Stochastic Gradient Descent in Continuous Time: A Central Limit Theorem

11 Oct 2017Justin SirignanoKonstantinos Spiliopoulos

Stochastic gradient descent in continuous time (SGDCT) provides a computationally efficient method for the statistical learning of continuous-time models, which are widely used in science, engineering, and finance. The SGDCT algorithm follows a (noisy) descent direction along a continuous stream of data... (read more)

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