arXiv (All)
open access
Budget-Independent Influence Maximization in Nearly Linear Time
Influence maximization asks for $k$ seed vertices that maximize the expected spread of a diffusion process in a network. Standard near-optimal-time algorithms based on reverse-reachable sampling achieve a $(1-1/e-\varepsilon)$ approximation, but their worst-case running-time bounds grow linearly wit
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Query Lower Bounds for Diffusion Sampling#1130527
- Critical and near-critical influence bounds for ferromagnetic Ising models#1034841
- The voter model on the hyperbolic graph#821115
- The price of anarchy in the max-distance network creation game is not constant#1123760
- Distance and resistance on random series-parallel graphs: logarithmic speeds and near-critical asymptotics#1049536
Record · ID 1049343
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive