Cross-domain Mixup (XMixup) improves the accuracy by 1.9% on average . Compared with other state-of-the-art transfer learning approaches, XMixup costs much less training time while still obtains higher accuracy . Compared to existing multitask learning algorithms, XMixups cost less training time and still obtains better accuracy than other approaches to transfer knowledge from source to target tasks . The study concludes that XMixups can be used to fine-tune the deep neural networks of the target task with a small sample size . The research was published in the journal Akademademademics, Akademics and Machine Machine Machine Intelligence (Machine Intelligence Intelligence) at the Open University, New York, October 1, 2013, and the University of Cambridge University, Washington, October 2, 2014, respectively, in the open-access to the Open Data Institute, October 3, 2013. The Open Data Center, October 4, 2014.

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Keywords : october - machine - open - university - transfer -

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