Murat A. Erdogdu

University of Toronto Department of Computer Science Department of Statistical Sciences Contact 100 St. George Street #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 a faculty member of the Machine Learning Group and the Vector Institute, and a CIFAR Chair in Artificial Intelligence. 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, theory

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

Recent Papers

• A. Anastasiou, K. Balasubramanian and M.A. Erdogdu, Normal Approximation for Stochastic Gradient Descent via Non-Asymptotic Rates of Martingale CLT, 2019

• M.A. Erdogdu, A. Ozdaglar, P. Parillo and N.D. Vanli, Convergence Rate of Block-Coordinate Maximization Burer-Monteiro Method for Solving Large SDPs, 2018

• M.A. Erdogdu, L. Mackey and O. Shamir, Global Non-convex Optimization with Discretized Diffusions, 2018

• M.A. Erdogdu, Y. Deshpande and A. Montanari, Inference in Graphical Models via Semidefinite Programming Hierarchies,  2017