Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Discriminability-Based Transfer between Neural Networks
Advances in Neural Information Processing Systems 5, [NIPS Conference]
Can chinese web pages be classified with english data source?
Proceedings of the 17th international conference on World Wide Web
Mapping and revising Markov logic networks for transfer learning
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Transfer learning via dimensionality reduction
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Text categorization with knowledge transfer from heterogeneous data sources
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Cross-domain video concept detection: A joint discriminative and generative active learning approach
Expert Systems with Applications: An International Journal
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Transfer learning is a method which aims to improve ''related'' tasks performance. Transfer learning tries to use information gained from related tasks solutions to improve performance of learning strategy. Transfer learning addresses the problem of how to utilize plenty of labeled data in a source domain to solve related but different problems in a target domain, even when the training and testing problems have different distributions or features (Pan, Kwok, & Yang, 2008). In this paper we have used transfer learning to improve performance of genetic algorithms.