Publication List of Laiwan Chan

• Computational Finance, Bioinformatics and Data Mining

• ICA

• Neural Networks

• Speech Recognition

• Fuzzy Systems

• Zhang Kun and Laiwan Chan. Efficient Factor GARCH Models and Factor-DCC Models, Quantitative Finance, Vol 9, Number 1, February 2009, pp. 71-91(21).

• Tu Zhou and Laiwan Chan. Clustered Dynamic Conditional Correlation Multi-variate GARCH Model, Data Warehousing and Knowledge Discovery, 10th International Conference, DaWak, 2008, Turin, Italy, September 2-5, Springer, Lecture Notes in Computer Science, Vol 5182, Edited by Song, Eder and Nguyen, 2008, pp. 206-216.

• Li Teng and Laiwan Chan. Discovering Distinct Patterns in Gene Expression Profiles, Journal of Integrative Bioinformatics, 5(2):105, 2008

• Li Teng and Laiwan Chan. Discovering Biclusters by Iteratively Sorting with Weighted Correlation Coefficient in Gene Expression Data, Journal of Signal Processing Systems, Springer New York, Volume 50, Number 3, March 2008, p267-280 (abs)

• Jian Li, Kun Zhang and Laiwan Chan. Independent Factor Reinforcement Learning for Portfolio Management, in Proc. of the 8th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2007), 2007, LNCS 4881, Eds H Yin et al, pp1020-1031.

• Li Teng and Laiwan Chan. Mining Order Preserving Patterns in Microarray data by Finding Frequent Orders, in the proceedings of the IEEE 7th International Symposium on BioInformatics & BioEngineering (BIBE'07), 2007, p1018-1026

• Kun Zhang and Laiwan Chan. Extensions of ICA for Causality Discovery in the Hong Kong Stock Market, Proceedings of 13th International Conference on Neural Information Processing (ICONIP 2006), Hong Kong, Springer, Lecture Notes in Computer Science, Vol 4234, 2006, pp. 400-409. (pdf)

• Jian Li and Laiwan Chan. Reward Adjustment Reinforcement Learning for Risk-averse Asset Allocation, in the proceeedings of the International Joint Conference on Neural Networks, IJCNN06, Vancourver, Canada. 2006

• Laiwan Chan. Bidirectional Reinforcement Learning for Asset Allocation, in the Proceedings of ICONIP. 2005. (pdf)

• Haiqin Yang, Kaizhu Huang, Laiwan Chan, Irwin King, Michael R. Lyu. Outliers Treatment in Support Vector Regression for Financial Time Series Prediction. ICONIP 2004: 1260-1265

• Laiwan Chan. The prediction performance of independent factor models. In Proceedings of the 2002 IEEE International Joint Conference on Neural Networks, May, 2002 - Honolulu, Hawaii, USA, 2002. (ps, pdf)

• Haiqin Yang, Irwin King, and Laiwan Chan. Non-fixed and asymmetrical margin approach to stock market prediction using support vector regression. In Proceedings of ICONIP 2002, Singapore, 2002. (pdf)

• Haiqin Yang, Laiwan Chan, and Irwin King. Support vector machine regression for volatile stock market prediction. In H. Yin et al., editor, Intelligent Data Engineering and Automated Learning'02 - IDEAL 2002, LNCS 2412, pages 391-396, 2002. (ps, pdf)

• Laiwan Chan and Siu-Ming Cha. Selection of Independent Factor Model in Finance. in proceedings of 3rd International Conference on Independent Component Analysis and blind Signal Separation, 2001 December 9-12, 2001 -- San Diego, California, USA. (ps, pdf)

• S. M. Cha and Laiwan Chan. Applying Independent Component Analysis to Factor Model in Finance. Intelligent Data Engineering and Automated Learning - IDEAL 2000, Data Mining, Financial Engineering and Intelligent Agents, ed. K.S. Leung, L.W. Chan and H. Meng, Springer, pp 538-544, 2000. (ps pdf)

• Y. Q. Zhang and Laiwan Chan. ForeNet: Fourier Recurrent Networks for Time Series Prediction. in Proceedings of ICONIP 2000, Korea, pp 576-582, 2000.

