Junbin Gao

Photo of Junbin Gao

BSc HUST; MSc HUST; PhD DUT
Professor

Rm 4085
H70 - Abercrombie Building
The University of Sydney
NSW 2006 Australia

Telephone +61 2 8627 4856
junbin.gao@sydney.edu.au

Professor Junbin Gao is recruiting high quality PhD students who would like to conduct research in the areas of Data Science and Machine Learning.

Bio

Junbin Gao is Professor of Big Data Analytics at the University of Sydney Business School. Prior to joining the University of Sydney in 2016, he was Professor in Computing from 2010 to 2016 and Associate Professor from 2005 to 2010 at Charles Sturt University (CSU). He was Senior Lecturer from Jan 2005 to July 2005 and Lecturer from Nov 2001 to Jan 2005 in the School of Mathematics, Statistics and Computer Science (now the School of Science and Technology) at University of New England (UNE). Between 1999 and 2001, he worked as a Research Fellow in the Department of Electronics and Computer Science at University of Southampton, England.

Junbin Gao graduated from Huazhong University of Science and Technology (HUST) in 1982 with a Bachelor Degree in Computational Mathematics. He obtained his PhD from Dalian University of Technology in 1991. Between 1991 and 1993 he worked as a postdoctoral research fellow investigating wavelet applications at Wuhan University. He was appointed as an Associate Professor in July 1993 and promoted to Professor in October 1997 in Department of Mathematics of HUST. He was Guest Professor (2003-2006) in the State Key Lab of Information Engineering in Surveying, Mapping and Remote Sensing at Wuhan University, China; Guest Professor (2007-2010) in the School of Computer Science and Technology at Huazhong University of Science and Technology, China; Guest Professor (2008-2011) in the School of Computers at Guangdong University of Technology, China; and Visiting Professor (2012-2015) in Beijing Municipal Key Lab of Multimedia and Intelligent Software Technology at Beijing University of Technology.

Until recently his major research interest has been machine learning and its application in data science, image analysis, pattern recognition, Bayesian learning & inference, and numerical optimization etc. He is the author of 260 academic research papers and two books. His recent research has involved new machine learning algorithms for big data in business. Prof Gao won two research grants in Discovery Project theme from the prestigious Australian Research Council (ARC).

Research Interests

Professor Junbin Gao began his research career by studying approximation theory and application of multivariate spline functions in numerical solutions for partial differential equations, continuing research work in wavelet applications in chemometrics, and becoming an outstanding researcher in machine learning, pattern recognition, Bayesian learning/inference, numerical optimisation and big data analytics in business.

One of interesting examples in Junbin’s recent research is to propose matrix neural networks and apply it in longitudinal relational data in politics research, where he further develops it to tensorial recurrent neural network. In a series of papers from 2014 to 2017 Junbin Gao showed how to conduct data subspace clustering and dimensionality reduction on manifolds particularly for the abstract Grassmann manifolds. Much of this work has been joint with a number of international collaborators. Junbin Gao’s work prior to 2014 is on dimensionality reduction, which was funded by the Australian Research Council (ARC), and the success can be seen in a series of paper between 2005 and 2013 and the research was quoted by The Australian newspaper in 2012.

More recently Junbin has focussed on designing machine learning algorithms for structural data such as tensor-valued data and manifold-valued data widely seen modern business and computer vision. In classical data analysis and machine learning algorithms, input data including manifold-valued data are generally regarded as or converted to vectorial data in a Euclidean space by ignoring useful prior information. However, for manifold-valued data, it is unclear how to extend those very powerful machine learning algorithms for vectorial data, such as the state-of-the-art Low Rank Representation models, onto general Riemannian manifolds due to loss of linearity structures over “curved” Riemannian manifolds.

In recent years there has been great progress in the research of commonly used matrix manifolds such as the tensor manifold/covariance descriptor, Stiefel manifold, Multinomial Manifold, Grassmann manifold, Kendall Shape manifolds and Low Rank matrix manifold.  The core idea is to explicitly incorporate geometry of manifolds for the purpose of learning algorithm design, which brings advantages of improving accuracy and efficiency and reducing computational cost of conventional machine learning algorithms. So answering questions about manifold-valued data modelling forces us to consider how sufficiently using Riemannian properties of the well-known matrix manifolds to assist designing new learning algorithms for manifold-valued data analysis.

There are applications in many areas, but Junbin Gao has a particular interest in what happens in international relation research and panel data in financial world, and also learning tasks in pattern analysis for computer vision tasks.

Current Research Supervision

  • Renlong Jie (PhD) Online Architecture Optimization for Deep Neural Networks.
  • Jessica Leung (PhD) Predictive modelling in insurance. (Primary Supervisor: Dmytro Matsypura and Co-supervisor: Boris Choy)
  • Suman Saha (PhD) Stock Market Movement Prediction and Portfolio Optimization Using Machine Learning Techniques. (Co-supervisor: Richard Gerlach)
  • Xuebin Zheng (PhD) Scalable Bayesian Inference for Machine Learning. (Co-supervisor: Marcel Scharth)
  • Bingxin Zhou (PhD) Generalized Variational Approximation with Riemannian Optimization. (Co-supervisor: Minh-Ngoc Tran)

Selected publications

2019

Journal Articles

Ali M, Gao J, and Antolovich M (2019) Parametric Classification of Bingham Distributions based on Grassmann Manifolds IEEE Transactions on Image Processing, 28 (12), 5771-5784. [More Information]

Chen H, Sun Y, Gao J, Hu Y, and Yin B (2019) Solving Partial Least Squares Regression via Manifold Optimization Approaches IEEE Transactions on Neural Networks and Learning Systems, 30 (2), 588-600. [More Information]

Chowdhury M, Gao J, and Islam R (2019) Extracting depth information from stereo images using a fast correlation matching algorithm International Journal of Computers and Applications, Published online: 11 Jul 2018. [More Information]

Hong X, and Gao J (2019) Estimating the square root of probability density function on Riemannian manifold Expert Systems, In Press. [More Information]

Ji Q, Sun Y, Gao J, Hu Y, and Yin B (2019) Nonlinear Subspace Clustering via Adaptive Graph Regularized Autoencoder IEEE Access, 7, 74122-74133. [More Information]

