Units:
4
Learning algorithms based on statistics. Possible topics include minimum-variance unbiased estimators, maximum likelihood estimation, likelihood ratio tests, resampling methods, linear logistic regression, feature selection, regularization, dimensionality reduction, manifold detection. An upper-division undergraduate course on probability and statistics such as Math 183 or 186, or any graduate course on statistics, pattern recognition, or machine learning is recommended
Prerequisites:
graduate standing