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mirror descent part1

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Evolution of Mirror Descent part1(Machine Learning Optimization)

#artificialintelligenceDec-9-2022, 21:30:31 GMT

Abstract: Mirror descent is a gradient descent method that uses a dual space of parametric models. The great idea has been developed in convex optimization, but not yet widely applied in machine learning. In this study, we provide a possible way that the mirror descent can help data-driven parameter initialization of neural networks. Abstract: The stochastic mirror descent (SMD) algorithm is a general class of training algorithms, which includes the celebrated stochastic gradient descent (SGD), as a special case. It utilizes a mirror potential to influence the implicit bias of the training algorithm.

descent, machine learning optimization, mirror descent part1, (7 more...)

#artificialintelligence

Genre: Research Report > New Finding (0.38)

Technology: Information Technology > Artificial Intelligence > Machine Learning > Statistical Learning > Gradient Descent (0.83)

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