Autonomous Graph Mining Algorithm Search with Best Speed/Accuracy Trade-off
AUTOGM is an automated system for graph mining algorithm development.
We first define a unified framework UNIFIEDGM that integrates various message-passing based graph algorithms, ranging from conventional algorithms like PageRank to graph neural networks. UNIFIEDGM defines a search space in which five parameters are required to determine a graph algorithm. Under this search space, AUTOGM explicitly optimizes for the optimal parameter set of UNIFIEDGM using Bayesian Optimization. AUTOGM defines a novel budget-aware objective function for the optimization to incorporate a practical issue — finding the best speed-accuracy trade-off under a computation budget — into the graph algorithm generation problem.
Details can be found in the original paper (https://minjiyoon.xyz/Paper/AutoGM.pdf)