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math.OC2024
Anisotropic Gaussian Smoothing for Gradient-based Optimization
Andrew Starnes, Guannan Zhang, Viktor Reshniak +1
This article introduces a novel family of optimization algorithms - Anisotropic Gaussian Smoothing Gradient Descent (AGS-GD), AGS-Stochastic Gradient Descent (AGS-SGD), and AGS-Ada…
math.OC2023
Improved Performance of Stochastic Gradients with Gaussian Smoothing
Andrew Starnes, Clayton Webster
This paper formalizes and analyzes Gaussian smoothing applied to two prominent optimization methods: Stochastic Gradient Descent (GSmoothSGD) and Adam (GSmoothAdam) in deep learnin…
math.OC2023
Gaussian smoothing gradient descent for minimizing functions (GSmoothGD)
Andrew Starnes, Anton Dereventsov, Clayton Webster
This work analyzes the convergence of a class of smoothing-based gradient descent methods when applied to optimization problems. In particular, Gaussian smoothing is employed to de…