Search Results for author: Yuzhen Mao

Found 3 papers, 2 papers with code

Dynamic Transfer Learning across Graphs

no code implementations1 May 2023 Haohui Wang, Yuzhen Mao, Jianhui Sun, Si Zhang, Yonghui Fan, Dawei Zhou

Transferring knowledge across graphs plays a pivotal role in many high-stake domains, ranging from transportation networks to e-commerce networks, from neuroscience to finance.

Transfer Learning

Last-Layer Fairness Fine-tuning is Simple and Effective for Neural Networks

2 code implementations8 Apr 2023 Yuzhen Mao, Zhun Deng, Huaxiu Yao, Ting Ye, Kenji Kawaguchi, James Zou

As machine learning has been deployed ubiquitously across applications in modern data science, algorithmic fairness has become a great concern.

Fairness Open-Ended Question Answering +1

Augmenting Knowledge Transfer across Graphs

1 code implementation9 Dec 2022 Yuzhen Mao, Jianhui Sun, Dawei Zhou

Given a resource-rich source graph and a resource-scarce target graph, how can we effectively transfer knowledge across graphs and ensure a good generalization performance?

Domain Adaptation Transfer Learning

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