Derives tighter generalization bounds for vector-valued neural networks and deep kernel methods in multi-task learning via Koopman and PF operators, with sketching for efficiency and a new vvRKHS framework.
In: Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence (UAI) (2021)
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Operator-Based Generalization Bound for Deep Learning: Insights on Multi-Task Learning
Derives tighter generalization bounds for vector-valued neural networks and deep kernel methods in multi-task learning via Koopman and PF operators, with sketching for efficiency and a new vvRKHS framework.