Wei Gao
Ph.D. Associate Professor

 LAMDA Group
 School of Artificial Intelligence
Nanjing University , Nanjing, China
Email: gaow(at)nju(dot)edu(dot)cn

Sections:                                           

[ Biography ]

 [ Research Interest ]

 [ Publication ]
Biogeraphy
Currently I am an Associate Professor of School of Artificial Intelligence in Nanjing University and a member of LAMDA Group, led by professor Zhi-Hua Zhou.

Before that, I received my M.Sc. degree in the Center for Combinatorics, Nankai University in June 2009 and I received my Ph.D. degree from Nanjing University in June 2014.

Research Interest
My research interests include: Learning Theory.

Publication [* denotes my student]
    

X.-R. Xie*, M.-J. Yuan*, X.-T. Bai*, W. Gao and Z.-H. Zhou. On the Gini-impurity Preservation for Privacy Random Forests. Advances in Neural Information Processing Systems 37  (NeurIPS'23), New Orleans, LA, 2023.

Z.-J. Zhou*, J. Ni*, J.-H. Yao* and W. Gao. On the Exploration of Local Significant Differences for Two-Sample Test. Advances in Neural Information Processing Systems 37  (NeurIPS'23), New Orleans, LA, 2023.

W. Gao, F. Xu and Z.-H. Zhou. Towards convergence rate analysis of random forests for classification. Artificial Intelligence 313: 103788, 2022.

J.-Q. Guo*, M.-Z. Teng*, W. Gao and Z.-H. Zhou. Fast provably robust decision trees and Boosting. In: Proceedings of the 39th International Conference on Machine Learning  (ICML'22), Maryland, MD, 2022.

M.-Z. Qian*, Z. Ai*, T. Zhang and W. Gao. On the optimization of margin distribution. In: Proceedings of the 31st International Joint Conference on Artificial Intelligence  (IJCAI'22), Vienna, Austria, 2022.

M.-J. Yuan* and W. Gao. Learning with Interactive Models over Decision-Dependent Distributions. In: Proceedings of the 14th Asian Conference on Machine Learning  (ACML'22), Hyderabad, India, 2022.

J. Li*, J.-Q. Guo* and W. Gao. Data removal from an AUC optimization model. Proceedings of the 26th Pacific-Asia Conference on Knowledge Discovery and Data Mining  (PAKDD'22), Chengdu, China, 2022.

W. Gao, T. Zhang, B.-B. Yang and Z.-H. Zhou. On the Noise Estimation Statistics. Artificial Intelligence 293: 103451, 2021.

W. Gao and Z.-H. Zhou. Towards convergence rate analysis of random forests for classification. Advances in Neural Information Processing Systems 33  (NeurIPS'20), Vancouver, Canada, 2020.

S.-Q. Shen*, B.-B. Yang* and W. Gao. AUC Optimization with a Reject Option. In: Proceedings of the 34th AAAI Conference on Artificial Intelligence  (AAAI'20), New York, NY, 2020.

B.-B. Yang*, W. Gao and M. Li. On the Robust Splitting Criterion of Random Forest. In: Proceedings of the 19th IEEE International Conference on Data Mining  ((ICDM'19), Beijing, China, 2019.

B.-B. Yang*, S.-Q. Shen* and W. Gao. Weighted Oblique Decision Trees. In: Proceedings of the 33rd AAAI Conference on Artificial Intelligence  (AAAI'19), Honolulu, HW, 2019.

M. Pang, W. Gao, M. Tao, Z.-H. Zhou. Unorganized malicious attacks detection. In: Advances in Neural Information Processing Systems 31  (NIPS'18), Montreal, Canada, 2018.

W. Gao and Z.-H. Zhou. Dropout radermacher complexity of deep neural networks. Science China: Information Sciences 59:072104(12) 2016.

W. Gao and Z.-H. Zhou. One-Pass AUC Optimization. Artificial Intelligence 236:1-29 2016.

W. Gao, L. Wang, Y.-F. Li and Z.-H. Zhou. Risk minimization in the presence of label noise. In: Proceedings of the 30th AAAI Conference on Artificial Intelligence  (AAAI'16), Phoenix, AZ 2016.

W. Gao and Z.-H. Zhou. On the consistency of AUC pairwise optimization. In: Proceedings of the 24th International Joint Conference on Artificial Intelligence  (IJCAI'15), Buenos Aires, Argentina 2015.

W. Gao and Z.-H. Zhou. On the doubt about margin explanation of boosting. Artificial Intelligence 203:1-18 2013.

W. Gao and Z.-H. Zhou. On the Consistency of Multi-label learning. Artificial Intelligence 199-200:22-44 2013.

W. Gao, R. Jin, S. Zhu and Z.-H. Zhou. One-pass AUC optimization. In: Proceedings of the 30th Annual Conference on machine Learning  (ICML'13), Atlanta GA 2013.

W. Gao and Z.-H. Zhou. Uniform convergence, statiliby and learnability for ranking problems. In: Proceedings of the 23rd International Joint Conference on Artificial Intelligence  (IJCAI'13), Beijing, China. [Best presentation]

W. Gao and Z.-H. Zhou. On the consistency of multi-label learning. In: Proceedings of the 24th Annual Conference on Learning Theory  (COLT'11), Budapest, Hungary, 2011.

W. Gao and Z.-H. Zhou. Approximation Stability and Boosting. In: Proceedings of the 21st International Conference on Algorithmic Learning Theory (ALT'10), Canberra, Australia, 2010.

W. Gao, Q.-H. Hou and G. Xin. On P-partitions related to ordinal sums of posets. European Journal of Combinatorics, 30:1370-1381 2009.


last modified@2020-11