Stochastic differential equations (3rd ed.): an introduction with applications
Stochastic differential equations (3rd ed.): an introduction with applications
Practical Issues in Temporal Difference Learning
Machine Learning
Fundamentals of Artificial Neural Networks
Fundamentals of Artificial Neural Networks
Pattern Recognition and Neural Networks
Pattern Recognition and Neural Networks
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We show that under reasonable conditions, online learning near a local minimum is similar to a multivariate Ornstein Uhlenbeck process. This implies that the parameter state oscillates randomly around the minimum point, with a Gaussian limiting distribution. We also develop a simple hypothesis test that detects Ornstein Uhlenbeck properties without storing the history of the learning process.