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11/19/2022
Can Gradient Descent Provably Learn Linear Dynamic Systems?
We study the learning ability of linear recurrent neural networks with g...
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09/29/2021
On the Provable Generalization of Recurrent Neural Networks
Recurrent Neural Network (RNN) is a fundamental structure in deep learni...
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06/10/2020
Is the Skip Connection Provable to Reform the Neural Network Loss Landscape?
The residual network is now one of the most effective structures in deep...
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10/14/2019
On the Convergence of Perturbed Distributed Asynchronous Stochastic Gradient Descent to Second Order Stationary Points in Non-convex Optimization
In this paper, the second order convergence of non-convex optimization i...
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07/10/2018
The asymptotic behaviors of self excitation information diffusion processes for a large number of individuals
The dynamics of opinion is a complex and interesting process, especially...
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07/10/2018
