菜单总览
— 教职人员 —

刘威

职位:

客座副教授

教育背景:

博士(哥伦比亚大学)

学士(浙江大学)

研究领域
机器学习、信息检索、大数据、计算机视觉
Email

wl2223@columbia.edu

个人简介:


刘威现任腾讯AI Lab杰出科学家与计算机视觉中心总监。在此之前,他获得美国哥伦比亚大学计算机科学与电子工程博士学位,曾任IBM沃森研究中心研究科学家。刘博士长期从事机器学习、计算机视觉、信息检索、大数据等AI核心领域的基础研究和技术开发。刘博士的科研成果获得了若干奖项与荣誉,如2011年度Facebook博士研究生奖学金,2013年度哥伦比亚大学优秀博士论文奖,2016与2017连续两年国际信息检索大会 (SIGIR) 最优论文荣誉奖,2018年度 "AI's 10 To Watch" 荣誉。刘博士现任多个国际重要AI期刊的编委,和多个国际顶级AI会议的领域主席。


学术著作:


Journal

Canyi Lu, Jiashi Feng, Yudong Chen, Wei Liu, Zhouchen Lin, and Shuicheng Yan, "Tensor Robust Principal Component Analysis with A New Tensor Nuclear Norm", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019.

 

Baoyuan Wu, Fan Jia, Wei Liu, Bernard Ghanem, and Siwei Lyu, "Multi-label Learning with Missing Labels Using Mixed Dependency Graphs", International Journal of Computer Vision (IJCV), vol. 126, no. 8, pp. 875-896, August 2018.

 

Yeqing Li, Wei Liu, and Junzhou Huang, "Sub-Selective Quantization for Learning Binary Codes in Large-Scale Image Search", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 40, no. 6, pp. 1526-1532, June 2018.

 

Guo-Jun Qi, Wei Liu, Charu Aggarwal, and Thomas Huang, "Joint Intermodal and Intramodal Label Transfers for Extremely Rare or Unseen Classes", IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 39, no. 7, pp. 1360-1373, July 2017.

 

Xiao Wang, Shiqian Ma, Donald Goldfarb, and Wei Liu, "Stochastic Quasi-Newton Methods for Nonconvex Stochastic Optimization", SIAM Journal on Optimization (SIOPT), vol. 27, no. 2, pp. 927-956, May 2017.

 

Wei Liu and Tongtao Zhang, "Multimedia Hashing and Networking", IEEE MultiMedia, vol. 23, no. 3, pp. 75-79, July-September 2016.

 

Jun Wang, Wei Liu, Sanjiv Kumar, and Shih-Fu Chang, "Learning to Hash for Indexing Big Data - A Survey", Proceedings of the IEEE, vol. 104, no. 1, pp. 34-57, January 2016.

 

Wei Liu, Jun Wang, and Shih-Fu Chang, "Robust and Scalable Graph-Based Semisupervised Learning", Proceedings of the IEEE, vol. 100, no. 9, pp. 2624-2638, September 2012.

 

Conference

Yunzhe Tao, Qi Sun, Qiang Du, and Wei Liu, "Nonlocal Neural Networks, Nonlocal Diffusion and Nonlocal Modeling", Advances in Neural Information Processing Systems (NeurIPS) 31, 2018.

 

Xing Yan, Weizhong Zhang, Lin Ma, Wei Liu, and Qi Wu, "Parsimonious Quantile Regression of Financial Asset Tail Dynamics via Sequential Learning", Advances in Neural Information Processing Systems (NeurIPS) 31, 2018.

 

Hongteng Xu, Wenlin Wang, Wei Liu, and Lawrence Carin, "Distilled Wasserstein Learning for Word Embedding and Topic Modeling", Advances in Neural Information Processing Systems (NeurIPS) 31, 2018.

 

Wenhan Luo, Peng Sun, Fangwei Zhong, Wei Liu, Tong Zhang, and Yizhou Wang, "End-to-end Active Object Tracking via Reinforcement Learning", in Proc. International Conference on Machine Learning (ICML), 2018.

