Additional Campus Affiliations
Professor, Siebel School of Computing and Data Science
Professor, Statistics
Recent Publications
Hao, Y., & Zhang, T. (2026). The Surprising Harmfulness of Benign Overfitting for Adversarial Robustness. IEEE Transactions on Information Theory, 72(8), 6023-6053. https://doi.org/10.1109/TIT.2026.3702992
Ye, H., Xiong, W., & Zhang, T. (2026). PMGT-VR: A Decentralized Proximal-Gradient Algorithmic Framework With Variance Reduction. IEEE transactions on pattern analysis and machine intelligence, 48(1), 408-420. https://doi.org/10.1109/TPAMI.2025.3606874
Zhang, J., Pan, R., Hu, Y., Shum, K. S., Yao, G., Liu, X., Pi, R., Dong, H., Diao, S., Lin, Y., Zhao, H., & Zhang, T. (2026). An Improved Autoregressive Evaluation Paradigm for Large Language Models. ACM Transactions on Intelligent Systems and Technology, 17(4), Article 80. https://doi.org/10.1145/3763000
Hao, Y., Pan, X., Zhang, H., Ye, C., Pan, R., & Zhang, T. (2025). Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods. Proceedings of Machine Learning Research, 267, 22116-22148.
Lin, Y., Liu, C., Ye, C., Lian, Q., Yao, Y., & Zhang, T. (2025). Optimal Sample Selection Through Uncertainty Estimation and Its Application in Deep Learning. Journal of Machine Learning Research, 26.