• X. Gao and Laiwan Chan. An Algorithm for Trading and Portfolio Management Using Q-learning and Sharpe Ratio Maximization. in Proceedings of ICONIP 2000, Korea, pp 832-837, 2000.

• S. M. Cha and Laiwan Chan. Trading Signal Prediction. in Proceedings of ICONIP 2000, Korea, pp 842-846, 2000.

• Kun Zhang and Laiwan Chan. Nonlinear Independent Component Analysis with Minimum Nonlinear Distortion, the 24th Annual International Conference on Machine Learning (ICML 2007), Corvallis, OR, US, Jun., 2007, pp. 1127--1134

• Kun Zhang and Laiwan Chan. Kernel-Based Nonlinear Independent Component Analysis, in the 7th Annual International Conference on Independent Component Analysis and Signal Separation (ICA 2007), London, UK, Sept., 2007, p301-308

• Kun Zhang and Laiwan Chan. Separating Convolutive Mixtures of More Than Two Sources by Mutual Information Minimization, in IEEE Signal Processing Letters, Dec 2007, 14(12) pp 992-995.

• Kun Zhang and Laiwan Chan. Dimension Reduction as a Deflation Method in ICA, in IEEE Signal Processing Letters, 13(1), pp45-48, 2006

• Kun Zhang and Laiwan Chan. ICA by PCA Approach: Relating Higher-Order Statistics to Second-Order Moments, in the proceedings of 6th International Conference on Independent Component Analysis and Blind Signal Separation (ICA 2006) , LNCS 3889, Charleston, SC, USA, Mar., 2006, pp. 311--318

• Kun Zhang and Laiwan Chan. An Adaptive Method for Subband Decompostion ICA, in Neural Computation 18(1), pp191-223, 2006

• Kun Zhang and Laiwan Chan. To apply score function difference based ICA algorithms to high-dimensional data, In the Proceedings of the 13th European Symposium on Artificial Neural Networks, Bruges, Belgium. pp 291 -- 297, 27-29 April, 2005.

• Kun Zhang and Laiwan Chan. Extended Gaussianization method for blind separation of post-non-linear mixtures Neural Computation, February 2005, vol 17, no 2, pp425-452(28). (abstract in ingenta) (abstract)

• Kun Zhang and Laiwan Chan. Practical Method for Blind Inversion of Wiener Systems. In the Proceedings of the International Joint Conference on Neural Networks, IJCNN04, Budapest, Hungary. pp 2163 -- 2168, 25-29 July, 2004. (pdf)

• Kun Zhang and Laiwan Chan. Dimension Reduction Based on Orthogonality - A decorrelation Method in ICA. In Artificial Neural Networks and Neural Information Processing - ICANN/ICONIP, 2003, LNCS 2714, Springer-Verlag, edited by Okyay Kaynak, Ethem Alpaydin, Erkki Oja, Lei Xu, pp 132--139, 2003.

• Laiwan Chan. The prediction performance of independent factor models. In Proceedings of the 2002 IEEE International Joint Conference on Neural Networks, May, 2002 - Honolulu, Hawaii, USA, 2002. (ps, pdf)

• Laiwan Chan and Siu-Ming Cha. Selection of Independent Factor Model in Finance. in proceedings of 3rd International Conference on Independent Component Analysis and blind Signal Separation, 2001 December 9-12, 2001 -- San Diego, California, USA. (ps, pdf)

• S. M. Cha and Laiwan Chan. Applying Independent Component Analysis to Factor Model in Finance. Intelligent Data Engineering and Automated Learning - IDEAL 2000, Data Mining, Financial Engineering and Intelligent Agents, ed. K.S. Leung, L.W. Chan and H. Meng, Springer, pp 538-544, 2000. (ps pdf)

• Kaizhu Huang, Haiqin Yang, Irwin King, Michael R. Lyu, Laiwan Chan. The Minimum Error Minimax Probability Machine. Journal of Machine Learning Research, 5(Oct):1253--1286, 2004. (abstract) (pdf)

• C.S. Leung and Laiwan Chan. Dual extended Kalman filtering in Recurrent Neural Networks Neural Networks, 16(2):223-239, 2003.

