Additional Campus Affiliations
Assistant Professor, Statistics
External Links
Highlighted Publications
Agterberg, J., Lubberts, Z., & Priebe, C. E. (2022). Entrywise Estimation of Singular Vectors of Low-Rank Matrices With Heteroskedasticity and Dependence. IEEE Transactions on Information Theory, 68(7), 4618-4650. https://doi.org/10.1109/TIT.2022.3159085
Agterberg, J., & Sulam, J. (2022). Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms. Proceedings of Machine Learning Research, 151, 6591-6629.
Recent Publications
Agterberg, J., & Zhang, A. R. (Accepted/In press). Estimating Higher-Order Mixed Memberships via the l2,∞ Tensor Perturbation Bound. Journal of the American Statistical Association. https://doi.org/10.1080/01621459.2024.2404265
Alyakin, A. A., Agterberg, J., Helm, H. S., & Priebe, C. E. (2024). Correcting a nonparametric two-sample graph hypothesis test for graphs with different numbers of vertices with applications to connectomics. Applied Network Science, 9(1), Article 1. https://doi.org/10.1007/s41109-023-00607-x
Acharyya, A., Agterberg, J., Trosset, M. W., Park, Y., & Priebe, C. E. (2023). Semisupervised regression in latent structure networks on unknown manifolds. Applied Network Science, 8(1), Article 75. https://doi.org/10.1007/s41109-023-00598-9
Agterberg, J., Lubberts, Z., & Priebe, C. E. (2022). Entrywise Estimation of Singular Vectors of Low-Rank Matrices With Heteroskedasticity and Dependence. IEEE Transactions on Information Theory, 68(7), 4618-4650. https://doi.org/10.1109/TIT.2022.3159085
Agterberg, J., & Sulam, J. (2022). Entrywise Recovery Guarantees for Sparse PCA via Sparsistent Algorithms. Proceedings of Machine Learning Research, 151, 6591-6629.