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SigmaX
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During a discussion in our lab last month, a professor mentioned to me that the behavior of Self-Organizing Maps can be described in terms of repeated applications of the Moore-Penrose psuedoinverse, in a vaguely similar way to how the Preceptron algorithmsingle-layer neural networks with Hebbian learning can be described by Principle Component Analysis.

An engineering student friend of mine confirmed that the MP inverse is used for dimensionality reduction, but I can't find any material on this online. Can someone point me to an article, paper, or book on the subject?

During a discussion in our lab last month, a professor mentioned to me that the behavior of Self-Organizing Maps can be described in terms of repeated applications of the Moore-Penrose psuedoinverse, in a vaguely similar way to how the Preceptron algorithm can be described by Principle Component Analysis.

An engineering student friend of mine confirmed that the MP inverse is used for dimensionality reduction, but I can't find any material on this online. Can someone point me to an article, paper, or book on the subject?

During a discussion in our lab last month, a professor mentioned to me that the behavior of Self-Organizing Maps can be described in terms of repeated applications of the Moore-Penrose psuedoinverse, in a vaguely similar way to how single-layer neural networks with Hebbian learning can be described by Principle Component Analysis.

An engineering student friend of mine confirmed that the MP inverse is used for dimensionality reduction, but I can't find any material on this online. Can someone point me to an article, paper, or book on the subject?

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SigmaX
SigmaX
  • 113
  • 4

What is the MP pseudoinverse's role in statistical learning and Self-Organizing Maps?

During a discussion in our lab last month, a professor mentioned to me that the behavior of Self-Organizing Maps can be described in terms of repeated applications of the Moore-Penrose psuedoinverse, in a vaguely similar way to how the Preceptron algorithm can be described by Principle Component Analysis.

An engineering student friend of mine confirmed that the MP inverse is used for dimensionality reduction, but I can't find any material on this online. Can someone point me to an article, paper, or book on the subject?