Books

• Junbin Gao et al., Chemometrics: From Basic to Wavelet Transform, (Chemical Analysis Series, Vol. 164), 2004 John Wiley & Sons Inc., ISBN 0-471-20242-8.
  
  
• Junbin Gao, MATLAB Programming, Huazhong University of Science and Technology Press, ISBN 7-5609-1864-6, 1998 (in Chinese)

Journal Publications

Here is a short list of my publications since 2000 which mainly covers my research works on machine learning. My earlier research works (about 40 journal papers) include the wavelet application, finite element analysis and multivariate spline theory. Some of those papers can be found through MathSciNet search engine of American Mathematical Society.

• Junbin Gao (with P Kwan, K. Kameyama and K. Toraichi), Content-based Image Retrieval of Cultural Heritages Symbols by Interaction of Visual Perspectives, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 25, No. 5 (2011) 643-673.
  
  
• Junbin Gao (with J. Zhang and D. Tien), Relevance Units Latent Variable Model and Nonlinear Dimension- ality Reduction, IEEE Transactions on Neural Networks, Vol. 21:1 (2010), pp. 123-135.
  
  
• Junbin Gao (with P. Kwan and D. Shi), Sparse Kernel Learning with LASSO and Its Bayesian Inference, Neural Networks, Vol. 23 (2010), Issue 2, pp 257-264.
  
  
• Junbin Gao (with P. Kwan, Y. Guo and K. Kameyama), A Learning Framework for Adaptive Fingerprint Identification, International Journal of Pattern Recognition and Artificial Intelligence, Vol. 24:1 (2010), pp15 - 38.
  
  
• Junbin Gao (with Y. Guo and P. Kwan), Comprehensive Analysis for the Local Fisher Discriminant Analysis, accepted by International Journal of Pattern Recognition and Artificial Intelligence, Vol. 23 (2009), 1129- 1143.
  
  
• Junbin Gao (with P. Kwan and Y. Guo), Robust Multivariate L1 Principal Component Analysis and Dimensionality Reduction, Neurocomputing, Vol. 72 (2009), pp 1242-1249.
  
  
• Junbin Gao (with Y. Guo and P. Kwan), Twin Kernel Embedding, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 30 (2008), pp 1490-1495
  
  
• Junbin Gao, Robust L1 Principal Component Analysis and Its Bayesian Variational Inference, Neural Computation, Vol.20:2 (2008), pp555-572
  
  
• Junbin Gao (with D.M. Shi and X.M. Liu), Critical Vector Learning to Construct Sparse Kernel Regression Modelling, Neural Networks, Vol 20 (2007), No. 7, pp 791-798
  
  
• Junbin Gao (with X Huang, W Lei, and A.S.M. Sajeev), A new algorithm for removing node overlapping in graph visualization, International Journal of Information Sciences, Vol.177 (2007), pp 2821-2844
  
  
• Junbin Gao (with T. Tian, S. Xu and K. Burrage), Simulated maximum likelihood method for estimating kinetic rates in gene expression, Bioinformatics, Vol.23 (2007), pp 84-91.
  
  
• Junbin Gao (with Y. Guo and P. Kwan), Kernel Laplacian Eigenmaps for Visualization of Non-vectorial Data, Lecture Notes on Artificial Intelligent, Vol. 4304 (2006), edn. by A. Sattar and B.H. Kang, pp. 1179 - 1183
  
  
• Junbin Gao (with D. Shi and G.S. Ng), The construction of wavelet network for speech signal processing, Neural Computing and Applications, Vol.15 (2006), pp217-222
  
  
• Junbin Gao (with D. Shi and D.S. Yeung), Sensitivity analysis applied to the construction of radial basis function networks, Neural Networks, Vol. 18(2005), p951-957.
  
  
• Junbin Gao (with D. Shi, Daniel Yeung and F. Chen), Radial basis function network pruning by sensitivity analysis, Lecture Notes in Computer Science, Vol. 3060 (2004), pp 380-390.
  
