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Xiaoguang Wang
Xiaoguang Wang
Alibaba iDST
Verified email at alibaba-inc.com
Title
Cited by
Cited by
Year
Boosting support vector machines for imbalanced data sets
BX Wang, N Japkowicz
Knowledge and information systems 25, 1-20, 2010
3272010
Boosting support vector machines for imbalanced data sets
NJ Benjamin X. Wang
Knowl. Inf. Syst. 1 (25), 1-20, 2010
327*2010
Boosting Support Vector Machines for Imbalanced Data Sets
NJ Benjamin X. Wang
ISMIS, 38-47, 2008
327*2008
Imbalanced data set learning with synthetic samples
BX Wang, N Japkowicz
Proc. IRIS machine learning workshop 19, 435, 2004
1402004
Improving the interpretability of deep neural networks with knowledge distillation
X Liu, X Wang, S Matwin
2018 IEEE International Conference on Data Mining Workshops (ICDMW), 905-912, 2018
1252018
Boosting support vector machines for imbalanced data sets
BX Wang, N Japkowicz
International Symposium on Methodologies for Intelligent Systems, 38-47, 2008
792008
Interpretable deep convolutional neural networks via meta-learning
X Liu, X Wang, S Matwin
2018 International Joint Conference on Neural Networks (IJCNN), 1-9, 2018
542018
Meta-MapReduce for scalable data mining
SMNJ Xuan Liu, Xiaoguang Wang
Journal of Big Data 2 (14), 2015
312015
Cost-Sensitive Boosting Algorithms for Imbalanced Multi-instance Datasets
XL Xiaoguang Wang, Stan Matwin, Nathalie Japkowicz
Canadian Conference on AI, 174-186, 2013
31*2013
Vessel route anomaly detection with Hadoop MapReduce
SM Xiaoguang Wang, Xuan Liu, Bo Liu, Erico N. de Souza
BigData Conference, 25-30, 2014
30*2014
Resampling and Cost-Sensitive Methods for Imbalanced Multi-instance Learning
SM Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz
ICDM, 808-816, 2013
23*2013
A distributed instance-weighted SVM algorithm on large-scale imbalanced datasets
SM Xiaoguang Wang, Xuan Liu
BigData Conference, 45-51, 2014
21*2014
Applying instance-weighted support vector machines to class imbalanced datasets
NJ Xiaoguang Wang, Xuan Liu, Stan Matwin
Xiaoguang Wang, Xuan Liu, Stan Matwin, Nathalie Japkowicz, 112-118, 2014
17*2014
Using SVM with Adaptively Asymmetric MisClassification Costs for Mine-Like Objects Detection
BN Xiaoguang Wang, Hang Shao, Nathalie Japkowicz, Stan Matwin, Xuan Liu ...
ICMLA, 78-82, 2012
17*2012
Meta-learning for large scale machine learning with MapReduce
NJ Xuan Liu, Xiaoguang Wang, Stan Matwin
BigData Conference, 105-110, 2013
12*2013
Automatic Target Recognition using multiple-aspect sonar images
BN Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz, Stan Matwin
IEEE Congress on Evolutionary Computation, 2330-2337, 2014
11*2014
Automated approach to classification of mine-like objects using multiple-aspect sonar images
X Wang, X Liu, N Japkowicz, S Matwin
Journal of Artificial Intelligence and Soft Computing Research 4 (2), 133-148, 2014
102014
Ensemble of Multiple Kernel SVM Classifiers
SM Xiaoguang Wang, Xuan Liu, Nathalie Japkowicz
Canadian Conference on AI, 239-250, 2014
9*2014
An Ensemble Method Based on AdaBoost and Meta-Learning
SM Xuan Liu, Xiaoguang Wang, Nathalie Japkowicz
Canadian Conference on AI, 278-285, 2013
9*2013
Partition-wise Recurrent Neural Networks for Point-based AIS Trajectory Classification.
X Jiang, EN de Souza, X Liu, BH Soleimani, X Wang, DL Silver, S Matwin
ESANN, 2017
82017
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