Transfer Learning, Multi-Task Learning, and Meta-Learning Explained: From Knowledge Reuse to Rapid Few-Shot Adaptation
This article examines three major knowledge reuse paradigms—transfer learning, multi-task learning, and meta-learning—to answer a core question: how can models use prior knowledge to learn new tasks faster? These approaches address data scarcity, task collaboration, and few-shot adaptation, respectively. Keywords: transfer learning, domain adaptation, meta-learning. Technical Specification Snapshot Parameter Details Core Topics Transfer Learning, Multi-Task … Read more