Jiang X, Song X, Zhang Y, Jiang J, Gao J, and Cai Z (2019) Laplacian Regularized Spatial-Aware Collaborative Graph for Discriminant Analysis of Hyperspectral Imagery Remote Sensing, 11 (1), 1-22. [More Information]

Ju F, Sun Y, Gao J, Antolovich M, Dong J, and Yin B (2019) Tensorizing Restricted Boltzmann Machine ACM Transactions on Knowledge Discovery from Data, 13 (3), 1-16. [More Information]

Ju F, Sun Y, Gao J, Hu Y, and Yin B (2019) Probabilistic Linear Discriminant Analysis With Vectorial Representation for Tensor Data IEEE Transactions on Neural Networks and Learning Systems, 30 (10), 2938-2950. [More Information]

Khan M, Khan T, Soomro T, Mir N, and Gao J (2019) Boosting sensitivity of a retinal vessel segmentation algorithm Pattern Analysis and Applications, 22 (2), 583-599. [More Information]

Li J, Huai H, Gao J, Kong D, and Wang L (2019) Spatial-temporal dynamic hand gesture recognition via hybrid deep learning model Journal on Multimodal User Interfaces, Published online: 14 May 2019. [More Information]

Soomro T, Afifi A, Gao J, Hellwich O, Zheng L, and Paul M (2019) Strided fully convolutional neural network for boosting the sensitivity of retinal blood vessels segmentation Expert Systems with Applications, 134, 36-52. [More Information]

Soomro T, Afifi A, Zheng L, Soomro S, Gao J, Hellwich O, and Paul M (2019) Deep Learning Models for Retinal Blood Vessels Segmentation: A Review IEEE Access, 7, 71696-71717. [More Information]

Wu L, Wang Y, Gao J, and Li X (2019) Where-and-When to Look: Deep Siamese Attention Networks for Video-based Person Re-identification IEEE Transactions on Multimedia, 21 (6), 1412-1424. [More Information]

Wu L, Wang Y, Li X, and Gao J (2019) Deep Attention-Based Spatially Recursive Networks for Fine-Grained Visual Recognition IEEE Transactions on Cybernetics, 49 (5), 1791-1802. [More Information]

Xu C, Yang J, and Gao J (2019) Coupled-learning convolutional neural networks for object recognition Multimedia Tools and Applications, 78 (1), 573-589. [More Information]

Yin M, Gao J, Xie S, and Guo Y (2019) Multiview Subspace Clustering via Tensorial t-Product Representation IEEE Transactions on Neural Networks and Learning Systems, 30 (3), 851-864. [More Information]

Zhang H, Qian J, Gao J, Yang J, and Xu C (2019) Scalable Proximal Jacobian Iteration Method With Global Convergence Analysis for Nonconvex Unconstrained Composite Optimizations IEEE Transactions on Neural Networks and Learning Systems, 30 (9), 2825-2839. [More Information]

Zhu M, Shi D, and Gao J (2019) Branched convolutional neural networks incorporated with Jacobian deep regression for facial landmark detection Neural Networks, 118, 127-139. [More Information]

Conference Proceeding

Piao X, Hu Y, Gao J, Sun Y, and Yin B (2019) Double Nuclear Norm Based Low Rank Representation on Grassmann Manifolds for Clustering IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019); Institute of Electrical and Electronics Engineers (IEEE), United States. [More Information]

Book Chapters

Soomro T, Gao J, Zheng L, Afifi A, and Soomro S (2019) Retinal Blood Vessels Extraction of Challenging Images Data mining : 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised selected papers; Springer, Singapore, 347-359. [More Information]

Wang B, and Gao J (2019) Unsupervised Learning on Grassmann Manifolds for Big Data Multimodal Analytics for Next-Generation Big Data Technologies and Applications; Springer International Publishing, Cham, 151-180. [More Information]

Yates D, Islam M, and Gao J (2019) SPAARC: A Fast Decision Tree Algorithm Data mining : 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised selected papers; Springer, Singapore, 43-55. [More Information]

Yates D, Islam Z, and Gao J (2019) Implementation and Performance Analysis of Data-Mining Classification Algorithms on Smartphones Data mining : 16th Australasian Conference, AusDM 2018, Bahrurst, NSW, Australia, November 28-30, 2018, Revised selected papers; Springer, Singapore, 331-343. [More Information]

2018

Journal Articles

Ali M, and Gao J (2018) Classification of matrix-variate Fisher-Bingham distribution via Maximum Likelihood Estimation using manifold valued data Neurocomputing, 295, 72-85. [More Information]

Chen H, Sun Y, Gao J, Hu Y, and Yin B (2018) Fast optimization algorithm on Riemannian manifolds and its application in low-rank learning Neurocomputing, 291, 59-70. [More Information]

Hu F, Liu W, Tsai S, Gao J, Bin N, and Chen Q (2018) An Empirical Study on Visualizing the Intellectual Structure and Hotspots of Big Data Research from a Sustainable Perspective Sustainability, 10 (3), 1-19. [More Information]

Ju F, Sun Y, Gao J, Hu Y, and Yin B (2018) Vectorial Dimension Reduction for Tensors Based on Bayesian Inference IEEE Transactions on Neural Networks and Learning Systems, 29 (10), 4579-4592. [More Information]

Qi N, Shi Y, Sun X, Wang J, Yin B, and Gao J (2018) Multi-Dimensional Sparse Models IEEE Transactions on Pattern Analysis and Machine Intelligence, 40 (1), 163-178. [More Information]

Soomro T, Khan T, Khan M, Gao J, Paul M, and Zheng L (2018) Impact of ICA-Based Image Enhancement Technique on Retinal Blood Vessels Segmentation IEEE Access, 6, 3524-3538. [More Information]

Wang B, Hu Y, Gao J, Ali M, Tien D, Sun Y, and Yin B (2018) Low Rank Representation on SPD Matrices with Log-Euclidean Metric Pattern Recognition, 76, 623-634. [More Information]

