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Transfer Learning with Recurrent Neural Network/Evidence
Method evidence record

Transfer Learning with Recurrent Neural Network

Transfer Learning with Recurrent Neural Network (TL-RNN) reuses weights learned by an RNN on a large source task — such as language modelling or sequence prediction — and adapts them to a new, often smaller target task. This strategy lets practitioners obtain strong sequence-modelling performance without the need for massive labelled datasets.

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Transfer Learning with Recurrent Neural Network (TL-RNN)
Taxonomic method record · ml-model / deep-learning
  • Pan, S. J., & Yang, Q. (2010). A Survey on Transfer Learning. IEEE Transactions on Knowledge and Data Engineering, 22(10), 1345–1359. · DOI 10.1109/TKDE.2009.191
  • Transfer learning. Wikipedia. · URL
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Related methods

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Taxonomic bucketFine-Tuned Recurrent Neural Networkmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketGated Recurrent Unitmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketLong Short-Term Memorymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRecurrent Neural Networkmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketTransfer Learning with LSTMmachine-suggested · Relational suggestion, not evidence.

Evidence status

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Sources

2 recorded citations, copied from the method source record.

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