• Y. Q. Zhang and Laiwan Chan. ForeNet: Fourier Recurrent Networks for Time Series Prediction. in Proceedings of ICONIP 2000, Korea, pp 576-582, 2000.

• Laiwan Chan and Chi-Cheong Szeto. Weight Groupings in the Training of Recurrent Networks. In Proceedings of the 2000 IEEE International Joint Conference on Neural Networks, Como, Italy, 2000.

• Edward Ho and Laiwan Chan. How to design a connectionist holistic parser ? Neural Computation, 11(8):1995-2016, 1999. (citations)

• John Sum, Chi-Sing Leung, Gilbert Young, Laiwan Chan, and Wing kay Kan. An adaptive bayesian pruning for neural networks in a non-stationary environment. Neural Computation, 11(4):977-994, 1999.

• Laiwan Chan. Weighted least square ensemble networks. In Proceedings of the 1999 IEEE International Joint Conference on Neural Networks, Washington D.C., 1999. (citation list from google)

• Laiwan Chan and Chi-Cheong Szeto. Training recurrent network with block-diagonal approximated Levenberg-Marquardt algorithm. In Proceedings of the 1999 IEEE International Joint Conference on Neural Networks, Washington D.C., 1999.

• A.W.K. Sim, C.T. Jin, Laiwan Chan, and P.H.W Leong. A comparison of methods for clustering electrophysiological multineuron recordings. In Engineering in Medicine and Biology Society, 1998. Proceedings of the 20th Annual International Conference of the IEEE, volume 3, pages 1381 - 1384, 1998.

• C. S. Leung and Laiwan Chan. An error control scheme for transmission of vector quantization data over noisy channels. IEEE Trans. on Signal Processing, 46(10):2767-2780, 1998.

• John P.F. Sum, Laiwan Chan, and Chi-Sing Leung. Extended Kalman filter-based pruning method for recurrent neural networks. Neural Computation, 10(6):1481-1506, 1998.

• Laiwan Chan and H. F. Chow. The prediction of Carbon-13 NMR chemical shifts using emsembles of networks. In Proceedings of the 1998 IEEE International Joint Conference on Neural Networks, Alaska, pages 96-100, 1998.

• Daqing Chen and Laiwan Chan. An adaptive learning rate for training ring-structure recurrent network. In The Proceeding of ICONIP'98, Japan, pages 1224 - 1227, 1998.

• Daqing Chen and Laiwan Chan. Training recurrent neural networks by using parallel recursive prediction error algorithm. In The Proceeding of ICONIP'98, Japan, pages 1393 - 1396, 1998.

• F.Y. Duan, I. King, Laiwan Chan, and L. Xu. Intra-block algorithm for digital watermarking. In 14th International Conference on Pattern Recognition (ICPR'98), Brisbane, Queensland, Australia, 17-20 August 1998. International Association of Pattern Recognition, IEEE Computer Society., volume I I, pages 1589-1591, 1998.

• F.Y. Duan, I. King, L. Xu, and Laiwan Chan. Intra-block max-min algorithm for embedding robust digital watermark into images. In Horace H.S. Ip and Arnold W.M. Smeulders, editors, Proceedings of the IAPR International Workshop on Multimedia Information Analysis and Retrieval, MINAR'98, also as Lecture Notes in Computer Science no. 1464, pages 255-264. Berlin Heidelberg, Germany, Springer-Verlag, 1998.

• I. King, L. Xu, and Laiwan Chan. Using rival penalized competitive clustering for feature indexing in Hong Kong's textile and fashion image database. In Proceedings to the International Joint Conference on Neural Networks (IJCNN'98), pages 237-240. IEEE Computer Press, May 4-9, 1998, 1998.

• C. S. Leung and Laiwan Chan. The behaviour of forgetting learning in Bidirectional Associative Memory. Neural Computation, 9(2):385-401, 1997.

• John P.F. Sum, C.S. Leung, Laiwan Chan, and Lei Xu. Yet another algorithm which can generate topography map. IEEE Trans. on Neural Networks, 8(5):1204 - 1207, 1997.

• C. S. Leung, Laiwan Chan, and Edmund Lai. Stability and statistical properties of second-order Bidirectional Associative Memory. IEEE Trans. Neural Networks, 8(2):267-277, 1997.

