Na Zou

Orcid: 0000-0003-1984-795X

According to our database1, Na Zou authored at least 55 papers between 2011 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

On csauthors.net:

Bibliography

2024
Shortcut Learning of Large Language Models in Natural Language Understanding.
Commun. ACM, January, 2024

Chasing Fairness in Graphs: A GNN Architecture Perspective.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
In-Processing Modeling Techniques for Machine Learning Fairness: A Survey.
ACM Trans. Knowl. Discov. Data, April, 2023

Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling.
J. Biomed. Informatics, 2023

Marginal Nodes Matter: Towards Structure Fairness in Graphs.
CoRR, 2023

CODA: Temporal Domain Generalization via Concept Drift Simulator.
CoRR, 2023

Beyond Fairness: Age-Harmless Parkinson's Detection via Voice.
CoRR, 2023

Towards Assumption-free Bias Mitigation.
CoRR, 2023

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods.
CoRR, 2023

Multi-Task Learning for Post-transplant Cause of Death Analysis: A Case Study on Liver Transplant.
CoRR, 2023

Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint.
CoRR, 2023

Weight Perturbation Can Help Fairness under Distribution Shift.
CoRR, 2023

Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions.
CoRR, 2023

Retiring $Δ$DP: New Distribution-Level Metrics for Demographic Parity.
CoRR, 2023

RELIANT: Fair Knowledge Distillation for Graph Neural Networks.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Mitigating Algorithmic Bias with Limited Annotations.
Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fair Graph Distillation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Data-centric AI: Techniques and Future Perspectives.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

DIVISION: Memory Efficient Training via Dual Activation Precision.
Proceedings of the International Conference on Machine Learning, 2023

Graph Mixup with Soft Alignments.
Proceedings of the International Conference on Machine Learning, 2023

Learning Fair Graph Representations via Automated Data Augmentations.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data.
Proceedings of the 11th IEEE International Conference on Healthcare Informatics, 2023

2022
Defense Against Explanation Manipulation.
Frontiers Big Data, 2022

Mitigating Relational Bias on Knowledge Graphs.
CoRR, 2022

Shortcut Learning of Large Language Models in Natural Language Understanding: A Survey.
CoRR, 2022

Towards Memory Efficient Training via Dual Activation Precision.
CoRR, 2022

Fair Machine Learning in Healthcare: A Review.
CoRR, 2022

FMP: Toward Fair Graph Message Passing against Topology Bias.
CoRR, 2022

Projection Uniformity of Asymmetric Fractional Factorials.
Axioms, 2022

AutoVideo: An Automated Video Action Recognition System.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learning.
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning.
Proceedings of the AMIA 2022, 2022

2021
Social network and family business: Uncovering hybrid family firms.
Soc. Networks, 2021

Fairness in Deep Learning: A Computational Perspective.
IEEE Intell. Syst., 2021

Modeling Techniques for Machine Learning Fairness: A Survey.
CoRR, 2021

AutoVideo: An Automated Video Action Recognition System.
CoRR, 2021

Mitigating Gender Bias in Captioning Systems.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

A Unified Taylor Framework for Revisiting Attribution Methods.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning.
Proceedings of the Companion of The 2020 Web Conference 2020, 2020

Multi-Channel Graph Neural Networks.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

Non-Local U-Nets for Biomedical Image Segmentation.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Multi-Channel Graph Convolutional Networks.
CoRR, 2019

PyODDS: An End-to-End Outlier Detection System.
CoRR, 2019

Modeling and simulation of human lower extremity motion.
Proceedings of the 2019 International Conference on Information and Communication Technology Convergence, 2019

Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks.
Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

2018
A General Embedding Framework for Heterogeneous Information Learning in Large-Scale Networks.
ACM Trans. Knowl. Discov. Data, 2018

多特征融合红外舰船尾流检测方法研究 (Research on Multi Feature Fusion Infrared Ship Wake Detection).
计算机科学, 2018

A Data Adaptive Biological Sequence Representation for Supervised Learning.
J. Heal. Informatics Res., 2018

Global Deep Learning Methods for Multimodality Isointense Infant Brain Image Segmentation.
CoRR, 2018

2015
A probabilistic framework of transfer learning - theory and application.
PhD thesis, 2015

A Transfer Learning Approach for Predictive Modeling of Degenerate Biological Systems.
Technometrics, 2015

2011
Design efficiency for minimum projection uniformity designs with two levels.
J. Syst. Sci. Complex., 2011


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