刘威威
必赢优惠y272net 计算机科学系 人工智能研究所 教授 (博导)
研究方向
刘威威, 必赢优惠y272net, 教授、博导。2017年8月于悉尼科技大学（University of Technology Sydney, UTS）获得博士学位，导师Ivor W.Tsang教授。主要研究方向为人工智能、机器学习，包括多标签学习、聚类、特征选择、稀疏学习和深度学习等。目前，已在世界顶级期刊及会议上发表CCF A类一作学术论文10余篇，其中，包括机器学习旗舰型期刊Journal of Machine Learning Research (JMLR)，模式识别、计算机视觉和机器学习应用顶级期刊IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)，机器学习顶级学术会议Neural Information Processing Systems（NIPS），The International Conference on Machine Learning (ICML) ，人工智能顶级学术会议AAAI、IJCAI。
2018年入选美国电气与电子工程师协会IEEE Senior Member。2018年担任神经网络顶级期刊IEEE Transactions on Neural Networks and Learning Systems（TNNLS）主要客座编辑（Leading Guest Editor）。曾获得Pattern Recognition Journal杰出审稿人奖，及2017年度中国留学基金委“优秀自费留学生”奖学金（澳大利亚地区计算机领域唯一获奖人）等荣誉。
热烈欢迎数学/统计专业、计算机相关专业学生报考我组博士或硕士，并招博士后，有意向者请发邮件：liuweiwei863@gmail.com
英文主页：https://sites.google.com/site/weiweiliuhomepage/
教育背景
2013年8月-2017年8月 澳大利亚悉尼科技大学 人工智能专业 博士
2010年9月-2013年7月 北京大学 软件工程专业 硕士
2006年8月-2010年6月 天津理工大学 交通运输专业 学士
工作经验
2019年1月-至今 必赢优惠y272net 必赢优惠y272net 教授
2017年8月-2018年8月 澳大利亚新南威尔士大学 博士后
教授课程
发表论文
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 in The 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). （中科院一区）
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. (中科院一区)
科研课题
研究团队
知识产权
IEEE Senior Member.
2017年度中国留学基金委“优秀自费留学生”奖学金。
杰出审稿人奖：Outstanding Reviewer Award of Pattern Recognition Journal.
最佳理论文章奖：Best Theory Paper Award from Centre for Artificial Intelligence, University of Technology Sydney.
学术服务
中科院一区学术期刊主要客座编辑:
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
CCF A类学术会议程序委员会成员:
包括AAAI、IJCAI、ICDE、WWW等。
国际研讨会程序委员会主席之一:
1，The 28th International Joint Conference on Artificial Intelligence (IJCAI-19) Workshop
2，The 10th Asian Conference on Machine Learning (ACML 2018) Workshop
国际学术会议高级程序委员会成员:
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD): 2019
国际顶级学术会议、期刊审稿人:
顶级会议：包括NIPS、ICML、AISTATS、 UAI、CVPR、ECCV 、ICCV、SDM等。
顶级期刊：包括TPAMI、TNNLS、 TKDE、 TKDD等。
成果展示
其他
