Title | 10302 Summary – Learning paradigms in dynamic environments |
Publication Type | Conference Papers |
Year of Publication | 2010 |
Authors | Hammer, B, Hitzler, P, Maass, W, Toussaint, M |
Editor | Hammer, B, Hitzler, P, Maass, W, Toussaint, M |
Conference Name | Learning paradigms in dynamic environments |
Number | 10302 |
Publisher | Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany |
Conference Location | Dagstuhl, Germany |
Abstract | The seminar centered around problems which arise in the context of machine learning in dynamic environments. Particular emphasis was put on a couple of specific questions in this context: how to represent and abstract knowledge appropriately to shape the problem of learning in a partially unknown and complex environment and how to combine statistical inference and abstract symbolic representations; how to infer from few data and how to deal with non i.i.d. data, model revision and life-long learning; how to come up with efficient strategies to control realistic environments for which exploration is costly, the dimensionality is high and data are sparse; how to deal with very large settings; and how to apply these models in challenging application areas such as robotics, computer vision, or the web. |
URL | http://drops.dagstuhl.de/opus/volltexte/2010/2802 |