Co-occurring keywords · papers mentioning both
Papers
Iterate Averaging in the Quest for Best Test Error
JMLR 2024
The Road Less Scheduled
NeurIPS 2024
Benign Overfitting of Constant-Stepsize SGD for Linear Regression
JMLR 2023
Stochastic Optimization under Distributional Drift
JMLR 2023
Benign Overfitting of Constant-Stepsize SGD for Linear Regression
COLT 2021
Convergence rates and approximation results for SGD and its continuous-time counterpart
COLT 2021
Increasing Iterate Averaging for Solving Saddle-Point Problems
AAAI 2021
Stochastic optimization under time drift: iterate averaging, step-decay schedules, and high probability guarantees
NeurIPS 2021
Obtaining Adjustable Regularization for Free via Iterate Averaging
ICML 2020
Open Problem: Do Good Algorithms Necessarily Query Bad Points?
COLT 2019
Stochastic Approximation of Smooth and Strongly Convex Functions: Beyond the $O(1/T)$ Convergence Rate
COLT 2019
Averaging Stochastic Gradient Descent on Riemannian Manifolds
COLT 2018
Iterate Averaging as Regularization for Stochastic Gradient Descent
COLT 2018
Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go?
AISTATS 2018