• C. S. Leung and Laiwan Chan. Transmission of vector quantized data over a noisy channel. IEEE Trans. on Neural Networks, 8(3):582-589, 1997.

• C. S. Leung, Laiwan Chan, and J. Sum. Attraction basin of Bidirectional Associative Memories. International Journal on Neural Systems, 7(6):715-726, 1997.

• Edward Ho and Laiwan Chan. Confluent preorder parsing of deterministic grammars. Connection Science, 9(3):269-293, 1997.

• C. S. Leung, P.F. Sum, A.C.Tsoi, and Laiwan Chan. Several aspects of pruning methods in recursive least square algorithms for neural networks. In K. Y. M. Wong, I. King, and D. Y. Yeung, editors, The oretical Aspects of Neural Computation, pages 71 - 80. Springer, 1997.

• Edward Ho and Laiwan Chan. Confluent preorder parser as a finite state automata. In Proceedings of International Conference on Artificial Neural Networks (ICANN'96), Bochum, Germany, pages 899 - 904, 1996.

• Laiwan Chan. Levenberg-Marquardt learning and regularization. In S. Amari, L. Xu, L. W. Chan, I. King, and K. S. Leung, editors, Progress in Neural Information Processing, pages 139 - 144. Springer Verlag, 1996.

• C.S. Leung, Laiwan Chan, and J. Sum. The statistical behavior of Bidirectional Associative Memory under forgetting learning. In S. Amari, L. Xu, L. W. Chan, I. King, and K. S. Leung, editors, Progress in Neural Information Processing, pages 188 - 193. Springer Verlag, 1996.

• P.K.S. Tam, J. Sum, C.S. Leung, and Laiwan Chan. Network response time for a general class of WTA. In S. Amari, L. Xu, Laiwan Chan, I. King, and K. S. Leung, editors, Progress in Neural Information Processing, pages 492 - 495. Springer Verlag, 1996.

• K.S.Edward Ho, W.S. Luk, and Laiwan Chan. Parallel implementation of the confluent preorder parser on DECmpp. In S. Amari, L. Xu, Laiwan Chan, I. King, and K. S. Leung, editors, Progress in Neural Information Processing, pages 1075 - 1080. Springer Verlag, 1996.

• C. S. Leung, Laiwan Chan, and John Sum. Storage behaviour and error correction capability of Bidirectional Associative Memory under forgetting learning. Neural, Parallel and Scientific Computations, 4(2):141-156, 1996.

• C. S. Leung, K. W. Wong, John Sum, and Laiwan Chan. On-line training and pruning for RLS algorithms. Electronics Letter, 32(23):2152-2153, 1996.

• K.I. Liu and Laiwan Chan. A constructive training algorithm for feedforward neural networks. In Proceedings of the First International Conference on Neural, Parallel and Scientific Computations, Atlanta, Georgia, USA, volume  1, pages 293 - 296, 1995.

• Tan Lee, P.C. Ching, and Laiwan Chan. Recurrent neural networks for speech modeling and speech recognition. In ICASSP-95, Proceedings of IEEE Int'l Conference on Acoustics, Speech, and Signal Processing, volume 5, pages 3319-3322, 1995.

• C. S. Leung, Laiwan Chan, and Edmund Lai. Stability, capacity, and statistical dynamics of second-order Bidirectional Associative Memory. IEEE Trans. Syst. Man Cybern., 25(10):1414-1423, 1995.

• Lai-Wan Chan. Connection reduction of the recurrent networks. In Proceeding of ICONIP'95, Beijing, volume 2, pages 813 - 816, 1995.

• Lai-Wan Chan, Man-Wai Chau, and Wing-Chung Chung. Globalor : a parallel implementation of the self -organizing map. In Proceeding of ICONIP'95, Beijing, volume 2, pages 625 - 628, 1995.

• Lai-Wan Chan and E.F.Y.Young. Chaos in recurrent networks. In The 1994 International Symposium on Speech, Image Processing and Neural Networks, Hong Kong, volume 1, pages 225-229, 1994.

• J. Sum and Lai-Wan Chan. Convergence of one-dimensional self-organizing map. In The 1994 International Symposium on Speech, Image Processing and Neural Networks, Hong Kong, volume 1, pages 81-84, 1994.

