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2020 – today
- 2024
[j16]Mengnan Du, Fengxiang He, Na Zou, Dacheng Tao, Xia Hu:
Shortcut Learning of Large Language Models in Natural Language Understanding. Commun. ACM 67(1): 110-120 (2024)- [j15]Sirui Ding, Shenghan Zhang
, Xia Hu, Na Zou:
Identify and mitigate bias in electronic phenotyping: A comprehensive study from computational perspective. J. Biomed. Informatics 156: 104671 (2024) - [j14]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang:
Unifying Fourteen Post-Hoc Attribution Methods With Taylor Interactions. IEEE Trans. Pattern Anal. Mach. Intell. 46(7): 4625-4640 (2024) - [c24]Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu:
Chasing Fairness in Graphs: A GNN Architecture Perspective. AAAI 2024: 21214-21222 - [c23]Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu:
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods. ICLR 2024 - [c22]Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li:
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. KDD 2024: 621-630 - [i35]Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li:
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. CoRR abs/2407.19398 (2024) - [i34]Zhimeng Jiang, Zirui Liu, Xiaotian Han, Qizhang Feng, Hongye Jin, Qiaoyu Tan, Kaixiong Zhou, Na Zou, Xia Ben Hu:
Gradient Rewiring for Editable Graph Neural Network Training. CoRR abs/2410.15556 (2024) - 2023
- [j13]Can Li, Sirui Ding, Na Zou, Xia Hu, Xiaoqian Jiang, Kai Zhang:
Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling. J. Biomed. Informatics 143: 104399 (2023) - [j12]Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou:
Marginal Nodes Matter: Towards Structure Fairness in Graphs. SIGKDD Explor. 25(2): 4-13 (2023) - [j11]Mingyang Wan, Daochen Zha, Ninghao Liu, Na Zou:
In-Processing Modeling Techniques for Machine Learning Fairness: A Survey. ACM Trans. Knowl. Discov. Data 17(3): 35:1-35:27 (2023) - [j10]Xiaotian Han, Zhimeng Jiang, Hongye Jin, Zirui Liu, Na Zou, Qifan Wang, Xia Hu:
Retiring ΔDP: New Distribution-Level Metrics for Demographic Parity. Trans. Mach. Learn. Res. 2023 (2023) - [c21]Shenghan Zhang, Haoxuan Li, Ruixiang Tang, Sirui Ding, Laila Rasmy, Degui Zhi, Na Zou, Xia Hu:
PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data. ICHI 2023: 268-275 - [c20]Hongyi Ling, Zhimeng Jiang, Youzhi Luo, Shuiwang Ji, Na Zou:
Learning Fair Graph Representations via Automated Data Augmentations. ICLR 2023 - [c19]Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou:
Graph Mixup with Soft Alignments. ICML 2023: 21335-21349 - [c18]Guanchu Wang, Zirui Liu, Zhimeng Jiang, Ninghao Liu, Na Zou, Xia Ben Hu:
DIVISION: Memory Efficient Training via Dual Activation Precision. ICML 2023: 36036-36057 - [c17]Daochen Zha, Kwei-Herng Lai, Fan Yang, Na Zou, Huiji Gao, Xia Hu:
Data-centric AI: Techniques and Future Perspectives. KDD 2023: 5839-5840 - [c16]Qizhang Feng, Zhimeng Stephen Jiang, Ruiquan Li, Yicheng Wang, Na Zou, Jiang Bian, Xia Hu:
Fair Graph Distillation. NeurIPS 2023 - [c15]Zhimeng Stephen Jiang, Xiaotian Han, Hongye Jin, Guanchu Wang, Rui Chen, Na Zou, Xia Hu:
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach. NeurIPS 2023 - [c14]Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu:
Mitigating Algorithmic Bias with Limited Annotations. ECML/PKDD (2) 2023: 241-258 - [c13]Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li:
RELIANT: Fair Knowledge Distillation for Graph Neural Networks. SDM 2023: 154-162 - [i33]Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li:
RELIANT: Fair Knowledge Distillation for Graph Neural Networks. CoRR abs/2301.01150 (2023) - [i32]Xiaotian Han, Zhimeng Jiang, Hongye Jin, Zirui Liu, Na Zou, Qifan Wang, Xia Hu:
Retiring $Δ$DP: New Distribution-Level Metrics for Demographic Parity. CoRR abs/2301.13443 (2023) - [i31]Sirui Ding, Ruixiang Tang, Daochen Zha, Na Zou, Kai Zhang, Xiaoqian Jiang, Xia Hu:
Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning. CoRR abs/2302.09400 (2023) - [i30]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Ziwei Yang, Zheyang Li, Quanshi Zhang:
Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions. CoRR abs/2303.01506 (2023) - [i29]Zhimeng Jiang, Xiaotian Han, Hongye Jin, Guanchu Wang, Na Zou, Xia Ben Hu:
Weight Perturbation Can Help Fairness under Distribution Shift. CoRR abs/2303.03300 (2023) - [i28]Shenghan Zhang, Haoxuan Li, Ruixiang Tang, Sirui Ding, Laila Rasmy, Degui Zhi, Na Zou, Xia Hu:
PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data. CoRR abs/2303.10794 (2023) - [i27]Chia-Yuan Chang, Jiayi Yuan, Sirui Ding, Qiaoyu Tan, Kai Zhang, Xiaoqian Jiang, Xia Hu, Na Zou:
Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint. CoRR abs/2303.13790 (2023) - [i26]Sirui Ding, Qiaoyu Tan, Chia-Yuan Chang, Na Zou, Kai Zhang, Nathan R. Hoot, Xiaoqian Jiang, Xia Hu:
Multi-Task Learning for Post-transplant Cause of Death Analysis: A Case Study on Liver Transplant. CoRR abs/2304.00012 (2023) - [i25]Hongyi Ling, Zhimeng Jiang, Meng Liu, Shuiwang Ji, Na Zou:
Graph Mixup with Soft Alignments. CoRR abs/2306.06788 (2023) - [i24]Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu:
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods. CoRR abs/2306.09468 (2023) - [i23]Chia-Yuan Chang, Yu-Neng Chuang, Kwei-Herng Lai, Xiaotian Han, Xia Hu, Na Zou:
Towards Assumption-free Bias Mitigation. CoRR abs/2307.04105 (2023) - [i22]Yicheng Wang, Xiaotian Han, Leisheng Yu, Na Zou:
Beyond Fairness: Age-Harmless Parkinson's Detection via Voice. CoRR abs/2309.13292 (2023) - [i21]Chia-Yuan Chang, Yu-Neng Chuang, Zhimeng Jiang, Kwei-Herng Lai, Anxiao Jiang, Na Zou:
CODA: Temporal Domain Generalization via Concept Drift Simulator. CoRR abs/2310.01508 (2023) - [i20]Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou:
Marginal Nodes Matter: Towards Structure Fairness in Graphs. CoRR abs/2310.14527 (2023) - [i19]Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu:
Chasing Fairness in Graphs: A GNN Architecture Perspective. CoRR abs/2312.12369 (2023) - 2022
- [j9]Kang Wang, Zujun Ou, Hong Qin, Na Zou:
Projection Uniformity of Asymmetric Fractional Factorials. Axioms 11(12): 716 (2022) - [j8]Ruixiang Tang, Ninghao Liu, Fan Yang, Na Zou, Xia Hu:
Defense Against Explanation Manipulation. Frontiers Big Data 5: 704203 (2022) - [c12]Sirui Ding, Ruixiang Tang, Daochen Zha, Na Zou, Kai Zhang, Xiaoqian Jiang, Xia Hu:
Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning. AMIA 2022 - [c11]Daochen Zha, Kwei-Herng Lai, Qiaoyu Tan, Sirui Ding, Na Zou, Xia Ben Hu:
Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learning. CIKM 2022: 2476-2485 - [c10]Daochen Zha, Zaid Pervaiz Bhat, Yi-Wei Chen, Yicheng Wang, Sirui Ding, Jiaben Chen, Kwei-Herng Lai, Mohammad Qazim Bhat, Anmoll Kumar Jain, Alfredo Costilla-Reyes, Na Zou, Xia Hu:
AutoVideo: An Automated Video Action Recognition System. IJCAI 2022: 5952-5955 - [i18]Zhimeng Jiang, Xiaotian Han, Chao Fan, Zirui Liu, Na Zou, Ali Mostafavi, Xia Hu:
FMP: Toward Fair Graph Message Passing against Topology Bias. CoRR abs/2202.04187 (2022) - [i17]Qizhang Feng, Mengnan Du, Na Zou, Xia Hu:
Fair Machine Learning in Healthcare: A Review. CoRR abs/2206.14397 (2022) - [i16]Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu:
Mitigating Algorithmic Bias with Limited Annotations. CoRR abs/2207.10018 (2022) - [i15]Guanchu Wang, Zirui Liu, Zhimeng Jiang, Ninghao Liu, Na Zou, Xia Ben Hu:
Towards Memory Efficient Training via Dual Activation Precision. CoRR abs/2208.04187 (2022) - [i14]Mengnan Du, Fengxiang He, Na Zou, Dacheng Tao, Xia Hu:
Shortcut Learning of Large Language Models in Natural Language Understanding: A Survey. CoRR abs/2208.11857 (2022) - [i13]Daochen Zha, Kwei-Herng Lai, Qiaoyu Tan, Sirui Ding, Na Zou, Xia Ben Hu:
Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learning. CoRR abs/2208.12433 (2022) - [i12]Yu-Neng Chuang, Kwei-Herng Lai, Ruixiang Tang, Mengnan Du, Chia-Yuan Chang, Na Zou, Xia Hu:
Mitigating Relational Bias on Knowledge Graphs. CoRR abs/2211.14489 (2022) - 2021
- [j7]Mengnan Du, Fan Yang, Na Zou, Xia Hu:
Fairness in Deep Learning: A Computational Perspective. IEEE Intell. Syst. 36(4): 25-34 (2021) - [j6]Ronald S. Burt, Sonja Opper, Na Zou:
Social network and family business: Uncovering hybrid family firms. Soc. Networks 65: 141-156 (2021) - [c9]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu:
