Publications associées à Momentum-Based Policy Gradient with Second-Order Information

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Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

Patrick Thiran, Negar Kiyavash, Saber Salehkaleybar

We study the performance of Stochastic Cubic Regularized Newton (SCRN) on a class of functions satisfying gradient dominance property with

1\le\alpha\le2

which holds in a wide range of applications in machine learning and signal processing. This conditio ...

NeurIPS2022

Momentum-Based Policy Gradient with Second-Order Information

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Stochastic Second-Order Methods Improve Best-Known Sample Complexity of SGD for Gradient-Dominated Function

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Deep Learning Generalization with Limited and Noisy Labels

Understanding generalization and robustness in modern deep learning

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Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs

Masked Training of Neural Networks with Partial Gradients