|Lu Sun, Assistant Professor|
Machine learning, pattern recognition and data mining
Dr. Lu Sun is an assistant professor with the School of Information Science and Technology at ShanghaiTech University, China. He received the B.S. degree in electrical engineering from Wuhan University, China, in 2009, the M.S. degree in electronic circuits and systems from Northeast Normal University, China, in 2013, and the Dr. Eng. degree in Information Engineering from Hokkaido University, Japan, in 2017. During 2017-2019, he worked as a postdoctoral researcher at Kyoto University, Japan. His research interests cover machine learning, data mining and pattern recognition, and currently focus on multi-label classification and multi-view multi-task learning.
Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka, Fast and Robust Multi-View Multi-Task Learning via Group Sparsity, in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 3499-3505, 2019, Macao, China.
Lu Sun, Canh Hao Nguyen, Hiroshi Mamitsuka, Multiplicative Sparse Feature Decomposition for Efficient Multi-View Multi-Task Learning, in Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019), 3506-3512, 2019, Macao, China.
Lu Sun and Mineichi Kudo, Multi-Label Classification by Polytree-Augmented Classifier Chains with Label-Dependent Features, Pattern Analysis and Applications, 22(3), 1029-1049, 2019.
Lu Sun and Mineichi Kudo, Optimization of Classifier Chains via Conditional Likelihood Maximization, Pattern Recognition, 74: 503-517, 2018.
Lu Sun, Mineichi Kudo and Keigo Kimura, READER: Robust Semi-Supervised Multi-Label Dimension Reduction, IEICE Transactions on Information and Systems, E100-D(10): 2597-2604, 2017.
Lu Sun, Mineichi Kudo and Keigo Kimura, Multi-Label Classification with Meta-Label-Specific Features, in Proceedings of the 23rd International Conference on Pattern Recognition (ICPR 2016), 1612-1617, 2016, Cancun, Mexico.
Lu Sun, Mineichi Kudo and Keigo Kimura, A Scalable Clustering-Based Local Multi-Label Classification Method, in Proceedings of the 22nd European Conference on Artificial Intelligence (ECAI 2016), 261-268, 2016, The Hague, Netherlands.
Lu Sun and Mineichi Kudo, Polytree-Augmented Classifier Chains for Multi-Label Classification, in Proceedings of the 24th International Joint Conference of Artificial Intelligence (IJCAI 2015), 3834-3840, 2015, Buenos Aires, Argentina.