A Unified Taylor Framework for Revisiting Attribution Methods. AAAI 2021: 11462-11469 - [c8]Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu:
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. KDD 2021: 258-268 - [c7]Ruixiang Tang, Mengnan Du, Yuening Li, Zirui Liu, Na Zou, Xia Hu:
Mitigating Gender Bias in Captioning Systems. WWW 2021: 633-645 - [i11]Huiqi Deng, Na Zou, Weifu Chen, Guocan Feng, Mengnan Du, Xia Hu:
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. CoRR abs/2104.06629 (2021) - [i10]Daochen Zha, Zaid Pervaiz Bhat, Yi-Wei Chen, Yicheng Wang, Sirui Ding, Anmoll Kumar Jain, Mohammad Qazim Bhat, Kwei-Herng Lai, Jiaben Chen, Na Zou, Xia Hu:
AutoVideo: An Automated Video Action Recognition System. CoRR abs/2108.04212 (2021) - [i9]Mingyang Wan, Daochen Zha, Ninghao Liu, Na Zou:
Modeling Techniques for Machine Learning Fairness: A Survey. CoRR abs/2111.03015 (2021) - [i8]Ruixiang Tang, Ninghao Liu, Fan Yang, Na Zou, Xia Hu:
Defense Against Explanation Manipulation. CoRR abs/2111.04303 (2021) - 2020
- [c6]Zhengyang Wang, Na Zou, Dinggang Shen, Shuiwang Ji:
Non-Local U-Nets for Biomedical Image Segmentation. AAAI 2020: 6315-6322 - [c5]Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, Xia Hu:
Multi-Channel Graph Neural Networks. IJCAI 2020: 1352-1358 - [c4]Yuening Li, Daochen Zha, Praveen Kumar Venugopal, Na Zou, Xia Hu:
PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning. WWW (Companion Volume) 2020: 153-157 - [i7]Yuening Li, Daochen Zha, Praveen Kumar Venugopal, Na Zou, Xia Hu:
PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning. CoRR abs/2003.05602 (2020) - [i6]Huiqi Deng, Na Zou, Mengnan Du, Weifu Chen, Guocan Feng, Xia Hu:
A Unified Taylor Framework for Revisiting Attribution Methods. CoRR abs/2008.09695 (2020)
2010 – 2019
- 2019
- [c3]Yuening Li, Xiao Huang, Jundong Li, Mengnan Du, Na Zou:
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks. CIKM 2019: 2233-2236 - [c2]Hao Yuan, Na Zou, Shaoting Zhang, Hanchuan Peng, Shuiwang Ji:
Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction. ICDM 2019: 806-815 - [c1]Meng Zhang, Na Zou, Ge Cao, Chunxiao Li:
Modeling and simulation of human lower extremity motion. ICTC 2019: 107-109 - [i5]Yuening Li, Xiao Huang, Jundong Li, Mengnan Du, Na Zou:
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks. CoRR abs/1908.03849 (2019) - [i4]Mengnan Du, Fan Yang, Na Zou, Xia Hu:
Fairness in Deep Learning: A Computational Perspective. CoRR abs/1908.08843 (2019) - [i3]Yuening Li, Daochen Zha, Na Zou, Xia Hu:
PyODDS: An End-to-End Outlier Detection System. CoRR abs/1910.02575 (2019) - [i2]Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, Xia Hu:
Multi-Channel Graph Convolutional Networks. CoRR abs/1912.08306 (2019) - 2018
- [j5]Hande Cakin, Berk Görgülü, Mustafa Gökçe Baydogan, Na Zou, Jing Li:
A Data Adaptive Biological Sequence Representation for Supervised Learning. J. Heal. Informatics Res. 2(4): 448-471 (2018) - [j4]Na Zou, Jinwen Tian:
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 45(11A): 172-175 (2018) - [j3]Xiao Huang, Jundong Li, Na Zou, Xia Hu:
A General Embedding Framework for Heterogeneous Information Learning in Large-Scale Networks. ACM Trans. Knowl. Discov. Data 12(6): 70:1-70:24 (2018) - [i1]Zhengyang Wang, Na Zou, Dinggang Shen, Shuiwang Ji:
Global Deep Learning Methods for Multimodality Isointense Infant Brain Image Segmentation. CoRR abs/1812.04103 (2018) - 2015
- [b1]Na Zou:
A probabilistic framework of transfer learning - theory and application. Arizona State University, Tempe, USA, 2015 - [j2]Na Zou, Yun Zhu, Ji Zhu, Mustafa Gökçe Baydogan, Wei Wang, Jing Li:
A Transfer Learning Approach for Predictive Modeling of Degenerate Biological Systems. Technometrics 57(3): 362-373 (2015) - 2011
- [j1]Hong Qin, Na Zou, Shangli Zhang:
Design efficiency for minimum projection uniformity designs with two levels. J. Syst. Sci. Complex. 24(4): 761-768 (2011)
Coauthor Index
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last updated on 2024-11-27 21:19 CET by the dblp team
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