O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions Gen Li*, Yuling Yan* (*=equal contribution) accepted to Journal of Machine Learning Research (conditioned on minor revisions), 2025 accepted in part to International Conference on Learning Representations (ICLR 2025)
The Isotonic Mechanism for Exponential Family Estimation in Machine Learning Peer Review Yuling Yan, Weijie J. Su, Jianqing Fan accepted to Journal of the Royal Statistical Society: Series B, 2025
Analysis of the ICML 2023 Ranking Data: Can Authors’ Opinions of Their Own Papers Assist Peer Review in Machine Learning? Buxin Su, Jiayao Zhang, Natalie Collina, Yuling Yan, Didong Li, Kyunghyun Cho, Jianqing Fan, Aaron Roth, Weijie J. Su accepted to Journal of the American Statistical Association, 2025
Learning Gaussian Mixtures Using the Wasserstein-Fisher-Rao Gradient Flow Yuling Yan*, Kaizheng Wang*, Philippe Rigollet (*=equal contribution) Annals of Statistics, vol. 52, no. 4, pp. 1774-1795, 2024
Inference for Heteroskedastic PCA with Missing Data Yuling Yan, Yuxin Chen, Jianqing Fan Annals of Statistics, vol. 52, no. 2, pp. 729–756, 2024
Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models Gen Li*, Yuling Yan* (*=equal contribution) Neural Information Processing Systems (NeurIPS), 2024
Model-Based Reinforcement Learning for Offline Zero-Sum Markov Games Yuling Yan, Gen Li, Yuxin Chen, Jianqing Fan Operations Research, vol. 72, no.6, pp. 2430-2445, 2024
Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning Gen Li, Yuling Yan, Yuxin Chen, Jianqing Fan Conference on Learning Theory (COLT), 2024
The Efficacy of Pessimism in Asynchronous Q-learning Yuling Yan, Gen Li, Yuxin Chen, Jianqing Fan IEEE Transactions on Information Theory, vol. 69, no. 11, pp. 7185-7219, 2023
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution Yuxin Chen, Jianqing Fan, Bingyan Wang, Yuling Yan (alphabetical order) Journal of the American Statistical Association, vol. 118, no. 542, pp. 858-868, 2023
Bridging Convex and Nonconvex Optimization in Robust PCA: Noise, Outliers, and Missing Data Yuxin Chen, Jianqing Fan, Cong Ma, Yuling Yan (alphabetical order) Annals of Statistics, vol. 49, no. 5, pp. 2948-2971, 2021
Sample-Efficient Reinforcement Learning for Linearly-Parameterized MDPs with a Generative Model Bingyan Wang*, Yuling Yan*, Jianqing Fan (*=equal contribution) Neural Information Processing Systems (NeurIPS), 2021
Noisy Matrix Completion: Understanding Statistical Guarantees for Convex Relaxation via Nonconvex Optimization Yuxin Chen, Yuejie Chi, Jianqing Fan, Cong Ma, Yuling Yan (alphabetical order) SIAM Journal on Optimization, vol. 30, no. 4, pp. 3098-3121, 2020
Efficient Clustering for Stretched Mixtures: Landscape and Optimality Kaizheng Wang, Yuling Yan, Mateo Díaz Neural Information Processing Systems (NeurIPS), 2020
Asymptotic Seed Bias in Respondent-driven Sampling Yuling Yan, Bret Hanlon, Sebastien Roch, Karl Rohe Electronic Journal of Statistics, vol. 14, no. 1, pp. 1577-1610, 2020
Inference and Uncertainty Quantification for Noisy Matrix Completion Yuxin Chen, Jianqing Fan, Cong Ma, Yuling Yan (alphabetical order) Proceedings of the National Academy of Sciences, vol. 116, no. 46, pp. 22931-22937, 2019
Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning Gen Li, Yuling Yan, Yuxin Chen, Jianqing Fan arXiv preprint arXiv:2304.07278, under revision at Mathematics of Operations Research, 2025 (accepted in part to COLT 2024)
O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions Gen Li*, Yuling Yan* (*=equal contribution) arXiv preprint arXiv:2409.18959, 2024 (accepted in part to ICLR 2025)
Entrywise Inference for Missing Panel Data: A Simple and Instance-Optimal Approach Yuling Yan, Martin J. Wainwright arXiv preprint arXiv:2401.13665, 2024
Inference under Staggered Adoption: Case Study of the Affordable Care Act Eric Xia*, Yuling Yan*, Martin J. Wainwright (*=equal contribution) arXiv preprint arXiv:2412.09482, 2024
When Can Weak Latent Factors Be Statistically Inferred? Yuheng Zheng, Yuling Yan, Jianqing Fan (alphabetical order) arXiv preprint arXiv:2407.03616, 2024
A Score-Based Density Formula, with Applications in Diffusion Generative Models Gen Li*, Yuling Yan* (*=equal contribution) arXiv preprint arXiv:2408.16765, 2024
Adaptivity and Convergence of Probability Flow ODEs in Diffusion Generative Models Jiaqi Tang, Yuling Yan arXiv preprint arXiv:2501.18863, 2025
Statistical Learning and Optimal Decision Making under Uncertainty Yuling Yan Ph.D. thesis, Princeton University, 202