Online Transfer Learning: Negative Transfer and Effect of Prior Knowledge

  title={Online Transfer Learning: Negative Transfer and Effect of Prior Knowledge},
  author={Xuetong Wu and Jonathan H. Manton and Uwe Aickelin and Jingge Zhu},
  journal={2021 IEEE International Symposium on Information Theory (ISIT)},
  • Xuetong Wu, J. Manton, +1 author Jingge Zhu
  • Published 4 May 2021
  • Computer Science, Mathematics
  • 2021 IEEE International Symposium on Information Theory (ISIT)
Transfer learning is a machine learning paradigm where the knowledge from one task is utilized to resolve the problem in a related task. On the one hand, it is conceivable that knowledge from one task could be useful for solving a related problem. On the other hand, it is also recognized that if not executed properly, transfer learning algorithms could in fact impair the learning performance instead of improving it - commonly known as negative transfer. In this paper, we study the online… Expand

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