Heterogeneous Domain Adaptation: An Unsupervised Approach
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2020.2973293
Abstract: Domain adaptation leverages the knowledge in one domain—the source domain—to improve learning efficiency in another domain—the target domain. Existing heterogeneous domain adaptation research is relatively well-progressed but only in situations where the target domain contains… read more here.
Keywords: heterogeneous domain; domain adaptation; homogeneous representations; target ... See more keywords
Semi-supervised Heterogeneous Domain Adaptation: Theory and Algorithms.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on pattern analysis and machine intelligence"
DOI: 10.1109/tpami.2022.3146234
Abstract: 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 available. This is done by leveraging knowledge acquired from… read more here.
Keywords: heterogeneous domain; domain adaptation; semi supervised; domain ... See more keywords
Heterogeneous Domain Adaptation With Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Pattern Analysis and Machine Intelligence"
DOI: 10.1109/tpami.2022.3163338
Abstract: Learning predictive models in new domains with scarce training data is a growing challenge in modern supervised learning scenarios. This incentivizes developing domain adaptation methods that leverage the knowledge in known domains (source) and adapt… read more here.
Keywords: domain adaptation; heterogeneous domain; adaptation adversarial; domain ... See more keywords