Boosting Independent Component Analysis
- URL: http://arxiv.org/abs/2112.06920v1
- Date: Sun, 12 Dec 2021 14:53:42 GMT
- Title: Boosting Independent Component Analysis
- Authors: Yunpeng Li, ZhaoHui Ye
- Abstract summary: We present a novel boosting-based algorithm for independent component analysis.
Our algorithm fills the gap in the nonparametric independent component analysis by introducing boosting to maximum likelihood estimation.
- Score: 5.770800671793959
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Independent component analysis is intended to recover the unknown components
as independent as possible from their linear mixtures. This technique has been
widely used in many fields, such as data analysis, signal processing, and
machine learning. In this paper, we present a novel boosting-based algorithm
for independent component analysis. Our algorithm fills the gap in the
nonparametric independent component analysis by introducing boosting to maximum
likelihood estimation. A variety of experiments validate its performance
compared with many of the presently known algorithms.
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