Incremental Learning Using a Grow-and-Prune Paradigm With Efficient Neural Networks

Deep neural networks (DNNs) have become a widely deployed model for numerous machine learning applications. However, their fixed architecture, substantial training cost, and significant model redundancy make it difficult to efficiently update them to accommodate previously unseen data. To solve thes...

Ausführliche Beschreibung