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DTAI News ML news Summer School: Constraint Programming Meets Data Mining

Summer School: Constraint Programming Meets Data Mining

The DTAI research group co-organizes:

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