A Simple Explanation of A Spectral Algorithm for Learning Hidden Markov Models
arXiv:1204.2477v11 citations
Originality Synthesis-oriented
AI Analysis
This is an incremental contribution aimed at making a known algorithm more accessible to researchers and practitioners in machine learning.
The paper provides a simplified linear algebraic explanation of an existing spectral algorithm for learning Hidden Markov Models, focusing on clarifying the method through precise claims and a key figure.
A simple linear algebraic explanation of the algorithm in "A Spectral Algorithm for Learning Hidden Markov Models" (COLT 2009). Most of the content is in Figure 2; the text just makes everything precise in four nearly-trivial claims.