CHU,WEI

Short CV



@chuwei.website

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Welcome to my homepage. I am with Alibaba Cloud now, leading a R&D team to develop distributed machine learning platform for large-scale learning tasks. Previously I was an associate research scientist of CCLS, Columbia University, a scientist of Yahoo! Labs, and then a principal scientist lead of Microsoft. Before I moved to US, I was a senior postdoctoral fellow of the Gatsby Computational Neuroscience Unit, University College London, working with Zoubin Ghahramani and David L. Wild on Machine Learning and Bioinformatics. I received Ph.D. degree at the Dept. of Mechanical Engineering, National University of Singapore, under the joint guidance of S. Sathiya Keerthi and Chong Jin Ong.


1. Recent Work

2. Publications

3. Source Code


1. Recent Work

P. Bennett, R. White, W. Chu, S. Dumais, P. Bailey, F. Borisyuk and X. Cui (2012) Modeling and measuring the impact of short and long-term behavior on search personalization, ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-35) (View Abstract)

L. Li, W. Chu, J. Langford, T. Moon, and X. Wang (2012) An unbiased offline evaluation of contextual bandit algorithms with generalized linear models, Journal of Machine Learning Research - Workshop and Conference Proceedings 26 (JMLR W&CP-26) (View Abstract)

W. Chu, M. Zinkevich, L. Li, A. Thomas, and B. Tseng (2011) Unbiased online active learning in data streams, ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-17) (View Abstract)

T. Moon, W. Chu, L. Li, Z. Zheng, Y. Chang (2012) Online learning framework for refining recency search results with user click feedback, to appear in Transactions on Information Systems (View Abstract)

L. Li, W. Chu, J. Langford and X. Wang (2011) Unbiased offline evaluation of contextual-bandit-based news article recommendation algorithms, in Proc. of ACM Web Search and Data Mining (WSDM-04) 297-306 (View Abstract)

L. Li, W. Chu, J. Langford and R. E. Schapire (2010) A contextual-bandit approach to personalized news article recommendation, in Proc. of International World Wide Web Conference (WWW-19) (View Abstract)

W. Chu and Z. Ghahramani (2009) Probabilistic models for incomplete multi-dimensional arrays, in Proc. of International Conference on Artificial Intelligence and Statistics (AISTATS-12) (View Abstract)

W. Chu and S.-T. Park (2009) Personalized recommendation on dynamic content using predictive bilinear models, in Proc. of International World Wide Web Conference (WWW-18) (View Abstract)

S.-T. Park and W. Chu (2009) Pairwise preference regression for cold-start recommendation, in Proc. of ACM Recommender Systems (RecSys-03) (View Abstract)

R. Silva, W. Chu and Z. Ghahramani (2007) Hidden common cause relations in relational learning, in Advances in Neural Information Processing Systems (NIPS-20) (View Abstract)

K. Yu and W. Chu (2007) Gaussian process models for link analysis and transfer learning, in Advances in Neural Information Processing Systems (NIPS-20) (View Abstract)

P. K. Shivaswamy, W. Chu and M. Jansche (2007) A support vector approach to censored targets, in Proc. of IEEE International Conference on Data Mining (ICDM-07) (View Abstract)

W. Chu, V. Sindhwani, Z. Ghahramani and S. S. Keerthi (2006) Relational learning with Gaussian processes, in Advances in Neural Information Processing Systems (NIPS-19) (View Abstract)

S. K. Shevade and W. Chu (2006) Minimum enclosing spheres formulations for support vector ordinal regression, in Proc. of IEEE International Conference on Data Mining (ICDM-06):1054-1058 (View Abstract)

V. Sindhwani, W. Chu and S. S. Keerthi (2007) Semi-supervised Gaussian process classifiers, in Proc. of International Joint Conferences on Artificial Intelligence (IJCAI-20):1059-1064 (View Abstract)

S. S. Keerthi and W. Chu (2005) A matching pursuit approach to sparse Gaussian process regression, in Advances in Neural Information Processing Systems (NIPS-18) (View Abstract)

W. Chu and Z. Ghahramani (2005) Preference learning with Gaussian processes, in Proc. of International Conference on Machine Learning (ICML-22):137-144 (View Abstract)

W. Chu and S. S. Keerthi (2005) New approaches to support vector ordinal regression, in Proc. of International Conference on Machine Learning (ICML-22):145-152 (View Abstract)

W. Chu and Z. Ghahramani (2005) Gaussian processes for ordinal regression, Journal of Machine Learning Research 6(Jul):1019--1041 (View Abstract)

W. Chu, Z. Ghahramani, F. Falciani, and D. L. Wild (2005) Biomarker discovery with Gaussian processes in microarray gene expression data, Bioinformatics 2005(21):3385-3393 (View Abstract)

W. Chu, Z. Ghahramani and D. L. Wild (2004) A graphical model for protein secondary structure prediction, in Proc. of International Conference on Machine Learning (ICML-21):161-168 (View Abstract)

W. Chu, S. S. Keerthi and C. J. Ong (2004) Bayesian support vector regression using a unified loss function, IEEE Transactions on Neural Networks 15(1):29-44 (View Abstract)


3. Source Code



email : email dot chuwei at gmail.com

2017.02.19