SMILE is affiliated with the School of Computer Science and Engineering. The founding director of SMILE Lab is Professor Xu Zenglin. It locates at the Main Building in Qingshuihe Campus, mainly in B1-201.
“SMILE” means “Statistical Machine Intelligence Learning”.
The main research interests of SMILE Lab bases on machine learning technology and its applications. Our research mainly involves: Semi-supervised learning, kernel learning, Bias learning, feature selection and extraction, multi-task learning, multi-view learning, active learning, online learning, matrix analysis, tensor analysis, deep learning, optimization algorithm, scalable learning, etc. The main application fields involve Internet, recommendation system, social network analysis, bioinformatics, neural Informatics, health data analysis, spatial safety data analysis, etc..
- 2019-06-03 Seminar on Machine Learning Crossing and Frontier Theory
- 2018-05-14 to 2018-05-15 Academic Seminar: Artificial Intelligence Forum
- 2016-08-03 International Symposium of Big Data and Machine Learning.
- 2016-06-16 “Statistical machine learning” series of lecture.
- 2015-12-16 Seminar on Artificial Intelligence frontier issues.
- 2015-11 The 11th Chinese Workshop on Machine Learning and Applications.(MLA 2015)
- 2019-06-20 Prof. Kun Huang, Indiana University, visited SMILE Lab and gave a talk.
- 2019-05-13 Prof.Junhui Wang ,City University of Hong Kong, visited SMILE Lab and gave a talk.
- 2019-03-27 Prof. Wray Buntine, Dr.Lan Du and Dr. Xiaojun Chang, Monash University, visited SMILE Lab and gave a talk.
- 2018-10-12 Prof. Yang Yu, Nanjing University, visited SMILE Lab and gave a talk.
- 2018-08-28 to 2018-08-31 Workshop on Advances in Deep Unsupervised Learning
- 2018-05-14 to 2018-05-15 The 1st International Conference on Electronic Science and Technology: Artificial intelligence branch
- 2018-05-09 Prof. Xu Zenglin’s team has published papers at the CCF A conference
- 2018-05-01 The paper titled as “Self-weighted Multi-View Clustering with Soft Capped Norm” is accepted by 《Knowledge-Based Systems》. Congratulations to Shudong Huang, Zhao Kang, and Zenglin Xu for their excellent work.
- 2018-04-17 Two papers titled as “Structured Inference for Recurrent Hidden Semi-Markov Model” and “Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification” are accepted by IJCAI 2018. Congratulations to Hao Liu, Lirong He, Haoli Bai , Zhao Kang, and Xiao Lu, for their excellent work.
- 2018-03-16 The paper titled as “Robust Multi-view Data Clustering with Multi-view Capped-Norm K-means” is accepted by 《Neurocomputing》. Congratulations to Shudong Huang, Yazhou Ren, and Zenglin Xu for their excellent work.
- 2018-03-06 The paper titled as “Learning Compact Recurrent Neural Networks with Block-Term Tensor Decomposition” is accepted by CVPR 2018. Congratulations to Jinmian Ye, Linnan Wang, Guangxi Li, Di Chen, Shandian Zhe, Xinqi Chu, and Zenglin Xu for their excellent work.
- 2018-02-03 The paper titled as “Adaptive Local Structure Learning for Document Co-clustering” is accepted by 《Knowledge-Based Systems》. Congratulations to Shudong Huang, Zenglin Xu, and Jiancheng Lv for their excellent work.