1 code implementation • NeurIPS 2023 • Yefan Zhou, Tianyu Pang, Keqin Liu, Charles H. Martin, Michael W. Mahoney, Yaoqing Yang
In particular, the learning rate, which can be interpreted as a temperature-like parameter within the statistical mechanics of learning, plays a crucial role in neural network training.
1 code implementation • 28 May 2023 • Yefan Zhou, Yaoqing Yang, Arin Chang, Michael W. Mahoney
Our approach uses temperature-like and load-like parameters to model the impact of neural network (NN) training hyperparameters on pruning performance.
1 code implementation • 30 Nov 2021 • Yefan Zhou, Yiru Shen, Yujun Yan, Chen Feng, Yaoqing Yang
Our finding shows that a leading factor in determining recognition versus reconstruction is how dispersed the training data is.