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We determine the information-theoretic cutoff value on separation of cluster centers for exact recovery of cluster labels in a K-component Gaussian mixture model with equal cluster sizes. Moreover, we show… Click to show full abstract
We determine the information-theoretic cutoff value on separation of cluster centers for exact recovery of cluster labels in a K-component Gaussian mixture model with equal cluster sizes. Moreover, we show that a semidefinite programming (SDP) relaxation of the K-means clustering method achieves such sharp threshold for exact recovery without assuming the symmetry of cluster centers.
Keywords:
cutoff exact;
cluster;
exact recovery;
recovery;
gaussian mixture
Journal Title: IEEE Transactions on Information Theory
Year Published: 2021
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Journal Title: IEEE Transactions on Information Theory
Year Published: 2021
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!