The Unreasonable Effectiveness of Stochastic Gradient Descent (in 3 minutes)

(3:34)

SGD Lecture 1

(1:7:32)

Rachel Ward (UT Austin) -- SGD with AdaGrad Adaptive Learning Rate

(43:53)

25. Stochastic Gradient Descent

(53:3)

Gradient Descent With Momentum (C2W2L06)

(9:21)

Stanford CS229: Machine Learning - Linear Regression and Gradient Descent | Lecture 2 (Autumn 2018)

(1:18:17)

Machine Learning 1 - Linear Classifiers, SGD | Stanford CS221: AI (Autumn 2019)

(1:20:34)

Lecture 4.3 Optimizers

(40:11)

Roadmap to learn and master Machine Learning

(59:30) 10

Lecture 7: Batch Size, SGD, Minibatch, second-order methods

(1:29:13)

Lecture 2.5 - Stochastic Gradient Descent

(8:18)

Risk Convergence and Algorithmic Regularization of Discrete-Stepsize (Stochastic) Gradient Descent

(15:55)

DeepNNs 2022: Lecture 4 Optimization and Stochastic Gradient Descent

(55:55)

22. Gradient Descent: Downhill to a Minimum

(52:44)

6A3 Stationary Behavior of Constant Stepsize SGD Type Algorithms: An Asymptotic Characterization

(17:38)

Stochastic Gradient Descent, Clearly Explained!!!

(10:53)

Optimization in Machine Learning: Lecture 6.2 (SGD for Deep Learning)

(1:22:55)

On the Foundations of Deep Learning: SGD, Overparametrization, and Generalization

(45:39)

Jason Lee (USC)--Towards a Foundation of Deep Learning: SGD, Overparametrization, and Generalization

(42:51)

Gradient Descent in 3 minutes

(3:6)