Who Cited It

A survey of transfer learning

2016 · Journal Of Big Data · 6,290 citations · 6 from inside this corpus

Karl R. Weiss low, Taghi M. Khoshgoftaar, Dingding Wang

Machine learning and data mining techniques have been used in numerous real-world applications. An assumption of traditional machine learning methodologies is the training data and testing data are taken from the same domain, such that the input feature space and data distribution characteristics are the same. However, in some real-world machine learning scenarios, this assumption does not hold. There are cases where training data is expensive or difficult to collect. Therefore, there is a need to create high-performance learners trained with more easily obtained data from different domains. This methodology is referred to as transfer learning. This survey paper formally defines transfer learning, presents information on current solutions, and reviews applications applied to transfer learning. Lastly, there is information listed on software downloads for various transfer learning solutions and a discussion of possible future research work. The transfer learning solutions surveyed are independent of data size and can be applied to big data environments.

A survey of transfer learning (2016)A survey of transfer learningA Survey on Transfer Learning (2009)A Survey on Transfer LearningIndexing by latent semantic analysis (1990)Indexing by latent semantic a…Mining and summarizing customer reviews (2004)Mining and summarizing custom…Distance Metric Learning for Large Margin Nearest Neighbor Classification (2009)Distance Metric Learning for …Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Ex… (2006)Manifold Regularization: A Ge…Learning and Transferring Mid-level Image Representations Using Convolutional Neural Netw… (2014)Learning and Transferring Mid…Adapting Visual Category Models to New Domains (2010)Adapting Visual Category Mode…Geodesic flow kernel for unsupervised domain adaptation (2012)Geodesic flow kernel for unsu…Information-theoretic metric learning (2007)Information-theoretic metric …Transfer Feature Learning with Joint Distribution Adaptation (2013)Transfer Feature Learning wit…Boosting for transfer learning (2007)Boosting for transfer learningCorrecting Sample Selection Bias by Unlabeled Data (2007)Correcting Sample Selection B…Domain adaptation with structural correspondence learning (2006)Domain adaptation with struct…Transfer Learning for Reinforcement Learning Domains: A Survey (2009)Transfer Learning for Reinfor…Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach (2011)Domain Adaptation for Large-S…Proceedings of the 20th conference on Uncertainty in artificial intelligence (2004)Proceedings of the 20th confe…Regularized multi--task learning (2004)Regularized multi--task learn…Frustratingly Easy Domain Adaptation (2009)Frustratingly Easy Domain Ada…A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data (2005)A Framework for Learning Pred…A Comprehensive Survey on Transfer Learning (2020)A Comprehensive Survey on Tra…Machine Learning: Algorithms, Real-World Applications and Research Directions (2021)Machine Learning: Algorithms,…Continual lifelong learning with neural networks: A review (2019)Continual lifelong learning w…A Survey on Deep Transfer Learning (2018)A Survey on Deep Transfer Lea…Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Researc… (2021)Deep Learning: A Comprehensiv…Text Data Augmentation for Deep Learning (2021)Text Data Augmentation for De…
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What this paper cites, inside the corpus

PaperYearCited
A Survey on Transfer Learning200923,670
Indexing by latent semantic analysis199012,850
Mining and summarizing customer reviews20047,754
Distance Metric Learning for Large Margin Nearest Neighbor Classification20094,256
Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Ex…20063,266
Learning and Transferring Mid-level Image Representations Using Convolutional Neural Netw…20143,197
Adapting Visual Category Models to New Domains20102,873
Geodesic flow kernel for unsupervised domain adaptation20122,219
Information-theoretic metric learning20072,047
Transfer Feature Learning with Joint Distribution Adaptation20132,033
Boosting for transfer learning20071,748
Correcting Sample Selection Bias by Unlabeled Data20071,566
Domain adaptation with structural correspondence learning20061,565
Transfer Learning for Reinforcement Learning Domains: A Survey20091,564
Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach20111,562
Proceedings of the 20th conference on Uncertainty in artificial intelligence20041,548
Regularized multi--task learning20041,481
Frustratingly Easy Domain Adaptation20091,396
A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data20051,370

What cites it, inside the corpus

PaperYearCited
A Comprehensive Survey on Transfer Learning20206,441
Machine Learning: Algorithms, Real-World Applications and Research Directions20215,368
Continual lifelong learning with neural networks: A review20193,145
A Survey on Deep Transfer Learning20182,907
Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Researc…20212,537
Text Data Augmentation for Deep Learning20211,701

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DOI · Open access copy · OpenAlex record

Topics

Domain Adaptation and Few-Shot LearningComputer Science
Machine Learning and Data ClassificationComputer Science
Data Stream Mining TechniquesComputer Science

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