Chen Zhao

According to our database, Chen Zhao authored at least 46 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools.

Minh-Hao Van, Prateek Verma, Chen Zhao, Xintao Wu

CoRR, June, 2025

Multi-Modal Foundation Models for Computational Pathology: A Survey.

Dong Li, Guihong Wan, Xintao Wu, Xinyu Wu, Xiaohui Chen, Yi He, Christine G. Lian, Peter K. Sorger, Yevgeniy R. Semenov, Chen Zhao

CoRR, March, 2025

A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks.

Dong Li, Guihong Wan, Xintao Wu, Xinyu Wu, Ajit Johnson Nirmal, Christine G. Lian, Peter K. Sorger, Yevgeniy R. Semenov, Chen Zhao

CoRR, January, 2025

Out-of-distribution detection in heterogeneous graphs via energy propagation.

Tao Yin, Chen Zhao, Xiaoyan Liu, Minglai Shao

Knowl. Based Syst., 2025

Evidence-Based Out-of-Distribution Detection on Multi-Label Graphs.

Ruomeng Ding, Xujiang Zhao, Chen Zhao, Minglai Shao, Zhengzhang Chen, Haifeng Chen

Proceedings of the 2025 SIAM International Conference on Data Mining, 2025

MLDGG: Meta-Learning for Domain Generalization on Graphs.

Qin Tian, Chen Zhao, Minglai Shao, Wenjun Wang, Yujie Lin, Dong Li

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

Hypergraph-Based Dynamic Graph Node Classification.

Xiaoxu Ma, Chen Zhao, Minglai Shao, Yujie Lin

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

GDDA: Semantic OOD Detection on Graphs under Covariate Shift via Score-Based Diffusion Models.

Zhixia He, Chen Zhao, Minglai Shao, Yujie Lin, Dong Li, Qin Tian

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Let The Jury Decide: Fair Demonstration Selection for In-Context Learning through Incremental Greedy Evaluation.

Sadaf Md. Halim, Chen Zhao, Xintao Wu, Latifur Khan, Christan Grant, Fariha Ishrat Rahman, Feng Chen

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Multi-View Unsupervised Column Subset Selection via Combinatorial Search (Student Abstract).

Guihong Wan, Ninghui Hao, Crystal Maung, Haim Schweitzer, Chen Zhao, Kun-Hsing Yu, Yevgeniy R. Semenov

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness.

Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen

ACM Trans. Knowl. Discov. Data, July, 2024

Fair In-Context Learning via Latent Concept Variables.

Karuna Bhaila, Minh-Hao Van, Kennedy Edemacu, Chen Zhao, Feng Chen, Xintao Wu

CoRR, 2024

MADOD: Generalizing OOD Detection to Unseen Domains via G-Invariance Meta-Learning.

Haoliang Wang, Chen Zhao, Feng Chen

CoRR, 2024

FEED: Fairness-Enhanced Meta-Learning for Domain Generalization.

Kai Jiang, Chen Zhao, Haoliang Wang, Feng Chen

CoRR, 2024

Fair Data Generation via Score-based Diffusion Model.

Yujie Lin, Dong Li, Chen Zhao, Minglai Shao

CoRR, 2024

Graphs Generalization under Distribution Shifts.

Qin Tian, Wenjun Wang, Chen Zhao, Minglai Shao, Wang Zhang, Dong Li

CoRR, 2024

3rd Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM).

Xujiang Zhao, Chen Zhao, Feng Chen, Jin-Hee Cho, Wei Hua, Haifeng Chen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI).

Chen Zhao, Feng Chen, Xintao Wu, Jundong Li, Haifeng Chen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously.

Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Supervised Algorithmic Fairness in Distribution Shifts: A Survey.

Minglai Shao, Dong Li, Chen Zhao, Xintao Wu, Yujie Lin, Qin Tian

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Towards Counterfactual Fairness-aware Domain Generalization in Changing Environments.

Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models.

Aneesh Komanduri, Chen Zhao, Feng Chen, Xintao Wu

Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

Learning Fair Invariant Representations under Covariate and Correlation Shifts Simultaneously.

