Publication

Chan, P. P. K., Liu, W., Chen, D., Yeung, D. S., Zhang F., Wang, X. Z., Hsu, C. C., “Face Liveness Detection based on Flash and no Flash Image Against 2D Spoofing Attack”, IEEE Transactions on Information Forensics and Security, submitted
‧ Chan, P. P. K., Lin, Z., Hu, X., Tseung, E.C.C, Yeung, D. S., “Sensitivity based robust learning for stacked autoencoder against evasion attack”, Neurocomputing, https://doi.org/10.1016/j.neucom.2017.06.032
‧ Chan, P. P. K., He, Z., Li, H., Yeung, D. S., “Data Sanitization against Adversarial Label Contamination Based on Data Complexity”, International Journal of Machine Learning and Cybernetics, Accepted
‧ Sun, B., Ng, W. W. Y., Chan, P. P. K, “Improved Sparse LSSVMS based on the Localized Generalization Error Model”, International Journal of Machine Learning and Cybernetics, 2016
‧ Yeung, D. S., Li, J., Ng, W. W. Y., Chan, P. P. K., “MLPNN training via a multiobjective optimization of training error and stochastic sensitivity”, IEEE Trans. Neural Netw. Learning Syst. 27(5), 978– 992, 2016
‧ Zhang, F., Chan, P.P.K., Biggio, B., Yeung, D.S., Roli, F., “Adversarial feature selection against evasion attacks”, IEEE Trans. Cybernetics 46(3), 766–777, 2016
‧ Biggio, B., Corona, I., He, Z., Chan, P. P. K., Giacinto, G., Yeung, D. S., Roli, F., “One-and-a-half-class multiple classifier systems for secure learning against evasion attacks at test time”, In: Multiple Classifier Systems – 12th International Workshop, MCS 2015, G‥unzburg, Germany, June 29 – July 1, 2015, Proceedings, pp. 168–180, 2015
‧ Chan, P. P. K., Yang, C., Yeung, D. S., Ng, W. W. Y., “Spam filtering for short messages in adversarial environment”, Neurocomputing 155, 167–176, 2015
‧ He, Z., Chan, P. P. K., Yeung, D. S., Pedrycz, W., Ng, W. W. Y., “Quantification of side-channel information leaks based on data complexity measures for web browsing”, International Journal of Machine Learning and, 6(4), 607–619, 2015
‧ Lv, Y., Ng, W. W. Y., Zeng, Z., Yeung, D. S., Chan, P. P. K., “Asymmetric cyclical hashing for large scale image retrieval”, IEEE Trans. Multimedia 17(8), 1225–1235, 2015
‧ Ng, W. W. Y., Li, J., Feng, S., Yeung, D. S., Chan, P. P. K., “Sensitivity based image filtering for multi-hashing in large scale image retrieval problems”, International Journal of Machine Learning and, 6(5), 777–794, 2015
‧ Ng, W. W., Lv Y. M., Zeng Z. Q., Yeung D. S. and Chan, P. P. K., “Sequential conditional entropy maximization semi-supervised hashing for semantic image retrieval”, International Journal of Machine Learning and Cybernetics, pp. 1-16, 2015
‧ Ng, W. W., Lv, Y.M., Yeung, D. S., Chan, P. P. K., “Two-phase mapping hashing”, Neurocomputing, vol. 151, pp. 1423-1429, 2015
‧ Li, J. C., Ng, W. W. Y., Yeung, D. Y., Chan, P. P. K., “Bi-firing deep neural networks”, International Journal of Machine Learning and Cybernetics, Vol 5, pp 73 – 83, 2014
‧ Ng, W. W., He, Z. M., Yeung, D. S. and Chan, P. P. K., “Steganalysis classifier training via minimizing sensitivity for different imaging sources”, Information Sciences, vol. 281, pp. 211-224, 2014
‧ Ng, W. W., Liang X. L., Li J. C., Yeung D. S. and Chan, P. P. K., “LG-Trader: Stock trading decision support based on feature selection by weighted localized generalization error model”, Neurocomputing, vol. 146, pp. 104-112, 2014
‧ Dong, C.R., Ng, W. W., Wang, X.Z., Chan, P. P. K., Yeung, D. S., “An improved differential evolution and its application to determining feature weights in similarity-based clustering”, Neurocomputing, vol. 146, 95-103, 2014
‧ Sun, B., Ng, W. W. Y , Yeung, D. S., Chan, P. P. K., “Hyper-parameter selection for sparse LS-SVM via minimization of its localized generalization error”, International Journal on Wavelets Multiresolution and Information Processing, 11 (03), 2013
‧ Chan P. P. K., Yeung D. S., Ng W. W., Lin C. M., and Liu J. N., “Dynamic fusion method using Localized Generalization Error Model”, Information Sciences, vol. 217, pp. 1-20, 2012
‧ Yeung D. S., Chan P. P. K., Ng W. W., ” Radial Basis Function network learning using localized generalization error bound “, Information Sciences, vol. 179, pp. 3199-3217, 2009