Liuyi Yao

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 43

Top Topics

Observational Data

Causal Inference

Top Venues

Publications

Yue Cui, Liuyi Yao, Zitao Li, Yaliang Li, Bolin Ding, Xiaofang Zhou
A Bargaining-based Approach for Feature Trading in Vertical Federated Learning. CoRR (2024)
Jiamu Bai, Daoyuan Chen, Bingchen Qian, Liuyi Yao, Yaliang Li
Federated Fine-tuning of Large Language Models under Heterogeneous Language Tasks and Client Resources. CoRR (2024)
Shuchang Tao, Liuyi Yao, Hanxing Ding, Yuexiang Xie, Qi Cao, Fei Sun, Jinyang Gao, Huawei Shen, Bolin Ding
When to Trust LLMs: Aligning Confidence with Response Quality. CoRR (2024)
Zhenqing Ling, Daoyuan Chen, Liuyi Yao, Yaliang Li, Ying Shen
On the Convergence of Zeroth-Order Federated Tuning in Large Language Models. CoRR (2024)
Zhen Qin, Daoyuan Chen, Wenhao Zhang, Liuyi Yao, Yilun Huang, Bolin Ding, Yaliang Li, Shuiguang Deng
The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective. CoRR (2024)
Shuchang Tao, Liuyi Yao, Hanxing Ding, Yuexiang Xie, Qi Cao, Fei Sun, Jinyang Gao, Huawei Shen, Bolin Ding
When to Trust LLMs: Aligning Confidence with Response Quality. ACL (Findings) (2024)
Yue Cui, Liuyi Yao, Yaliang Li, Ziqian Chen, Bolin Ding, Xiaofang Zhou
An Auction-based Marketplace for Model Trading in Federated Learning. CoRR (2024)
Zhenqing Ling, Daoyuan Chen, Liuyi Yao, Yaliang Li, Ying Shen
On the Convergence of Zeroth-Order Federated Tuning for Large Language Models. KDD (2024)
Shen Li, Liuyi Yao, Jinyang Gao, Lan Zhang, Yaliang Li
Double-I Watermark: Protecting Model Copyright for LLM Fine-tuning. CoRR (2024)
Dawei Gao, Zitao Li, Weirui Kuang, Xuchen Pan, Daoyuan Chen, Zhijian Ma, Bingchen Qian, Liuyi Yao, Lin Zhu, Chen Cheng, Hongzhu Shi, Yaliang Li, Bolin Ding, Jingren Zhou
AgentScope: A Flexible yet Robust Multi-Agent Platform. CoRR (2024)
Zitao Li, Bolin Ding, Liuyi Yao, Yaliang Li, Xiaokui Xiao, Jingren Zhou
Performance-Based Pricing of Federated Learning via Auction. Proc. VLDB Endow. 17 (6) (2024)
Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. KDD (2023)
Liuyi Yao, Yaliang Li, Sheng Li, Jinduo Liu, Mengdi Huai, Aidong Zhang, Jing Gao
Concept-Level Model Interpretation From the Causal Aspect. IEEE Trans. Knowl. Data Eng. 35 (9) (2023)
Daoyuan Chen, Liuyi Yao, Dawei Gao, Bolin Ding, Yaliang Li
Efficient Personalized Federated Learning via Sparse Model-Adaptation. CoRR (2023)
Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou, Jinduo Liu, Mengdi Huai, Jing Gao
Path-specific Causal Fair Prediction via Auxiliary Graph Structure Learning. WWW (2023)
Daoyuan Chen, Liuyi Yao, Dawei Gao, Bolin Ding, Yaliang Li
Efficient Personalized Federated Learning via Sparse Model-Adaptation. ICML (2023)
Yuexiang Xie, Zhen Wang, Dawei Gao, Daoyuan Chen, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity. Proc. VLDB Endow. 16 (5) (2023)
Zeyu Qin, Liuyi Yao, Daoyuan Chen, Yaliang Li, Bolin Ding, Minhao Cheng
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks. CoRR (2023)
Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. KDD (2022)
Zhen Wang, Weirui Kuang, Yuexiang Xie, Liuyi Yao, Yaliang Li, Bolin Ding, Jingren Zhou
FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning. CoRR (2022)
Mengdi Huai, Jinduo Liu, Chenglin Miao, Liuyi Yao, Aidong Zhang
Towards Automating Model Explanations with Certified Robustness Guarantees. AAAI (2022)
Mengdi Huai, Tianhang Zheng, Chenglin Miao, Liuyi Yao, Aidong Zhang
On the Robustness of Metric Learning: An Adversarial Perspective. ACM Trans. Knowl. Discov. Data 16 (5) (2022)
