Learning Paradigms in Dynamic Environments

TitleLearning Paradigms in Dynamic Environments
Publication TypeConference Paper
Year of Publication2010
AuthorsBarbara Hammer, Pascal Hitzler, Wolfgang Maass, Marc Toussaint
Conference NameDagstuhl Seminar Proceedings 10302
PublisherSchloss Dagstuhl
Conference LocationDagstuhl, 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.

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.
year: 2010
venue name: Dagstuhl Seminar Proceedings 10302
hasURL: http://knoesis.wright.edu/library/download/10302.pdf

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