Murat A. Erdogdu


University of Toronto
Department of Computer Science
Department of Statistical Sciences


100 St.George St. #5016b,
Toronto, ON M5S 3G3
erdogdu at cs.toronto dot edu

I am an assistant professor at the University of Toronto in departments of Computer Science and Statistical Sciences. I am also a faculty member of the Vector Institute. Before, I was a postdoctoral researcher at Microsoft Research - New England. I did my Ph.D. at Department of Statistics at Stanford University where I was jointly advised by Mohsen Bayati and Andrea Montanari. I have an M.S. degree in Computer Science from Stanford, and B.S. degrees in Electrical Engineering and Mathematics, both from Bogazici University.

Research Interests

  • Optimization: Non-convex, convex algorithms for machine learning

  • Machine Learning: Graphical models, message passing algorithms

  • Statistics: High-dimensional data analysis, regularization and shrinkage

Selected Papers

M.A. Erdogdu, Y. Deshpande, A. Montanari, Inference in Graphical Models via SDP Hierarchies, NIPS 2017
M.A. Erdogdu, M. Bayati, L.H. Dicker Scaled Least Squares Estimator for GLMs in Large-Scale Problems, NIPS 2016
M.A. Erdogdu, Newton-Stein Method: An optimization method for GLMs via Stein’s lemma, NIPS 2015
M.A. Erdogdu and A. Montanari, Convergence rates of sub-sampled Newton methods, NIPS 2015
M. Bayati, M.A. Erdogdu, A. Montanari, Estimating Lasso risk and noise level, NIPS 2013