# Correlation Clustering with Same-Cluster Queries Bounded by Optimal Cost

@article{Saha2019CorrelationCW, title={Correlation Clustering with Same-Cluster Queries Bounded by Optimal Cost}, author={Barna Saha and Sanjay Subramanian}, journal={ArXiv}, year={2019}, volume={abs/1908.04976} }

Several clustering frameworks with interactive (semi-supervised) queries have been studied in the past. Recently, clustering with same-cluster queries has become popular. An algorithm in this setting has access to an oracle with full knowledge of an optimal clustering, and the algorithm can ask the oracle queries of the form, "Does the optimal clustering put vertices $ u $ and $ v $ in the same cluster?" Due to its simplicity, this querying model can easily be implemented in real crowd-sourcing…

## 13 Citations

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This work proposes two algorithms with provable theoretical guarantees and verifies their effectiveness via an extensive set of experiments on both synthetic and real-world data.

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This work develops robust learning methods that tolerate general semi-random noise obtaining qualitatively the same guarantees as the best possible methods in the fully-random model.

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