  
• Junbin Gao, S.R. Gunn and C.J. Harris, SVM Regression through Variational Methods and Its Sequential Implementation, Research Report, Neurocomputing, Vol.55 (2003), 151-167.
  
  
• Junbin Gao, S.R. Gunn and C.J. Harris, Mean Field Method for the SVM Regression, Neurocomputing, Vol. 50 (2003), 391-405.
  
  
• Junbin Gao, S. Gunn and J. Kandola, Adapting Kernels by Variational Approach in SVM, Lecture Notes in Artificial Intelligence, Vol.2557 (2002), pp 395 -- 406
  
  
• Junbin Gao and C.J. Harris, Some Remarks on Kalman Filters for the Multisensor Fusion, Information Fusion Journal, Vol.3 (2002), 191-201.
  
  
• Junbin Gao and C.J. Harris, Adaptive Multiscale Basis Method for Modelling Discrete-time Nonlinear Dynamic Systems, International Journal of Control, Vol.75, No.3 (2002), pp 141-153.
  
  
• Junbin Gao, S.R. Gunn, C.J. Harris and M.Q. Brown, A Probabilistic Framework for SVM Regression with Gaussian Process, Machine Learning, Vol.46 (2002), pp 71-89.
  
  
• Junbin Gao, C.J. Harris and S.R. Gunn, On a Class of Support Vector Kernels Based on Frames in Function Hilbert Spaces, Neural Computation, Vol.13, No.9 (2001), pp 1975 - 1994.
  
  
• C.J. Harris and Junbin Gao, Adaptive Linear Finite Element Method for Modelling Nonlinear Dynamic Systems, International Journal of Systems Science, Vol.31, No.10 (2000), pp1241-1248.
  
  
• Junbin Gao, Constructing the rectangular element for plate bending problem by interpolation methods, Numerical Mathematics a Journal of Chinese Universities, Vol. 22, No.1 ( 2000), pp 75-84.
  
  
• Junbin Gao, Z.H. Wang and N.C. Wang, Study of Schwarz alternating procedure on the union of two disks, Journal of Huazhong University of Science and Technology, Vol.28, No.4 (2000), pp112-114.

Refereed Conferences Papers (Selected)

• Gao Junbin (with Adrian Letchford and Lihong Zheng), Penalized Least Squares for Smoothing Financial Time Series, Proceedings of The 24th Australasian Joint Conference on Artificial Intelligence (AI2011), 5th-8th December 2011, Perth, Western Australia.
  
  
• Gao Junbin, Image Matting via Local Tangent Space Alignment, Proceedings of The 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011), Noosa Heads, Australia.
  
  
• Gao Junbin, Multi-task Beta Process Sparse Kernel Machines, Proceedings of IJCNN 2011, pp153-158, San Jose, USA
  
  
• Gao Junbin (with Y. Guo), Local Feature Based Tensor Kernel for Image Manifold Learning, Proc of PAKDD 2011 II, Shenzhen, China, 24-28 May 2011, pp544-554.
  
  
• Gao Junbin (with Bin Tong, Nguyen Huy Thach and Einoshin Suzuki), Gaussian Process for Dimensionality Reduction in Transfer Learning, Proc. Eleventh SIAM International Conference on Data Mining (SDM), pp. 783-794, April 2011, Phoenix/Mesa, Arizona.
  
  
• Gao Junbin (with X. Jiang, T. Wang and P. Kwan), Learning Gradient via Gaussian Process, Proceedings of PAKDD 2010, Part II, Lecture Notes on Artificial Intelligence, Vol. 6119, pp. 113-124, 2010.
  
  
• Gao Junbin (with J. Zhang), Sparse Kernel Learning and the Relevance Units Machine, Proceedings of PAKDD 2009, Lecture Notes on Artificial Intelligence, Vol. 5476(2009), pp612-619.
  
