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引用“”的文章On the Complexity of Robust PCA and ℓ 1-Norm Low-Rank Matrix Approximation

标题/作者	年份
The why and how of nonnegative matrix factorization N Gillis Regularization, optimization, kernels, and support vector machines 12 (257 …	2014
Recovery guarantees for one-hidden-layer neural networks K Zhong, Z Song, P Jain, PL Bartlett, IS Dhillon International conference on machine learning, 4140-4149	2017
Nonnegative matrix factorization N Gillis Society for Industrial and Applied Mathematics	2020
Low rank approximation with entrywise l1-norm error Z Song, DP Woodruff, P Zhong Proceedings of the 49th Annual ACM SIGACT Symposium on Theory of Computing …	2017
An overview of robust subspace recovery G Lerman, T Maunu Proceedings of the IEEE 106 (8), 1380-1410	2018
Introduction to nonnegative matrix factorization N Gillis arXiv preprint arXiv:1703.00663	2017
Algorithms for $\ell_p $ low-rank approximation F Chierichetti, S Gollapudi, R Kumar, S Lattanzi, R Panigrahy, ... International Conference on Machine Learning, 806-814	2017
Learning discrete distributions from untrusted batches M Qiao, G Valiant arXiv preprint arXiv:1711.08113	2017
Approximation schemes for low-rank binary matrix approximation problems FV Fomin, PA Golovach, D Lokshtanov, F Panolan, S Saurabh ACM Transactions on Algorithms (TALG) 16 (1), 1-39	2019
Parameterized low-rank binary matrix approximation FV Fomin, PA Golovach, F Panolan Data Mining and Knowledge Discovery 34, 478-532	2020
Low-rank matrix approximation in the infinity norm N Gillis, Y Shitov Linear Algebra and its Applications 581, 367-382	2019
Low rank approximation of binary matrices: Column subset selection and generalizations C Dan, KA Hansen, H Jiang, L Wang, Y Zhou arXiv preprint arXiv:1511.01699	2015
Average Case Column Subset Selection for Entrywise $\ell_1 $-Norm Loss Z Song, D Woodruff, P Zhong Advances in Neural Information Processing Systems 32	2019
Computing large-scale matrix and tensor decomposition with structured factors: A unified nonconvex optimization perspective X Fu, N Vervliet, L De Lathauwer, K Huang, N Gillis IEEE Signal Processing Magazine 37 (5), 78-94	2020
A robust algorithm for classification and diagnosis of brain disease using local linear approximation and generalized autoregressive conditional heteroscedasticity model A Hamzenejad, S Jafarzadeh Ghoushchi, V Baradaran, A Mardani Mathematics 8 (8), 1268	2020
Risk source-based constructability appraisal using supervised machine learning D Kifokeris, Y Xenidis Automation in Construction 104, 341-359	2019
An empirical evaluation of sketching for numerical linear algebra Y Dahiya, D Konomis, DP Woodruff Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …	2018
Approximation Algorithms for $\ell_0 $-Low Rank Approximation K Bringmann, P Kolev, D Woodruff Advances in neural information processing systems 30	2017
Heuristic search algorithm for dimensionality reduction optimally combining feature selection and feature extraction B He, S Shah, C Maung, G Arnold, G Wan, H Schweitzer Proceedings of the AAAI conference on artificial intelligence 33 (01), 2280-2287	2019
Optimal analysis of subset-selection based l_p low-rank approximation C Dan, H Wang, H Zhang, Y Zhou, PK Ravikumar Advances in Neural Information Processing Systems 32	2019

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