MNL-Bandit : a dynamic learning approach to assortment selection
Year of publication: |
2019
|
---|---|
Authors: | Agrawal, Shipra ; Avadhanula, Vashist ; Goyal, Vineet ; Zeevi, Assaf |
Published in: |
Operations research. - Catonsville, MD : INFORMS, ISSN 0030-364X, ZDB-ID 123389-0. - Vol. 67.2019, 5, p. 1453-1485
|
Subject: | exploration-exploitation | assortment optimization | upper confidence bound | multinomial logit |
-
On upper bounds for assortment optimization under the mixture of multinomial logit models
Kunnumkal, Sumit, (2015)
-
Choosing an n-pack of substitutable products
Fox, Edward, (2018)
-
An exact method for (constrained) assortment optimization problems with product costs
Leitner, Markus, (2024)
- More ...
-
On the tightness of an LP relaxation for rational optimization and its applications
Avadhanula, Vashist, (2016)
-
A tractable online learning algorithm for the multinomial logit contextual bandit
Agrawal, Priyank, (2023)
-
Parimutuel betting on permutations
Agrawal, Shipra, (2008)
- More ...