• W.C. Chan and Lai-Wan Chan. A multiresolution learning method for back-propagation networks. In World Congress on Neural Networks 1994, San Diego, volume III, pages 46-51, 1994.

• W.C. Chan and Lai-Wan Chan. Transformation of back-propagation networks in multi-resolution learning. In IEEE Conference on Neural Networks 1994, Orlando, volume 1, pages 290-294, 1994.

• E.F.Y. Young and Lai-Wan Chan. Parallel implementation of partially connected recurrent network. In IEEE Conference on Neural Networks 1994, Orlando, volume IV, pages 2058-2063, 1994.

• Lai-wan Chan and Fung yu Young. Ring-structured recurrent neural network. In Proceedings of World Congress on Neural Networks 1993, Portland, vol ume 4, pages 328-331, 1993.

• Lai-wan Chan and Fung yu Young. Using recurrent network for time series prediction. In Proceedings of World Congress on Neural Networks 1993, Portland, vol ume 4, pages 332-336, 1993.

• Lai-Wan Chan. Neural networks for collective translational invariant object recognition. International Journal of Pattern Recognition and Artificial Intelligence, 6(1):143-156, 1992. Also appeared in Neural Networks in Vision and Pattern Recognition ed. by J. Skrzypek and W. Karplus, World Scientific Publishing, 1992.

• C.C. Hui and Lai-Wan Chan. An error correcting algorithm for Hopfield network. In Proceedings of the International Joint Conference on Neural Networks, Baltimore, U.S.A., volume 1, pages 920-925, 1992.

• F.Y. Young and Lai-Wan Chan. Sequence recognition using recurrent backpropagation network. In Proceedings of The International Joint Conference on Neural Networks, Beijing, China, volume 2, pages 557-562, 1992.

• P.C.Yip and Lai-Wan Chan. Multi-level network architectures for motion detection. In Proceedings of The International Joint Conference on Neural Networks, Beijing, China, volume 3, pages 131-136, 1992.

• Lai-Wan Chan. Optimisation using delta rule network. In Proceeding of The International Computer Science Conference, Hong Kong, pages 113-119, 1992.

• Lai-Wan Chan. Analysis of the internal representations in neural networks for machine intelligence. In Proceedings of Ninth National Conference on Artificial Intelligence, AAAI-91, Anaheim, California, USA, volume 2, pages 578 -583, 1991.

• Lai-Wan Chan. Feature deactivation using partial inhibitory networks during multiple object recognition. In Proceedings of The International Joint Conference on Neural Networks, IJCNN91, Seattle, USA., volume 1, pages I-199-204, 1991.

• Lai-Wan Chan. Translational invariant object recognition using back propagation networks. In Proceedings of The International Joint Conference on Neural Networks, IJCNN91, Seattle, USA., volume 2, pages II-A915, 1991.

• Lai-Wan Chan, P.T.T. Chiu, and J.Y.W. Chow. The backpropagation unfold recurrent rule. In Proceedings of The International Joint Conference on Neural Networks, Singapore, volume 1, pages 734-739, 1991.

• Lai-Wan Chan and P.C. Yip. Neural networks for 3-D motion detection from a sequence of image frames. In Proceedings of The International Joint Conference on Neural Networks, Singapore, volume 3, pages 2013-2018, 1991.

• Lai-Wan Chan and F. Fallside. Inhibitory network for multiple object recognition. In Proceeding of the International Neural Network Conference, Paris, France, volume 1, pages 87-90, 1990.

• Lai-Wan Chan. Efficacy of different learning algorithms of the back propagation network. In IEEE Region 10 Conference on Computer and Communication System (TENCON'90), pages 23-27, 1990.

• F. Fallside and Lai-Wan Chan. Connectionist models and geometric reasoning. In J. Woodwark, editor, Geometric Reasoning, pages 65-82. Oxford Science Publications, 1989.

• Lai-Wan Chan and F. Fallside. An adaptive training algorithm for back propagation networks. Computer Speech and Language, pages 205-218, 1987.

• Edward Ho and Laiwan Chan. Extracting error productions from a neural network-based LR parser. Neurocomputing, Vol 47, issues 1-4, pp 189-206, 2002.

