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On the Role of Edge Dependency in Graph Generative Models
Our evaluation, conducted on real-world datasets, focuses on assessing the output quality and overlap of our proposed models in comparison to other popular models.
Query-Efficient Correlation Clustering
Up to constant factors, our algorithm yields a provably optimal trade-off between the number of queries $Q$ and the worst-case error attained, even for adaptive algorithms.
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