How Machine Learning and Auction Theory Power Facebook Advertising

More than 1 million individuals use Facebook everyday, and over 2.5 million Pages on Facebook advertise their business, products, and services. To say the least, Facebook runs one of the world’s largest online advertising marketplaces where advertisers bid and pay for impressions, clicks, conversions, and other KPIs. Throughout everything, the rankings and pricing of ads depends on the predicted probability of clicks and conversions (via Simons Institute for the Theory of Computing). In the talk below, Eric Sodomka (Research Scientist at Facebook) gives a brief overview of the algorithmic problems underlying the Facebook ads auction. He also shares lessons the Facebook team learned from building the scalable machine learning platform that millions of advertisers impact everyday. Sign up here for our weekly digest of top articles, industry news,…


Link to Full Article: How Machine Learning and Auction Theory Power Facebook Advertising