For the scalability of industrial online advertising systems, a two-stage auction architecture is
widely used to enable efficient ad allocation on a large set of corpus within a limited …

We develop a general framework for selecting a small pool of candidate solutions to
maximize the chances that one will be optimal for a combinatorial optimization problem …

A Multi-Agent Cooperative Learning (MACL) system is an artificial intelligence (AI) system
where multiple learning agents work together to complete a common task. Recent empirical …

Motivated by practical concerns in the online advertising industry, we study a bidder subset
selection problem in single-item auctions. In this problem, a large pool of candidate bidders …

We consider Bidder Selection Problem (BSP) in position auctions motivated by practical
concerns of online advertising platforms. In this problem, the platform sells ad slots via an …

We consider a combinatorial multi-armed bandit problem for maximum value reward
function under maximum value and index feedback. This is a new feedback structure that …

The design of internet advertisement systems is both an auction design problem and an
information retrieval (IR) problem. As an auction, the designer needs to take the participants …

Motivated by recent developments in designing algorithms based on individual item scores
for solving utility maximization problems, we study the framework of using test scores …

In the Bidder Selection Problem (BSP) there is a large pool of n potential advertisers
competing for ad slots on the user's web page. Due to strict computational restrictions, the …

We consider the problem of sketching a stochastic valuation function, defined as the
expectation of a valuation function of independent random item values. We show that for …