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randomized orthogonal greedy algorithm

Randomized Greedy Algorithms for Neural Network Optimization in Solving Partial Differential Equations

Xiaofeng Xu, Ph.D. Student, Applied Mathematics and Computational Sciences
Jul 15, 17:00 - 19:00

B4 L5 R5220

PDEs optimization machine learning randomized orthogonal greedy algorithm

This thesis introduces the randomized orthogonal greedy algorithm (ROGA) to bridge the gap between theoretical and practical performance of shallow neural networks for solving partial differential equations by overcoming key optimization challenges to achieve provably optimal convergence rates.

Computer, Electrical and Mathematical Sciences and Engineering (CEMSE)

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