Junbin Gao

2009
32	EE	Paul Wing Hing Kwan, Junbin Gao, Graham Leedham: A User-Centered Framework for Adaptive Fingerprint Identification. PAISI 2009: 89-100
31	EE	Junbin Gao, Jun Zhang: Sparse Kernel Learning and the Relevance Units Machine. PAKDD 2009: 612-619
30	EE	Junbin Gao, Paul W. Kwan, Yi Guo: Robust multivariate L1 principal component analysis and dimensionality reduction. Neurocomputing 72(4-6): 1242-1249 (2009)
2008
29	EE	Junbin Gao, Michael Antolovich, Paul W. Kwan: L1 LASSO Modeling and Its Bayesian Inference. Australasian Conference on Artificial Intelligence 2008: 318-324
28		Adrian O'Connor, Junbin Gao, John Louis: Using a Stochastic Funnel to find NLR Starting Values. GEM 2008: 96-102
27	EE	Richard Yi Da Xu, Junbin Gao, Michael Antolovich: Novel methods for high-resolution facial image capture using calibrated PTZ and static cameras. ICME 2008: 45-48
26	EE	Junbin Gao: Robust L1 Principal Component Analysis and Its Bayesian Variational Inference. Neural Computation 20(2): 555-572 (2008)
2007
25		Kok-Leong Ong, Wenyuan Li, Junbin Gao: Integrating Artificial Intelligence and Data Mining - Proceedings of the 2nd International Workshop on Integrating Artificial Intelligence and Data Mining (AIDM 2007). December 2007. Proceedings Australian Computer Society 2007
24	EE	Yi Guo, Paul Wing Hing Kwan, Junbin Gao: Learning Optimal Kernel from Distance Metric in Twin Kernel Embedding for Dimensionality Reduction and Visualization of Fingerprints. ADMA 2007: 227-238
23	EE	Matthew Robards, Junbin Gao, Philip Charlton: A Discriminant Analysis for Undersampled Data. AIDM 2007: 11-18
22	EE	Junbin Gao, Richard Y. Xu: Mixture of the Robust L1 Distributions and Its Applications. Australian Conference on Artificial Intelligence 2007: 26-35
21	EE	Yi Guo, Junbin Gao, Paul Wing Hing Kwan: Twin Kernel Embedding with Relaxed Constraints on Dimensionality Reduction for Structured Data. Australian Conference on Artificial Intelligence 2007: 659-663
20	EE	Yi Guo, Paul Wing Hing Kwan, Junbin Gao: Twin Kernel Embedding with Back Constraints. ICDM Workshops 2007: 319-324
19	EE	Xiaomao Liu, Shujuan Cao, Junbin Gao, Jun Zhang: The Kernelized Geometrical Bisection Methods. ISNN (2) 2007: 680-688
18	EE	Tianhai Tian, Songlin Xu, Junbin Gao, Kevin Burrage: Simulated maximum likelihood method for estimating kinetic rates in gene expression. Bioinformatics 23(1): 84-91 (2007)
17	EE	Xiaodi Huang, Wei Lai, A. S. M. Sajeev, Junbin Gao: A new algorithm for removing node overlapping in graph visualization. Inf. Sci. 177(14): 2821-2844 (2007)
16	EE	Junbin Gao, Daming Shi, Xiaomao Liu: Significant vector learning to construct sparse kernel regression models. Neural Networks 20(7): 791-798 (2007)
2006
15	EE	Paul Wing Hing Kwan, Junbin Gao: A multi-step strategy for approximate similarity search in image databases. ADC 2006: 139-147
14	EE	Yi Guo, Junbin Gao, Paul Wing Hing Kwan: Kernel Laplacian Eigenmaps for Visualization of Non-vectorial Data. Australian Conference on Artificial Intelligence 2006: 1179-1183
13	EE	Daming Shi, Fei Chen, Geok See Ng, Junbin Gao: The construction of wavelet network for speech signal processing. Neural Computing and Applications 15(3-4): 217-222 (2006)
2005
12	EE	Kishor Vaidya, A. S. M. Sajeev, Junbin Gao: E-procurement assimilation: an assessment of e-business capabilities and supplier readiness in the Australian public sector. ICEC 2005: 429-434
11	EE	Daming Shi, Daniel S. Yeung, Junbin Gao: Sensitivity analysis applied to the construction of radial basis function networks. Neural Networks 18(7): 951-957 (2005)
2004
10	EE	Daming Shi, Junbin Gao, Daniel S. Yeung, Fei Chen: Radial Basis Function Network Pruning by Sensitivity Analysis. Canadian Conference on AI 2004: 380-390
9	EE	Daming Shi, Geok See Ng, Junbin Gao, Daniel S. Yeung: Critical Vector Learning to Construct RBF Classifiers. ICPR (3) 2004: 359-362
8	EE	Junbin Gao, Fei Chen, Daming Shi: On the construction of support wavelet network. SMC (4) 2004: 3204-3207
2003
7	EE	Junbin Gao, Steve R. Gunn, Chris J. Harris: Mean field method for the support vector machine regression. Neurocomputing 50: 391-405 (2003)
6	EE	Junbin Gao, Steve R. Gunn, Chris J. Harris: SVM regression through variational methods and its sequential implementation. Neurocomputing 55(1-2): 151-167 (2003)
2002
5	EE	Junbin Gao, Steve R. Gunn, Jaz S. Kandola: Adapting Kernels by Variational Approach in SVM. Australian Joint Conference on Artificial Intelligence 2002: 395-406
4	EE	Junbin Gao, Chris J. Harris: Some remarks on Kalman filters for the multisensor fusion. Information Fusion 3(3): 191-201 (2002)
3		Junbin Gao, Steve R. Gunn, Chris J. Harris, Martin Brown: A Probabilistic Framework for SVM Regression and Error Bar Estimation. Machine Learning 46(1-3): 71-89 (2002)
2001
2		Junbin Gao, Chris J. Harris, Steve R. Gunn: On a Class of Support Vector Kernels Based on Frames in Function Hilbert Spaces. Neural Computation 13(9): 1975-1994 (2001)
2000
1	EE	Chris J. Harris, Junbin Gao: Adaptive linear finite-element method for modelling nonlinear dynamic systems. Int. J. System Science 31(10): 1241-1248 (2000)