Wang B, Hu Y, Gao J, Sun Y, and Yin B (2018) Localized LRR on Grassmann Manifold: An Extrinsic View IEEE Transactions on Circuits and Systems for Video Technology, 28 (10), 2524-2536. [More Information]

Wang B, Yongli H, Gao J, Sun Y, and Yin B (2018) Partial sum minimization of singular values representation on grassmann manifolds ACM Transactions on Knowledge Discovery from Data, 12 (1), 1-22. [More Information]

Wang Y, Wu L, Lin X, and Gao J (2018) Multiview Spectral Clustering via Structured Low-Rank Matrix Factorization IEEE Transactions on Neural Networks and Learning Systems, 29 (10), 4833-4843. [More Information]

Wu L, Wang Y, Gao J, and Li X (2018) Deep adaptive feature embedding with local sample distributions for person re-identification Pattern Recognition, 73, 275-288. [More Information]

Wu L, Wang Y, Li X, and Gao J (2018) What-and-where to match: Deep spatially multiplicative integration networks for person re-identification Pattern Recognition, 76, 727-738. [More Information]

Xu C, Yang J, Gao J, Lai H, and Yan S (2018) SRNN: Self-regularized neural network Neurocomputing, 273, 260-270. [More Information]

Yin M, Wu Z, Shi D, Gao J, and Xie S (2018) Locally adaptive sparse representation on Riemannian manifolds for robust classification Neurocomputing, 310, 69-76. [More Information]

Yin M, Xie S, Wu Z, Zhang Y, and Gao J (2018) Subspace Clustering via Learning an Adaptive Low-Rank Graph IEEE Transactions on Image Processing, 27 (8), 3716-3728. [More Information]

Yin M, Zeng D, Gao J, Wu Z, and Xie S (2018) Robust Multinomial Logistic Regression Based on RPCA IEEE Journal on Selected Topics in Signal Processing, 12 (6), 1144-1154. [More Information]

Zhang Z, Xu C, Yang J, Gao J, and Cui Z (2018) Progressive Hard-Mining Network for Monocular Depth Estimation IEEE Transactions on Image Processing, 27 (8), 3691-3702. [More Information]

Zheng W, Xu C, Yang J, Gao J, and Zhu F (2018) Low-rank structure preserving for unsupervised feature selection Neurocomputing, 314, 360-370. [More Information]

Zhu F, Gao J, Xu C, Yang J, and Tao D (2018) On Selecting Effective Patterns for Fast Support Vector Regression Training IEEE Transactions on Neural Networks and Learning Systems, 29 (8), 3610-3622. [More Information]

Conference Proceedings

Chowdhury M, Islam R, and Gao J (2018) Fast and robust biometric authentication scheme using human ear 13th EAI International Conference on Security and Privacy in Communication Networks (SecureComm 2017); Springer, Ontario. [More Information]

Chowdhury M, Jahan S, Islam R, and Gao J (2018) Malware detection for healthcare data security 14th International EAI Conference on Security and Privacy in Communication Networks (SecureComm 2018); Springer, Cham. [More Information]

Hu X, Sun Y, Gao J, Hu Y, and Yin B (2018) Locality Preserving Projection Based on F-norm The Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18); AAAI Press, Palo Alto.

Jahan S, Chowdhury M, Islam R, and Gao J (2018) Security and privacy protection for eHealth data 4th International Conference on Future Network Systems and Security (FNSS 2018); Springer Verlag, Paris. [More Information]

Song X, Jiang X, Gao J, Cai Z, and Hong X (2018) Functional Locality Preserving Projection for Dimensionality Reduction 2018 IEEE International Joint Conference on Neural Networks (IJCNN); Institute of Electrical and Electronics Engineers (IEEE), Rio de Janeiro. [More Information]

Soomro T, Afifi A, Gao J, Hellwich O, Paul M, and Zheng L (2018) Strided U-Net Model: Retinal Vessels Segmentation using Dice Loss 2018 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2018); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Wang B, Hu Y, Gao J, Sun Y, and Yin B (2018) Cascaded low rank and sparse representation on grassmann manifolds 27th International Joint Conference on Artificial Intelligence (IJCAI 2018); International Joint Conferences on Artificial Intelligence, Stockholm. [More Information]

Wang G, Kang W, Wu Q, Wang Z, and Gao J (2018) Generative Adversarial Network (GAN) Based Data Augmentation for Palmprint Recognition 2018 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2018); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Zhang Y, Chandra R, and Gao J (2018) Cyclone Track Prediction with Matrix Neural Networks 2018 IEEE International Joint Conference on Neural Networks (IJCNN); Institute of Electrical and Electronics Engineers (IEEE), Rio de Janeiro. [More Information]

Zhu M, Shi D, Chen S, and Gao J (2018) Branched convolutional neural networks for face alignment 19th Pacific-Rim Conference on Multimedia, PCM 2018; Springer, Cham. [More Information]

Book Chapter

Jiang X, Gao J, Liu X, Cai Z, Zhang D, and Liu Y (2018) Shared Deep Kernel Learning for Dimensionality Reduction Advances in Knowledge Discovery and Data Mining: 22nd Pacific-Asia Conference, PAKDD 2018 Melbourne, VIC, Australia, June 3�6, 2018 Proceedings, Part III; Springer, Cham, 297-308. [More Information]

2017

Journal Articles

Chowdhury M, Gao J, and Islam R (2017) Robust human detection and localization in security applications Concurrency and Computation: Practice and Experience, 29 (23), 1-17. [More Information]

Hong X, Chen S, Guo Y, and Gao J (2017) l1-norm penalised orthogonal forward regression International Journal of Systems Science, 48 (10), 2195-2201. [More Information]

Hong X, Gao J, and Chen S (2017) Zero-Attracting Recursive Least Squares Algorithms IEEE Transactions on Vehicular Technology, 66 (1), 213-221. [More Information]

Jiang X, Fang X, Chen Z, Gao J, Jiang J, and Cai Z (2017) Supervised Gaussian Process Latent Variable Model for Hyperspectral Image Classification IEEE Geoscience and Remote Sensing Letters, 14 (10), 1760-1764. [More Information]

