Figure 1: Illustration given, depicted and (ii) red/pink.

Typically, forecasts are designed without knowledge of a downstream controller's task objective, and thus simply optimize formean prediction error. However, such task-agnostic representations are often too large to stream over a communication network and do not emphasize salient temporal features for cooperativecontrol.

How does a human being distinguish the motions of a piece of paper and a piece of cloth? A high-school physics teacher might answer that they are both tangentially inextensible but cloth cannot resist any bending force from the normal direction.

These clusters of neurons form large hierarchical modules along the cortex.

Knowledge distillation (KD) has been widely used to improve the test accuracy of a "student" network, by training it to mimic the soft probabilities of a trained