Junfeng Wen 闻俊锋
Athabasca Hall 111
Department of Computing Science
University of Alberta
Canada, T6G 2E8
Email: junfeng D-O-T wen A~T ualberta D-O-T ca
I am a Ph.D. student working with Prof. Russ Greiner and Prof. Dale Shuurmans in AICML. My primary research interests are transfer learning and representation learning.
Sep.2013 - Present, Department of Computing Science, University of Alberta, Doctor of Philosophy
Sep.2011 - Jun.2013, Department of Computing Science, University of Alberta, Master of Science
Sep.2007 - Jun.2011, College of Computer Science and Technology, Chu Kochen Honors College, Zhejiang University, Bachelor of Engineering (with Honor)
Jan.2010 - May.2010, Department of Computer Science, The University of Hong Kong, Exchange Student, Bachelor of Engineering
V. Ganapathiraman, X. Zhang, Y. Yu and J. Wen. Convex Two-Layer Modeling with Latent Structure. In Twenty-Ninth Neural Information Processing Systems (NIPS), 2016. [pdf]
J. Wen, R. Greiner and D. Schuurmans. Correcting Covariate Shift with the Frank-Wolfe Algorithm. In Twenty-Fourth International Joint Conference on Artificial Intelligence (IJCAI), 2015. [pdf] [code]
M. White, J. Wen, M. Bowling and D. Schuurmans. Optimal Estimation of Multivariate ARMA Models. In Twenty-Ninth Annual Conference on Artificial Intelligence (AAAI), 2015. Also invited to ICRA 2015. [pdf] [code]
J. Wen, C. Yu and R. Greiner. Robust Learning under Uncertain Test Distributions: Relating Covariate Shift to Model Misspecification. In International Conference of Machine Learning (ICML), 2014. [pdf] [code]
2016 Fall: TA of CMPUT 466/551 Machine Learning, University of Alberta
2015 Fall: Instructor of CMPUT 274 Introduction to Tangible Computing, University of Alberta
2012 Fall: Head TA of CMPUT 101 Introduction to Computing, University of Alberta
2011 Winter: Primary TA of CMPUT 101 Introduction to Computing, University of Alberta
2011 Fall: Secondary TA of CMPUT 101 Introduction to Computing, University of Alberta
2013 Fall: Statistical Inference (A+), University of Alberta, by Prof. Ivan Mizera. (Lecture notes. Let me know if you find any errors or typos.)
2013 Fall: Online Learning (A), University of Alberta, by Prof. Csaba Szepesvari and Dr. Andras Gyorgy.
2012 Fall: Probabilistic Graphical Models (earned 96.5%), Coursera (Stanford University), by Prof. Daphne Koller.
2012 Fall: Neural Networks for Machine Learning (earned 97.7%), Coursera (University of Toronto), by Prof. Geoffrey Hinton.
2011 Winter: Representation Learning (A+), University of Alberta, by Prof. Dale Shuurmans.
2011 Fall: Machine Learning (A), University of Alberta, by Prof. Dale Shuurmans. (Lecture notes. Let me know if you find any errors or typos.)
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