Li F, Xin L, Guo Y, Gao J, and Jia X (2017) A Framework of Mixed Sparse Representations for Remote Sensing Images IEEE Transactions on Geoscience and Remote Sensing, 55 (2), 1210-1221. [More Information]

Liu Q, Shao G, Wang Y, Gao J, and Leung H (2017) Log-Euclidean Metrics for Contrast Preserving Decolorization IEEE Transactions on Image Processing, 26 (12), 5772-5783. [More Information]

Shi D, Wang J, Cheng D, and Gao J (2017) A global-local affinity matrix model via EigenGap for graph-based subspace clustering Pattern Recognition Letters, 89, 67-72. [More Information]

Soomro T, Gao J, Khan T, Hani A, Khan M, and Paul M (2017) Computerised approaches for the detection of diabetic retinopathy using retinal fundus images: a survey Pattern Analysis and Applications, 20 (4), 927-961. [More Information]

Soomro T, Khan M, Gao J, Khan T, and Paul M (2017) Contrast normalization steps for increased sensitivity of a retinal image segmentation method Signal, Image and Video Processing, 11 (8), 1509-1517. [More Information]

Wang B, Hu Y, Gao J, Sun Y, and Yin B (2017) Laplacian LRR on Product Grassmann Manifolds for Human Activity Clustering in Multicamera Video Surveillance IEEE Transactions on Circuits and Systems for Video Technology, 27 (3), 554-566. [More Information]

Zhu F, Yang J, Gao J, Xu C, Xu S, and Gao C (2017) Finding the samples near the decision plane for support vector learning Information Sciences, 382-383, 292-307. [More Information]

Conference Proceedings

Chowdhury M, Gao J, and Islam R (2017) Biometric authentication using facial recognition 12th EAI International Conference on Security and Privacy in Communication Networks (SecureComm 2016); Springer Verlag, Berlin, Germany. [More Information]

Chowdhury M, Islam R, and Gao J (2017) Robust ear biometric recognition using neural network 12th IEEE Conference on Industrial Electronics and Applications (ICIEA 2017); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ. [More Information]

Liu S, Sun Y, Hu Y, Gao J, Ju F, and Yin B (2017) Matrix variate RBM model with Gaussian distributions The International Joint Conference on Neural Networks (IJCNN 2017); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Soomro T, Gao J, Paul M, and Zheng L (2017) Retinal blood vessel extraction method based on basic filtering schemes 2017 IEEE International Conference on Image Processing (ICIP 2017); Institute of Electrical and Electronics Engineers (IEEE), China. [More Information]

Wang B, Hu Y, Gao J, Sun Y, Chen H, Ali M, and Yin B (2017) Locality Preserving Projections for Grassmann manifold 26th International Joint Conference on Artificial Intelligence (IJCAI 2017); International Joint Conferences on Artificial Intelligence, Melbourne. [More Information]

Wang Q, Gao J, and Li H (2017) Grassmannian Manifold Optimization Assisted Sparse Spectral Clustering 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017); Institute of Electrical and Electronics Engineers (IEEE), Honolulu. [More Information]

Zhang Y, Shi D, Gao J, and Cheng D (2017) Low-Rank-Sparse Subspace Representation for Robust Regression 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017); Institute of Electrical and Electronics Engineers (IEEE), Honolulu. [More Information]

Book Chapters

Bai M, Zhang B, and Gao J (2017) Tensorial Neural Networks and Its Application in Longitudinal Network Data Analysis Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part II; Springer, Cham, 562-571. [More Information]

Gao J, Guo Y, and Wang Z (2017) Matrix Neural Networks Advances in Neural Networks - ISNN 2017: 14th International Symposium, ISNN 2017, Sapporo, Hakodate, and Muroran, Hokkaido, Japan, June 21-26, 2017, Proceedings, Part I; Springer, Cham, 313-320. [More Information]

Wang P, He Z, Xie K, Gao J, and Antolovich M (2017) A Nonnegative Projection Based Algorithm for Low-Rank Nonnegative Matrix Approximation Neural Information Processing: 24th International Conference, ICONIP 2017 Guangzhou, China, November 14-18, 2017 Proceedings, Part I; Springer, Cham, 240-247. [More Information]

Zhang Y, and Gao J (2017) Assessing the Performance of Deep Learning Algorithms for Newsvendor Problem Neural Information Processing: 24th International Conference, ICONIP 2017 Guangzhou, China, November 14-18, 2017 Proceedings, Part I; Springer, Cham, 912-921. [More Information]

2016

Journal Articles

Dong J, Gao J, Ju F, and Shen J (2016) Modulus Methods for Nonnegatively Constrained Image Restoration SIAM Journal on Imaging Sciences (SIIMS), 9 (3), 1226-1246. [More Information]

Fu Y, Gao J, Tien D, Lin Z, and Hong X (2016) Tensor LRR and Sparse Coding-Based Subspace Clustering IEEE Transactions on Neural Networks and Learning Systems, 27 (10), 2120-2133. [More Information]

Ju F, Sun Y, Gao J, Hu Y, and Yin B (2016) Nonparametric tensor dictionary learning with beta process priors Neurocomputing, 218, 120-130. [More Information]

Paul M, Xiao R, Gao J, and Bossomaier T (2016) Reflectance Prediction Modelling for Residual-based Hyperspectral Image Coding PloS One, 11 (10), 1-16. [More Information]

Rahman A, Gao J, D'Este C, and Ahmed S (2016) An Assessment of the Effects of Prior Distributions on the Bayesian Predictive Inference International Journal of Statistics and Probability, 5 (5), 31-42. [More Information]

Soomro T, and Gao J (2016) Non-Invasive Contrast Normalisation and Denosing Technique for the Retinal Fundus Image Annals of Data Science, 3 (3), 265-279. [More Information]

Sun Y, Gao J, Hong X, Mishra B, and Yin B (2016) Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization IEEE Transactions on Pattern Analysis and Machine Intelligence, 38 (3), 476-489. [More Information]

Wang J, Shi D, Cheng D, Zhang Y, and Gao J (2016) LRSR: Low-Rank-Sparse representation for subspace clustering Neurocomputing, 214, 1026-1037. [More Information]

