3 papers
stat.ML2025
Stochastic Matching Bandits with Rare Optimization Updates
Jung-hun Kim, Min-hwan Oh
We introduce a bandit framework for stochastic matching under the multinomial logit (MNL) choice model. In our setting, agents on one side are assigned to arms on the other…
stat.ML2025
Dynamic Assortment Selection and Pricing with Censored Preference Feedback
Jung-hun Kim, Min-hwan Oh
In this study, we investigate the problem of dynamic multi-product selection and pricing by introducing a novel framework based on a \textit{censored multinomial logit} (C-MNL) cho…
stat.ML2024
Queueing Matching Bandits with Preference Feedback
Jung-hun Kim, Min-hwan Oh
In this study, we consider multi-class multi-server asymmetric queueing systems consisting of queues on one side and servers on the other side, where jobs randomly arrive i…