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On the Theoretical Properties of Noise Correlation in Stochastic Optimization
This generalizes processes based on Brownian motion, such as the Ornstein-Uhlenbeck process.
Anticorrelated Noise Injection for Improved Generalization
Injecting artificial noise into gradient descent (GD) is commonly employed to improve the performance of machine learning models.
Thiele's Differential Equation Based on Markov Jump Processes with Non-countable State Space
In modern life insurance, Markov processes in continuous time on a finite or at least countable state space have been over the years an important tool for the modelling of the states of an insured.
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