Topology and Data Reduction

This tutorial by Javier Perera-Lago explores the intersection of topology and data reduction techniques within green artificial intelligence. Learn about methods to decrease energy consumption during machine learning model training by selecting only the most representative elements from training datasets. Discover various data reduction approaches and understand how to evaluate reduction quality using epsilon representativeness, complete with practical examples. The 12-minute presentation provides a concise overview of this important field that helps make AI more environmentally sustainable.