Qianli Liao

Current Advisees

Past Advisees

Alex Chen - UROP
Tom Dudzik - UROP
Xiaolu Guo - EIT
Parker Hao - EIT
Gabe Hege - Graduate Student
Erwin Hilton - Graduate Student
Zhuoqiao Hong - Graduate Student
Kriti Jain - EIT
Ivan Jutamulia - Undergraduate Research Assistant
Sule Kahraman - UROP
Jessica Liu - EIT
Sofia Luo - UROP
Vivian Qian - UROP
Alizee Schoen - UROP
Prachi Sinha - EIT
David Walter - Graduate Student
Alex Yang - UROP
Mingshi Yang - UROP
Kevin Yue - UROP
Queenie Zhang - UROP
Tong Zhao - UROP

Projects

CBMM Publications

W. Xiao, Chen, H., Liao, Q., and Poggio, T., Biologically-Plausible Learning Algorithms Can Scale to Large Datasets, in International Conference on Learning Representations, 2019.
T. Poggio and Liao, Q., Theory I: Deep networks and the curse of dimensionality, Bulletin of the Polish Academy of Sciences: Technical Sciences, vol. 66, no. 6, 2018.
T. Poggio and Liao, Q., Theory II: Deep learning and optimization, Bulletin of the Polish Academy of Sciences: Technical Sciences, vol. 66, no. 6, 2018.
H. Mhaskar, Liao, Q., and Poggio, T., When and Why Are Deep Networks Better Than Shallow Ones?, AAAI-17: Thirty-First AAAI Conference on Artificial Intelligence. 2017.
Q. Liao, Leibo, J. Z., and Poggio, T., How Important Is Weight Symmetry in Backpropagation?, in Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, AZ., 2016.
Q. Liao, Leibo, J. Z., and Poggio, T., How Important Is Weight Symmetry in Backpropagation?, in Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), Phoenix, AZ., 2016.
J. Z. Leibo, Liao, Q., and Poggio, T., Subtasks of Unconstrained Face Recognition. 9th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. (VISAPP)., Lisbon, Portugal, 2014.