Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on
Least Squares

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Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares

2 June 2022

Mert Gurbuzbalaban

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Papers citing "Algorithmic Stability of Heavy-Tailed Stochastic Gradient Descent on Least Squares"

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Title
Time-independent Generalization Bounds for SGLD in Non-convex Settings Tyler Farghly Patrick Rebeschini 73 24 0 25 Nov 2021
Stability and Deviation Optimal Risk Bounds with Convergence Rate $O(1/n)$ Yegor Klochkov Nikita Zhivotovskiy 60 62 0 22 Mar 2021
Convergence Rates of Stochastic Gradient Descent under Infinite Noise Variance Hongjian Wang Mert Gurbuzbalaban Lingjiong Zhu Umut cSimcsekli Murat A. Erdogdu 66 42 0 20 Feb 2021
Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning Pan Zhou Jiashi Feng Chao Ma Caiming Xiong Guosheng Lin E. Weinan 82 234 0 12 Oct 2020
Hausdorff Dimension, Heavy Tails, and Generalization in Neural Networks Umut Simsekli Ozan Sener George Deligiannidis Murat A. Erdogdu 76 56 0 16 Jun 2020
On the Heavy-Tailed Theory of Stochastic Gradient Descent for Deep Neural Networks Umut Simsekli Mert Gurbuzbalaban T. H. Nguyen G. Richard Levent Sagun 75 59 0 29 Nov 2019
Mean estimation and regression under heavy-tailed distributions--a survey Gabor Lugosi S. Mendelson 98 244 0 10 Jun 2019
Estimation of the Parameters of Multivariate Stable Distributions Aastha M. Sathe Neelesh Shankar Upadhye 23 15 0 26 Feb 2019
Traditional and Heavy-Tailed Self Regularization in Neural Network Models Charles H. Martin Michael W. Mahoney 76 125 0 24 Jan 2019
Data-Dependent Stability of Stochastic Gradient Descent Ilja Kuzborskij Christoph H. Lampert MLT 99 166 0 05 Mar 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 73 521 0 13 Feb 2017
Algorithms for Learning Kernels Based on Centered Alignment Corinna Cortes M. Mohri Afshin Rostamizadeh 73 546 0 02 Mar 2012