Distribution Estimation

This lecture covers the topic of distribution estimation, focusing on methods to estimate underlying distributions from samples. It discusses fitness functions, loss functions, and the importance of choosing the right estimator for different scenarios. The instructor explains the concept of empirical estimation and the criteria for selecting the most suitable estimator. Various techniques such as min-max criteria and upper/lower bounds are explored, along with their implications in real-world applications. The lecture also delves into the challenges of estimating distributions accurately and the significance of making informed choices based on the data at hand.