Murat A. Erdogdu

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Andrea MontanariProfessor of Electrical Engineering and Statistics, Stanford UniversityVerified email at stanford.edu
Lee H. DickerRutgers University, Department of Statistics and BiostatisticsVerified email at stat.rutgers.edu
Denny WuUniversity of TorontoVerified email at cs.toronto.edu
Krishnakumar BalasubramanianUniversity of California, DavisVerified email at ucdavis.edu
Jure LeskovecProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Qingyuan ZhaoUniversity of CambridgeVerified email at statslab.cam.ac.uk
Anand RajaramanPartner, Rocketship.vcVerified email at cs.stanford.edu
Umut SimsekliINRIA - École Normale SupérieureVerified email at inria.fr
Mohsen BayatiAssociate Professor, Stanford UniversityVerified email at stanford.edu
Jimmy BaUniversity of TorontoVerified email at cs.toronto.edu
Lester MackeyMicrosoft ResearchVerified email at microsoft.com
George DeligiannidisAssociate Professor in Statistics, University of OxfordVerified email at stats.ox.ac.uk
Taiji SuzukiThe University of TokyoVerified email at mist.i.u-tokyo.ac.jp
Ozan SenerAppleVerified email at cs.stanford.edu
Nadia FawazApplied Research Scientist, PinterestVerified email at pinterest.com
Matthew Shunshi ZhangUniversity of TorontoVerified email at mail.utoronto.ca
Ohad ShamirWeizmann Institute of ScienceVerified email at weizmann.ac.il
Hakan InanStanford UniversityVerified email at stanford.edu
Stanislav VolgushevUniversity of TorontoVerified email at utstat.toronto.edu
Lu YuUniversity of TorontoVerified email at mail.utoronto.ca

Murat A. Erdogdu

Stanford University

Verified email at stanford.edu - Homepage

Optimization Statistics Machine Learning


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Seismic: A self-exciting point process model for predicting tweet popularity Q Zhao, MA Erdogdu, HY He, A Rajaraman, J Leskovec Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015	583	2015
Convergence rates of sub-sampled Newton methods MA Erdogdu, A Montanari Advances in Neural Information Processing Systems, 1090-1098, 2015	198*	2015
Global non-convex optimization with discretized diffusions MA Erdogdu, L Mackey, O Shamir Advances in Neural Information Processing Systems 31, 2018	70	2018
Estimating lasso risk and noise level M Bayati, MA Erdogdu, A Montanari Advances in Neural Information Processing Systems 26, 2013	52	2013
Generalization of two-layer neural networks: An asymptotic viewpoint J Ba, M Erdogdu, T Suzuki, D Wu, T Zhang International conference on learning representations, 2019	44	2019
Stochastic runge-kutta accelerates langevin monte carlo and beyond X Li, Y Wu, L Mackey, MA Erdogdu Advances in neural information processing systems 32, 2019	37	2019
Flexible results for quadratic forms with applications to variance components estimation LH Dicker, MA Erdogdu The Annals of Statistics 45 (1), 386-414, 2017	30	2017
Maximum likelihood for variance estimation in high-dimensional linear models LH Dicker, MA Erdogdu Artificial Intelligence and Statistics, 159-167, 2016	24	2016
Accelerating SVRG via second-order information R Kolte, MA Erdogdu, A Ozgür Neural Information Processing Systems Workshop on Optimization for Machine …, 2015	23	2015
Hausdorff dimension, heavy tails, and generalization in neural networks U Simsekli, O Sener, G Deligiannidis, MA Erdogdu NeurIPS, 2020	22*	2020
On the convergence of langevin monte carlo: The interplay between tail growth and smoothness MA Erdogdu, R Hosseinzadeh arXiv preprint arXiv:2005.13097, 2020	21	2020
Robust estimation of neural signals in calcium imaging H Inan, MA Erdogdu, M Schnitzer Advances in neural information processing systems 30, 2017	21	2017
Inference in graphical models via semidefinite programming hierarchies MA Erdogdu, Y Deshpande, A Montanari Advances in Neural Information Processing Systems 30, 2017	21	2017
Privacy-utility trade-off under continual observation MA Erdogdu, N Fawaz 2015 IEEE International Symposium on Information Theory (ISIT), 1801-1805, 2015	20	2015
Convergence rate of block-coordinate maximization Burer–Monteiro method for solving large SDPs MA Erdogdu, A Ozdaglar, PA Parrilo, ND Vanli Mathematical Programming, 1-39, 2021	19	2021
Privacy-utility trade-off for time-series with application to smart-meter data MA Erdogdu, N Fawaz, A Montanari Workshops at the Twenty-Ninth AAAI Conference on Artificial Intelligence, 2015	18	2015
Normal approximation for stochastic gradient descent via non-asymptotic rates of martingale CLT A Anastasiou, K Balasubramanian, MA Erdogdu Conference on Learning Theory, 115-137, 2019	17	2019
Scaled least squares estimator for glms in large-scale problems MA Erdogdu, LH Dicker, M Bayati Advances in Neural Information Processing Systems 29, 2016	16	2016
Newton-Stein method: A second order method for GLMs via Stein's lemma MA Erdogdu Advances in Neural Information Processing Systems 28, 2015	14	2015
An analysis of constant step size sgd in the non-convex regime: Asymptotic normality and bias L Yu, K Balasubramanian, S Volgushev, MA Erdogdu Advances in Neural Information Processing Systems 34, 2021	13	2021

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