TY - JOUR
T1 - Trends in Machine Learning for Signal Processing
AU - Adali, Tulay
AU - Miller, David J.
AU - Diamantaras, Konstantinos I.
AU - Larsen, Jan
PY - 2011
Y1 - 2011
N2 - 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.
AB - 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.
U2 - 10.1109/MSP.2011.942319
DO - 10.1109/MSP.2011.942319
M3 - Journal article
SN - 1053-5888
VL - 28
SP - 193
EP - 196
JO - I E E E - Signal Processing Magazine
JF - I E E E - Signal Processing Magazine
IS - 6
ER -