May 19, 2022 · This work establishes the first linear convergence result for vanilla two-layer neural networks trained by continuous-time noisy gradient descent in the mean- ...
Oct 18, 2022 · Abstract. We consider optimizing two-layer neural networks in the mean-field regime where the learning dynamics of network weights can be ...
This work establishes a new linear convergence result for two-layer neural networks trained by continuous-time noisy gradient descent in the mean-field regime.
This work establishes the first linear convergence result for vanilla two-layer neural networks trained by continuous-time noisy gradient descent in the ...
Mean-Field Analysis of Two-Layer Neural Networks - DeepAI
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May 19, 2022 · This work establishes a new linear convergence result for two-layer neural networks trained by continuous-time noisy gradient descent in the ...
This work establishes the first linear convergence result for vanilla two-layer neural networks trained by continuous-time noisy gradient descent in the mean- ...
Mean-Field Analysis of Two-Layer Neural Networks: Global Optimality with Linear Convergence Rates. Jingwei Zhang, Xunpeng Huang. 2022, arXiv.org. PDF · S2 logo ...
In this paper, we study the feature learning ability of two-layer neural networks in the mean-field regime through the lens of kernel methods. To.
Feb 10, 2020 · A mean-field analysis in a generalized neural tangent kernel regime is provided, and it is shown that noisy gradient descent with weight ...
Missing: Optimality | Show results with:Optimality
For optimizing two-layer neural network in the mean-field regime, we establish quantitative global convergence rate of PDA in minimizing an KL-regularized ...