A Learning Theoretic Framework for Clustering with Similarity Functions

Abstract

Problems of clustering data from pairwise similarity information are ubiquitous in Computer Science.<lb>Theoretical treatments typically view the similarity information as ground-truth and then design algorithms<lb>to (approximately) optimize various graph-based objective functions. However, in most applications, this<lb>similarity information is merely… (More)

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