| SAFS: A deep feature selection approach for precision medicine MZ Nezhad, D Zhu, X Li, K Yang, P Levy 2016 IEEE international conference on bioinformatics and biomedicine (BIBM …, 2016 | 79 | 2016 |
| Explainable recommendation via interpretable feature mapping and evaluation of explainability D Pan, X Li, X Li, D Zhu arXiv preprint arXiv:2007.06133, 2020 | 50 | 2020 |
| On the Learning Property of Logistic and Softmax Losses for Deep Neural Networks X Li, X Li, D Pan, D Zhu AAAI 2020, 2020 | 23 | 2020 |
| Predicting clinical outcomes with patient stratification via deep mixture neural networks X Li, D Zhu, P Levy AMIA Summits on Translational Science Proceedings 2020, 367, 2020 | 21 | 2020 |
| Improving adversarial robustness via probabilistically compact loss with logit constraints X Li, X Li, D Pan, D Zhu Proceedings of the AAAI conference on artificial intelligence 35 (10), 8482-8490, 2021 | 19 | 2021 |
| Interpreting age effects of human fetal brain from spontaneous fMRI using deep 3D convolutional neural networks X Li, J Hect, M Thomason, D Zhu 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), 1424-1427, 2020 | 13 | 2020 |
| Leveraging auxiliary measures: a deep multi-task neural network for predictive modeling in clinical research X Li, D Zhu, P Levy BMC medical informatics and decision making 18, 45-53, 2018 | 10 | 2018 |
| Multinomial classification with class-conditional overlapping sparse feature groups X Li, D Zhu, M Dong Pattern Recognition Letters 101, 37-43, 2018 | 10 | 2018 |
| A novel procedure for statistical inference and verification of gene regulatory subnetwork H Gong, J Klinger, K Damazyn, X Li, S Huang BMC bioinformatics 16, 1-10, 2015 | 9 | 2015 |
| Sdt: A tree method for detecting patient subgroups with personalized risk factors X Li, D Zhu, M Dong, MZ Nezhad, A Janke, PD Levy AMIA Summits on Translational Science Proceedings 2017, 193, 2017 | 8 | 2017 |
| Robust feature selection via l2, 1-norm in finite mixture of regression X Li, D Zhu Pattern Recognition Letters 108, 15-22, 2018 | 7 | 2018 |
| Learning compact features via in-training representation alignment X Li, X Li, D Pan, Y Qiang, D Zhu Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8675-8683, 2023 | 4 | 2023 |
| Predictive deep network with leveraging clinical measure as auxiliary task X Li, D Zhu, P Levy 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2017 | 4 | 2017 |
| Hemodynamic profiles by non-invasive monitoring of cardiac index and vascular tone in acute heart failure patients in the emergency department: External validation and clinical … NE Harrison, S Meram, X Li, MB White, S Henry, S Gupta, D Zhu, P Pang, ... Plos one 17 (3), e0265895, 2022 | 3 | 2022 |
| Improve SGD Training via Aligning Mini-batches X Li, D Pan, X Li, D Zhu arXiv preprint arXiv:2002.09917, 2020 | 1 | 2020 |
| A Non-2-step Nilsystem With Linear Polynomial Complexity X Li, Z Ruifeng ADVANCES IN MATHEMATICS (CHINA) 43 (4), 2014 | | 2014 |
