Graph propagation queries can be accelerated by replacing Taylor expansions with Chebyshev polynomials, yielding a claimed O(sqrt(N)) reduction in iterations and a local push algorithm.
Scaling graph neural networks with approximate pagerank
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Scaling Up Graph Propagation Computation on Large Graphs: A Local Chebyshev Approximation Approach
Graph propagation queries can be accelerated by replacing Taylor expansions with Chebyshev polynomials, yielding a claimed O(sqrt(N)) reduction in iterations and a local push algorithm.