Efficient regret bounds for online bid optimisation in budget-limited sponsored search auctions

L Tran-Thanh, L Stavrogiannis, V Naroditskiy… - uai2014, 30th Conf. on …, 2014 - microsoft.com
We study the problem of an advertising agent who needs to intelligently distribute her
budget across a sequence of online keyword bidding auctions. We assume the closing price
of each auction is governed by the same unknown distribution, and study the problem of
making provably optimal bidding decisions. Learning the distribution is done under
censored observations, ie the closing price of an auction is revealed only if the bid we place
is above it. We consider three algorithms, namely ε− First, Greedy Product-Limit (GPL) and …

Efficient regret bounds for online bid optimisation in budget-limited sponsored search auctions: 30th Conference on Uncertainty in Artificial Intelligence, UAI 2014

L Tran-Thanh, L Stavrogiannis, V Naroditskiy, V Robu… - 2014 - research.tue.nl
We study the problem of an advertising agent who needs to intelligently distribute her
budget across a sequence of online keyword bidding auctions. We assume the closing price
of each auction is governed by the same unknown distribution, and study the problem of
making provably optimal bidding decisions. Learning the distribution is done under
censored observations, ie the closing price of an auction is revealed only if the bid we place
is above it. We consider three algorithms, namely ε-First, Greedy Product-Limit (GPL) and …
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