This paper summarizes the display advertising literature, organizing the content by the
agents in the display advertising ecosystem, and proposes new research directions. In doing …

Online advertising, as a vast market, has gained significant attention in various platforms
ranging from search engines, third-party websites, social media, and mobile apps. The …

Thompson sampling is one of oldest heuristic to address the exploration/exploitation trade-
off, but it is surprisingly not very popular in the literature. We present here some empirical …

User response prediction is a crucial component for personalized information retrieval and
filtering scenarios, such as recommender system and web search. The data in user …

Clickthrough and conversation rates estimation are two core predictions tasks in display
advertising. We present in this article a machine learning framework based on logistic …

In targeted display advertising, the goal is to identify the best opportunities to display a
banner ad to an online user who is most likely to take a desired action such as purchasing a …

This paper presents the design of a fully deployed multistage transfer learning system for
targeted display advertising, highlighting the important role of problem formulation and the …

User response prediction, which models the user preference wrt the presented items, plays
a key role in online services. With two-decade rapid development, nowadays the cumulated …

In performance display advertising a key metric of a campaign effectiveness is its conversion
rate--the proportion of users who take a predefined action on the advertiser website, such as …

User interest and behavior modeling is a critical step in online digital advertising. On the one
hand, user interests directly impact their response and actions to the displayed …