Chen Zhao

Orcid: 0000-0002-6400-0048

Affiliations:
  • Baylor University, Waco, TX, USA
  • Kitware Inc. (former)
  • University of Texas at Dallas, TX, USA (former)


According to our database1, Chen Zhao authored at least 35 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness.
ACM Trans. Knowl. Discov. Data, July, 2024

FEED: Fairness-Enhanced Meta-Learning for Domain Generalization.
CoRR, 2024

GDDA: Semantic OOD Detection on Graphs under Covariate Shift via Score-Based Diffusion Models.
CoRR, 2024

Fair Data Generation via Score-based Diffusion Model.
CoRR, 2024

Graphs Generalization under Distribution Shifts.
CoRR, 2024

3rd Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM).
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI).
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Supervised Algorithmic Fairness in Distribution Shifts: A Survey.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Towards Counterfactual Fairness-aware Domain Generalization in Changing Environments.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models.
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.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024

2023
Fairness-Aware Domain Generalization under Covariate and Dependence Shifts.
CoRR, 2023

Pursuing Counterfactual Fairness via Sequential Autoencoder Across Domains.
CoRR, 2023

Towards Effective Semantic OOD Detection in Unseen Domains: A Domain Generalization Perspective.
CoRR, 2023

An Automated Vulnerability Detection Framework for Smart Contracts.
CoRR, 2023

2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Towards Fair Disentangled Online Learning for Changing Environments.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI).
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Multi-Label Temporal Evidential Neural Networks for Early Event Detection.
Proceedings of the IEEE International Conference on Acoustics, 2023

Open Set Action Recognition via Multi-Label Evidential Learning.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Adaptation Speed Analysis for Fairness-aware Causal Models.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Contrastive Representation Learning Based on Multiple Node-centered Subgraphs.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Layer Adaptive Deep Neural Networks for Out-of-Distribution Detection.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2022

Adaptive Fairness-Aware Online Meta-Learning for Changing Environments.
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).
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.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Fairness-Aware Online Meta-learning.
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.
Proceedings of the IEEE International Conference on Blockchain and Cryptocurrency, 2021

2020
A Reweighted Meta Learning Framework for Robust Few Shot Learning.
CoRR, 2020

A Primal-Dual Subgradient Approach for Fair Meta Learning.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Fair Meta-Learning For Few-Shot Classification.
Proceedings of the 2020 IEEE International Conference on Knowledge Graph, 2020

Unfairness Discovery and Prevention For Few-Shot Regression.
Proceedings of the 2020 IEEE International Conference on Knowledge Graph, 2020

2019
Rank-Based Multi-task Learning for Fair Regression.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019


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