Xuanying Chen, Zhining Liu, Li Yu, Liuyi Yao, Wenpeng Zhang, Yi Dong, Lihong Gu, Xiaodong Zeng, Yize Tan, Jinjie Gu
Imbalance-Aware Uplift Modeling for Observational Data. AAAI (2022)
Yuexiang Xie, Zhen Wang, Daoyuan Chen, Dawei Gao, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou
FederatedScope: A Comprehensive and Flexible Federated Learning Platform via Message Passing. CoRR (2022)
Liuyi Yao, Dawei Gao, Zhen Wang, Yuexiang Xie, Weirui Kuang, Daoyuan Chen, Haohui Wang, Chenhe Dong, Bolin Ding, Yaliang Li
A Benchmark for Federated Hetero-Task Learning. CoRR (2022)
Liuyi Yao, Zijun Yao, Jianying Hu, Jing Gao, Zhaonan Sun
Deep Staging: An Interpretable Deep Learning Framework for Disease Staging. ICHI (2021)
Liuyi Yao, Yaliang Li, Sheng Li, Mengdi Huai, Jing Gao, Aidong Zhang
SCI: Subspace Learning Based Counterfactual Inference for Individual Treatment Effect Estimation. CIKM (2021)
Siqing Li, Liuyi Yao, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Tonglei Guo, Bolin Ding, Ji-Rong Wen
Debiasing Learning based Cross-domain Recommendation. KDD (2021)
Gabriel Guo, Hanbin Zhang, Liuyi Yao, Huining Li, Chenhan Xu, Zhengxiong Li, Wenyao Xu
MSLife: Digital Behavioral Phenotyping of Multiple Sclerosis Symptoms in the Wild Using Wearables and Graph-Based Statistical Analysis. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5 (4) (2021)
Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, Aidong Zhang
A Survey on Causal Inference. ACM Trans. Knowl. Discov. Data 15 (5) (2021)
Peng Cui, Zheyan Shen, Sheng Li, Liuyi Yao, Yaliang Li, Zhixuan Chu, Jing Gao
Causal Inference Meets Machine Learning. KDD (2020)
Jinduo Liu, Junzhong Ji, Guangxu Xun, Liuyi Yao, Mengdi Huai, Aidong Zhang
EC-GAN: Inferring Brain Effective Connectivity via Generative Adversarial Networks. AAAI (2020)
Mengdi Huai, Jianhui Sun, Renqin Cai, Liuyi Yao, Aidong Zhang
Malicious Attacks against Deep Reinforcement Learning Interpretations. KDD (2020)
Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, Aidong Zhang
A Survey on Causal Inference. CoRR (2020)
Liuyi Yao, Yaliang Li, Yezheng Li, Hengtong Zhang, Mengdi Huai, Jing Gao, Aidong Zhang
DTEC: Distance Transformation Based Early Time Series Classification. SDM (2019)
Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, Aidong Zhang
ACE: Adaptively Similarity-Preserved Representation Learning for Individual Treatment Effect Estimation. ICDM (2019)
Qiuling Suo, Liuyi Yao, Guangxu Xun, Jianhui Sun, Aidong Zhang
Recurrent Imputation for Multivariate Time Series with Missing Values. ICHI (2019)
Jinduo Liu, Junzhong Ji, Liuyi Yao, Aidong Zhang
Estimating Brain Effective Connectivity in fMRI data by Non-stationary Dynamic Bayesian Networks. BIBM (2019)
Liuyi Yao, Sheng Li, Yaliang Li, Hongfei Xue, Jing Gao, Aidong Zhang
On the Estimation of Treatment Effect with Text Covariates. IJCAI (2019)
Mengdi Huai, Hongfei Xue, Chenglin Miao, Liuyi Yao, Lu Su, Changyou Chen, Aidong Zhang
Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm. IJCAI (2019)
Yaliang Li, Liuyi Yao, Nan Du, Jing Gao, Qi Li, Chuishi Meng, Chenwei Zhang, Wei Fan
Finding Similar Medical Questions from Question Answering Websites. CoRR (2018)
Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, Aidong Zhang
Representation Learning for Treatment Effect Estimation from Observational Data. NeurIPS (2018)
Liuyi Yao, Lu Su, Qi Li, Yaliang Li, Fenglong Ma, Jing Gao, Aidong Zhang
Online Truth Discovery on Time Series Data. SDM (2018)