( en | de | ru )

 

Disambiguation of "Erdogdu, Murat A."

Author of the publication

copydeleteadd this publication to your clipboard
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD.

, , , , and . CoRR, (2022)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Madi Muratbekov

Amir Muratagic

Irina Muratalijewa

Ilona Muráti

Bettina Muratović

 

Other publications of authors with the same name

Neural Networks Efficiently Learn Low-Dimensional Representations with SGD., , , , and . CoRR, (2022)Generalization of Two-layer Neural Networks: An Asymptotic Viewpoint., , , , and . ICLR, OpenReview.net, (2020)Convergence and Optimality of Policy Gradient Methods in Weakly Smooth Settings., , and . AAAI, page 9066-9073. AAAI Press, (2022)Estimating LASSO Risk and Noise Level., , and . NIPS, page 944-952. (2013)An Analysis of Constant Step Size SGD in the Non-convex Regime: Asymptotic Normality and Bias., , , and . NeurIPS, page 4234-4248. (2021)On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method., , and . NeurIPS, (2020)Mirror Descent Strikes Again: Optimal Stochastic Convex Optimization under Infinite Noise Variance., , , , and . COLT, volume 178 of Proceedings of Machine Learning Research, page 65-102. PMLR, (2022)Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo., , , , and . COLT, volume 178 of Proceedings of Machine Learning Research, page 2896-2923. PMLR, (2022)Generalization Bounds for Stochastic Gradient Descent via Localized ε-Covers., , and . CoRR, (2022)Flexible results for quadratic forms with applications to variance components estimation, and . (2015)cite arxiv:1509.04388.