Coauthor Index

1	Michael Antolovich	[27] [29]
2	Martin Brown	[3]
3	Kevin Burrage	[18]
4	Shujuan Cao	[19]
5	Philip Charlton	[23]
6	Fei Chen	[8] [10] [13]
7	Steve R. Gunn	[2] [3] [5] [6] [7]
8	Yi Guo	[14] [20] [21] [24] [30]
9	Chris J. Harris	[1] [2] [3] [4] [6] [7]
10	Xiaodi Huang	[17]
11	Jaz S. Kandola	[5]
12	Paul W. Kwan	[29] [30]
13	Paul Wing Hing Kwan	[14] [15] [20] [21] [24] [32]
14	Wei Lai	[17]
15	Graham Leedham (C. G. Leedham)	[32]
16	Wenyuan Li	[25]
17	Xiaomao Liu	[16] [19]
18	John Louis	[28]
19	Geok See Ng	[9] [13]
20	Adrian O'Connor	[28]
21	Kok-Leong Ong	[25]
22	Matthew Robards	[23]
23	A. S. M. Sajeev	[12] [17]
24	Daming Shi	[8] [9] [10] [11] [13] [16]
25	Tianhai Tian	[18]
26	Kishor Vaidya	[12]
27	Richard Y. Xu	[22]
28	Richard Yi Da Xu	[27]
29	Songlin Xu	[18]
30	Daniel S. Yeung	[9] [10] [11]
31	Jun Zhang	[19] [31]

Colors in the list of coauthors