劉威威
437bwin必贏國際官網 計算機科學系 人工智能研究所 教授 (博導)
研究方向
劉威威, 437bwin必贏國際官網, 教授、博導。2017年8月于悉尼科技大學（University of Technology Sydney, UTS）獲得博士學位，導師Ivor W.Tsang教授。主要研究方向為人工智能、機器學習，包括多標簽學習、聚類、特征選擇、稀疏學習和深度學習等。目前，已在世界頂級期刊及會議上發表CCF A類一作學術論文10余篇，其中，包括機器學習旗艦型期刊Journal of Machine Learning Research (JMLR)，模式識別、計算機視覺和機器學習應用頂級期刊IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)，機器學習頂級學術會議Neural Information Processing Systems（NIPS），The International Conference on Machine Learning (ICML) ，人工智能頂級學術會議AAAI、IJCAI。
2018年入選美國電氣與電子工程師協會IEEE Senior Member。2018年擔任神經網絡頂級期刊IEEE Transactions on Neural Networks and Learning Systems（TNNLS）主要客座編輯（Leading Guest Editor）。曾獲得Pattern Recognition Journal杰出審稿人獎，及2017年度中國留學基金委“優秀自費留學生”獎學金（澳大利亞地區計算機領域唯一獲獎人）等榮譽。
熱烈歡迎數學/統計專業、計算機相關專業學生報考我組博士或碩士，并招博士后，有意向者請發郵件：liuweiwei863@gmail.com
英文主頁：https://sites.google.com/site/weiweiliuhomepage/
教育背景
2013年8月-2017年8月 澳大利亞悉尼科技大學 人工智能專業 博士
2010年9月-2013年7月 北京大學 軟件工程專業 碩士
2006年8月-2010年6月 天津理工大學 交通運輸專業 學士
工作經驗
2019年1月-至今 437bwin必贏國際官網 437bwin必贏國際官網 教授
2017年8月-2018年8月 澳大利亞新南威爾士大學 博士后
教授課程
發表論文
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)
科研課題
研究團隊
知識產權
IEEE Senior Member.
2017年度中國留學基金委“優秀自費留學生”獎學金。
杰出審稿人獎：Outstanding Reviewer Award of Pattern Recognition Journal.
最佳理論文章獎：Best Theory Paper Award from Centre for Artificial Intelligence, University of Technology Sydney.
學術服務
中科院一區學術期刊主要客座編輯:
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
CCF A類學術會議程序委員會成員:
包括AAAI、IJCAI、ICDE、WWW等。
國際研討會程序委員會主席之一:
1，The 28th International Joint Conference on Artificial Intelligence (IJCAI-19) Workshop
2，The 10th Asian Conference on Machine Learning (ACML 2018) Workshop
國際學術會議高級程序委員會成員:
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD): 2019
國際頂級學術會議、期刊審稿人:
頂級會議：包括NIPS、ICML、AISTATS、 UAI、CVPR、ECCV 、ICCV、SDM等。
頂級期刊：包括TPAMI、TNNLS、 TKDE、 TKDD等。
成果展示
其他
