Optimization and Machine Learning
Lubos Brieda, Joseph Wang, Robert K. Martin · 2024
This chapter covers two separate, but related topics. We first begin by introducing several numerical approaches for finding optimal input parameters that reduce the difference between the predicted and the expected (true) value. We next provide a very elementary introduction to machine learning, which involves optimization of the coefficient space based on a large set of training data. We develop a simple neural network for classifying real values.