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Mert Gurbuzbalaban, Ph.D.

Affiliations: 
2012 Mathematics New York University, New York, NY, United States 
Area:
Applied Mathematics, Computer Science
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"Mert Gurbuzbalaban"
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Michael L. Overton grad student 2012 NYU
 (Theory and methods for problems arising in robust stability, optimization and quantization.)

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Publications

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Aybat NS, Fallah A, Gürbüzbalaban M, et al. (2020) Robust Accelerated Gradient Methods for Smooth Strongly Convex Functions Siam Journal On Optimization. 30: 717-751
Gürbüzbalaban M, Ozdaglar AE, Vanli ND, et al. (2020) Randomness and Permutations in Coordinate Descent Methods Mathematical Programming. 181: 349-376
Gürbüzbalaban M, Ozdaglar AE, Parrilo PA. (2019) Convergence Rate of Incremental Gradient and Incremental Newton Methods Siam Journal On Optimization. 29: 2542-2565
Gürbüzbalaban M, Ozdaglar A, Parrilo P. (2019) Why Random Reshuffling Beats Stochastic Gradient Descent Mathematical Programming. 1-36
Mokhtari A, Gürbüzbalaban M, Ribeiro A. (2018) Surpassing Gradient Descent Provably: A Cyclic Incremental Method with Linear Convergence Rate Siam Journal On Optimization. 28: 1420-1447
Vanli ND, Gurbuzbalaban M, Ozdaglar A. (2018) Global Convergence Rate of Proximal Incremental Aggregated Gradient Methods Siam Journal On Optimization. 28: 1282-1300
Gürbüzbalaban M, Ozdaglar AE, Parrilo PA. (2017) On the Convergence Rate of Incremental Aggregated Gradient Algorithms Siam Journal On Optimization. 27: 1035-1048
Eaton J, Grundel S, Gürbüzbalaban M, et al. (2017) Polynomial Root Radius Optimization with Affine Constraints Mathematical Programming. 165: 509-528
Eaton J, Grundel S, Gürbüzbalaban M, et al. (2015) Polynomial stabilization with bounds on the controller coefficients Ifac Proceedings Volumes (Ifac-Papersonline). 48: 382-387
Gürbüzbalaban M, Ozdaglar A, Parrilo P. (2015) A globally convergent incremental Newton method Mathematical Programming. 151: 283-313
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