arXiv Artificial Intelligence

Limits of Transfer Learning

1 hour ago 17.09.2026 07:00 👁 1 views
Limits of Transfer Learning

Quick summary

arXiv:2006.12694v2 Announce Type: replace-cross Abstract: Transfer learning involves taking information and insight from one problem domain and applying it to a new problem domain. Although widely used in practice, theory for transfer learning remains less well-developed. To address this, we prove several novel results related to transfer learning, showing the need to carefully select which sets of information to transfer and the need for dependence between transferred information and target problems. Furthermore, we prove how the degree of probabilistic change in an algorithm using transfer l

Key takeaways

  • arXiv:2006.12694v2 Announce Type: replace-cross Abstract: Transfer learning involves taking information and insight from one problem domain and applying it to a new problem domain.
  • Although widely used in practice, theory for transfer learning remains less well-developed.
  • To address this, we prove several novel results related to transfer learning, showing the need to carefully select which sets of information to transfer and the need for dependence between transferred information and target problems.

Why it matters

The importance of “Limits of Transfer Learning” will be measured by what changes in practice. User behavior, access conditions, verifiable performance and responsible-use outcomes are the signals worth following.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