Average performance analysis of the stochastic gradient method for online PCA

Yoav Freund and Robert E Schapire, A decision-theoretic generalization of on-line learning and an application to boosting , Journal of computer and system sciences 55

1997

Earlier work this paper cites.

Shai Shalev-Shwartz et al., Online learning and online convex optimization , Foundations and Trends® in Machine Learning 4

2012

Earlier work this paper cites.

Suvrit Sra, Sebastian Nowozin, and Stephen J Wright, Optimization for machine learning , Mit Press, 2012

Original

2012

Earlier work this paper cites.

Afonso S Bandeira, Ten lectures and forty-two open problems in the mathematics of data science , 2015

2015

Earlier work this paper cites.

Hervé Cardot and David Degras, Online principal component analysis in high dimension: Which algorithm to choose? , arXiv preprint arXiv:1511.03688 (2015)

Original

2015

Cited alongside, same era.

Chi Jin, Sham M Kakade, Cameron Musco, Praneeth Netrapalli, and Aaron Sidford, Robust shift-and-invert preconditioning: Faster and more sample efficient algorithms for eigenvector computation , arXiv preprint arXiv:1510.08896 (2015)

Original

2015

Cited alongside, same era.

Haipeng Luo and Robert E Schapire, Achieving all with no parameters: Adanormalhedge , Conference on Learning Theory, 2015, pp. 1286–1304

2015

Cited alongside, same era.

Ohad Shamir, Convergence of stochastic gradient descent for pca , arXiv preprint arXiv:1509.09002 (2015)

Original

2015

Later among the works it cites.

Zeyuan Allen-Zhu and Yuanzhi Li, Lazysvd: Even faster svd decomposition yet without agonizing pain , Advances in Neural Information Processing Systems, 2016, pp. 974–982

2016

Later among the works it cites.

Elad Hazan et al., Introduction to online convex optimization , Foundations and Trends® in Optimization 2

2016

Later among the works it cites.