Mert Gürbüzbalaban

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Lingjiong ZhuFlorida State UniversityDirección de correo verificada de fsu.edu
Umut SimsekliINRIA - École Normale SupérieureDirección de correo verificada de inria.fr
Asuman OzdaglarMathworks Professor, EECS, MITDirección de correo verificada de mit.edu
Necdet Serhat AybatIndustrial and Manufacturing Engineering, Penn State UniversityDirección de correo verificada de psu.edu
Pablo A. ParriloProfessor of Electrical Engineering and Computer Science, Massachusetts Institute of TechnologyDirección de correo verificada de mit.edu
BUGRA CANRutgers UniversityDirección de correo verificada de scarletmail.rutgers.edu
Xuefeng GaoThe Chinese University of Hong KongDirección de correo verificada de se.cuhk.edu.hk
Michael L. OvertonProfessor of Computer Science and Mathematics, New York UniversityDirección de correo verificada de cs.nyu.edu
Saeed SooriUniversity of TorontoDirección de correo verificada de cs.toronto.edu
Yuanhan HuRutgers UniversityDirección de correo verificada de rutgers.edu
Alireza FallahUC BerkeleyDirección de correo verificada de berkeley.edu
Nuri Denizcan VanliMassachusetts Institute of TechnologyDirección de correo verificada de mit.edu
Maryam Mehri DehnaviUniversity of TorontoDirección de correo verificada de cs.toronto.edu
Levent SagunFAIRDirección de correo verificada de meta.com
Aryan MokhtariUniversity of Texas at AustinDirección de correo verificada de austin.utexas.edu
Anant RajAssistant Professor, Indian Institute of Science, BengaluruDirección de correo verificada de iisc.ac.in
Xuan ZhangPh.D. Student, The Pennsylvania State UniversityDirección de correo verificada de psu.edu
Alejandro RibeiroUniversity of PennsylvaniaDirección de correo verificada de seas.upenn.edu
Gaël RichardProfessor, Télécom Paris, Institut polytechnique de ParisDirección de correo verificada de telecom-paris.fr
Thanh Huy NguyenTélécom ParisDirección de correo verificada de telecom-paristech.fr

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Mert Gürbüzbalaban

Rutgers University

Dirección de correo verificada de business.rutgers.edu - Página principal

Optimization Machine Learning Data Science Applied Mathematics Computational Science


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
A tail-index analysis of stochastic gradient noise in deep neural networks U Simsekli, L Sagun, M Gurbuzbalaban International Conference on Machine Learning, 5827-5837, 2019	275	2019
Why random reshuffling beats stochastic gradient descent M Gürbüzbalaban, A Ozdaglar, PA Parrilo Mathematical Programming 186, 49-84, 2021	217	2021
On the convergence rate of incremental aggregated gradient algorithms M Gurbuzbalaban, A Ozdaglar, PA Parrilo SIAM Journal on Optimization 27 (2), 1035-1048, 2017	174	2017
The heavy-tail phenomenon in SGD M Gurbuzbalaban, U Simsekli, L Zhu International Conference on Machine Learning, 3964-3975, 2021	140	2021
Global Convergence of Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Stochastic Optimization: Non-Asymptotic Performance Bounds and Momentum-Based Acceleration X Gao, M Gurbuzbalaban, Z Lingjiong arXiv preprint arXiv:1809.04618, 2018	100*	2018
Convergence rate of incremental gradient and incremental Newton methods M Gurbuzbalaban, A Ozdaglar, PA Parrilo SIAM Journal on Optimization 29 (4), 2542-2565, 2019	74	2019
Global convergence rate of proximal incremental aggregated gradient methods ND Vanli, M Gurbuzbalaban, A Ozdaglar SIAM Journal on Optimization 28 (2), 1282-1300, 2018	64	2018
Fast Approximation of the Norm via Optimization over Spectral Value Sets N Guglielmi, M Gürbüzbalaban, ML Overton SIAM Journal on Matrix Analysis and Applications 34 (2), 709-737, 2013	64	2013
Robust accelerated gradient methods for smooth strongly convex functions NS Aybat, A Fallah, M Gurbuzbalaban, A Ozdaglar SIAM Journal on Optimization 30 (1), 717-751, 2020	63	2020
A universally optimal multistage accelerated stochastic gradient method NS Aybat, A Fallah, M Gurbuzbalaban, A Ozdaglar Advances in neural information processing systems 32, 2019	63	2019
First exit time analysis of stochastic gradient descent under heavy-tailed gradient noise TH Nguyen, U Simsekli, M Gurbuzbalaban, G Richard Advances in neural information processing systems 32, 2019	58	2019
Fractional underdamped langevin dynamics: Retargeting sgd with momentum under heavy-tailed gradient noise U Simsekli, L Zhu, YW Teh, M Gurbuzbalaban International conference on machine learning, 8970-8980, 2020	56	2020
A globally convergent incremental Newton method M Gürbüzbalaban, A Ozdaglar, P Parrilo Mathematical Programming 151 (1), 283-313, 2015	54	2015
Accelerated linear convergence of stochastic momentum methods in wasserstein distances B Can, M Gurbuzbalaban, L Zhu International Conference on Machine Learning, 891-901, 2019	50	2019
Convergence rates of stochastic gradient descent under infinite noise variance H Wang, M Gurbuzbalaban, L Zhu, U Simsekli, MA Erdogdu Advances in Neural Information Processing Systems 34, 18866-18877, 2021	47	2021
Surpassing gradient descent provably: A cyclic incremental method with linear convergence rate A Mokhtari, M Gurbuzbalaban, A Ribeiro SIAM Journal on Optimization 28 (2), 1420-1447, 2018	46	2018
When cyclic coordinate descent outperforms randomized coordinate descent M Gurbuzbalaban, A Ozdaglar, PA Parrilo, N Vanli Advances in Neural Information Processing Systems 30, 2017	45	2017
On Nesterov’s nonsmooth Chebyshev–Rosenbrock functions M Gürbüzbalaban, ML Overton Nonlinear Analysis: Theory, Methods & Applications 75 (3), 1282-1289, 2012	37	2012
A stochastic subgradient method for distributionally robust non-convex and non-smooth learning M Gürbüzbalaban, A Ruszczyński, L Zhu Journal of Optimization Theory and Applications 194 (3), 1014-1041, 2022	36*	2022
Robust distributed accelerated stochastic gradient methods for multi-agent networks A Fallah, M Gürbüzbalaban, A Ozdaglar, U Şimşekli, L Zhu Journal of machine learning research 23 (220), 1-96, 2022	33	2022

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