arXiv (Cornell University)· 2015· Preprint
Escaping From Saddle Points --- Online Stochastic Gradient for Tensor\n Decomposition
- 611citations
- 2015year
Short summary
This paper introduces a novel stochastic gradient descent method that guarantees convergence to a local minimum for non-convex functions, a significant improvement over existing methods prone to saddle points.
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Computational MathematicsMathematics