[HTML][HTML] A survey on heterogeneous transfer learning
O Day, TM Khoshgoftaar - Journal of Big Data, 2017 - Springer
Transfer learning has been demonstrated to be effective for many real-world applications as
it exploits knowledge present in labeled training data from a source domain to enhance a …
it exploits knowledge present in labeled training data from a source domain to enhance a …
Edge-cloud polarization and collaboration: A comprehensive survey for ai
Influenced by the great success of deep learning via cloud computing and the rapid
development of edge chips, research in artificial intelligence (AI) has shifted to both of the …
development of edge chips, research in artificial intelligence (AI) has shifted to both of the …
Semi-supervised heterogeneous domain adaptation: Theory and algorithms
Semi-supervised heterogeneous domain adaptation (SsHeDA) aims to train a classifier for
the target domain, in which only unlabeled and a small number of labeled data are …
the target domain, in which only unlabeled and a small number of labeled data are …
Multisource heterogeneous unsupervised domain adaptation via fuzzy relation neural networks
In unsupervised domain adaptation (UDA), a classifier for a target domain is trained with
labeled source data and unlabeled target data. Existing UDA methods assume that the …
labeled source data and unlabeled target data. Existing UDA methods assume that the …
Heterogeneous cross-company defect prediction by unified metric representation and CCA-based transfer learning
Cross-company defect prediction (CCDP) learns a prediction model by using training data
from one or multiple projects of a source company and then applies the model to the target …
from one or multiple projects of a source company and then applies the model to the target …
Survey on transfer learning research
庄福振， 罗平， 何清， 史忠植 - Journal of Software, 2014 - jos.org.cn
近年来, 迁移学习已经引起了广泛的关注和研究. 迁移学习是运用已存有的知识对不同但相关
领域问题进行求解的一种新的机器学习方法. 它放宽了传统机器学习中的两个基本假设:(1) …
领域问题进行求解的一种新的机器学习方法. 它放宽了传统机器学习中的两个基本假设:(1) …
Heterogeneous domain adaptation: An unsupervised approach
Domain adaptation leverages the knowledge in one domain-the source domain-to improve
learning efficiency in another domain-the target domain. Existing heterogeneous domain …
learning efficiency in another domain-the target domain. Existing heterogeneous domain …
Domain adaptation by mixture of alignments of second-or higher-order scatter tensors
In this paper, we propose an approach to the domain adaptation, dubbed Second-or Higher-
order Transfer of Knowledge (So-HoT), based on the mixture of alignments of second-or …
order Transfer of Knowledge (So-HoT), based on the mixture of alignments of second-or …
Cost-sensitive transfer kernel canonical correlation analysis for heterogeneous defect prediction
Cross-project defect prediction (CPDP) refers to predicting defects in a target project using
prediction models trained from historical data of other source projects. And CPDP in the …
prediction models trained from historical data of other source projects. And CPDP in the …