Optimal Connectivity through Network Gradients for the Restricted Boltzmann Machine. (arXiv:2209.06932v1 [cs.LG])

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 curves of shallow networks, such as the classic Restricted
Boltzmann Machines (RBM). A fundamental problem is efficiently finding
connectivity patterns that improve the learning curve. Recent principled
approaches explicitly include network connections as parameters that must be
optimized in the model, but often rely on continuous …

arxiv boltzmann connectivity machine network