137 citations · 165 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
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…
Bridging the gap between regret minimization and best arm identification, with application to A/B tests
Rémy Degenne, Thomas Nedelec, Clément Calauzènes +1
State of the art online learning procedures focus either on selecting the best alternative ("best arm identification") or on minimizing the cost (the "regret"). We merge these two…
Thresholding at the monopoly price: an agnostic way to improve bidding strategies in revenue-maximizing auctions
Thomas Nedelec, Marc Abeille, Clément Calauzènes +3
We address the problem of improving bidders' strategies in prior-dependent revenue-maximizing auctions and introduce a simple and generic method to design novel bidding strategies…