Lecture

Statistical Learning Models: Risk and Empirical Risk Minimization

Description

This lecture introduces the concept of statistical learning models, which consist of observations, a class of functions, and a loss function. It explains the population risk and the goal of finding the function that minimizes it. The lecture then covers empirical risk minimization as an approach to approximate the optimal function by minimizing the empirical average of the loss. It delves into the strong law of large numbers and provides examples of empirical risk minimization in both parametric and non-parametric settings. The lecture concludes with discussions on estimators, loss functions, and the performance evaluation of maximum-likelihood estimators in various models.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.