Wu F, Hu Y, Gao J, Sun Y, and Yin B (2016) Ordered Subspace Clustering With Block-Diagonal Priors IEEE Transactions on Cybernetics, 46 (12), 3209-3219. [More Information]

Xu C, Lu C, Liang X, Gao J, Zheng W, Wang T, and Yan S (2016) Multi-Loss Regularized Deep Neural Network IEEE Transactions on Circuits and Systems for Video Technology, 26 (12), 2273-2283. [More Information]

Yin M, Gao J, and Lin Z (2016) Laplacian Regularized Low-Rank Representation and Its Applications IEEE Transactions on Pattern Analysis and Machine Intelligence, 38 (3), 504-517. [More Information]

Zhu F, Yang J, Gao J, and Xu C (2016) Extended nearest neighbor chain induced instance-weights for SVMs Air Medical Journal, 60 (December), 863-874. [More Information]

Conference Proceedings

Ali M, Gao J, and Antolovich M (2016) MLE-Based Learning on Grassmann Manifolds 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2016); Institute of Electrical and Electronics Engineers (IEEE), Gold Coast. [More Information]

Ali M, Gao J, and Antolovich M (2016) Classification on Stiefel and Grassmann Manifolds via Maximum Likelihood Estimation of Matrix Distributions 2016 International Joint Conference on Neural Networks (IJCNN 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Chowdhury M, Gao J, and Islam M (2016) Detection of Human Faces Using Neural Networks The 23rd International Conference on Neural Information Processing (ICONIP 2016); Springer International Publishing, Cham. [More Information]

Chowdhury M, Gao J, and Islam R (2016) Fuzzy rule based approach for face and facial feature extraction in biometric authentication 2016 International Conference on Image and Vision Computing New Zealand (IVCNZ 2016); Institute of Electrical and Electronics Engineers (IEEE), Palmerston North. [More Information]

Chowdhury M, Gao J, and Islam R (2016) Human detection and localization in secure access control by analysing facial features 11th IEEE Conference on Industrial Electronics and Applications (ICIEA 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Chowdhury M, Gao J, and Islam R (2016) Fuzzy Logic Based Filtering for Image De-noising 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Chowdhury M, Gao J, and Islam R (2016) Fast stereo matching with fuzzy correlation 11th IEEE Conference on Industrial Electronics and Applications (ICIEA 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Chowdhury M, Gao J, and Islam R (2016) Distance Measurement of Objects using Stereo Vision 9th Hellenic Conference on Artificial Intelligence (SETN 2016); Association for Computing Machinery (ACM), New York. [More Information]

Hong X, and Gao J (2016) A Fast Algorithm to Estimate the Square Root of Probability Density Function AI-2016 Thirty-sixth SGAI International Conference on Artificial Intelligence: Incorporating Applications and Innovations in Intelligent Systems XXIV; Springer, Cham. [More Information]

Hong X, and Gao J (2016) Manifold optimization for nonnegative coefficient logistic regression 2016 International Joint Conference on Neural Networks (IJCNN 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Jiang X, Song X, Gao J, Cai Z, and Zhang D (2016) Nonparametrically Guided Autoencoder with Laplace Approximation For Dimensionality Reduction 2016 International Joint Conference on Neural Networks (IJCNN 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Ju F, Sun Y, Gao J, Liu S, Hu Y, and Yin B (2016) Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Khan M, Soomro T, Khan T, Bailey D, Gao J, and Mir N (2016) Automatic retinal vessel extraction algorithm based on contrast-sensitive schemes 2016 International Conference on Image and Vision Computing New Zealand (IVCNZ 2016); Institute of Electrical and Electronics Engineers (IEEE), Palmerston North. [More Information]

Qi G, Sun Y, Gao J, Hu Y, and Li J (2016) Matrix Variate Restricted Boltzmann Machine 2016 International Joint Conference on Neural Networks (IJCNN 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Soomro T, and Gao J (2016) Neural Network based denoised methods for Retinal Fundus and MRI Brain Images 2016 International Joint Conference on Neural Networks (IJCNN 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Soomro T, Gao J, Khan M, Khan T, and Paul M (2016) Role of Image Contrast Enhancement Technique for Ophthalmologist as Diagnostic Tool for Diabetic Retinopathy 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2016); Institute of Electrical and Electronics Engineers (IEEE), Gold Coast. [More Information]

Soomro T, Khan M, Gao J, Khan T, Paul M, and Mir N (2016) Automatic Retinal Vessel Extraction Algorithm 2016 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2016); Institute of Electrical and Electronics Engineers (IEEE), Gold Coast. [More Information]

Tan M, Xiao S, Gao J, Xu D, van den Hengel A, and Shi Q (2016) Proximal Riemannian Pursuit for Large-scale Trace-norm Minimization 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Wang B, Hu Y, Gao J, Sun Y, and Yin B (2016) Product Grassmann Manifold Representation and Its LRR Models 30th AAAI Conference on Artificial Intelligence (AAAI 2016); AAAI Press, United States.

Yin M, Guo Y, Gao J, He Z, and Xie S (2016) Kernel Sparse Subspace Clustering on Symmetric Positive Definite Manifolds 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2016); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

2015

Journal Articles

Cui L, Ling Z, Poon J, Poon S, Chen H, Gao J, Kwan P, and Fan K (2015) Generalized Gaussian reference curve measurement model for high-performance liquid chromatography with diode array detector separation and its solution by multi-target intermittent particle swarm optimization Journal of Chemometrics, 29 (3), 146-153. [More Information]

Guo Y, Gao J, and Li F (2015) Random spatial subspace clustering Knowledge-Based Systems, 74, 106-118. [More Information]

Hong X, Chen S, Gao J, and Harris C (2015) Nonlinear Identification Using Orthogonal Forward Regression With Nested Optimal Regularization IEEE Transactions on Cybernetics, 45 (12), 2925-2936. [More Information]

Hong X, Gao J, Chen S, and Zia T (2015) Sparse Density Estimation on the Multinomial Manifold IEEE Transactions on Neural Networks and Learning Systems, 26 (11), 2972-2977. [More Information]

Ju F, Sun Y, Gao J, Hu Y, and Yin B (2015) Image Outlier Detection and Feature Extraction via L1-Norm-Based 2D Probabilistic PCA IEEE Transactions on Image Processing, 24 (12), 4834-4846. [More Information]

