A dynamic pricing problem is difficult due to the highly dynamic environment and unknown
demand distributions. In this article, we propose a deep reinforcement learning (DRL) …

We study a variant of the display-ad allocation problem where an online publisher needs to
decide which subset of advertisement slots should be used in order to fulfill guaranteed …

Real-time bidding systems, which utilize auctions to allocate user impressions to competing
advertisers, continue to enjoy success in digital advertising. Assessing the effectiveness of …

Online advertising is one of the most important sources of income for many online
publishers. The process is as easy as placing slots in the website and selling those slots in …

This paper studies reserve prices computed to maximize the expected profit of the seller
based on historical observations of the top two bids from online auctions in an asymmetric …

Many real-world problems have multiple, conflicting objectives. Without knowing the utility
function of the decision maker, one must extensively learn all Pareto-efficient trade-offs to …

In this paper we consider an online publisher that sells advertisement space and propose a
method for learning optimal reserve prices in second-price auctions. We study a limited …

One of the main mechanisms that online publishers use in online advertising in order to sell
their advertisement space is the real-time bidding (RTB) mechanism. In RTB the publisher …

Real time bidding is one of the most popular ways of selling impressions in online
advertising, where online ad publishers allocate some blocks in their websites to sell in …

As an online advertising business emerges as an important tool for finding new customers
and ending up with a profit creation, the real time bidding (RTB) system has gained a …