Robust Matrix Completion with Heavy-tailed Noise
Author:
Affiliation:
1. Department of Operations Research and Financial Engineering, Princeton University
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/01621459.2024.2375037
Reference70 articles.
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2. P. Alquier V. Cottet and G. Lecué. Estimation bounds and sharp oracle inequalities of regularized procedures with lipschitz loss functions. The Annals of Statistics 47(4):2117–2144 2019.
3. G. Bassett Jr and R. Koenker. Asymptotic theory of least absolute error regression. Journal of the American Statistical Association 73(363):618–622 1978.
4. C. Brownlees E. Joly and G. Lugosi. Empirical risk minimization for heavy-tailed losses. The Annals of Statistics 43(6):2507–2536 2015.
5. S. Burer and R. D. Monteiro. A nonlinear programming algorithm for solving semidefinite programs via low-rank factorization. Mathematical Programming 95(2):329–357 2003.
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