Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The solution of some random NP-hard problems in polynomial expected time
Journal of Algorithms
The metropolis algorithm for graph bisection
Discrete Applied Mathematics
Algorithms for graph partitioning on the planted partition model
Random Structures & Algorithms
Permitted and forbidden sets in symmetric threshold-linear networks
Neural Computation
Spectral Partitioning of Random Graphs
FOCS '01 Proceedings of the 42nd IEEE symposium on Foundations of Computer Science
A spectral heuristic for bisecting random graphs
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Eigenvalues and graph bisection: An average-case analysis
SFCS '87 Proceedings of the 28th Annual Symposium on Foundations of Computer Science
CiE '07 Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World
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Motivated by the belief propagation, we propose a simple and deterministic message passing algorithm for the Graph Bisection problem and related problems. The running time of the main algorithm is linear w.r.t. the number of vertices and edges. For evaluating its average-case correctness, planted solution models are used. For the Graph Bisection problem under the standard planted solution model with probability parameters p and r, we prove that our algorithm yields a planted solution with probability 1–δ if p–r=Ω(n−1/2log(n/δ)).