Optimizing Connectivity through Network Gradients for the Restricted Boltzmann Machine. (arXiv:2209.06932v2 [cs.LG] UPDATED)

Leveraging sparse networks to connect successive layers in deep neural
networks has recently been shown to provide benefits to large scale
state-of-the-art models. However, network connectivity also plays a significant
role on the learning performance of shallow networks, such as the classic
Restricted Boltzmann Machines (RBM). Efficiently finding sparse connectivity
patterns that improve the learning performance of shallow networks is a
fundamental problem. While recent principled approaches explicitly include
network connections as model parameters that must be optimized, they often …

arxiv boltzmann connectivity machine network