100 citations · 106 across the 4 of their papers we have counts for
4 papers
Unsupervised Learning of Initialization in Deep Neural Networks via Maximum Mean Discrepancy
Cheolhyoung Lee, Kyunghyun Cho
Despite the recent success of stochastic gradient descent in deep learning, it is often difficult to train a deep neural network with an inappropriate choice of its initial paramet…
A Non-monotonic Self-terminating Language Model
Eugene Choi, Kyunghyun Cho, Cheolhyoung Lee
Recent large-scale neural autoregressive sequence models have shown impressive performances on a variety of natural language generation tasks. However, their generated sequences of…
Mixout: Effective Regularization to Finetune Large-scale Pretrained Language Models
Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang
In natural language processing, it has been observed recently that generalization could be greatly improved by finetuning a large-scale language model pretrained on a large unlabel…
Directional Analysis of Stochastic Gradient Descent via von Mises-Fisher Distributions in Deep learning
Cheolhyoung Lee, Kyunghyun Cho, Wanmo Kang
Although stochastic gradient descent (SGD) is a driving force behind the recent success of deep learning, our understanding of its dynamics in a high-dimensional parameter space is…