8 citations · 16 across the 10 of their papers we have counts for
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cs.LG2021★ 1 cited
Dropout in Training Neural Networks: Flatness of Solution and Noise Structure
Zhongwang Zhang, Hanxu Zhou, Zhi-Qin John Xu
It is important to understand how the popular regularization method dropout helps the neural network training find a good generalization solution. In this work, we show that the tr…
cs.CL2021★ 5 cited
A Unified Pre-training Framework for Conversational AI
Siqi Bao, Bingjin Chen, Huang He +7
In this work, we explore the application of PLATO-2 on various dialogue systems, including open-domain conversation, knowledge grounded dialogue, and task-oriented conversation. PL…
cs.LG2021★ 8 cited
Towards Understanding the Condensation of Neural Networks at Initial Training
Hanxu Zhou, Qixuan Zhou, Tao Luo +2
Empirical works show that for ReLU neural networks (NNs) with small initialization, input weights of hidden neurons (the input weight of a hidden neuron consists of the weight from…