19 citations · 40 across the 5 of their papers we have counts for
5 papers
Homotopy Relaxation Training Algorithms for Infinite-Width Two-Layer ReLU Neural Networks
Yahong Yang, Qipin Chen, Wenrui Hao
In this paper, we present a novel training approach called the Homotopy Relaxation Training Algorithm (HRTA), aimed at accelerating the training process in contrast to traditional…
A Weight Initialization Based on the Linear Product Structure for Neural Networks
Qipin Chen, Wenrui Hao, Juncai He
Weight initialization plays an important role in training neural networks and also affects tremendous deep learning applications. Various weight initialization strategies have alre…
Power Series Expansion Neural Network
Qipin Chen, Wenrui Hao, Juncai He
In this paper, we develop a new neural network family based on power series expansion, which is proved to achieve a better approximation accuracy in comparison with existing neural…
A randomized Newton's method for solving differential equations based on the neural network discretization
Qipin Chen, Wenrui Hao
We develop a randomized Newton's method for solving differential equations, based on a fully connected neural network discretization. In particular, the randomized Newton's method…
A homotopy training algorithm for fully connected neural networks
Qipin Chen, Wenrui Hao
In this paper, we present a Homotopy Training Algorithm (HTA) to solve optimization problems arising from fully connected neural networks with complicated structures. The HTA dynam…