Techniques Toward Optimizing Viewability in RTB Ad Campaigns Using Reinforcement Learning

no code implementations • 21 May 2021 • Michael Tashman, John Hoffman, Jiayi Xie, Fengdan Ye, Atefeh Morsali, Lee Winikor, Rouzbeh Gerami

Reinforcement learning (RL) is an effective technique for training decision-making agents through interactions with their environment.

Bayesian Optimization Decision Making +3

Online and Scalable Model Selection with Multi-Armed Bandits

no code implementations • 25 Jan 2021 • Jiayi Xie, Michael Tashman, John Hoffman, Lee Winikor, Rouzbeh Gerami

Many online applications running on live traffic are powered by machine learning models, for which training, validation, and hyper-parameter tuning are conducted on historical data.

BIG-bench Machine Learning Model Selection +1

Dynamic Bidding Strategies with Multivariate Feedback Control for Multiple Goals in Display Advertising

no code implementations • 1 Jun 2020 • Michael Tashman, Jiayi Xie, John Hoffman, Lee Winikor, Rouzbeh Gerami

This method generates a control score for each KPI, based on both the output of a PID controller module and a metric that quantifies the importance of each KPI for internal business needs.