Nimita Rajendra Shinde

Memory-Efficient Approximation Algorithms for Max-k-Cut and Correlation Clustering

Max-k-Cut and correlation clustering are fundamental graph partitioning problems. For a graph $G=(V,E)$ with $n$ vertices, the methods with the best approximation guarantees for Max-k-Cut and the Max-Agree variant of correlation clustering involve solving SDPs with $\mathcal{O}(n^2)$ constraints and…