Publications

Randomized sampling and approximation

1. Katy Craig, Braxton Osting, Dong Wang, Yiming Xu, Wasserstein archetypal analysis, Appl. Math. Opt. (2024)
2. Reza Gheissari, Aukosh Jagannath, Yiming Xu, Finding planted cliques using Markov chain Monte Carlo, arxiv (2023)
3. Yiming Xu, Akil Narayan, Randomized weakly admissible meshes, J. Approx. Theory (2023)
4. Osman A. Malik, Yiming Xu, Nuojin Cheng, Stephen Becker, Alireza Doostan, Akil Narayan, Fast algorithms for monotone lower subsets of Kronecker least squares problems, arxiv (2022)
5. Ruijian Han, Braxton Osting, Dong Wang, Yiming Xu, Probabilistic methods for approximate archetypal analysis, Inf. Inference (2022)
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)
7. Braxton Osting, Dong Wang, Yiming Xu, Dominique Zosso, Consistency of archetypal analysis, SIMODS (2021)

Comparison data analysis and choice models

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

Multifidelity methods

1. 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)
2. 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)
3. Yiming Xu, Akil Narayan, Budget-limited distribution learning in multifidelity problems, Numer. Math. (2023)
4. Yiming Xu, Vahid Keshavarzzadeh, Robert M. Kirby, Akil Narayan, A bandit-learning approach to multifidelity approximation, SIAM J. Sci. Comput. (2022)

Others

1. Zhitong Xu, Da Long, Yiming Xu, Guang Yang, Shandian Zhe, Houman Owhadi, Toward Efficient Kernel-Based Solvers for Nonlinear PDEs, arxiv (2024)
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)