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The research work is exciting! I noticed that you formulate the automated graph contrastive learning as the min-max optimization problem. May I ask that why not use the bi-level optimization where the upper level objective is to search the augmentation operations and the lower level objective is to optimize the contrastive loss (like existing one-shot neural architecture search methods)?
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