Ort: Paderborn

The DA2PL workshop has been launched with the goal of bringing together researchers from operations research and the decision sciences with scholars from machine learning. It aims at providing a forum for discussing recent advances and identifying new research challenges in the intersection of both fields, which is marked by the growing field of preference learning, thereby supporting a cross-fertilisation of these disciplines.

Following the two previous editions of this workshop, which took place in Mons in 2012 and Paris in 2014, DA2PL’2016 will be held at the University of Paderborn, Germany. Supported by the Association of European Operational Research Societies, it will this time be organized in the form of a EURO Mini Conference.

DA2PL’2016 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.

We solicit full research papers as well as extended abstracts reporting on more preliminary results. Submissions must be written in English and formatted according to the electronic template. The page limit is 6 for full papers and 2 for extended abstracts. Submissions must be submitted through EasyChair and will be reviewed by at least two referees. This year, 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 for PhD students to present and discuss 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 offer a possibility to mark a submission as a student paper.

Important dates:
Submission site opens: April 1, 2016
Paper submission: August 22, 2016
Author notification: September 30, 2016
Camera-ready version: October 21, 2016

Further Information: