2014 Press Releases
UCC hosts AI conference
The 11th International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming is being held in Cork this week.
The conference includes workshops, a Master Class on Data Mining, Machine Learning and Constraint Programming with the Main Conference taking place on May 21-23, 2014. Barry O’Sullivan and Helmut Simonis, from the Insight Centre for Data Analytics at UCC are co-chairs of the conference while Helmut Simonis is also the program chair of the event.
After a successful series of five CPAIOR international workshops in Ferrara (Italy), Paderborn (Germany), Ashford (UK), Le Croisic (France), and Montreal (Canada), in 2004 CPAIOR evolved into an international conference. More than 100 participants attended the first meeting held in Nice (France). In the subsequent years, CPAIOR was held in Prague (Czech Republic), Cork (Ireland), Brussels (Belgium), Paris (France), Pittsburgh (USA), Bologna (Italy), Berlin (Germany), Nantes (France), and Yorktown Heights (USA). In 2014 CPAIOR has returned to Ireland.
The aim of the CPAIOR conference series is to bring together researchers from constraint programming (CP), artificial intelligence (AI), and operations research (OR) to present new techniques or applications in the intersection of these fields, as well as to provide an opportunity for researchers in one area to learn about techniques in the others. A key objective of the conference is to demonstrate how the integration of techniques from different fields can lead to highly novel and effective new methods for large and complex problems. Therefore, papers that actively combine, integrate, or contrast approaches from more than one of the areas were especially welcome. Application papers showcasing CP/AI/OR techniques on innovative and challenging applications or experience reports on such applications were also strongly encouraged.
In all, 70 long and short papers were submitted to the conference. Out of these, the international Program Committee selected 33 papers for inclusion in the proceedings, published by Springer, and for presentation at the conference. In addition, there will be three invited talks by Chris Beck, University of Toronto, Canada; Francois Pachet, Sony CSL, Paris, France; Mehmet Dincbas, COSYTEC SA, Orsay, France.
The technical program of the conference were preceded by a day of workshops selected by Lars Kotthoff (Insight, UCC).
Siegfried Nijssen (KU Leuven) and Lars Kotthoff (Insight UCC) organized a master-class on the topic of Optimization and Machine Learning, providing an overview of this interesting area for PhD students, academics and practitioners. The masterclass will be presented by Andrea Passerini, Univerity of Trento, Italy; Ian Davidson, University of California at Davis, USA; Frank Hutter, Albert-Ludwigs-Universitaet, Freiburg, Germany; Georgiana Ifrim, Insight Centre for Data Analytics, University College Dublin, Ireland and Helmut Simonis, Insight Centre for Data Analytics, University College Cork, Ireland.
The conference programme may be viewed at http://4c.ucc.ie/cpaior2014/
About the Insight Centre for Data Analytics
The Insight Centre for Data Analytics is a joint initiative between researchers at University College Dublin, NUI Galway, University College Cork, and Dublin City University, as well as other partner institutions. It will bring together a critical mass of more than 200 researchers from Ireland's leading ICT centres to develop a new generation of data analytics technologies in a number of key application areas.
The €88m centre is funded by Science Foundation Ireland and a wide range of industry partners. Insight’s research focus encompasses a broad range of data analytic technologies and challenges, from machine learning, decision analytics and social network analysis to linked data, recommender systems and the sensor web. And together with more than 30 partner companies Insight researchers and PhD students are solving critical challenges in the areas of Connected Health and the Discovery Economy.