License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DagSemProc.10302.2
URN: urn:nbn:de:0030-drops-28027
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2010/2802/
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Hammer, Barbara ;
Hitzler, Pascal ;
Maass, Wolfgang ;
Toussaint, Marc
10302 Summary -- Learning paradigms in dynamic environments
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.
BibTeX - Entry
@InProceedings{hammer_et_al:DagSemProc.10302.2,
author = {Hammer, Barbara and Hitzler, Pascal and Maass, Wolfgang and Toussaint, Marc},
title = {{10302 Summary – Learning paradigms in dynamic environments}},
booktitle = {Learning paradigms in dynamic environments},
pages = {1--4},
series = {Dagstuhl Seminar Proceedings (DagSemProc)},
ISSN = {1862-4405},
year = {2010},
volume = {10302},
editor = {Barbara Hammer and Pascal Hitzler and Wolfgang Maass and Marc Toussaint},
publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
address = {Dagstuhl, Germany},
URL = {https://drops.dagstuhl.de/opus/volltexte/2010/2802},
URN = {urn:nbn:de:0030-drops-28027},
doi = {10.4230/DagSemProc.10302.2},
annote = {Keywords: Summary}
}
Keywords: |
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Summary |
Collection: |
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10302 - Learning paradigms in dynamic environments |
Issue Date: |
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2010 |
Date of publication: |
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05.11.2010 |