 

Li Shen, Peng Sun, Yitong Wang, Wei Liu, and Tong Zhang, "An Algorithmic Framework of Variable Metric Over-Relaxed Hybrid Proximal Extra-Gradient Method", in Proc. International Conference on Machine Learning (ICML), 2018.

 

Weizhong Zhang, Bin Hong, Lin Ma, Wei Liu, and Tong Zhang, "Safe Element Screening for Submodular Function Minimization", in Proc. International Conference on Machine Learning (ICML), 2018.

 

Xinpeng Chen, Jingyuan Chen, Lin Ma, Jian Yao, Wei Liu, Jiebo Luo, and Tong Zhang, "Fine-grained Video Attractiveness Prediction Using Multimodal Deep Learning on a Large Real-world Dataset", in Proc. The Web Conference (WWW), 2018.

 

Shixiang Chen, Shiqian Ma, and Wei Liu, "Geometric Descent Method for Convex Composite Minimization", Advances in Neural Information Processing Systems (NeurIPS) 30, 2017.

 

Dongsheng Li, Chao Chen, Wei Liu, Tun Lu, Ning Gu, and Stephen M. Chu, "Mixture-Rank Matrix Approximation for Collaborative Filtering", Advances in Neural Information Processing Systems (NeurIPS) 30, 2017.

 

Li Shen, Wei Liu, GanZhao Yuan, and Shiqian Ma, "GSOS: Gauss-Seidel Operator Splitting Algorithm for Multi-Term Nonsmooth Convex Composite Optimization", in Proc. International Conference on Machine Learning (ICML), 2017. 

 

Jingyuan Chen, Hanwang Zhang, Xiangnan He, Liqiang Nie, Wei Liu, and Tat-Seng Chua, "Attentive Collaborative Filtering: Multimedia Recommendation with Item- and Component-Level Attention", in Proc. International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2017.

 

Fumin Shen, Yadong Mu, Yang Yang, Wei Liu, Li Liu, Jingkuan Song, and Heng Tao Shen, "Classification by Retrieval: Binarizing Data and Classifiers", in Proc. International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2017 (Best Paper Award Honorable Mention).

 

Hanwang Zhang, Fumin Shen, Wei Liu, Xiangnan He, Huanbo Luan, and Tat-Seng Chua, "Discrete Collaborative Filtering", in Proc. International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2016 (Best Paper Award Honorable Mention).

 

Wei Liu, Cun Mu, Sanjiv Kumar, and Shih-Fu Chang, "Discrete Graph Hashing",  Advances in Neural Information Processing Systems (NeurIPS) 27, 2014.

 

Wei Liu, Gang Hua, and John R. Smith, "Unsupervised One-Class Learning for Automatic Outlier Removal", in Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014.

 

Wei Liu, Jun Wang, Yadong Mu, Sanjiv Kumar, and Shih-Fu Chang, "Compact Hyperplane Hashing with Bilinear Functions", in Proc. International Conference on Machine Learning (ICML), 2012.

 

Wei Liu, Jun Wang, Rongrong Ji, Yu-Gang Jiang, and Shih-Fu Chang, "Supervised Hashing with Kernels", in Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2012.

 

Wei Liu, Jun Wang, Sanjiv Kumar, and Shih-Fu Chang, "Hashing with Graphs", in Proc. International Conference on Machine Learning (ICML), 2011.

 

Wei Liu, Yu-Gang Jiang, Jiebo Luo, and Shih-Fu Chang, "Noise Resistant Graph Ranking for Improved Web Image Search", in Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2011.

 

Wei Liu, Shiqian Ma, Dacheng Tao, Jianzhuang Liu, and Peng Liu, "Semi-Supervised Sparse Metric Learning Using Alternating Linearization Optimization", in Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2010.

 

Wei Liu, Junfeng He, and Shih-Fu Chang, "Large Graph Construction for Scalable Semi-Supervised Learning", in Proc. International Conference on Machine Learning (ICML), 2010.

 

Wei Liu and Shih-Fu Chang, "Robust Multi-Class Transductive Learning with Graphs", in Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2009.