TY - JOUR
T1 - Majorization-Minimization Algorithms in Signal Processing, Communications, and Machine Learning
AU - Sun, Ying
AU - Babu, Prabhu
AU - Palomar, Daniel P.
N1 - Publisher Copyright:
© 1991-2012 IEEE.
PY - 2017/2/1
Y1 - 2017/2/1
N2 - This paper gives an overview of the majorization-minimization (MM) algorithmic framework, which can provide guidance in deriving problem-driven algorithms with low computational cost. A general introduction of MM is presented, including a description of the basic principle and its convergence results. The extensions, acceleration schemes, and connection to other algorithmic frameworks are also covered. To bridge the gap between theory and practice, upperbounds for a large number of basic functions, derived based on the Taylor expansion, convexity, and special inequalities, are provided as ingredients for constructing surrogate functions. With the pre-requisites established, the way of applying MM to solving specific problems is elaborated by a wide range of applications in signal processing, communications, and machine learning.
AB - This paper gives an overview of the majorization-minimization (MM) algorithmic framework, which can provide guidance in deriving problem-driven algorithms with low computational cost. A general introduction of MM is presented, including a description of the basic principle and its convergence results. The extensions, acceleration schemes, and connection to other algorithmic frameworks are also covered. To bridge the gap between theory and practice, upperbounds for a large number of basic functions, derived based on the Taylor expansion, convexity, and special inequalities, are provided as ingredients for constructing surrogate functions. With the pre-requisites established, the way of applying MM to solving specific problems is elaborated by a wide range of applications in signal processing, communications, and machine learning.
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U2 - 10.1109/TSP.2016.2601299
DO - 10.1109/TSP.2016.2601299
M3 - Article
AN - SCOPUS:85002739348
SN - 1053-587X
VL - 65
SP - 794
EP - 816
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 3
M1 - 7547360
ER -