劉威威，男，博士，武漢大學計算機學院計算機科學系教授，博士生導師。
基本介紹
- 中文名：劉威威
- 學位/學歷：博士
- 職業：教師
- 專業方向：機器學習與智慧型互動,人工智慧
- 任職院校：武漢大學計算機學院
人物經歷,研究方向,學術成果,
人物經歷
2013年8月-2017年8月 澳大利亞悉尼科技大學 人工智慧專業 博士
2010年9月-2013年7月 北京大學 軟體工程專業 碩士
2019年1月-至今 武漢大學 計算機學院 教授
2017年8月-2018年8月 澳大利亞新南威爾斯大學 博士後
研究方向
人工智慧、機器學習，包括多標籤學習、聚類、特徵選擇、稀疏學習和深度學習等。
學術成果
Refereed Conference Papers
Haobo Wang ,Weiwei Liu, Yang Zhao, Chen Zhang, Tianlei Hu , Gang Chen, Discriminative and Correlative Partial Multi-Label Learning, to appear in International Joint Conference on Artificial Intelligence (IJCAI), 2019.(CCF A)
Weiwei Liu, Xiaobo Shen,Sparse Extreme Multi-label Learning with Oracle Property, to appear inThe International Conference on Machine Learning (ICML), 2019. (CCF A)
Chen Chen, Haobo Wang,Weiwei Liu, Xingyuan Zhao, Tianlei Hu and Gang Chen,
Two-Stage Label Embedding via Neural Factorization Machine for Multi-Label Classification,
to appear in AAAI Conference on Artificial Intelligence (AAAI), 2019.(CCF A)
Xiaobo Shen,Weiwei Liu, Yong Luo, Yew Soon Ong and Ivor W.Tsang, Deep Binary
Prototype Multi-label Learning, International Joint Conference on Artificial Intelligence
(IJCAI), 2018: 2675-2681.(CCF A)
Xiaobo Shen, Shirui Pan,Weiwei Liu, Yew Soon Ong and Quan-Sen Sun, Discrete
Network Embedding, International Joint Conference on Artificial Intelligence (IJCAI),
2018: 3549-3555.(CCF A)
Jing Wang, Feng Tian,Weiwei Liu, Xiao Wang, Wenjie Zhang and Kenji Yamanishi,
Ranking Preserving Nonnegative Matrix Factorization, International Joint Conference
on Artificial Intelligence (IJCAI), 2018: 2776-2782.(CCF A)
Weiwei Liu, Zhuanghua Liu, Ivor W.Tsang,Wenjie Zhang, and Xuemin Lin, Doubly Approximate Nearest Neighbor Classification, AAAI Conference on Artificial Intelligence
(AAAI), 2018: 3683-3690.(CCF A)
Xiaobo Shen*,Weiwei Liu*, Ivor W.Tsang, Quan-Sen Sun, and Yew Soon Ong, Compact
Multi-label Learning, AAAI Conference on Artificial Intelligence (AAAI), 2018: 4066-4073. (* equally contributed).(CCF A)
Weiwei Liu,Xiaobo Shen, and Ivor W.Tsang, Sparse Embedded k-Means Clustering,
Advances in Neural Information Processing Systems (NIPS), 2017: 3321-3329.(CCF A)
Jing Chai,Weiwei Liu,Ivor W.Tsang and Xiaobo Shen, Compact Multiple-Instance
Learning, International Conference on Information and Knowledge Management (CIKM),
2017: 2007-2010.
Xiaobo Shen,Weiwei Liu, Ivor W.Tsang, Fumin Shen, and Quan-Sen Sun, Compressed
K-means for Large-scale Clustering, AAAI Conference on Artificial Intelligence (AAAI),2017: 2527-2533.(CCF A)
Weiwei Liu, and Ivor W.Tsang, Sparse Perceptron Decision Tree for Millions of Dimensions,
AAAI Conference on Artificial Intelligence (AAAI), 2016: 1881-1887.(CCF A)
Weiwei Liu, and Ivor W.Tsang, On the Optimality of Classifier Chain for Multi-label Classification, Advances in Neural Information Processing Systems (NIPS), 2015: 712-720.(CCF A)
Weiwei Liu, and Ivor W.Tsang, Large Margin Metric Learning for Multi-Label Prediction,
AAAI Conference on Artificial Intelligence (AAAI), 2015: 2800-2806.(CCF A)
Weiwei Liu, Zhi-Hong Deng, Xiuwen Gong, Frank Jiang, Ivor W. Tsang, Effectively
Predicting Whether and When a Topic Will Become Prevalent in a Social Network, AAAI Conference on Artificial Intelligence (AAAI), 2015: 210-216.(CCF A)
Refereed Journal Papers
Weiwei Liu, Donna Xu, Ivor W. Tsang, and Wenjie Zhang, Metric Learning for Multioutput
Tasks, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 41(2): 408-422, 2019.(CCF A)
Weiwei Liu, Xiaobo Shen, Bo Du, Ivor W.Tsang, Wenjie Zhang, and Xuemin Lin, IEEE
Transactions on Image Processing (TIP), 28(2): 577-588, 2019.(CCF A)
Xiaobo Shen, Fumin Shen, Li Liu, Yun-Hao Yuan,Weiwei Liu, and Quan-Sen Sun,
Multi-view Discrete Hashing for Scalable Multimedia Search, ACM Transactions on
Intelligent Systems and Technology (TIST), 9(5): 53:1-53:21, 2018.
Xiaobo Shen*,Weiwei Liu*, Ivor W. Tsang, Quan-Sen Sun and Yew-Soon Ong, Multilabel
Prediction via Cross-view Search, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 29(9): 4324-4338, 2018. (* equally contributed). （中科院一區）
Weiwei Liu, and Ivor W. Tsang, Making Decision Trees Feasible in Ultrahigh Feature
and Label Dimensions, Journal of Machine Learning Research (JMLR), 18(81): 1-36, 2017.(CCF A)
Weiwei Liu, Ivor W. Tsang, and Klaus-Robert Müller, An Easy-to-hard Learning Paradigm
for Multiple Classes and Multiple Labels, Journal of Machine Learning Research (JMLR), 18(94): 1-38, 2017.(CCF A)
Weiwei Liu, Zhi-Hong Deng, Xiaoran Xu, He Liu, and Xiuwen Gong, Mining Top K
Spread Sources for a Specific Topic and a Given Node, IEEE Transactions on Cybernetics
(TCYB), 45(11): 2472-2483, 2015. (中科院一區)