Wang F, Sahli H, Gao J, Jiang D, and Verhelst W (2015) Relevance units machine based dimensional and continuous speech emotion prediction Multimedia Tools and Applications, 74 (22), 9983-10000. [More Information]

Xu C, Lu C, Gao J, Wang T, and Yan S (2015) Facial Analysis With a Lie Group Kernel IEEE Transactions on Circuits and Systems for Video Technology, 25 (7), 1140-1150. [More Information]

Xu C, Lu C, Gao J, Zheng W, Wang T, and Yan S (2015) Discriminative Analysis for Symmetric Positive Definite Matrices on Lie Groups IEEE Transactions on Circuits and Systems for Video Technology, 25 (10), 1576-1585. [More Information]

Yin M, Gao J, and Cai S (2015) Image super-resolution via 2D tensor regression learning Computer Vision and Image Understanding, 132, 12-23. [More Information]

Yin M, Gao J, and Guo Y (2015) Nonlinear low-rank representation on Stiefel manifolds Electronics Letters, 51 (10), 749-751. [More Information]

Yin M, Gao J, Lin Z, Shi Q, and Guo Y (2015) Dual Graph Regularized Latent Low-Rank Representation for Subspace Clustering IEEE Transactions on Image Processing, 24 (12), 4918-4933. [More Information]

Yin M, Gao J, Shi D, and Cai S (2015) Band-Level Correlation Noise Modeling for Wyner-Ziv Video Coding with Gaussian Mixture Models Circuits, Systems and Signal Processing, 34 (7), 2237-2254. [More Information]

Zhang H, Lin Z, Zhang C, and Gao J (2015) Relations Among Some Low-Rank Subspace Recovery Models Neural Computation, 27 (9), 1915-1950. [More Information]

Conference Proceedings

Fu Y, Gao J, Hong X, and Tien D (2015) Low rank representation on riemannian manifold of symmetric positive definite matrices 2015 SIAM International Conference on Data Mining 2015 (SDM 2015); SIAM Publications, Vancouver.

Guo Y, Gao J, Li F, Tierney S, and Yin M (2015) Low rank sequential subspace clustering 2015 International Joint Conference on Neural Networks (IJCNN 2015); Institute of Electrical and Electronics Engineers (IEEE), Killarney. [More Information]

Hong X, and Gao J (2015) Sparse density estimation on multinomial manifold combining local component analysis 2015 International Joint Conference on Neural Networks (IJCNN 2015); Institute of Electrical and Electronics Engineers (IEEE), Killarney. [More Information]

Tan M, Shi Q, van den Hengel A, Shen C, Gao J, Hu F, and Zhang Z (2015) Learning graph structure for multi-label image classification via clique generation The 28th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2015); Institute of Electrical and Electronics Engineers (IEEE), Boston. [More Information]

Tierney S, Guo Y, and Gao J (2015) Selective Multi-Source Total Variation Image Restoration 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2015); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey.

Wang B, Hu Y, Gao J, Sun Y, and Yin B (2015) Low rank representation on grassmann manifolds 12th Asian Conference on Computer Vision (ACCV 2014); Springer, Cham, Switzerland. [More Information]

2014

Journal Articles

Cui A, Ling Z, Poon J, Poon S, Chen H, Gao J, Kwan P, and Fan K (2014) A parallel model of independent component analysis constrained by a 5-parameter reference curve and its solution by multi-target particle swarm optimization Analytical Methods, 6 (8), 2679-2686. [More Information]

Cui L, Ling Z, Poon J, Poon S, Gao J, and Kwan P (2014) A Decomposition Model for HPLC-DAD Data Set and Its Solution by Particle Swarm Optimization Applied Computational Intelligence and Soft Computing, 2014, 1-10. [More Information]

Cui L, Poon J, Poon S, Chen H, Gao J, Kwan P, Fan K, and Ling Z (2014) An improved independent component analysis model for 3D chromatogram separation and its solution by multi-areas genetic algorithm BMC Bioinformatics, 15 (Suppl 12), 1-10. [More Information]

Guo Y, Berman M, and Gao J (2014) Group subset selection for linear regression Computational Statistics and Data Analysis, 75, 39-52. [More Information]

Guo Y, Gao J, and Li F (2014) Spatial subspace clustering for drill hole spectral data Journal of Applied Remote Sensing, 8 (1), 1-19. [More Information]

Hong X, Gao J, Jiang X, and Harris C (2014) Fast identification algorithms for Gaussian process model Neurocomputing, 133, 25-31. [More Information]

Hong X, Gao J, Jiang X, and Harris C (2014) Estimation of Gaussian process regression model using probability distance measures Systems Science & Control Engineering, 2 (1), 655-663. [More Information]

Jiang X, Gao J, Wang T, and Shi D (2014) TPSLVM: A Dimensionality Reduction Algorithm Based On Thin Plate Splines IEEE Transactions on Cybernetics, 44 (10), 1795-1807. [More Information]

Liu R, Lin Z, Su Z, and Gao J (2014) Linear time Principal Component Pursuit and its extensions using l1 filtering Neurocomputing, 142, 529-541. [More Information]

Piao X, Hu Y, Sun Y, Yin B, and Gao J (2014) Correlated Spatio-Temporal Data Collection in Wireless Sensor Networks Based on Low Rank Matrix Approximation and Optimized Node Sampling Sensors, 14 (12), 23137-23158. [More Information]

Tong B, Gao J, Nguyen Huy T, Shao H, and Suzuki E (2014) Transfer dimensionality reduction by Gaussian process in parallel Knowledge and Information Systems, 38 (3), 567-597. [More Information]

Xu C, Wang T, Gao J, Cao S, Tao W, and Liu F (2014) An Ordered-Patch-Based Image Classification Approach on the Image Grassmannian Manifold IEEE Transactions on Neural Networks and Learning Systems, 25 (4), 728-737. [More Information]

Yin M, Gao J, Tien D, and Cai S (2014) Blind image deblurring via coupled sparse representation Journal of Visual Communication and Image Representation, 25 (5), 814-821. [More Information]

