Qingyao Wu
Qingyao Wu
School of Software Engineering, South China University of Technology
Verified email at scut.edu.cn - Homepage
TitleCited byYear
Stratified sampling for feature subspace selection in random forests for high dimensional data
Y Ye, Q Wu, JZ Huang, MK Ng, X Li
Pattern Recognition 46 (3), 769-787, 2013
ForesTexter: an efficient random forest algorithm for imbalanced text categorization
Q Wu, Y Ye, H Zhang, MK Ng, SS Ho
Knowledge-Based Systems 67, 105-116, 2014
SNP selection and classification of genome-wide SNP data using stratified sampling random forests
Q Wu, Y Ye, Y Liu, MK Ng
IEEE transactions on nanobioscience 11 (3), 216-227, 2012
Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests
TT Nguyen, JZ Huang, Q Wu, TT Nguyen, MJ Li
BMC genomics 16 (2), S5, 2015
Discrimination-aware channel pruning for deep neural networks
Z Zhuang, M Tan, B Zhuang, J Liu, Y Guo, Q Wu, J Huang, J Zhu
Advances in Neural Information Processing Systems, 875-886, 2018
ML-FOREST: A multi-label tree ensemble method for multi-label classification
Q Wu, M Tan, H Song, J Chen, MK Ng
IEEE transactions on knowledge and data engineering 28 (10), 2665-2680, 2016
Markov-miml: A markov chain-based multi-instance multi-label learning algorithm
Q Wu, MK Ng, Y Ye
Knowledge and information systems 37 (1), 83-104, 2013
A unified framework for metric transfer learning
Y Xu, SJ Pan, H Xiong, Q Wu, R Luo, H Min, H Song
IEEE Transactions on Knowledge and Data Engineering 29 (6), 1158-1171, 2017
ML-TREE: A tree-structure-based approach to multilabel learning
Q Wu, Y Ye, H Zhang, TWS Chow, SS Ho
IEEE transactions on neural networks and learning systems 26 (3), 430-443, 2014
Unknown Chinese word extraction based on variety of overlapping strings
Y Ye, Q Wu, Y Li, KP Chow, LCK Hui, SM Yiu
Information Processing & Management 49 (2), 497-512, 2013
MR-NTD: Manifold regularization nonnegative tucker decomposition for tensor data dimension reduction and representation
X Li, MK Ng, G Cong, Y Ye, Q Wu
IEEE transactions on neural networks and learning systems 28 (8), 1787-1800, 2016
Cotransfer learning using coupled Markov chains with restart
Q Wu, MK Ng, Y Ye
IEEE Intelligent Systems 29 (4), 26-33, 2013
Visual grounding via accumulated attention
C Deng, Q Wu, Q Wu, F Hu, F Lyu, M Tan
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018
Online transfer learning with multiple homogeneous or heterogeneous sources
Q Wu, H Wu, X Zhou, M Tan, Y Xu, Y Yan, T Hao
IEEE Transactions on Knowledge and Data Engineering 29 (7), 1494-1507, 2017
Co-transfer learning via joint transition probability graph based method
MK Ng, Q Wu, Y Ye
Proceedings of the 1st international workshop on cross domain knowledge …, 2012
Multi-label collective classification via markov chain based learning method
Q Wu, MK Ng, Y Ye, X Li, R Shi, Y Li
Knowledge-Based Systems 63, 1-14, 2014
Learning Discriminative Correlation Subspace for Heterogeneous Domain Adaptation.
Y Yan, W Li, MKP Ng, M Tan, H Wu, H Min, Q Wu
IJCAI, 3252-3258, 2017
Protein functional properties prediction in sparsely-label PPI networks through regularized non-negative matrix factorization
Q Wu, Z Wang, C Li, Y Ye, Y Li, N Sun
BMC systems biology 9 (1), S9, 2015
Collective prediction of protein functions from protein-protein interaction networks
Q Wu, Y Ye, MK Ng, SS Ho, R Shi
BMC bioinformatics 15 (2), S9, 2014
Online heterogeneous transfer by hedge ensemble of offline and online decisions
Y Yan, Q Wu, M Tan, MK Ng, H Min, IW Tsang
IEEE transactions on neural networks and learning systems 29 (7), 3252-3263, 2017
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