no code implementations • 14 Oct 2023 • Nicolo Cesa-Bianchi, Roberto Colomboni, Maximilian Kasy
This implies that (i) welfare maximization is harder than the multi-armed bandit problem (with a rate of $T^{1/2}$ for finite policy sets), and (ii) our algorithm achieves the optimal rate.
no code implementations • 3 Jul 2023 • Dirk van der Hoeven, Ciara Pike-Burke, Hao Qiu, Nicolo Cesa-Bianchi
Here, before making their prediction, each expert must be paid.
no code implementations • NeurIPS 2016 • Haipeng Luo, Alekh Agarwal, Nicolo Cesa-Bianchi, John Langford
We propose Sketched Online Newton (SON), an online second order learning algorithm that enjoys substantially improved regret guarantees for ill-conditioned data.
no code implementations • NeurIPS 2013 • Nicolo Cesa-Bianchi, Ofer Dekel, Ohad Shamir
In particular, we show that with switching costs, the attainable rate with bandit feedback is $\widetilde{\Theta}(T^{2/3})$.
