Personal information

No personal information available

Activities

Collapse all

Works (7)

Is Sharing Neighbor Generator in Federated Graph Learning Safe?

IEEE Transactions on Knowledge and Data Engineering
2024 | Journal article
DOI: 10.1109/TKDE.2024.3482448
Contributors: Liuyi Yao; Zhen Wang; Yuexiang Xie; Yaliang Li; Weirui Kuang; Daoyuan Chen; Bolin Ding
Source: check_circle
Crossref

On the Convergence of Zeroth-Order Federated Tuning for Large Language Models

2024-08-25 | Conference paper
DOI: 10.1145/3637528.3671865
Contributors: Zhenqing Ling; Daoyuan Chen; Liuyi Yao; Yaliang Li; Ying Shen
Source: check_circle
Crossref

Concept-Level Model Interpretation From the Causal Aspect

IEEE Transactions on Knowledge and Data Engineering
2023-09-01 | Journal article
DOI: 10.1109/TKDE.2022.3209997
Contributors: Liuyi Yao; Yaliang Li; Sheng Li; Jinduo Liu; Mengdi Huai; Aidong Zhang; Jing Gao
Source: check_circle
Crossref

Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks

2023-08-06 | Conference paper
DOI: 10.1145/3580305.3599898
Contributors: Zeyu Qin; Liuyi Yao; Daoyuan Chen; Yaliang Li; Bolin Ding; Minhao Cheng
Source: check_circle
Crossref

Path-specific Causal Fair Prediction via Auxiliary Graph Structure Learning

2023-04-30 | Conference paper
DOI: 10.1145/3543507.3583280
Contributors: Liuyi Yao; Yaliang Li; Bolin Ding; Jingren Zhou; Jinduo Liu; Mengdi Huai; Jing Gao
Source: check_circle
Crossref

On the Robustness of Metric Learning: An Adversarial Perspective

ACM Transactions on Knowledge Discovery from Data
2022-10-31 | Journal article
DOI: 10.1145/3502726
Contributors: Mengdi Huai; Tianhang Zheng; Chenglin Miao; Liuyi Yao; Aidong Zhang
Source: check_circle
Crossref

A Survey on Causal Inference

ACM Transactions on Knowledge Discovery from Data
2021-10-31 | Journal article
DOI: 10.1145/3444944
Contributors: Liuyi Yao; Zhixuan Chu; Sheng Li; Yaliang Li; Jing Gao; Aidong Zhang
Source: check_circle
Crossref

Peer review (2 reviews for 1 publication/grant)

Review activity for International journal of data science and analytics. (2)
How many people are using ORCID?