A tractable online learning algorithm for the multinomial logit contextual bandit

DOI10.1016/j.ejor.2023.02.036arXiv2011.14033OpenAlexW3135859538MaRDI QIDQ6113379

Priyank Agrawal, Theja Tulabandhula, Vashist Avadhanula

Publication date: 11 July 2023

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2011.14033

zbMATH Keywords

sequential decision-makingrevenue managementmulti-armed banditOR in marketingmultinomial logit model

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Cites Work

• Unnamed Item
• Assortment optimization under the sequential multinomial logit model
• Self-concordant analysis for logistic regression
• An online algorithm for the risk-aware restless bandit
• An exact method for assortment optimization under the nested logit model
• Product assortment and space allocation strategies to attract loyal and non-loyal customers
• Design and pricing of extended warranty menus based on the multinomial logit choice model
• Filtered Poisson process bandit on a continuum
• Dynamic Assortment Optimization with a Multinomial Logit Choice Model and Capacity Constraint
• Linearly Parameterized Bandits
• Demand Estimation and Assortment Optimization Under Substitution: Methodology and Application
• MNL-Bandit: A Dynamic Learning Approach to Assortment Selection
• Finite-time analysis of the multiarmed bandit problem

This page was built for publication: A tractable online learning algorithm for the multinomial logit contextual bandit