Publications

Random approximation and sampling

1. Ben Adcock, Bernhard Hientzsch, Akil Narayan, Yiming Xu, Hybrid least squares for learning functions from highly noisy data, arxiv (2025)
2. Tom Alberts, Yiming Xu, Qiang Ye, Joint stochastic localization and applications, arxiv (2025)
3. Osman A. Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan, Fast algorithms for least square problems with Kronecker lower subsets, arxiv (2025)
4. Reza Gheissari, Aukosh Jagannath, Yiming Xu, Finding planted cliques using gradient descent, SIAM J. Math. Data Sci. (2025)
5. Yiming Xu, Akil Narayan, Randomized weakly admissible meshes, J. Approx. Theory (2023)
6. Yiming Xu, Akil Narayan, Hoang Tran, Clayton G. Webster, Analysis of the ratio of l1 and l2 norms in compressed sensing, Appl. Comput. Harmon. Anal. (2021)

Statistical ranking

1. Pinjun Dong, Ruijian Han, Binyan Jiang, Yiming Xu, Statistical ranking with dynamic covariates, J. R. Stat. Soc. Ser. B Methodol. (2025)
2. Ruijian Han, Yiming Xu, A unified analysis of likelihood-based estimators in the Plackett-Luce model, Ann. Stat. (to appear)
3. Ruijian Han, Wenlu Tang, Yiming Xu, Statistical inference for pairwise comparison models, arxiv (2024)
4. Ruijian Han, Yiming Xu, Kani Chen, A general pairwise comparison model for extremely sparse networks, J. Amer. Statist. Assoc. (2023)

Archetypal analysis

1. Katy Craig, Braxton Osting, Dong Wang, Yiming Xu, Wasserstein archetypal analysis, Appl. Math. Opt. (2024)
2. Ruijian Han, Braxton Osting, Dong Wang, Yiming Xu, Probabilistic methods for approximate archetypal analysis, Inf. Inference (2023)
3. Braxton Osting, Dong Wang, Yiming Xu, Dominique Zosso, Consistency of archetypal analysis, SIAM J. Math. Data Sci. (2021)

Multifidelity methods

1. Thomas Dixon, Alex Gorodetsky, John Jakeman, Akil Narayan, Yiming Xu, Optimally balancing exploration and exploitation to automate multi-fidelity statistical estimation, arxiv (2025)
2. Ruijian Han, Boris Kramer, Dongjin Lee, Akil Narayan, Yiming Xu, An approximate control variates approach to multifidelity distribution estimation, SIAM/ASA J. Uncertain. Quantif. (2024)
3. Nuojin Cheng, Osman A. Malik, Yiming Xu, Stephen Becker, Alireza Doostan, Akil Narayan, Subsampling of parametric models with bi-fidelity boosting, SIAM/ASA J. Uncertain. Quantif. (2024)
4. Yiming Xu, Akil Narayan, Budget-limited distribution learning in multifidelity problems, Numer. Math. (2023)
5. Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan, A bandit-learning approach to multifidelity approximation, SIAM J. Sci. Comput. (2022)

Conference Proceedings

1. Zhitong Xu, Da Long, Yiming Xu, Guang Yang, Shandian Zhe, Houman Owhadi, Toward efficient kernel-based solvers for nonlinear PDEs, ICML (2025)
2. Shibo Li, Michael Penwarden, Yiming Xu, Conor Tillinghast, Akil Narayan, Robert M. Kirby, Shandian Zhe, Meta learning of interface conditions for multi-domain physics-informed neural networks, ICML (2023)
3. Zheng Wang, Yiming Xu, Conor Tillinghast, Shibo Li, Akil Narayan, Shandian Zhe, Nonparametric embeddings of sparse high-order interaction events, ICML (2022)