  This paper presents AdaptEx, a self-service contextual bandit platform widely
used at Expedia Group, that leverages multi-armed bandit algorithms to
personalize user experiences at scale. AdaptEx considers the unique context of
each visitor to select the optimal variants and learns quickly from every
interaction they make. It offers a powerful solution to improve user
experiences while minimizing the costs and time associated with traditional
testing methods. The platform unlocks the ability to iterate towards optimal
product solutions quickly, even in ever-changing content and continuous "cold
start" situations gracefully.

Information Retrieval;Artificial Intelligence;Machine Learning