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Publications by Cao, Peng

In Journal (refereed)

1. H. Jiang, P. Cao, M. Xu, J. Yang, O. Zaiane. "Hi-GCN: A hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction ". Computers in Biology and Medicine, 127, December 2020. view
2. P. Cao, F. Ren, C. Wan, J. Yan, O. Zaiane. " Efficient multi-kernel multi-instance learning using weakly supervised and imbalanced data for diabetic retinopathy diagnosis". Computerized Medical Imaging and Graphics, 69, pp 112-124, November 2018. view
3. P. Cao, X. Liu, J. Yang, D. Zhao, M. Huang, O. Zaiane. "Generalized fused group lasso regularized multi-task feature learning for predicting cognitive outcomes in Alzheimers disease". Computer Methods and Programs in Biomedicine, 162, pp 19-45, August 2018. view
4. P. Cao, X. Liu, S. Liu, J. Yang, D. Zhao, M. Huang, O. Zaiane. "L_2,1 - L_1 regularized nonlinear multi-task representation learning for cognitive performance prediction of Alzheimer's disease". Pattern Recognition, 79, pp 195-215, July 2018. view
5. P. Cao, X. Liu, J. Yang, D. Zhao, M. Huang, J. Zhang, O. Zaiane. "Nonlinearity-Aware based dimensionality reduction and over-sampling for AD/MCI classification from MRI Measures". Computers in Biology and Medicine, 91, pp 21-37, December 2017. view
6. P. Cao, X. Liu, O. Zaiane, D. Zhao. "Sparse shared structure based multi-task learning for MRI based Cognitive Performance prediction of Alzheimer's disease". Pattern Recognition, 72, pp 219-235, December 2017. view
7. P. Cao, X. Liu, J. Yang, D. Zhao, W. Li, M. Huang, O. Zaiane. "A Multi-kernel based framework for heterogeneous feature selection and oversampling for computer-aided detection of pulmonary nodules". Pattern Recognition, 64, pp 327-346, April 2017. view
8. P. Cao, X. Liu, D. Zhao, M. Huang, O. Zaiane, J. Zhang, W. Li. "L2,1-norm regularized multi-kernel based joint nonlinear feature selection and over-sampling for imbalanced data classification". Neurocomputing, 234(C), pp 38-57, April 2017. view
9. P. Cao, X. Liu, D. Zhao, M. Huang, O. Zaiane, J. Zhang, W. Li. "A L2,1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD". Computer Methods and Programs in Biomedicine, 140(C), pp 211-231, March 2017. view
10. F. Ren, P. Cao, W. Li, D. Zhao, O. Zaiane. "Ensemble based adaptive over-sampling method for imbalanced data learning in computer aided detection of microaneurysm". Computerized Medical Imaging and Graphics, 55, pp 54-67, January 2017. view
11. P. Cao, D. Zhao, O. Zaiane. "Hybrid probabilistic sampling with random subspace for imbalanced data learning". Intelligent Data Analysis: An International Journal, 18(6), pp 1089-1108, November 2014. PDFview
12. P. Cao, D. Zhao, O. Zaiane. "Ensemble-based hybrid probabilistic sampling for imbalanced data learning in Lung nodule CAD". Computerized Medical Imaging and Graphics, 38(3), pp 137-150, April 2014. PDFview
13. J. Zhang, P. Cao, D. Gross, O. Zaiane. "On the application of multi-class classification in physical therapy recommendation". Health Information Science and Systems, 1(15), December 2013. PDFview

In Conference (refereed)

14. P. Cao, S. Tang, M. Huang, J. Yang, D. Zhao, A. Trabelsi, O. Zaiane. "Feature-aware Multi-task feature learning for Predicting Cognitive Outcomes in Alzheimer’s disease". IEEE International Conference on Bioinformatics and Biomedicine , (ed: Illhoi Yoo, Jinbo Bi, Xiaohua Hu), pp n/a, November 2019. PDFview
15. X. Liu, P. Cao, J. Yang, D. Zhao, O. Zaiane. "Group guided sparse group lasso multi-task learning for cognitive performance prediction of Alzheimer's disease". International Conference on Brain Informatics, Beijing, China, November 2017. PDFview
16. P. Cao, X. Liu, O. Zaiane, D. Zhao. "Sparse multi-kernel based multi-task learning for joint prediction of clinical scores and biomarker identification in Alzheimer's Disease". International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Quebec City, Canada, September 2017. PDFview
17. P. Cao, X. Liu, D. Zhao, O. Zaiane. "Cost sensitive Ranking Support Vector Machine for Multi-label Data Learning". International Conference on Hybrid Intelligent Systems, Marrakech, Morocco, November 2016. PDFview
18. P. Cao, X. Liu, D. Zhao, O. Zaiane. "Sparse learning and hybrid probabilistic oversampling for Alzheimers Disease diagnosis". International Conference on Hybrid Intelligent Systems, Marrakech, Morocco, November 2016. PDFview
19. P. Cao, D. Zhao, O. Zaiane. "Measure optimized cost-sensitive neural network ensemble for multiclass imbalance data learning". International Conference on Hybrid Intelligent Systems, Hammamet, Tunisia, pp 35-40, December 2013. PDFview
20. P. Cao, B. Li, D. Zhao, O. Zaiane. "A novel cost sensitive neural network ensemble for multiclass imbalance data learning". IJCNN, August 2013. PDFview
21. P. Cao, D. Zhao, O. Zaiane. "Measure optimized wrapper framework for multi-class imbalanced data learning: An empirical study". IJCNN, August 2013. PDFview
22. P. Cao, D. Zhao, O. Zaiane. "Measure oriented cost-sensitive SVM for 3D nodule detection". Annual International Conference of the IEEE Engineering in Medicine and Biology Society, July 2013. PDFview
23. P. Cao, D. Zhao, O. Zaiane. "Cost sensitive adaptive random subspace ensemble for computer-aided nodule detection". IEEE International Symposium on Computer-Based Medical Systems, Porto, Portugal, pp 173-178, June 2013. PDFview
24. P. Cao, D. Zhao, O. Zaiane. "A PSO-based Cost-Sensitive Neural Network for Imbalanced Data Classification". Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), April 2013. PDFview
25. P. Cao, D. Zhao, O. Zaiane. "An optimized cost-effective SVM for imbalanced data learning". Proceeding of the Pacific Asia Conference on Knowledge Discovery and Data Mining, (ed: Pei, J., Tseng, V.S., Cao, L., Motoda, H., Xu, G.), pp 280-292, April 2013. PDFview

In Workshop

26. P. Cao, Z. Teng, M. Huang, J. Yang, D. Zhao, A. Trabelsi, O. Zaiane. "An ensemble framework with l21-norm regularized hypergraph laplacian multi-label learning for clinical data prediction". International Workshop on Biomedical and Health Informatics, (ed: Illhoi Yoo, Jinbo Bi, Xiaohua Hu), pp 1436-1442, November 2019. PDFview

Other Categories

27. P. Cao, O. Zaiane, D. Zhao. " A Measure optimized cost-sensitive learning framework for imbalanced data classification". Biologically-Inspired Techniques for Knowledge Discovery and Data Mining, Advances in Data Mining an, Biologically-Inspired Techniques for Knowledge Discovery and Data Mining, Advances in Data Mining and Database Management Book Series, IGI Global, (ed: Shafiq Alam, Yun Sing Koh, and Gillian Dobbie), pp 1-24, October 2014. PDFview
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