Subnetworks

Subnetworks refer to a smaller network that is part of a larger network. In the context of data science and artificial intelligence, subnetworks are often used in deep learning models to improve efficiency and reduce computational costs. Subnetworks are created by removing certain layers or nodes from a larger neural network, resulting in a smaller and more specialized network that can perform specific tasks. This process is known as network pruning. Subnetworks can also be used for transfer learning, where a pre-trained subnetwork is used as a starting point for a new task, allowing for faster and more efficient training. Subnetworks can be optimized using various techniques such as evolutionary algorithms, reinforcement learning, and gradient-based methods.
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