Search Results - subject:"Bandit algorithm"

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Keyword-level Bayesian online bid optimization for sponsored search advertising

Majima, Kaito; Kawakami, Kosuke; Ishizuka, Kota; … - In: Operations research forum 5 (2024) 2, pp. 1-32

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015179784

Probability-based A/B testing with Adaptive Minimax Regret (AMR) criterion for long-term customer metrics

Abe, Makoto - 2024

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015055882

A PAC algorithm in relative precision for bandit problem with costly sampling

Billaud Friess, Marie; Macherey, Arthur; Nouy, Anthony; … - In: Mathematical methods of operations research : ZOR 96 (2022) 2, pp. 161-185

Persistent link: https://ebvufind01.dmz1.zbw.eu/10013454997

Efficient counterfactual learning from bandit feedback

Narita, Yusuke; Yasui, Shota; Yata, Kohei - 2018

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011948939

Convergence in models with bounded expected relative hazard rates

Oyarzun, Carlos; Ruf, Johannes - In: Journal of Economic Theory 154 (2014) C, pp. 229-244

We provide a general framework to study stochastic sequences related to individual learning in economics, learning automata in computer sciences, social learning in marketing, and other applications. More precisely, we study the asymptotic properties of a class of stochastic sequences that take...

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011076665

Convergence in models with bounded expected relative hazard rates

Oyarzun, Carlos; Ruf, Johannes - In: Journal of economic theory 154 (2014), pp. 229-244

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010481363