| Techniques for interpretable machine learning M Du, N Liu, X Hu Communications of the ACM 63 (1), 68-77, 2019 | 689 | 2019 |
| Towards Explanation of DNN-based Prediction with Guided Feature Inversion M Du, N Liu, Q Song, X Hu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 106 | 2018 |
| An embarrassingly simple approach for trojan attack in deep neural networks R Tang, M Du, N Liu, F Yang, X Hu Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 64 | 2020 |
| Is a Single Vector Enough? Exploring Node Polysemy for Network Embedding N Liu, Q Tan, Y Li, H Yang, J Zhou, X Hu Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 61 | 2019 |
| Contextual Outlier Interpretation N Liu, D Shin, X Hu Proceedings of the 27th International Joint Conference on Artificial …, 2018 | 50 | 2018 |
| Accelerated local anomaly detection via resolving attributed networks N Liu, X Huang, X Hu Proceedings of the 26th International Joint Conference on Artificial …, 2017 | 50 | 2017 |
| Deep Representation Learning for Social Network Analysis Q Tan, N Liu, X Hu Frontiers in Big Data 2, 2, 2019 | 46 | 2019 |
| Adversarial Detection with Model Interpretation N Liu, H Yang, X Hu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 44 | 2018 |
| On Interpretation of Network Embedding via Taxonomy Induction N Liu, X Huang, J Li, X Hu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018 | 40 | 2018 |
| On Attribution of Recurrent Neural Network Predictions via Additive Decomposition M Du, N Liu, F Yang, S Ji, X Hu The Web Conference (WWW), 2019 | 37 | 2019 |
| Learning to Hash with Graph Neural Networks for Recommender Systems Q Tan, N Liu, X Zhao, H Yang, J Zhou, X Hu The Web Conference (WWW), 2020 | 34 | 2020 |
| An Interpretable Classification Framework for Information Extraction from Online Healthcare Forums J Gao, N Liu, M Lawley, X Hu Journal of Healthcare Engineering, 2017 | 34 | 2017 |
| Sparse-interest network for sequential recommendation Q Tan, J Zhang, J Yao, N Liu, J Zhou, H Yang, X Hu Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 31 | 2021 |
| Learning Credible Deep Neural Networks with Rationale Regularization M Du, N Liu, F Yang, X Hu IEEE International Conference on Data Mining (ICDM), 2019 | 31 | 2019 |
| Towards Interpretation of Recommender Systems with Sorted Explanation Paths F Yang, N Liu, S Wang, X Hu 2018 IEEE International Conference on Data Mining (ICDM), 667-676, 2018 | 24 | 2018 |
| Dynamic memory based attention network for sequential recommendation Q Tan, J Zhang, N Liu, X Huang, H Yang, J Zhou, X Hu Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4384-4392, 2021 | 21 | 2021 |
| Adversarial Attacks and Defenses: An Interpretation Perspective N Liu, M Du, R Guo, H Liu, X Hu ACM SIGKDD Explorations Newsletter, 2021 | 19* | 2021 |
| Machine learning to predict rapid progression of carotid atherosclerosis in patients with impaired glucose tolerance X Hu, PD Reaven, A Saremi, N Liu, MA Abbasi, H Liu, RQ Migrino, ... EURASIP Journal on Bioinformatics and Systems Biology 2016 (1), 14, 2016 | 19 | 2016 |
| EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks Y Dong, N Liu, B Jalaian, J Li The Web Conference (WWW), 2022 | 15 | 2022 |
| Representation Interpretation with Spatial Encoding and Multimodal Analytics N Liu, M Du, X Hu ACM International Conference on Web Search and Data Mining (WSDM), 2019 | 15 | 2019 |
Xia "Ben" HuAssociate Professor of Computer Science, Rice UniversityVerified email at rice.edu
