Document Type
Conference Proceeding
Publication Date
7-1-2010
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.
Repository Citation
Hammer, B.,
& Hitzler, P.
(2010). 10302 Summary - Learning Paradigms in Dynamic Environments. Dagstuhl Seminar Proceedings 10302.
https://corescholar.libraries.wright.edu/cse/86
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Comments
Summary of the proceedings at the Learning Paradigms in Dynamic Environments Seminar, Dagstuhl, Germany, July 25-20, 2010.