Online Advertisement, Optimization and Stochastic Networks

Bid optimization in online advertisement auctions

We consider the problem of online keyword advertising auctions among multiple bidders with limited budgets, and propose a bidding heuristic to optimize the utility for bidders by equalizing the return-on-investment for each bidder across all keywords. We show that natural auction mechanisms combined with this heuristic can experience chaotic cycling (as is the case with many current advertiseme...

Online Stochastic and Robust Optimization

This paper considers online stochastic optimization problems where uncertainties are characterized by a distribution that can be sampled and where time constraints severely limit the number of offline optimizations which can be performed at decision time and/or in between decisions. It reviews our recent progress in this area, proposes some new algorithms, and reports some new experimental resu...

Online Stochastic Optimization Without Distributions

This paper considers online stochastic scheduling problems where time constraints severely limit the number of optimizations which can be performed at decision time and/or in between decisions. Prior research has demonstrated that, whenever a distribution of the inputs is available for sampling, online stochatic algorithms may produce significant improvements in solution quality over oblivious ...

Adaptive Targeting for Online Advertisement

Ranked Items Auctions and Online Advertisement

We study auctions for a set of ranked items where each buyer has a unit demand. This setting has promising applications in areas such as keyword auctions in the search engine advertising industry, the sale of quality ranked raw materials, etc. An auction mechanism suitable for this setting is the simultaneous pooled auction (SPA), where each bidder simultaneously submits a single bid and is all...