Matching is a classic problem with a rich history and a significant impact, both on the theory
of algorithms and in practice. Recently there has been a surge of interest in the online …

The most significant progress in recent years in online display advertising is what is known
as the Real-Time Bidding (RTB) mechanism to buy and sell ads. RTB essentially facilitates …

In this paper we study bid optimisation for real-time bidding (RTB) based display advertising.
RTB allows advertisers to bid on a display ad impression in real time when it is being …

The real-time bidding (RTB), aka programmatic buying, has recently become the fastest
growing area in online advertising. Instead of bulking buying and inventory-centric buying …

We study the multi-armed bandit problem with multiple plays and a budget constraint for
both the stochastic and the adversarial setting. At each round, exactly K out of N possible …

We study the multi-armed bandit problems with budget constraint and variable costs (MAB-
BV). In this setting, pulling an arm will receive a random reward together with a random cost …

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 …

We present algorithms for a class of resource allocation problems both in the online setting
with stochastic input and in the offline setting. This class of problems contains many …

Being an emerging paradigm for display advertising, Real-Time Bidding (RTB) drives the
focus of the bidding strategy from context to users' interest by computing a bid for each …

A large fraction of online advertisement is sold via repeated second price auctions. In these
auctions, the reserve price is the main tool for the auctioneer to boost revenues. In this work …