Monte Carlo methods for preference learning

P. Viappiani

Research output: Contribution to book/anthology/report/conference proceedingBook chapterResearchpeer-review

3 Citations (Scopus)

Abstract

Utility elicitation is an important component of many applications, such as decision support systems and recommender systems. Such systems query the users about their preferences and give recommendations based on the system's belief about the utility function. Critical to these applications is the acquisition of prior distribution about the utility parameters and the possibility of real time Bayesian inference. In this paper we consider Monte Carlo methods for these problems.
Original languageEnglish
Title of host publicationLearning and Intelligent Optimization : 6th International Conference, LION 6, Paris, France, January 16-20, 2012, Revised Selected Papers
EditorsYoussef Hamadi, Marc Schoenauer
Number of pages6
PublisherSpringer Publishing Company
Publication date1 Jan 2012
Pages503-508
ISBN (Print)978-3-642-34412-1
ISBN (Electronic)978-3-642-34413-8
DOIs
Publication statusPublished - 1 Jan 2012
Event6th International Conference, LION 6 - Paris, France
Duration: 16 Jan 201220 Jan 2012

Conference

Conference6th International Conference, LION 6
Country/TerritoryFrance
CityParis
Period16/01/201220/01/2012
SeriesLecture Notes in Computer Science
Volume7219
ISSN0302-9743

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