Zhang H, Lin Z, Zhang C, and Gao J (2014) Robust latent low rank representation for subspace clustering Neurocomputing, 145, 369-373. [More Information]

Conference Proceedings

Bull G, Gao J, and Antolovich M (2014) Image Segmentation Using Dictionary Learning and Compressed Random Features The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, USA. [More Information]

Cui A, Poon J, Poon S, Gao J, Kwan P, and Ling Z (2014) Separation model of Generalized Reference Curve Measurement for HPLC-DAD and it solution by multi-target Bare Bones Particle Swarm Optimization 2014 IEEE International Conference Bioinformatics and Biomedicine (IEEE BIBM 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, USA. [More Information]

Fu Y, Gao J, Hong X, and Tien D (2014) Tensor Regression Based on Linked Multiway Parameter Analysis 14th IEEE International Conference on Data Mining (ICDM 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Fu Y, Gao J, Sun Y, and Hong X (2014) Joint multiple dictionary learning for Tensor sparse coding 2014 International Joint Conference on Neural Networks (IJCNN 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Fu Y, Gao J, Tien D, and Lin Z (2014) Tensor LRR based subspace clustering 2014 International Joint Conference on Neural Networks (IJCNN 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Jiang X, Gao J, Hong X, and Cai Z (2014) Gaussian Processes Autoencoder for Dimensionality Reduction 18th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining (PAKDD 2014); Springer-Verlag, Taiwan. [More Information]

Letchford A, Gao J, and Zheng L (2014) Smoothing security prices 22nd International Conference on Pattern Recognition (ICPR 2014); Institute of Electrical and Electronics Engineers (IEEE), Stockholm. [More Information]

Shao G, Gao J, Wang T, Liu F, Shu Y, and Yang Y (2014) Fuzzy c-means clustering with a new regularization term for image segmentation 2014 International Joint Conference on Neural Networks (IJCNN 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Shao G, Gao J, Wang T, Liu F, Shu Y, and Yang Y (2014) Image Segmentation Based on Spatially Coherent Gaussian Mixture Model The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, USA. [More Information]

Sun Y, Gao J, Hong X, Guo Y, and Harris C (2014) Dimensionality reduction assisted tensor clustering 2014 International Joint Conference on Neural Networks (IJCNN 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Tierney S, Gao J, and Guo Y (2014) Affinity pansharpening and image fusion The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, USA. [More Information]

Tierney S, Gao J, and Guo Y (2014) Subspace clustering for sequential data 27th IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Tierney S, Gao J, and Guo Y (2014) The W-Penalty and Its Application to Alpha Matting with Sparse Labels The International Conference on Digital Image Computing: Techniques and Applications (DICTA 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, USA. [More Information]

Yin M, Gao J, Sun Y, and Cai S (2014) Blocky artifact removal with low-rank matrix recovery 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, USA. [More Information]

Yin M, Guo Y, and Gao J (2014) Linear Subspace Learning via sparse dimension reduction 2014 International Joint Conference on Neural Networks (IJCNN 2014); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

2013

Journal Articles

Cheng D, Nguyen M, Gao J, and Shi D (2013) On the construction of the relevance vector machine based on Bayesian Ying-Yang harmony learning Neural Networks, 48, 173-179. [More Information]

Hong X, Gao J, Chen S, and Harris C (2013) Particle swarm optimisation assisted classification using elastic net prefiltering Neurocomputing, 122, 210-220. [More Information]

Shi D, Gao J, Rahmdel P, Antolovich M, and Clark T (2013) UND: Unite-and-divide method in fourier and radon domains for line segment detection IEEE Transactions on Image Processing, 22 (6), 2500-2505. [More Information]

Conference Proceedings

Cui A, Poon J, Poon S, Fan K, Chen H, Gao J, Kwan P, and Ling Z (2013) Parallel model of independent component analysis constrained by reference curves for HPLC-DAD and its solution by multi-areas genetic algorithm 2013 IEEE International Conference on Bioinformatics and Biomedicine (BIBM2013); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, United States. [More Information]

Gao J, Guo Y, and Yin M (2013) Restricted Boltzmann machine approach to couple dictionary training for image super-resolution 2013 20th IEEE International Conference on Image Processing (ICIP 2013); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Guo Y, Gao J, and Li F (2013) Large scale hyperspectral data segmentation by random spatial subspace clustering 33rd IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2013); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Guo Y, Gao J, and Li F (2013) Dimensionality Reduction with Dimension Selection 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2013); Springer, Berlin. [More Information]

Guo Y, Gao J, and Sun Y (2013) Endmember extraction by exemplar finder 9th International Conference on Advanced Data Mining and Applications (ADMA 2013); Springer, Berlin. [More Information]

Hong X, Guo Y, Chen S, and Gao J (2013) Sparse model construction using coordinate descent optimization 18th International Conference on Digital Signal Processing (DSP 2013); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Li F, Tang L, Li C, Guo Y, and Gao J (2013) A new super resolution method based on combined sparse representations for remote sensing imagery Image and Signal Processing for Remote Sensing XIX; Society of Photo-Optical Instrumentation Engineers (SPIE), Bellingham. [More Information]

Tierney S, Bull G, and Gao J (2013) Image Matting for Sparse User Input by Iterative Refinement 2013 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2013); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Yin M, Cai S, and Gao J (2013) Robust face recognition via double low-rank matrix recovery for feature extraction 2013 20th IEEE International Conference on Image Processing (ICIP 2013); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

2012

Journal Articles

Gao J, Shi Q, and Caetano T (2012) Dimensionality reduction via compressive sensing Pattern Recognition Letters, 33 (9), 1163-1170. [More Information]

Jiang X, Gao J, Wang T, and Zheng L (2012) Supervised latent linear Gaussian process latent variable model for dimensionality reduction IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics, 42 (6), 1620-1632. [More Information]

Conference Proceedings

Bull G, and Gao J (2012) Transposed Low Rank Representation for Image Classification International Conference on Digital Image Computing Techniques and Applications (DICTA 2012); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, United States of America. [More Information]

Gao J, Paul M, and Liu J (2012) The Image Matting Method with Regularized Matte 13th IEEE International Conference on Multimedia and Expo (ICME 2012); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, USA. [More Information]

Guo Y, Gao J, and Hong X (2012) Constrained Grouped Sparsity The 25th Australasian Joint Conference on Artificial Intelligence (AI 2012); Springer, Heidelberg. [More Information]

Jiang X, Gao J, Shi D, and Wang T (2012) Thin Plate Spline Latent Variable Models for dimensionality reduction 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012; Institute of Electrical and Electronics Engineers (IEEE), Piscataway.

