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stochastic gradient descent

1088 papers

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Also known as

SGD ASGD SAGA SGM SGDA PSGD SKGD

Co-occurring keywords

non-convex optimization (546) distributed learning (563) neural network optimization (1293) convergence rate (606) convex optimization (1320) neural network (6616) variance reduction (520) stochastic optimization (1060) convergence analysis (394) differential privacy (1010)

Papers

Conditionally Gaussian PAC-Bayes AISTATS 2022
On the Theoretical Properties of Noise Correlation in Stochastic Optimization NIPS 2022
Neural Network Weights Do Not Converge to Stationary Points: An Invariant Measure Perspective ICML 2022
Efficiency Ordering of Stochastic Gradient Descent NIPS 2022
Benign Underfitting of Stochastic Gradient Descent NIPS 2022
Privacy of Noisy Stochastic Gradient Descent: More Iterations without More Privacy Loss NIPS 2022
The dynamics of representation learning in shallow, non-linear autoencoders ICML 2022
Generalization Bounds for Gradient Methods via Discrete and Continuous Prior NIPS 2022
Constrained Langevin Algorithms with L-mixing External Random Variables NIPS 2022
Detached Error Feedback for Distributed SGD with Random Sparsification ICML 2022
Heavy-tailed Streaming Statistical Estimation AISTATS 2022
Last Iterate Risk Bounds of SGD with Decaying Stepsize for Overparameterized Linear Regression ICML 2022
Three-stage Evolution and Fast Equilibrium for SGD with Non-degerate Critical Points ICML 2022
Towards Noise-adaptive, Problem-adaptive (Accelerated) Stochastic Gradient Descent ICML 2022
Convergence Rates of Non-Convex Stochastic Gradient Descent Under a Generic Lojasiewicz Condition and Local Smoothness ICML 2022
Towards understanding how momentum improves generalization in deep learning ICML 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks ICML 2022
Power-Law Escape Rate of SGD ICML 2022
Making SGD Parameter-Free COLT 2022
SGD with Coordinate Sampling: Theory and Practice JMLR 2022
Distributed Stochastic Gradient Descent: Nonconvexity, Nonsmoothness, and Convergence to Local Minima JMLR 2022
Stability vs Implicit Bias of Gradient Methods on Separable Data and Beyond COLT 2022
Fast Mixing of Stochastic Gradient Descent with Normalization and Weight Decay NIPS 2022
A Momentumized, Adaptive, Dual Averaged Gradient Method JMLR 2022
Mean-field Analysis of Piecewise Linear Solutions for Wide ReLU Networks JMLR 2022