最先进的svd算法的相关参考文献有哪些

以下是一些最先进的SVD算法的相关参考文献：

1. Halko, N., Martinsson, P. G., & Tropp, J. A. (2011). Finding structure with randomness: Probabilistic algorithms for constructing approximate matrix decompositions. SIAM review, 53(2), 217-288.

2. Gower, J. C., & Lipovetsky, S. (2018). Matrix factorization for data analysis. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 8(2), e1233.

3. Sun, Y., Mahoney, M. W., & Yan, S. (2015). A provable approach for scalable and accurate tensor decomposition. In Advances in neural information processing systems (pp. 1513-1521).

4. Kuleshov, V., & Ermon, S. (2018). Tensor factorization via matrix factorization: A scalable optimization perspective. In Advances in Neural Information Processing Systems (pp. 1329-1339).

5. Arora, R., Hazan, E., & Kale, S. (2012). The multiplicative weights update method: a meta-algorithm and applications. Theory of Computing, 8(1), 121-164.