A Drutsa - International Conference on Machine Learning, 2020 - proceedings.mlr.press
We study learning algorithms that optimize revenue in repeated contextual posted-price auctions where a seller interacts with a single strategic buyer that seeks to maximize his …
A Drutsa - Proceedings of the 26th International Conference on …, 2017 - dl.acm.org
We study revenue optimization learning algorithms for repeated posted-price auctions where a seller interacts with a (truthful or strategic) buyer that holds a fixed valuation. We …
G Jauvion, N Grislain, P Dkengne Sielenou… - Proceedings of the 24th …, 2018 - dl.acm.org
Over the last decade, digital media (web or app publishers) generalized the use of real time ad auctions to sell their ad spaces. Multiple auction platforms, also called Supply-Side …
A Drutsa - International Conference on Machine Learning, 2018 - proceedings.mlr.press
We study revenue optimization learning algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation for a …
A Vanunts, A Drutsa - Advances in Neural Information …, 2019 - proceedings.neurips.cc
We study revenue optimization pricing algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation. When the …
Efficient learning in multi-armed bandit mechanisms such as pay-per-click (PPC) auctions typically involves three challenges: 1) inducing truthful bidding behavior (incentives), 2) …
A Drutsa - International Conference on Machine Learning, 2020 - proceedings.mlr.press
We study revenue optimization learning algorithms for repeated second-price auctions with reserve where a seller interacts with multiple strategic bidders each of which holds a fixed …
M Bichler, A Gupta, L Mathews… - arXiv preprint arXiv …, 2023 - arxiv.org
The transition of display ad exchanges from second-price to first-price auctions has raised questions about its impact on revenue. Evaluating this shift empirically proves challenging …
A Drutsa - arXiv preprint arXiv:1707.05101, 2017 - arxiv.org
We study revenue optimization learning algorithms for repeated posted-price auctions where a seller interacts with a single strategic buyer that holds a fixed private valuation for a …