I am a fourth-year Ph.D. student in the Department of Brain and Cognitive Sciences at MIT working with Dr. Suvrit Sra.
I am also affiliated with LIDS and the Machine Learning Group at MIT.
I aim to combine the power of nonlinear optimization and differential geometry to solve difficult optimization problems. I am interested in machine learning and, more broadly, modeling and solving real world computational problems.
77 Massachusetts Avenue,
Cambridge MA, 02139
|Email:||hongyiz (at) mit (dot) edu|
|2013 - Present||Massachusetts Institute of Technology|
|Ph.D. candidate in Cognitive Science|
|2008 - 2013||Peking University|
|Bachelor in Machine Intelligence|
|2015/2016 Fall||Teaching Assistant,|
|MIT 9.520/6.860 -- Statistical Learning Theory and Applications|
|2014 Fall||Teaching Assistant,|
|MIT 9.66/6.804/9.660 -- Computational Cognitive Science|
|2012 Summer||Research Intern,|
|at TTI Chicago with Prof. Raquel Urtasun|
PublicationsMatrix Completion from O(n) Samples in Linear Time. [arXiv]
arXiv:1702.02267 [stat.ML] (Short version to appear in COLT 2017)
Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds. [Paper][Supplemental]
The 30th Conference on Neural Information Processing Systems (NIPS 2016).
First-order Methods for Geodesically Convex Optimization. [Paper]
The 29th Annual Conference on Learning Theory (COLT 2016)
Physics 101: Learning Physical Object Properties from Unlabeled Videos. [Paper][Project]
Proceedings of the British Machine Vision Conference 2016 (BMVC 2016)
Writing Customized Proposals for Probabilistic Programs as Probabilistic Programs.
3rd NIPS Workshop on Probabilistic Programming. 2014.
Understanding High-Level Semantics by Modeling Traffic Patterns. [Paper][Supplemental][Video]
International Conference on Computer Vision (ICCV'13)