activity
20172020
most citedOffline A/B testing for Recommender Systems

137 citations · 150 across the 4 of their papers we have counts for

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Showing cs.GTShow all

5 papers · 1 filter

cs.GT2020

Learning in repeated auctions

Thomas Nedelec, Clément Calauzènes, Noureddine El Karoui +1

Online auctions are one of the most fundamental facets of the modern economy and power an industry generating hundreds of billions of dollars a year in revenue. Auction theory has…

cs.GT2019

Adversarial learning for revenue-maximizing auctions

Thomas Nedelec, Jules Baudet, Vianney Perchet +1

We introduce a new numerical framework to learn optimal bidding strategies in repeated auctions when the seller uses past bids to optimize her mechanism. Crucially, we do not assum…

cs.GT20191 cited

Robust Stackelberg buyers in repeated auctions

Clément Calauzènes, Thomas Nedelec, Vianney Perchet +1

We consider the practical and classical setting where the seller is using an exploration stage to learn the value distributions of the bidders before running a revenue-maximizing a…

cs.GT20196 cited

Learning to bid in revenue-maximizing auctions

Thomas Nedelec, Noureddine El Karoui, Vianney Perchet

We consider the problem of the optimization of bidding strategies in prior-dependent revenue-maximizing auctions, when the seller fixes the reserve prices based on the bid distribu…

cs.GT2018

Explicit shading strategies for repeated truthful auctions

Marc Abeille, Clément Calauzènes, Noureddine El Karoui +2

With the increasing use of auctions in online advertising, there has been a large effort to study seller revenue maximization, following Myerson's seminal work, both theoretically…