On 5/1/14, Luc De Raedt <[email protected]> wrote: > *********************************************************************************** > Call for Participation > > Summer School: Constraint Programming Meets Data Mining > http://kdd.isti.cnr.it/ICONSummerSchool/ > supported by the EU FP 7 FET Open Project ICON > http://www.icon-fet.eu/ > *********************************************************************************** > > > In industry, society and science, advanced software is used for solving, > planning, scheduling and resource allocation problems, collectively known as > constraint satisfaction or optimization problems. At the same time, one > continuously gathers vast amounts of data about these problems. This summer > school starts from the observation that current software typically does not > exploit such data to update schedules, resources and plans and aims at > introducing a new approach in which gathered data is analysed systematically > in order to dynamically revise and adapt constraints and optimization > criteria. Ultimately, this could create a new ICT paradigm, called Inductive > Constraint Programming, that bridges the gap between the areas of data > mining and machine learning on the one hand, and constraint programming and > optimization on the other hand. If successful, this would change the face of > data mining as well as constraint programming technology. It would not only > allow one to use data mining techniques in constraint programming to improve > the formulation and solution of constraint satisfaction problems, but also > to employ declarative constraint programming principles in data mining and > machine learning. > > > One remarkable example is society, where human activities mediated by ICT > generates big data in the form > of digital traces that cannot only be used to evaluate the performance of > the underlying > constraint satisfaction and optimization models but also to automatically > revise and improve > the underlying models so that the solutions are automatically adapted to the > behavior > of the people. As one example, consider a public transportation schedule > that continuously > adapts itself to the real mobility patterns of people represented by the > digital traces of individual travels. > Thus the knowledge mined in (big) data can help to adapt schedules, > resources and plans to > the real dynamics in the real world. > > So far, constraint solving has evolved quite independently from machine > learning and > data mining. There has recently been a growing interest in the integration > of these two > fields, which can work in two ways: (a) constraint solvers can be included > in machine > learning and data mining algorithms; and (b) machine learning and data > mining can help > in addressing and formulating constraint problems. Promising initial results > have been achieved in both directions, > in the ICON project and beyond and further research is ongoing to establish > a full integration. > > The summer school "Constraint Programming meets Data Mining", organized by > the FP7-ICT > FET Open project ICON “Inductive Constraint Programming” > (http://www.icon-fet.eu) provides > an intensive training opportunity to learn the essentials of recent research > on constraint > solving, machine learning and data mining, and the key aspects related to > their integration. > > Students will follow lectures from top experts of the fields, and will > receive personalized > training on selected exercises in hands-on labs. > > - Christian Bessiere, CNRS, University of Montpellier - France > - Ian Davidson, University of California, Davis, US > - Luc De Raedt, KU Leuven - Belgium > - Tias Guns, KU Leuven - Belgium > - Lars Kotthoff, University College Cork - Ireland > - Yuri Malitsky, University College Cork - Ireland > - Mirco Nanni, ISTI-CNR, Pisa - Italy > - Siegfried Nijssen, KU Leuven and University of Leiden - Belgium / The > Netherlands > - Dino Pedreschi, University of Pisa - Italy > - Salvatore Ruggieri, University of Pisa - Italy > - Helmut Simonis, University College Cork - Ireland > > > > *** Important Dates *** > Deadline for application: May 20, 2014 > Notification: May 30, 2014 > Summer school starts: September 1st, 2014 > Summer school ends: September 5, 2014 > > *** Venue *** > The venue for this event is Sampieri, an old fishing village, perhaps the > most picturesque in the province of Ragusa, Sicily, Italy. This village is > characterized by stone houses and very small streets in old stones. > > The Summer school is held at the Marsa Siclà Residence in Sampieri, which is > composed by 82 apartments and by the Club House including bar, > restaurant/pizzeria, and other collective services. > Residence facilities include: swimming-pool, volley court and a tennis > court, soccer court, ping-pong table, etc. > > For more details see http://www.marsasicla.it/en/ > > > We are looking forward to your participation! > > *** School committees *** > > Steering Committee > > Christian Bessiere, CNRS, University of Montpellier - France > Remi Coletta, University of Montpellier - Frances > Luc De Raedt, KU Leuven - Belgium (Co-Program Chair) > Siegfried Nijssen, KU Leuven and University of Leiden - Belgium/The > Netherlands > Barry O'Sullivan, University College Cork - Ireland > Dino Pedreschi, University of Pisa - Italy (Co-Program Chair) > Helmut Simonis, University College Cork - Ireland > Franco Turini, University of Pisa - Italy > Salvatore Ruggieri, University of Pisa - Italy > > Organizing Committee > > Anna Monreale, University of Pisa - Italy > Valerio Grossi, University of Pisa - Italy > Mirco Nanni, ISTI-CNR, Pisa - Italy > Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm >
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