Rethinking Knowledge Distillation in Collaborative Machine Learning: Memory, Knowledge, and Their Interactions

This article from ArXiv likely explores advancements in knowledge distillation, a technique used to transfer knowledge from a larger model to a smaller one, within the context of collaborative machine learning. The focus on memory, knowledge, and their interactions suggests an investigation into how these elements influence the effectiveness of distillation in a collaborative setting, potentially addressing challenges like communication overhead or privacy concerns.