Journal article
Trends in Machine Learning for Signal Processing
University of Maryland, College Park1
Pennsylvania State University2
Alexander Technological Educational Institute of Thessaloniki3
Cognitive Systems, Department of Informatics and Mathematical Modeling, Technical University of Denmark4
Department of Informatics and Mathematical Modeling, Technical University of Denmark5
By putting the accent on learning from the data and the environment, the Machine Learning for SP (MLSP) Technical Committee (TC) provides the essential bridge between the machine learning and SP communities. While the emphasis in MLSP is on learning and data-driven approaches, SP defines the main applications of interest, and thus the constraints and requirements on solutions, which include computational efficiency, online adaptation, and learning with limited supervision/reference data.
Language: | English |
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Publisher: | IEEE |
Year: | 2011 |
Pages: | 193-196 |
ISSN: | 15580792 and 10535888 |
Types: | Journal article |
DOI: | 10.1109/MSP.2011.942319 |
ORCIDs: | Larsen, Jan |