Letchford A, Gao J, and Zheng L (2012) Optimizing the moving average 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012; Institute of Electrical and Electronics Engineers (IEEE), Piscataway.

Paul M, Gao J, and Anotolovich M (2012) 3D motion estimation for 3D video coding 2012 IEEE International Conference on Acoustics, Speech and Signal Processing; Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Rahman M, Islam M, Bossomaier T, and Gao J (2012) CAIRAD: A co-appearance based analysis for Incorrect Records and Attribute-values Detection 2012 Annual International Joint Conference on Neural Networks, IJCNN 2012; Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Tierney S, and Gao J (2012) Natural image matting with total variation regularisation International Conference on Digital Image Computing Techniques and Applications (DICTA 2012); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, United States of America. [More Information]

2011

Journal Articles

Kwan P, Kameyama K, Gao J, and Toraichi K (2011) Content-based Image Retrieval of Cultural Heritage Symbols by Interaction of Visual Perspectives International Journal of Pattern Recognition and Artificial Intelligence, 25 (5), 643-673. [More Information]

Poon S, Poon J, McGrane M, Zhou X, Kwan P, Zhang R, Liu B, Gao J, Loy C, Chan K, and Sze D (2011) A novel approach in discovering significant interactions from TCM patient prescription data International Journal of Data Mining and Bioinformatics, 5 (4), 353-368. [More Information] [More Information]

Conference Proceedings

Bull G, and Gao J (2011) Classification of Hand-Written Digits Using Chordiograms 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, USA. [More Information]

Gao J (2011) Multi-task beta process sparse kernel machines 2011 International Joint Conference on Neural Networks (IJCNN 2011); Institute of Electrical and Electronics Engineers (IEEE), Piscataway. [More Information]

Gao J (2011) Image Matting via Local Tangent Space Alignment 2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, USA. [More Information]

Guo Y, and Gao J (2011) Local Feature Based Tensor Kernel for Image Manifold Learning 15th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2011; Springer, Heidelberg, Germany. [More Information]

Poon S, Fan K, Poon J, Loy C, Chan K, Kuan P, Zhou X, Gao J, Zhang R, Wang Y, and et al (2011) Analysis of herbal formulation in TCM: Infertility as a case study IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW 2011); Institute of Electrical and Electronics Engineers (IEEE), Los Alamitos, CA, USA. [More Information]

Tong B, Gao J, Thack N, and Suzuki E (2011) Gaussian Process for Dimensionality Reduction in Transfer Learning 11th SIAM International Conference on Data Mining (SDM 2011); SIAM Publications, Mesa, AZ, USA.

Book Chapter

Abraham J, Kwan P, and Gao J (2011) Fingerprint Matching using A Hybrid Shape and Orientation Descriptor State of the art in Biometrics; InTech Publishers, Rijeka, Croatia, 25-56. [More Information]

2010

Journal Articles

Gao J, Kwan P, and Shi D (2010) Sparse kernel learning with LASSO and Bayesian inference algorithm Neural Networks, 23 (2), 257-264. [More Information]

Gao J, Zhang J, and Tien D (2010) Relevance Units Latent Variable Model and Nonlinear Dimensionality Reduction IEEE Transactions on Neural Networks, 21 (1), 123-135. [More Information]

Kwan P, Gao J, Guo Y, and Kameyama K (2010) A learning framework for adaptive fingerprint identification using relevance feedback International Journal of Pattern Recognition and Artificial Intelligence, 24 (1), 15-38. [More Information]

Conference Proceedings

Jiang X, Gao J, Wang T, and Kwan P (2010) Learning Gradients with Gaussian Processes 14th Pacific-Asia Conference on Advanced in Knowledge Discovery and Data Mining (PAKDD 2010); Springer, Germany. [More Information]

McGrane M, Poon S, Poon J, Chan K, Loy C, Zhou X, Zhang R, Liu B, Kwan P, Sze D, and et al (2010) Analysis of Synergistic and Antagonistic Effects of TCM: Cases on Diabetes and Insomnia 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops BIBMW 2010; Institute of Electrical and Electronics Engineers (IEEE), USA. [More Information]

Poon J, Poon S, Yin D, Chan K, Loy C, Zhou X, Zhang R, Liu B, Kwan P, Sze D, and et al (2010) Studying Herb-Herb Interaction for Insomnia through the theory of Complementarities 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops BIBMW 2010; Institute of Electrical and Electronics Engineers (IEEE), USA. [More Information]

Zheng L, Gao J, and He X (2010) Efficient character segmentation on car license plates 11th International Conference on Control, Automation, Robotics and Vision (ICARCV 2010); Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, USA. [More Information]

2009

Journal Articles

Gao J, Kwan P, and Guo L (2009) Robust multivariate L1 principal component analysis and dimensionality reduction Neurocomputing, 72 (4-6), 1242-1249. [More Information]

Gao J, Kwan P, and Huang X (2009) Comprehensive Analysis for the Local Fisher Discriminant Analysis International Journal of Pattern Recognition and Artificial Intelligence, 23 (6), 1129-1143. [More Information]

Book

Gao J, Kwan P, Poon J, and Poon S (2009) Proceedings of the Workshop Advances and Issues in Biomedical Data Mining (AIBDM'09); Printing House of Thammasat University - Rangsit Campus, Thailand.

253138

Selected grants

2018 - 2019

2018 - 2019

2017

Recent Units Taught

  • BUSS4001 Business Honours Research Methods

  • BUSS4313 Business Analytics Honours B

  • QBUS5001 Quantitative Methods for Business

  • QBUS6810 Statistical Learning and Data Mining

  • QBUS6840 Predictive Analytics