On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems

Dan Garber. On the Convergence of Stochastic Gradient Descent with Low-Rank Projections for Convex Low-Rank Matrix Problems. In Jacob D. Abernethy, Shivani Agarwal 0001, editors, Conference on Learning Theory, COLT 2020, 9-12 July 2020, Virtual Event [Graz, Austria]. Volume 125 of Proceedings of Machine Learning Research, pages 1666-1681, PMLR, 2020. [doi]

References

No references recorded for this publication.

Cited by

No citations of this publication recorded.