Unbiased Learning to Rank - Lessons from Baidu's Large-Scale Search Dataset

Explore a 15-minute conference talk from ACM that delves into unbiased learning-to-rank systems through the lens of Baidu's extensive search dataset. Learn about fairness in ranking algorithms as researchers Philipp Hager, Romain Deffayet, Jean-Michel Renders, Onno Zoeter, and Maarten de Rijke present their findings on how theoretical approaches to unbiased learning translate to real-world applications in search engine ranking systems. Gain insights into the practical challenges and lessons learned from implementing fairness principles in large-scale search environments.