A General Framework for Accurate and Private Mean Estimation
Zhouhao Yang, Xingyu Xu, and Yuantao Gu. "A general framework for accurate and private mean estimation." IEEE Signal Processing Letters 29 (2022): 2293-2297.
Zhouhao Yang’s Curriculum Vitae
Zhouhao Yang, Xingyu Xu, and Yuantao Gu. "A general framework for accurate and private mean estimation." IEEE Signal Processing Letters 29 (2022): 2293-2297.
Zhouhao Yang, et al. "Distributionally robust policy gradient for offline contextual bandits." International Conference on Artificial Intelligence and Statistics. PMLR, 2023.
Qianli Shen, Yezhen Wang, Zhouhao Yang, Xiang Li, Haonan Wang, Yang Zhang, Jonathan Scarlett, Zhanxing Zhu, Kenji Kawaguchi, "Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization." The Thirty-Eighth Annual Conference on Neural Information Processing Systems, 2024.
Zheyuan Hu*, Zhouhao Yang*, Yezhen Wang*, George Em Karniadakis, Kenji Kawaguchi, "Bias-Variance Trade-off in Physics-Informed Neural Networks with Randomized Smoothing for High-Dimensional PDEs." SIAM Journal on Scientific Computing 47.4 (2025): C846-C872.
Haoyang Cao*, Yuchao Dong*, Zhouhao Yang*, "A Two-fold Randomization Framework for Impulse Control Problems." To appear in SIAM Journal on Control and Optimization, 2026.
Zhouhao Yang*, Yezhen Wang*, Kenji Kawaguchi, Vladimir Braverman, Haoyang Cao, "Heavy-Tailed Flow Matching via Random Clocks." Accepted and to appear in NeurIPS 2026.
Yezhen Wang*, Zhouhao Yang*, Fanyi Pu, Kenji Kawaguchi, "Unlocking More Granular Control of Memory-Efficient LLM Finetuning." Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-26), pp. 4985–4993, 2026. doi: 10.24963/ijcai.2026/555.
Yan Hao Ling, Zhouhao Yang, Jonathan Scarlett, "Statistical Mean Estimation with Coded Relayed Observations." IEEE Transactions on Information Theory, vol. 72, no. 10, pp. 7329–7343, 2026. doi: 10.1109/TIT.2026.3716635.
Zhouhao Yang*, Nan Chen*, Soufiane Hayou, "Training-Free versus Training-Based Intent Classification in LLMs: Accuracy, Robustness, and Failure Modes." in Third Conference on Language Modeling, 2026.