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A Note on the Global Convergence of Multilayer Neural Networks in the
  Mean Field Regime

A Note on the Global Convergence of Multilayer Neural Networks in the Mean Field Regime

16 June 2020
H. Pham
Phan-Minh Nguyen
    MLTAI4CE
ArXiv (abs)PDFHTML

Papers citing "A Note on the Global Convergence of Multilayer Neural Networks in the Mean Field Regime"

4 / 4 papers shown
Limiting fluctuation and trajectorial stability of multilayer neural
  networks with mean field training
Limiting fluctuation and trajectorial stability of multilayer neural networks with mean field trainingNeural Information Processing Systems (NeurIPS), 2021
H. Pham
Phan-Minh Nguyen
158
6
0
29 Oct 2021
Global Convergence of Three-layer Neural Networks in the Mean Field
  Regime
Global Convergence of Three-layer Neural Networks in the Mean Field RegimeInternational Conference on Learning Representations (ICLR), 2021
H. Pham
Phan-Minh Nguyen
MLTAI4CE
367
23
0
11 May 2021
Modeling from Features: a Mean-field Framework for Over-parameterized
  Deep Neural Networks
Modeling from Features: a Mean-field Framework for Over-parameterized Deep Neural Networks
Cong Fang
Jason D. Lee
Pengkun Yang
Tong Zhang
OODFedML
274
62
0
03 Jul 2020
Landscape Connectivity and Dropout Stability of SGD Solutions for
  Over-parameterized Neural Networks
Landscape Connectivity and Dropout Stability of SGD Solutions for Over-parameterized Neural NetworksInternational Conference on Machine Learning (ICML), 2019
Aleksandr Shevchenko
Marco Mondelli
487
41
0
20 Dec 2019
1
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