Support Union Recovery in Meta Learning of Gaussian Graphical Models. - Qian Zhang 067; Yilin Zheng; Jean Honorio (CoRR, 2020)

Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation. - Qian Zhang 067; Yilin Zheng; Jean Honorio (ICML, 2021)

Functional Linear Regression of CDFs. - Qian Zhang 067; Anuran Makur; Kamyar Azizzadenesheli (CoRR, 2022)

Non-reversible Parallel Tempering for Deep Posterior Approximation. - Wei Deng 002; Qian Zhang 067; Qi Feng 005; Faming Liang; Guang Lin 001 (AAAI, 2023)

Universal Rates for Multiclass Learning. - Steve Hanneke; Shay Moran; Qian Zhang 067 (COLT, 2023)

Reward Selection with Noisy Observations. - Kamyar Azizzadenesheli; Trung Dang; Aranyak Mehta; Alexandros Psomas 001; Qian Zhang 067 (CoRR, 2023)

Improved Sample Complexity for Multiclass PAC Learning. - Steve Hanneke; Shay Moran; Qian Zhang 067 (NeurIPS, 2024)

On Convergence of Federated Averaging Langevin Dynamics. - Wei Deng 002; Qian Zhang 067; Yian Ma; Zhao Song 002; Guang Lin 001 (UAI, 2024)

Sparse Contextual CDF Regression. - Kamyar Azizzadenesheli; William Lu; Anuran Makur; Qian Zhang 067 (Trans. Mach. Learn. Res., 2024)

Functional Linear Regression of Cumulative Distribution Functions. - Qian Zhang 067; Anuran Makur; Kamyar Azizzadenesheli (Trans. Mach. Learn. Res., 2024)

Bayesian Federated Learning with Hamiltonian Monte Carlo: Algorithm and Theory. - Jiajun Liang; Qian Zhang 067; Wei Deng 002; Qifan Song; Guang Lin 001 (J. Comput. Graph. Stat., 2025)