The school will include lectures on predictive modelling methods for big and complex data. More specifically, the lectures will present methods handling the following complexity aspects: (a) structured data as input or output of the prediction process, (b) very large/massive datasets, with many examples and/or many input/output dimensions, where data may be streaming at high rates, (c) incompletely/partially labelled data, and (d) data placed in a spatio-temporal or network context. Each of these is a major challenge to current ML/DM approaches and is the central topic of active research in areas such as structured-output prediction, mining data streams, semi-supervised learning, and mining network data. The applicability and the potential of the presented methods will be demonstrated on several showcases from molecular biology, sensor networks, multimedia, and social networks.
The lectures will be given by world leading researchers and experts in machine learning and data mining, as well as experts from the application domains. The program will include talks on the following topics:
The MAESTRA Summer School is not a commercial event and payment of a registration fee is not required from the attendees. Instead, the major organization costs are covered by the FP7 EU project MAESTRA. The registration for the event covers admission to all sessions, school materials, coffee breaks, the school dinner, and the networking session at the St. Naum complex. The registration does not cover accommodation and meals (except the school dinner). The school venue offers lodging at very affordable rates (i.e., full-board service for 35 EUR, see the pricelist).
The venue provides limited seating, hence, the school will be open for 50 participants. The participants will be selected based on the “first-come, first-served” principle.
Please fill out the registration form provided here: