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This work provides improved guarantees for streaming principle component analysis (PCA).
T. Krasulina, “Method of stochastic approximation in the determination of the largest eigenvalue of the mathematical expectation of random matrices,” Automatation and Remote Control , pp. 50–56, 1970
1970
Earlier work this paper cites.
P.-Å. Wedin, “Perturbation bounds in connection with singular value decomposition,” BIT Numerical Mathematics , vol. 12, no. 1, pp. 99–111, 1972
1972
Earlier work this paper cites.
E. Oja, “Simplified neuron model as a principal component analyzer,” Journal of mathematical biology , vol. 15, no. 3, pp. 267–273, 1982
1982
Earlier work this paper cites.
P. M. Hall, A. D. Marshall, and R. R. Martin, “Incremental eigenanalysis for classification.” in BMVC , vol. 98. Citeseer, 1998, pp. 286–295
1998
Earlier work this paper cites.
I. M. Johnstone, “On the distribution of the largest eigenvalue in principal components analysis,” Annals of statistics , pp. 295–327, 2001
2001
Earlier work this paper cites.
I. Jolliffe, Principal component analysis . Wiley Online Library, 2002
2002
Earlier work this paper cites.
J. Weng, Y. Zhang, and W.-S. Hwang, “Candid covariance-free incremental principal component analysis,” Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol. 25, no. 8, pp. 1034–1040, 2003
2003
Earlier work this paper cites.
M. K. Warmuth and D. Kuzmin, “Randomized PCA algorithms with regret bounds that are logarithmic in the dimension,” in Advances in Neural Information Processing Systems 19, Proceedings of the Twentieth Annual Conference on Neural Information Processing Systems, Vancouver, British Columbia, Canada, December 4-7, 2006 , 2006, pp. 1481–1488
2006
Earlier work this paper cites.
D. A. Ross, J. Lim, R.-S. Lin, and M.-H. Yang, “Incremental learning for robust visual tracking,” International Journal of Computer Vision , vol. 77, no. 1-3, pp. 125–141, 2008
2008
Earlier work this paper cites.
K. L. Clarkson and D. P. Woodruff, “Numerical linear algebra in the streaming model,” in Proceedings of the forty-first annual ACM symposium on Theory of computing . ACM, 2009, pp. 205–214
2009
Cited alongside, same era.
2010
Cited alongside, same era.
M. Cohen, Y. T. Lee, G. Miller, J. Pachocki, and A. Sidford, “Geometric median in nearly linear time,” To Appear in 48th Annual Symposium on the Theory of Computing (STOC) 2016 , 2010
2010
Cited alongside, same era.
J. A. Tropp, “User-friendly tail bounds for sums of random matrices,” Foundations of Computational Mathematics , vol. 12, no. 4, pp. 389–434, 2012
2012
Cited alongside, same era.
G. H. Golub and C. F. Van Loan, Matrix computations . JHU Press, 2012, vol. 3
M. Hardt and E. Price, “The noisy power method: A meta algorithm with applications,” in Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada , 2014, pp. 2861–2869
2014
Later among the works it cites.
C. D. Sa, C. Re, and K. Olukotun, “Global convergence of stochastic gradient descent for some non-convex matrix problems,” in Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015 , 2015, pp. 2332–2341
2015
Later among the works it cites.
2015
Later among the works it cites.
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2012
Cited alongside, same era.
A. Balsubramani, S. Dasgupta, and Y. Freund, “The fast convergence of incremental pca,” in Advances in Neural Information Processing Systems , 2013, pp. 3174–3182
2013
Cited alongside, same era.
I. Mitliagkas, C. Caramanis, and P. Jain, “Memory limited, streaming pca,” in Advances in Neural Information Processing Systems , 2013, pp. 2886–2894
2013
Cited alongside, same era.
E. Liberty, “Simple and deterministic matrix sketching,” in Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining . ACM, 2013, pp. 581–588
2013
Cited alongside, same era.
J. Nelson and H. L. Nguyên, “Osnap: Faster numerical linear algebra algorithms via sparser subspace embeddings,” in Foundations of Computer Science (FOCS), 2013 IEEE 54th Annual Symposium on . IEEE, 2013, pp. 117–126
2013
Cited alongside, same era.
2015
Later among the works it cites.
2015
Later among the works it cites.
C. Boutsidis, D. Garber, Z. Karnin, and E. Liberty, “Online principal components analysis,” in Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms . SIAM, 2015, pp. 887–901
2015
Later among the works it cites.
O. Shamir, “A stochastic PCA and SVD algorithm with an exponential convergence rate,” in Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015 , 2015, pp. 144–152
2015
Later among the works it cites.
2015
Later among the works it cites.