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ідея - Correlation Clustering
Approximation Algorithms for the Correlation Clustering Problem
The authors propose the cluster LP as a strong linear program that unifies previous relaxations for the Correlation Clustering problem, and present improved approximation algorithms and hardness results based on this new framework.
Efficient Combinatorial Algorithm for Correlation Clustering with Improved Approximation Guarantee
We present a novel combinatorial algorithm that achieves a 2 - 2/13 < 1.847-approximation for the Correlation Clustering problem, substantially improving over the classic 3-approximation. Our algorithm uses a local search approach combined with a systematic "flipping" technique to escape bad local minima.
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