While transposable passin In [17], theauthorsmaskto constrains satisfy diversity sparsity R C, supposeRandC are thesparsitys.

The "black-box" nature of representations, combined with the known susceptibility of networks to learn spurious correlations [

However, such a global learning rate schedule does not take into account the structural characteristics of neural networks (NNs).

Energy-efficient computing is of primary importance to the effective deployment of deep neural networks (DNNs), particularly in edge devices and in on-chip AI systems. Increasing DNN computation's energy efficiency and lowering its carbon footprint require iterative efforts from both chip designers and algorithm developers.