LGAISep 28, 2019

A Note On k-Means Probabilistic Poverty

arXiv:1910.00413v21 citations
Originality Synthesis-oriented
AI Analysis

This is an incremental theoretical result for researchers in clustering algorithms, highlighting a limitation in k-means.

The paper demonstrates that k-means with random initialization fails to achieve probabilistic k-richness, as proven through a counterexample.

It is proven, by example, that the version of $k$-means with random initialization does not have the property probabilistic k-richness.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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