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Liuyi Yao

I'm currently a staff in Alibaba DAMO Academy. I obtained my PhD degree in Department of Computer Science and Engineering in University at Buffalo under the advisory of Prof. Aidong Zhang and Prof. Jing Gao in 2020. Before that, I got my B.S. degree in statistics from Nanjing University in 2015.

I have board interests in Data Mining and Machine Learning. I am particularly interested in Causal Inference, Federated Learning and Temporal Data Analysis.

Publication [Google Scholar] [DBLP]

2022
  • Mengdi Huai, Tianhang Zheng, Chenglin Miao, Liuyi Yao, Aidong Zhang, On the Robustness of Metric Learning: An Adversarial Perspective, ACM Transactions on Knowledge Discovery from Data (TKDD). [ pdf ]
  • 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. Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, (AAAI 2022). [ pdf ]
2021
  • Liuyi Yao, Yaliang Li, Sheng Li, Mengdi Huai, Jing Gao, Aidong Zhang, SCI: Subspace Learning Based Counterfactual Inference for Individual Treatment Effect Estimation, Proceedings of the 30th ACM International Conference on Information & Knowledge Management, (CIKM 2021).
  • Siqing Li, Liuyi Yao, Shanlei Mu, Wayne Xin Zhao, Yaliang Li, Tonglei Guo, Bolin Ding, Ji-Rong Wen, and Mengdi Huai, Aidong Zhang, Debiasing Learning based Cross-domain Recommendation. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, (KDD 2021).
  • Liuyi Yao, Zijun Yao, Jianying Hu, Jing Gao, Zhaonan Sun, Deep Staging: An Interpretable Deep Learning Framework for Disease Staging. 2021 IEEE 9th International Conference on Healthcare Informatics, (ICHI 2021).
  • Liuyi Yao, Zhixuan Chu, Sheng Li, Yaliang Li, Jing Gao, Aidong Zhang. A Survey on Causal Inference. ACM Transactions on Knowledge Discovery from Data (TKDD)
2020
  • Mengdi Huai, Jianhui Sun, Renqin Cai, Liuyi Yao, Aidong Zhang, Malicious attacks against deep reinforcement learning interpretations. Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, (KDD 2020, Best Paper Runner-up).
  • Sheng Li, Liuyi Yao, Yaliang Li, Jing Gao and Aidong Zhang, Representation Learning for Causal Inference, the Thirty-Fourth AAAI Conference on Artificial Intelligence, Tutorial, (AAAI 2020). [ slides ]
  • Jinduo Liu, Junzhong Ji, Guangxu Xun, Liuyi Yao, and Mengdi Huai, Aidong Zhang, EC-GAN: Inferring Brain Effective Connectivity via Generative Adversarial Networks. Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, (AAAI 2020).
2019
  • Jinduo Liu, Junzhong Ji, Liuyi Yao, Aidong Zhang, Estimating Brain Effective Connectivity in fMRI Data by Non-stationary Dynamic Bayesian Networks. IEEE International Conference on Bioinformatics and Biomedicine, (BIBM 2019).
  • Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, and Aidong Zhang. ACE: Adaptively Similarity-preserved Representation Learning for Individual Treatment Effect Estimation. Proceedings of the 19th IEEE International Conference on Data Mining (ICDM 2019).
  • Liuyi Yao, Sheng Li, Yaliang Li, Hongfei Xue, Jinggao, and Aidong Zhang. On the Estimation of Treatment Effect with Text Covariates. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2019).
  • Mengdi Huai, Hongfei Xue, Chenglin Miao, Liuyi Yao, Lu Su, Changyou Chen, and Aidong Zhang. Deep Metric Learning: The Generalization Analysis and an Adaptive Algorithm. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI 2019).
  • Liuyi Yao, Yaliang Li, Yezheng Li, Hengtong Zhang, Mengdi Huai, Jing Gao, Aidong Zhang. DTEC: Distance Transformation Based Early Time Series Classication. Proceedings of the 2019 SIAM International Conference on Data Mining (SDM 2019).
  • Suo Qiuling, Yao Liuyi,Xun Guangxu, Sun Jianhui, Zhang Aidong. Recurrent Imputation for Multivariate Time Series with Missing Values. 2019 IEEE International Conference on Healthcare Informatics (ICHI 2019).
2018
  • Liuyi Yao, Sheng Li, Yaliang Li, Mengdi Huai, Jing Gao, and Aidong Zhang. Representation Learning for Treatment Effect Estimation from Observational Data. Advances in Neural Information Processing Systems 31 (NeurIPS 2018). [ Code ] [ Poster ]
  • Liuyi Yao, Lu Su, Qi Li, Yaliang Li, Fenglong Ma, Jing Gao and Aidong Zhang. Online Truth Discovery on Time Series Data. Proceedings of the 2018 SIAM International Conference on Data Mining (SDM 2018).

Preprint

  • 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. ArXiv preprint arXiv:2206.03436.
  • 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. ArXiv preprint arXiv:2204.05562.
  • 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. ArXiv preprint arXiv:2204.05011.
  • Yaliang Li, Liuyi Yao, Nan Du, Jing Gao, Qi Li, Chuishi Meng, Chenwei Zhang, Wei Fan. Finding Similar Medical Questions from Question Answering Websites. ArXiv preprint arXiv:1810.05983.

Work Experience

Research Intern, May 2019 - Aug. 2019, IBM Thomas J. Watson Research Center, Yorktown Heights.

Staff, Oct 2020 - present, Alibaba DAMO Academy.