Search Results for author:
Found 3 papers, 0 papers with code
Online Preselection with Context Information under the Plackett-Luce Model
We consider an extension of the contextual multi-armed bandit problem, in which, instead of selecting a single alternative (arm), a learner is supposed to make a preselection in the form of a subset of alternatives.
Preference-based Online Learning with Dueling Bandits: A Survey
The aim of this paper is to provide a survey of the state of the art in this field, referred to as preference-based multi-armed bandits or dueling bandits.
Ranking Distributions based on Noisy Sorting
We also introduce a generalization of the model, in which the constraints on pairwise preferences are relaxed, and for which maximum likelihood estimation can be carried out based on a variation of the generalized iterative scaling algorithm.
