Tag Archives: Zoutendijk-Wolfe Convergence Theorem

LM101-068: How to Design Automatic Learning Rate Selection for Gradient Descent Type Machine Learning Algorithms

LM101-068: How to Design Automatic Learning Rate Selection for Gradient Descent Type Machine Learning Algorithms Episode Summary: This 68th episode of Learning Machines 101 discusses a broad class of unsupervised, supervised, and reinforcement machine learning algorithms which iteratively update their parameter vector by adding a perturbation based upon all of the training data. This process is repeated, making… Read More »