• 机器学习、模式识别、数据挖掘等人工智能领域

孙露博士，本科毕业于武汉大学电子信息学院，硕士毕业于东北师范大学物理学院，博士毕业于日本北海道大学信息科学研究院，之后，孙露博士在日本京都大学从事博士后的研究工作。目前，孙露博士在上海科技大学信息科学与技术学院担任tenure-track助理教授、博士生导师、研究员。孙露博士的研究兴趣包括机器学习、模式识别、数据挖掘等人工智能领域，目前主要集中在多标签分类及多视角多任务学习与应用。

1. 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.

2. 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.

3. 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.

4. Lu Sun and Mineichi Kudo, Optimization of Classifier Chains via Conditional Likelihood Maximization, Pattern Recognition, 74: 503-517, 2018.

5. 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.

6. 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.

7. 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.

8. 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.