Trends in Machine Learning for Signal Processing

Tulay Adali, David J. Miller, Konstantinos I. Diamantaras, Jan Larsen

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    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.
    Original languageEnglish
    JournalI E E E - Signal Processing Magazine
    Volume28
    Issue number6
    Pages (from-to)193-196
    ISSN1053-5888
    DOIs
    Publication statusPublished - 2011

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