  
• Gao Junbin (with Y. Guo and P. Kwan), Robust L1 PCA and Its Application in Image Denoising, submitted to SPIE MIPPR 2007
  
  
• Gao Junbin (with Y. Guo and P. Kwan), A Learning Framework for Examiner-Centric Fingerprint Classification using Spectral Features, submitted to SPIE MIPPR 2007
  
  
• Gao Junbin (with Y. Guo), Integration of Shape Context and Semigroup Kernel in image classification, to appear in Proceedings of ICMLC 2007
  
  
• Gao Junbin (with Y. Guo and P. Kwan), Learning Out-of-Sample Mapping in Non-vectorial Data Reduction using Constrained Twin Kernel Embedding, to appear in Proceedings of ICMLC 2007
  
  
• Gao Junbin (with Y. Guo and P. Kwan), Learning Optimal Kernel from Distance Metric in Twin Kernel Embedding for Dimensionality Reduction and Visualization of Fingerprints, Lecture Notes in Artificial Intelligence, Vol. 4632 (2007), pp227-238, Proceeding of ADMA 2007.
  
  
• Gao,Junbin (with Y. Guo, P. W. Kwan and K. X. Hou), Visualization of Protein Structure Relationships using Twin Kernel Embedding, to appear in Proceeding of ICBBE 2007
  
  
• Gao, Junbin (with X. Liu, S. Cao and J. ZHANG), The Kernelized Geometrical Bisection Methods, Lecture Notes in Computer Science, Vol. 4492 (2007), pp681-688, Springer-Verlag
  
  
• Gao Junbin (with Y. Guo), Manifolds of Bag of Pixels: A Better Representation for Image Recognition?, Proceeding of the IEEE International Conference on SMC 2006, Taiwan, pp3618-3622
  
  
• Gao Junbin (with Y. Guo and P. Kwan), Visualization of Non-vectorial Data using Twin Kernel Embedding, Proceedings of the International Workshop on Integrating AI and Data Mining (AIDM 2006) in Australia, IEEE Computer Society, pp11-17, ISBN 0-7695-2730-2
  
  
• Gao Junbin (with P. Kwan and Y. Guo), Fingerprint Matching using Enhanced Shape Context, Proceedings of the Image and Vision Computing New Zealand 2006, Great Barrier Island, New Zealand, pp115-120
  
  
• Paul W.H. Kwan and Junbin Gao, A Multi-step Strategy for Approximate Similarity Search in Image Databases, Proceedings of The Seventeenth Australasian Database Conference (ADC 2006), Hobart, TAS, Australia, January 16-19, 2006, pp.139-147
  
  
• Junbin Gao and Daming Shi, Sparse Kernel Regression Modelling Based on L1 Significant Vector Learning, Proceedings of 2005 International Conference on Neural Networks and Brain, 13-15 October 2005, Beijing, pp1925-1930, ISBN 0-7803-9422-4.
  
  
• K.Vaidya, A.S.M. Sajeev and Junbin Gao, e-Procurement Assimilation: An Assessment of e-Business Capabilities and Supplier Readiness in the Australian Public Sector, in Proceedings of 7th International Conference on Electronic Commerce, Xian, China, pp429-434. ISBN 1-59593-113-9
  
  
• Paul W.H. Kwan, Kazuo Toraichi, Keisuke Kameyama, Junbin Gao and Nobuyuki Otsu), A Multi-step Strategy for Shape Similarity Search in Kamon Image Database, Proceedings of Image and Vision Computing New Zealand Conference (IVCNZ 2005), University of Otago, Dunedin, 28 - 29 Nov, 2005, pp. 266-271.
  
