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On the Existence of Global Minima and Convergence Analyses for Gradient Descent Methods in the Training of Deep Neural Networks
Arnulf Jentzen, Adrian Riekert
2022-07-06
41390
4206
Pages:141-246
Open-access
Convergence of Stochastic Gradient Descent under a Local Ćojasiewicz Condition for Deep Neural Networks
Jing An, Jianfeng Lu
2025-06-03
8323
752
Pages:89-107
Open-access
A Local Convergence Theory for the Stochastic Gradient Descent Method in Non-Convex Optimization with Non-Isolated Local Minima
Taehee Ko, Xiantao Li
2023-06-06
26126
2446
Pages:138-160
Open-access
A Deep Uzawa-Lagrange Multiplier Approach for Boundary Conditions in PINNs and Deep Ritz Methods
Charalambos G. Makridakis, Aaron Pim, Tristan Pryer
2025-09-12
22854
266
Pages:166-191
Open-access
Convergence Analysis of Discrete Diffusion Model: Exact Implementation Through Uniformization
Hongrui Chen, Lexing Ying
2025-06-03
8373
724
Pages:108-127
Open-access
Approximation Results for Gradient Flow Trained Neural Networks
Gerrit Welper
2024-06-27
25011
2369
Pages:107-175
Open-access
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