Learning Stabilizing Latent Feedback Controllers via Multi-Step Backward Losses
It is shown that learning linear autoencoders and latent dynamics with multi-step prediction-reconstruction losses with backward losses provably recovers the structure needed for stabilization, and why both reconstruction and a multi-step horizon are essential.
Paul Lutkus, L. Lindemann, Stephen Tu
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