|Title||Learning Paradigms in Dynamic Environments|
|Publication Type||Conference Paper|
|Year of Publication||2010|
|Authors||Barbara Hammer, Pascal Hitzler, Wolfgang Maass, Marc Toussaint|
|Conference Name||Dagstuhl Seminar Proceedings 10302|
|Conference Location||Dagstuhl, Germany|
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.
|Full Text|| |
Barbara Hammer, Pascal Hitzler, Wolfgang Maass and Marc Toussaint, '10302 Summary - Learning paradigms in dynamic environments,' In: B. Hammer, P. Hitzler, W. Maass, M. Toussaint, 10302 Abstracts Collection - Learning paradigms in dynamic environments, Dagstuhl Seminar Proceedings 10302, Dagstuhl, Germany, 2010. ISSN 1862-4405.