Dear Colleagues,
We would like to invite you to join us for our second seminar in the RMP practice webinar series:
Speaker: Vahab Mirrokni, Google Research
Title: Recent Trends in Online Ad Markets: Robustness, Learning, and Automation
Time: 8-9 pm Eastern Time (5-6 pm Pacific Time) on Wednesday, February 10th, 2021 (including audience Q&A)
Moderator: Santiago Balseiro, Columbia University
Register here. You could leave your questions with our speaker now and any time before the live event. (If you are a member of the RMP section and would like to attend but can't make it to the virtual event, you still need to register to receive a recording when it becomes available.)
Abstract: We provide an overview of recent trends and future challenges in online ad markets with a focus on robustness, incentive-aware learning, and the auto-bidding world. In the first part, we discuss (adversarial) robustness in designing online algorithms, learning, and pricing schemes. In particular, we present online learning algorithms that work under stochastic models with adversarial corruptions and describe recently developed algorithmic techniques that achieve the best of many worlds in a variety of online stochastic and adversarial models. Along the same lines, we discuss the design of dynamic mechanisms for repeated auctions that are robust to the presence of noise or imprecise forecasts. Next, we touch upon robustness in pricing, and explore incentive-aware learning algorithms for pricing in both dynamic and static auctions. We complement these results by exploring data-driven techniques to measure the extent to which bidders have incentives to strategize their bids in ad auctions. Finally, we highlight the challenges that emerge as the majority of advertisers adopt automatic bidding algorithms to bid on their behalf and the market transitions to the so-called auto-bidding world.
Bio: Vahab Mirrokni is a distinguished scientist, heading the New York and Zurich algorithms research groups at Google Research. The group consists of three main sub-teams: market algorithms, large-scale graph mining, and large-scale optimization. He received his PhD from MIT in 2005 and his B.Sc. from Sharif University of Technology in 2001. He joined Google Research in 2008, after spending a couple of years at Microsoft Research, MIT and Amazon.com. He is the co-winner of paper awards at KDD'15, ACM EC'08, and SODA'05. His research areas include algorithms, distributed and stochastic optimization, and computational economics. Recently he has been working on various algorithmic problems in machine learning, online optimization and dynamic mechanism design, and distributed algorithms for large-scale graph mining.
Feel free to share this invitation with your network of colleagues and students. We look forward to seeing you at the webinar.
Best Regards,
The RMP section board
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Rene Caldentey
Eli B. and Harriet B. Williams Professor of Operations Management
The University of Chicago, Booth School of Business
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