These problems share a common nested optimization structure, and have inspired intensive study on the theory and algorithmic development of bilevel optimization. Prior efforts have been taken mainly on the single-machine scenario.

This allows us to include clustering in end-to-end trainable pipelines, with efficient gradients.

However, the completion accuracy can be drastically different over different entries.