| A machine learning approach for air quality prediction: Model regularization and optimization D Zhu, C Cai, T Yang, X Zhou Big data and cognitive computing 2 (1), 5, 2018 | 205 | 2018 |
| When auc meets dro: Optimizing partial auc for deep learning with non-convex convergence guarantee D Zhu, G Li, B Wang, X Wu, T Yang International Conference on Machine Learning, 27548-27573, 2022 | 31 | 2022 |
| A robust zero-sum game framework for pool-based active learning D Zhu, Z Li, X Wang, B Gong, T Yang AISTATS, 517-526, 2019 | 21 | 2019 |
| Deep unsupervised binary coding networks for multivariate time series retrieval D Zhu, D Song, Y Chen, C Lumezanu, W Cheng, B Zong, J Ni, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (02), 1403-1411, 2020 | 18 | 2020 |
| Libauc: A deep learning library for x-risk optimization Z Yuan, D Zhu, ZH Qiu, G Li, X Wang, T Yang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 15 | 2023 |
| Label distributionally robust losses for multi-class classification: Consistency, robustness and adaptivity D Zhu, Y Ying, T Yang International Conference on Machine Learning, 43289-43325, 2023 | 13* | 2023 |
| deBWT: parallel construction of Burrows–Wheeler Transform for large collection of genomes with de Bruijn-branch encoding B Liu, D Zhu, Y Wang Bioinformatics 32 (12), i174-i182, 2016 | 12 | 2016 |
| Benchmarking deep auroc optimization: Loss functions and algorithmic choices D Zhu, X Wu, T Yang arXiv preprint arXiv:2203.14177, 2022 | 10 | 2022 |
| Provable Multi-instance Deep AUC Maximization with Stochastic Pooling D Zhu, B Wang, Z Chen, Y Wang, M Sonka, X Wu, T Yang International Conference on Machine Learning, 43205-43227, 2023 | 4 | 2023 |
| Non-smooth weakly-convex finite-sum coupled compositional optimization Q Hu, D Zhu, T Yang Advances in Neural Information Processing Systems 36, 2023 | 4 | 2023 |
| Monitoring computing system status by implementing a deep unsupervised binary coding network D Song, Y Chen, C Lumezanu, T Mizoguchi, H Chen, D Zhu US Patent App. 17/002,960, 2021 | 1 | 2021 |
| Function Aligned Regression: A Method Explicitly Learns Functional Derivatives from Data D Zhu, L Jerby-Arnon arXiv preprint arXiv:2402.06104, 2024 | | 2024 |
| From distributionally robust optimization to broader machine learning applications D Zhu The University of Iowa, 2023 | | 2023 |
