty-Eighth International Conference on Machine Learning (ICML), Bellevue, WA, USA, June 2011.

  39. M. Li, X.-C. Lian, J.T. Kwok, B. Lu. Time and space efficient spectral clustering via column sampling. Proceedings of the International Conference on Computer Vision and Pattern Recognition (CVPR), Colorado Springs, CO, USA, June 2011.

    2010

  40. Y.-F. Li, J.T. Kwok, Z.-H. Zhou. Cost-sensitive semi-supervised support vector machine. Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence (AAAI), Atlanta, Georgia, USA. July 2010.

  41. C. Hu, J.T. Kwok. Manifold regularization for structured outputs via the joint kernel. Proceedings of the International Joint Conference on Neural Networks (IJCNN), Barcelona, Spain, July 2010.

  42. M. Li, J.T. Kwok, B. Lu. Making large-scale Nystrom approximation possible. Proceedings of the Twenty-Seventh International Conference on Machine Learning (ICML), Haifa, Isreal, June 2010.

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

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

    2009

  45. 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.

  46. 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.

  47. 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.

  48. 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.

  49. 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.

  50. 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.

  51. 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.

  52. 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.

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

  54. 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.

  55. 2008

  56. 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.

  57. 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.

  58. 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

  59. 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.

  60. 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.

  61. 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.

  62. 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.

  63. 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

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

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

  66. 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.

  67. 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.

  68. 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.

  69. 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.

  70. 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.

  71. 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.

  72. 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.

  73. 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, PA, USA, June 2006. (abstract) (data)

  74. 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, PA, USA, June 2006. (abstract)

  75. 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, PA, USA, June 2006. (abstract)

  76. 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.

  77. 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)

  78. 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)

  79. 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

  80. 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)

  81. 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)

  82. 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)

  83. 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)

  84. 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)

  85. 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)

  86. 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)

  87. 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

  88. 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.

  89. 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.

  90. 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)

  91. 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)

  92. 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)

  93. 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)

  94. 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)

  95. 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)

  96. 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)

  97. 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)

  98. 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)

  99. 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)

  100. 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)

  101. 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)

  102. 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)

  103. 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)

  104. 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)

  105. 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)

  106. 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)

  107. 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)

  108. 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)

  109. 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)

  110. 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)

  111. 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)

  112. 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)

  113. 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)

  114. 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)

  115. 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)

  116. 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.

  117. 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.

  118. 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.

  119. 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.

  120. 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.

  121. 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.

  122. 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.

Book Chapters

  1. J.T. Kwok, Z.-H. Zhou, L. Xu. Machine Learning. Handbook of Computational Intelligence: pp.495-522, Springer 2015.

Edited Books

  1. J. Kim, J. Kwok, K. Sumiya, B.-T. Zhang (Eds.): Special issue on the First International Conference on Big Data and Smart Computing 2014. Data Knowledge Engineering, 104: 15-16 2016.
  2. J.T. Kwok, Z.H. Zhou (Eds.): Special Issue on Sino-foreign-interchange Conference on Intelligence Science and Intelligent Data 2013. Neurocomputing, 2015.
  3. J.T. Kwok, L. Zhang, H. Lu (Eds.): Selected papers from the 2011 International Conference on Neural Information Processing (ICONIP 2011). Neurocomputing 129, 2014.
  4. L. Zhang, J.T. Kwok, C. Zhang (Eds.): Special Issue for ISNN 2010. Neurocomputing 76, 2012.
  5. B.-L. Lu, L. Zhang, J.T. Kwok (Eds.): Neural Information Processing - 18th International Conference, Proceedings, Springer June 2011.
  6. L. Zhang, B.-L. Lu, J.T. Kwok (Eds.): Advances in Neural Networks: 7th International Symposium on Neural Networks, ISNN 2010. Springer June 2010.
  7. 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.
  8. 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.