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===========C A L L F O R P A P E R S============

DA2PL 2022: From Multiple Criteria Decision Aid to Preference Learning

Université de Technologie de Compiègne, France

November 17-18, 2022

https://da2pl.pre.utc.fr/

======== AIM

DA2PL 2022 (From Multiple Criteria Decision Aid to Preference Learning) aims to bring together researchers from decision analysis and machine learning. It provides a forum for discussing recent advances and identifying new research challenges in the intersection of both fields, thereby supporting a cross-fertilisation of these disciplines.

Following the five previous editions of this workshop, which took place in Mons in 2012, Paris in 2014, Paderborn in 2016, Poznan in 2018, and Trento (virtually) in 2020, DA2PL 2022 will be held at the Université de Technologie de Compiègne, France, the 17 and 18 november.

======================== DA2PL 2022 vs COVID-19

We expect DA2PL to be mainly a physical event. We will provide a virtual option for participants wishing to be there remotely, but will request at least one full registration per submitted paper.

======== TOPICS

DA2PL 2022 solicits contributions to the usage of theoretically supported preference models and formalisms in preference learning as well as communications devoted to innovative preference learning methods in decision analysis and multicriteria decision aiding. Specific topics of interest include, but are not limited to:

• quantitative and qualitative approaches to modelling preferences, user feedback and training data;

• preference representation in terms of graphical models, logicalformalisms, and soft constraints;

• dealing with incomplete and uncertain preferences;

• preference aggregation and disaggregation;

• learning utility functions using regression-based approaches;

• preference elicitation and active learning;

• preference learning in combinatorial domains;

• learning relational preference models and related regression problems;

• classification problems, such as ordinal and hierarchical classification;

• inducing monotonic decision models for preference representation;

• comparison of different preference learning paradigms (e.g., monolithic vs. decomposition);

• ranking problems, such as object ranking, instance ranking and label ranking;

• complementarity of preference models and hybrid methods;

• explanation of recommendations;

• applications of preference learning, such as web search, information retrieval, electronic commerce, games, personalization, recommender systems, …

============= Submissions

Submissions must be written in English and formatted according to the electronic template that is available at

https://da2pl.pre.utc.fr/wp-content/uploads/sites/70/2022/03/DA2PL22_templat...

The page limit is 8 for full papers, although extended abstracts (maximum two pages) are welcome, too. As usual for DA2PL, submissions are NOT anonymous. According to the template, names of authors should be stated in the manuscript. All submissions will be reviewed by at least two referees.

Submissions must be submitted through EasyChair at

https://easychair.org/conferences/?conf=da2pl

Following a successful experience from the latest editions, DA2PL will provide a special opportunity for doctoral students to explore and develop their research interests. A special session at the conference will be devoted to PhD students, for presenting and discussing their ongoing research work. Therefore, we specifically encourage young researchers to submit their work (as full paper or extended abstract, depending on the maturity of the PhD project); the submission site will provide the option to mark a submission as a student paper.

================= Important dates

May 1st: submissions open September 1st: paper submission deadline September 30th: author notification November 3rd: Camera-ready version of papers November 17-18: Conference

=========================== Organization and contacts

General chairs

Khaled Belahcene, Université de Technologie de Compiègne (khaled.belahcene(a)hds.utc.fr) Sébastien Destercke, Université de Technologie de Compiègne (sebastien.destercke(a)utc.fr)