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Multi-Dimensional Balanced Graph Partitioning via Projected Gradient Descent

Summary: Proposes multi-dimensional balanced graph partitioning for distributed graphs; uses randomized projected gradient descent on a non-convex relaxation to enforce multi-weight balance. Projection-based algorithm scales to graphs with billions of edges and outperforms current baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12014
Venue
VLDB
Year
2019
Pagerank
6.1387773e-05
Overall Rank
4,497 | 68.72%
DOI
10.14778/3324301.3324307

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