Yujia Li

Profile Picture


Department of Computer Science
University of Toronto
UofT Email 		I'm a Ph.D. student at University of Toronto. I'm a member of the machine learning group and my advisor is Prof. Richard Zemel. My research now focuses on structured output learning, especially image labeling problems. Before coming to Toronto, I obtained my bachelor's degree from Tsinghua University, Beijing, China. I was an intern Research and Development engineer at Baidu, Inc. in the summer of 2011, a Research Intern with the Speech Group at Microsoft Research Redmond in the summer of 2014, and a Research Intern with the Machine Learning and Perception group at Microsoft Research Cambridge in the summer of 2015.

News

  • Code for our ICLR 2016 paper "Gated Graph Sequence Neural Networks" is available now.
  • Two papers accepted to appear in ICLR 2016.
  • One paper accepted to appear in ICML 2015.
  • One paper accepted to appear in ICASSP 2015.
  • One paper accepted to appear in NIPS 2014 workshop on Transfer and Multi-Task Learning.
  • Part of my work at MSR this summer on wrist gesture recognition is integrated into the Microsoft product Torque. More media coverage from Yahoo!, CNET, Engadget, The Verge, GeekWire, VentureBeat, PCWorld, BetaNews and many others.
  • Code and data for our ICML'14 paper is available now.
  • I'm TA'ing CSC 411 "Machine Learning and Data Mining" again this Fall.
  • One paper accepted to appear in ICML 2014 workshop on Learning Tractable Probabilistic Models.
  • One paper accepted to appear in ICML 2014.

Education

2013.2-Present      Ph.D. Student
Department of Computer Science, University of Toronto, Toronto, ON, Canada
 
2011.9-2013.1      Master of Science
Department of Computer Science, University of Toronto, Toronto, ON, Canada
 
2007.8-2011.7 Bachelor of Engineering
School of Software, Tsinghua University, Beijing, China

Publications

Conference Papers

Gated Graph Sequence Neural Networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt and Richard Zemel
International Conference on Learning Representations (ICLR), 2016
[arXiv] [slides] [poster] [code] [talk]

The Variational Fair Auto Encoder
Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, Richard Zemel
International Conference on Learning Representations (ICLR), 2016
Oral Presentation
[arXiv]

Generative Moment Matching Networks
Yujia Li, Kevin Swersky and Richard Zemel
International Conference on Machine Learning (ICML), 2015
[paper] [arXiv preprint] [code] [project page]

Feedback-Based Handwriting Recognition from Inertial Sensor Data for Wearable Devices
Yujia Li, Kaisheng Yao and Geoffrey Zweig
The 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015
[paper]

High Order Regularization for Semi-Supervised Learning of Structured Output Problems
Yujia Li and Richard Zemel
International Conference on Machine Learning (ICML), 2014
[paper + supplementary material] [slides] [poster] [data] [code] [video]

Exploring Compositional High Order Pattern Potentials for Structured Output Learning
Yujia Li, Daniel Tarlow and Richard Zemel
The 26th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2013
Oral Presentation
[paper] [supplementary material] [slides] [poster] [data] [code] [video]

Celebrity Recommendation with Collaborative Social Topic Regression
Xuetao Ding, Xiaoming Jin, Yujia Li and Lianghao Li
Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2013
[paper]


Workshop Papers

Learning Unbiased Features
Yujia Li, Kevin Swersky and Richard Zemel
NIPS workshop on Transfer and Multi-Task Learning, 2014
[paper] [slides] [poster]

Mean Field Networks
Yujia Li and Richard Zemel
ICML workshop on Learning Tractable Probabilistic Models, 2014
[paper] [slides] [poster]


Thesis

Exploring Compositional High Order Pattern Potentials for Structured Output Learning
M.Sc. Thesis
[paper]


Talks

Generative Moment Matching Networks (2015) at Toronto Machine Learning Group Seminar. [pdf]

A Tutorial on Dual Decomposition (2014) at Toronto Machine Learning Group Meeting. [pdf]


Teaching Experience

Courses TA'ed at University of Toronto Courses TA'ed at Tsinghua University
  • Spring 2011, Advanced Data Structures
  • Spring 2011, Machine Learning and Knowledge Discovery

Honors and Awards

  • 2016, ICLR travel award.
  • 2015, Microsoft Ph.D. fellowship (US and Canada) finalist.
  • 2015, ICML travel grant.
  • 2013, CVPR travel grant.
  • 2013, University of Toronto School of Graduate Studies conference grant.
  • 2008-2010, University-wide comprehensive merit scholarship, three times - Including Kai-Feng Scholarship, which is the highest amount among all scholarships and awarded to only 30 undergraduate students in Tsinghua University every year.
  • 2008, 2nd Prize - Chinese National College Physics Contest
  • 2006, 1st Prize - Chinese Physics Olympiad (CPhO) in Provinces
  • 2005, 2nd Prize - Chinese National Olympiad in Informatics in Provinces (NOIP)

Other Stuff

My name in Chinese: My Name

A list of my old projects can be found here.

I'm the admin of the machine learning group website, let me know if you want to post anything on it.

I swim and run regularly every week. I like playing badminton. I'm a fan of NBA. Following are some activities that I have participated in.

  • 2010, Finished Half Marathon - 30th Beijing International Marathon
  • 2010, Volunteer - Data Statistics group, China Open (Tennis)
  • 2009, Visiting Student - Tohoku University, Sendai, Japan.
  • 2009, Vice President - Student Association of Science and Technology, School of Software, Tsinghua University
    • Co-organized the first regional software design contest, which attracts around 70 teams from 7 main universities in Beijing to participate.
  • 2008-2009, Section Chief - Student Union, School of Software, Tsinghua University
  • 2008, Staff, Out Standing Staff Laureate - Media Village, Beijing Olympic Games
  • 2008, Finished 10km - 28th Beijing International Marathon