  
• Junbin Gao (with D. Shi and F. Chen), On the construction of Support Wavelet Networks, Proceeding of the International Conference on Systems, Man and Cybernetics, ISBN 0-7803-8567-5, 10-13 October 2004, The Hague, The Netherlands
  
  
• J. Soar, K. Vaidya and Junbin Gao, Implementing e-procurement initiatives: impact of organisational learning across the public sector. In: 5th International Conference of the Continuous Innovation Network (CINet), 22-25 Sep 2004, Sydney, Australia
  
  
• Junbin Gao and Lei Zhang, The error bar estimation for the soft classification with Gaussian process models, 9th Online World Conference on Soft Computing in Industrial Applications, September 20--26, 2004.
  
  
• Junbin Gao (with L. Zhang), Critical vector learning to construct sparse modelling with PRESS statistic, Proceeding of the Int. Conf. on Machine Learning and Cybern, 26-29th August 2004, Shanghai, China. ISBN 0-7803-8403-2
  
  
• Junbin Gao (with D. Shi and R. Tilanil), Univariate Time Series Forecasting with Fuzzy CMAC, Proceeding of the Int. Conf. on Machine Learning and Cybern. 26-29th August 2004, Shanghai, China. ISBN 0-7803-8403-2
  
  
• Junbin Gao (with L Wang), Least Square Protoface Method, Proceedings of Int. Conf. on Computational Intelligence for Modelling, Control and Automation, Gold Coast, Australia, 12-14 July 2004
  
  
• Junbin Gao, An Investigation into Error Propagation in Chained Models, Proc. of the Second International Conference on Machine Learning and Cybernetics, Xi'an, 2-5 Nov. 2003, p1168-1173.
  
  
• Junbin Gao, J.S. Kandola and S.R. Gunn, Bayesian Interpretable Sparse Kernels, workshop of Kernel Methods on NIPS'2001.
  
  
• Junbin Gao, S.R. Gunn and C.J. Harris, A New Implementation for SVM Regression Based on Mean Field Analysis, 2001 International Conference on Computational Intelligence for Modelling, Control and Automation - CIMCA'2001.
  
  
• Gao Junbin, Kernel method in Pattern Recognition and Classification, ( Invited Paper), in Proceedings of SPIE: Image Extraction, Segmentation, and Recognition, Vol. 4550 (2001), pp 9-18. (International Conference on Multispectral Image Processing and Pattern Recognition, 22-24 Oct. 2001, Wuhan, China)
  
  
• C.J. Harris and Junbin Gao, Adaptive Multiscale Basis Method for Nonlinear Modeling: Function Space Decomposition Approach, in Proceeding of SCI'99/ISAS'99, editor: N. Callaos and M. Aveledo etc., International Institute of Informatics and Systems, Orlando, USA, 1999.

Invited Talks/Seminars

• Gao, J.B. (27 May 2011). Image Matting, Faculty of Computer and Technology, Guangdong University of Technology, Guangzhou, China.
  
  
• Gao, J.B. (11 Jan 2011). Image Matting with Zero-One Constraints, Faculty of Control Engineering, Huazhong University of Science and Technology, Wuhan, China.
  
  
• Gao, J.B. (23 June 2010). Tutorial for Dimensionality Reduction, The 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Hyderabad, India.
  
  
• Gao, J.B. (24 Sept 2009). Beta Process and Its Application in Sparse Regression, Statistical Machine Learning Group, NICTA, Canberra, Australia
  
  
• Gao, J.B. (21 Oct 2006). Dimensionality reduction and manifold learning, School of Science and Technology, University of New England, Armidale Australia.
  
  
• Gao, J.B. (31 Oct. 2003). Introduction to Kernel Methods, Department of Mathematics, Zhongshan University, Guangzhou, China.
  
  
• Gao, J.B. (Dec. 2002 -- Jan. 2003). A Series of Talks on Kernel Machine Algorithm. State Key Lab of of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University.
  
  
• Gao, J.B. (Dec. 2002). Adaptive Kernels in SVM. Department of Applied Mathematics, The Hong Kong Polytechnic University (abstract)
  
  
• Gao, J.B. (June 2001). An introduction to Wavelets, Presented at ISIS Meeting, Department of Electronics and Computer Science, University of Southampton.