Research map / Graph learning / Graph algorithms and clustering
Improved Communication Cost in Distributed PageRank Computation – A Theoretical Study
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace initial Radar-Push rounds with Fractional-Push (float-valued messages) and keep Radar-Push for later rounds | distributed PageRank approximation · bandwidth-generalized congested clique | bandwidth per pair per round: from O(log^{2d+3} n) to O(d log^3 n) bits | Helped |
| Replace initial Radar-Push rounds with Fractional-Push (float-valued messages) and keep Radar-Push for later rounds | distributed PageRank approximation · bandwidth-generalized congested clique | communication rounds | No clear effect |
Closest papers by meaning
- Accelerated Evolving Set Processes for Local PageRank Computation (NeurIPS 2025 · similarity 0.87)
- Complexity of Classical Acceleration for $\ell_1$-Regularized PageRank (NeurIPS 2026 · similarity 0.84)
- Decentralized Ranking Aggregation via Gossip: Convergence and Robustness (NeurIPS 2026 · similarity 0.84)
- Fast Algorithms for Hypergraph PageRank with Applications to Semi-Supervised Learning (ICML 2024 · similarity 0.83)
- Robust Distributed Estimation: Extending Gossip Algorithms to Ranking and Trimmed Means (NeurIPS 2025 · similarity 0.83)
- Differentially Private Graph Diffusion with Applications in Personalized PageRanks (NeurIPS 2024 · similarity 0.83)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.