Clustering using Max-norm Constrained Optimization

Details Clustering using Max-norm Constrained Optimization Clustering using Max-norm Constrained Optimization

2012-02-25

arxiv.org/abs/1202.5598v4

Computer Science

Learning

Scientific paper

We suggest using the max-norm as a convex surrogate constraint for
clustering. We show how this yields a better exact cluster recovery guarantee
than previously suggested nuclear-norm relaxation, and study the effectiveness
of our method, and other related convex relaxations, compared to other
clustering approaches.

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