Dong Li, Chen Zhao, Minglai Shao, Wenjun Wang

Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023

Fairness-Aware Domain Generalization under Covariate and Dependence Shifts.

Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen

CoRR, 2023

Pursuing Counterfactual Fairness via Sequential Autoencoder Across Domains.

Yujie Lin, Chen Zhao, Minglai Shao, Baoluo Meng, Xujiang Zhao, Haifeng Chen

CoRR, 2023

Towards Effective Semantic OOD Detection in Unseen Domains: A Domain Generalization Perspective.

Haoliang Wang, Chen Zhao, Yunhui Guo, Kai Jiang, Feng Chen

CoRR, 2023

An Automated Vulnerability Detection Framework for Smart Contracts.

Feng Mi, Chen Zhao, Zhuoyi Wang, Sadaf Md. Halim, Xiaodi Li, Zhouxiang Wu, Latifur Khan, Bhavani Thuraisingham

CoRR, 2023

2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making.

Xujiang Zhao, Chen Zhao, Feng Chen, Jin-Hee Cho, Haifeng Chen

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Towards Fair Disentangled Online Learning for Changing Environments.

Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI).

Chen Zhao, Feng Chen, Xintao Wu, Haifeng Chen, Jiayu Zhou

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Multi-Label Temporal Evidential Neural Networks for Early Event Detection.

Xujiang Zhao, Xuchao Zhang, Chen Zhao, Jin-Hee Cho, Lance M. Kaplan, Dong Hyun Jeong, Audun Jøsang, Haifeng Chen, Feng Chen

Proceedings of the IEEE International Conference on Acoustics, 2023

Open Set Action Recognition via Multi-Label Evidential Learning.

Chen Zhao, Dawei Du, Anthony Hoogs, Christopher Funk

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Adaptation Speed Analysis for Fairness-aware Causal Models.

Yujie Lin, Chen Zhao, Minglai Shao, Xujiang Zhao, Haifeng Chen

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Contrastive Representation Learning Based on Multiple Node-centered Subgraphs.

Dong Li, Wenjun Wang, Minglai Shao, Chen Zhao

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Layer Adaptive Deep Neural Networks for Out-of-Distribution Detection.

Haoliang Wang, Chen Zhao, Xujiang Zhao, Feng Chen

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Adaptive Fairness-Aware Online Meta-Learning for Changing Environments.

Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD22).

Chen Zhao, Feng Chen, Xintao Wu, Christopher Funk, Anthony Hoogs

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

A Nested Bi-level Optimization Framework for Robust Few Shot Learning.

KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Feng Chen, Rishabh K. Iyer

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining.

Zhuoyi Wang, Yuqiao Chen, Chen Zhao, Yu Lin, Xujiang Zhao, Hemeng Tao, Yigong Wang, Latifur Khan

Proceedings of the WWW '21: The Web Conference 2021, 2021

Fairness-Aware Online Meta-learning.

Chen Zhao, Feng Chen, Bhavani Thuraisingham

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

VSCL: Automating Vulnerability Detection in Smart Contracts with Deep Learning.

Feng Mi, Zhuoyi Wang, Chen Zhao, Jinghui Guo, Fawaz Ahmed, Latifur Khan

Proceedings of the IEEE International Conference on Blockchain and Cryptocurrency, 2021

2020

A Reweighted Meta Learning Framework for Robust Few Shot Learning.

KrishnaTeja Killamsetty, Changbin Li, Chen Zhao, Rishabh K. Iyer, Feng Chen

CoRR, 2020

A Primal-Dual Subgradient Approach for Fair Meta Learning.

Chen Zhao, Feng Chen, Zhuoyi Wang, Latifur Khan

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Fair Meta-Learning For Few-Shot Classification.

Chen Zhao, Changbin Li, Jincheng Li, Feng Chen

Proceedings of the 2020 IEEE International Conference on Knowledge Graph, 2020

Unfairness Discovery and Prevention For Few-Shot Regression.

Chen Zhao, Feng Chen

Proceedings of the 2020 IEEE International Conference on Knowledge Graph, 2020

2019

Rank-Based Multi-task Learning for Fair Regression.

Chen Zhao, Feng Chen

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019