• Edward Ho and Laiwan Chan. Analyzing Holistic Parsers: Implications for Robust Parsing and Systematicity. Neural Computation, 13:5, pp 1137-1170, 2001.

• Edward Ho and Laiwan Chan. How to design a connectionist holistic parser ? Neural Computation, 11(8):1995-2016, 1999. (citations)

• Chiu Fai Chong, Laiwan Chan, and Pak Chung Ching. Hierarchical mixtures of experts for phonetic classification. In 1996 International Symposium on Multi-Technology Information Processing (ISMIP'96), Hsinchu, Taiwan, pages 461 - 466, 1996.

• Alfred Y.P. Ng, Tan Lee, P. C. Ching, and Laiwan Chan. Recent advances in Cantonese speech recognition. In 1996 International Symposium on Multi-Technology Information Processing (ISMIP'96), pages 134 - 144, 1996.

• Edward Ho and Laiwan Chan. Syntactic parsing using RAAM. In Proceedings of World Congress on Neural Networks, volume 1, pages 485-488, 1995.

• Tan Lee, P.C. Ching, Laiwan Chan, Y.H. Cheng, and Brian Mak. Tone recognition of isolated Cantonese syllables. IEEE Transaction on Speech and Audio Processing, May, 3(3):204 - 209, 1995. (citations)

• Tan Lee, P.C. Ching, and Laiwan Chan. An RNN based speech recognition system with discriminative training. In Proceedings of the 4th European Conference on Speech Communication and Technology, volume 3, pages 1667-1670, 1995.

• Y.P.A. Ng, P.C. Ching, and Lai-Wan Chan. Automatic recognition of Cantonese lexical tones in connected speech by multi-layer perceptron. In ESCA. EUROSPEECH'95. 4th European Conference on Speech Communication and Technology, Madrid, September 1995, pages 2205-2208, 1995.

• Edward Ho and Lai-Wan Chan. Linearization + confluent influence = efficient connectionist representations of parse trees for grammatical influence. In Proceedings of International Symposium on Artificial Neural Networks, Taiwan, pages IS-24-IS-31, 1995.

• Edward Ho and Lai-Wan Chan. Representing sentence structures in neural networks. In Proceedings of International Conference on Neural Information Processing, Korea, volume 3, pages 1462-1467, 1994.

• T. Lee, P.C. Ching, Lai-Wan Chan, and B. Mak. A NN-based one classifier for Cantonese. In Proceeding of the International Joint Conference on Neural Networks, Nagoya, Japan, volume 1, pages 287-290, 1993.

• C.W. Tsik, P.C. Ching, and Lai-Wan Chan. Large vocabulary isolated Cantonese word recognition using problem decomposition and hierarchical neural networks. In Proceedings of The Third Meeting of Japan Neural Network Society, Japan, pages 207-208, 1992.

• Yiu-Leung Yeng and Laiwan Chan. Codebook refinement with membership function. In The International Symposium on Fuzzy Logic, volume 1, pages 105-111, 1995.

• Lai-Wan Chan. The interpolation property of fuzzy polynomial approximation. In The 1994 International Symposium on Speech, Image Processing and Neural Networks, Hong Kong, volume 2, pages 449-452, 1994.

• Lai-Wan Chan. The fuzzy polynomial rules. In World Congress on Neural Networks 1994, San Diego, volume I, pages 805-810, 1994.

• J. Sum and Lai-Wan Chan. Fuzzy self-organizing map. In World Congress on Neural Networks 1994, San Diego, volume I, pages 732-737, 1994.

• J. Sum and Lai-Wan Chan. Fuzzy self-organizing map : Mechanism and convergence. In IEEE Conference on Neural Networks 1994, Orlando, volume 3, pages 1674-1679, 1994.

• J. Sum and Lai-Wan Chan. Alternative membership function for sequential fuzzy clustering. In IEEE Conference on Fuzzy Systems 1994, Orlando, volume III, pages 1846-1851, 1994.

• Lai-Wan Chan. The fuzzy function approximation as piecewise Lagrange interpolation. In Yeung Yam and K. S. Leung, editors, The Future Directions of Fuzzy Theory and Systems, Hong Kong. World Scientific Publisher, 1993.