Predicting the probability that a user will click on a specific advertisement has been a
prevalent issue in online advertising, attracting much research attention in the past decades …

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 …

There is more to images than their objective physical content: for example, advertisements
are created to persuade a viewer to take a certain action. We propose the novel problem of …

Click through rate (CTR) prediction of image ads is the core task of online display
advertising systems, and logistic regression (LR) has been frequently applied as the …

Computational Advertising, popularly known as online advertising or Web advertising, refers
to finding the most relevant ads matching a particular context on the Web. The context …

Real-time bidding (RTB) is an emerging and promising business model for online
computational advertising in the age of big data. Based on analysis of massive amounts of …

Today, billions of display ad impressions are purchased on a daily basis through a public
auction hosted by real time bidding (RTB) exchanges. A decision has to be made for …

Visual media have important persuasive power, but prior computer vision approaches have
predominantly ignored the persuasive aspects of images. In this work, we propose a suite of …

In online display advertising, state-of-the-art Click Through Rate (CTR) prediction algorithms
rely heavily on historical information, and they work poorly on growing number of new ads …

Contextual advertising is a textual advertising displayed within the content of a generic web
page. Predicting the probability that users will click on ads plays a crucial role in contextual …