The 8th DeSI Lab Seminar

The 8th DeSI Lab Seminar on Fuzzy rule-based domain adaptation in homogeneous and heterogeneous spaces.

Title: Fuzzy rule-based domain adaptation in homogeneous and heterogeneous spaces

Presenter: Hua Zuo

Abstract: 

Domain adaptation aims to leverage knowledge acquired from a related domain (called source domain) to improve the efficiency of completing a prediction task (classification or regression) in the current domain (called target domain) which has different probability distribution from the source domain. We proposed fuzzy rule-based methods to deal with the domain adaptation in homogeneous and heterogeneous spaces, no matter the numbers of fuzzy rules in two domains are match or not. Further, we consider the cases that multiple source domains are available in transfer learning based on fuzzy rule-based models. Although some algorithms have been proposed, there are still issues that haven't been solved.

Location: CB11.05.100

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Acknowledgement of Country

UTS acknowledges the Gadigal people of the Eora Nation, the Boorooberongal people of the Dharug Nation, the Bidiagal people and the Gamaygal people, upon whose ancestral lands our university stands. We would also like to pay respect to the Elders both past and present, acknowledging them as the traditional custodians of knowledge for these lands.