Stochastic Chebyshev Gradient Descent for Spectral Optimization

Insu Han, Haim Avron, Jinwoo Shin

Neural Information Processing Systems 

Unfortunately, computing the gradient of a spectral function is generally of cubic complexity, as such gradient descent methods are rather expensive for optimizing objectives involving the spectral function.

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