Most transfer learning (TL) methods focus on single-source domain adaptation (DA) within the same machine, overlooking variability within the source domain and missing the opportunity to leverage ...

Transfer learning is a machine learning technique ... models on large datasets to perform well in new, often smaller, domains with limited labeled data. It has become increasingly popular in ...

Transfer Learning for Reinforcement Learning Domains: A Survey. Matthew E. Taylor and Peter Stone. Journal of Machine Learning Research, 10(1):1633–1685, 2009.

In particular, we conduct a systematic study on the transferability of (1) models pre-trained on iNat2021, the most recent large-scale fine-grained dataset, (2) 14 top self-supervised ImageNet models, ...

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Domains.co.za has become the first South African registrar to offer a free Domain Transfer Lock feature for all .co.za, .org.za, .net.za and .web.za domain customers. This added layer of security ...

While deepfake generation advances in complexity, it also becomes more computationally demanding. In contrast, detection is learning to do more with less.

Transfer Learning via Inter-Task Mappings for Temporal Difference Learning. Matthew E. Taylor, Peter Stone, and Yaxin Liu. Journal of Machine Learning Research, 8(1):2125–2167, 2007.