3 papers
cs.LG2023
Robust Neural Pruning with Gradient Sampling Optimization for Residual Neural Networks
Juyoung Yun
This research embarks on pioneering the integration of gradient sampling optimization techniques, particularly StochGradAdam, into the pruning process of neural networks. Our main…
cs.LG2023
Continuous 16-bit Training: Accelerating 32-bit Pre-Trained Neural Networks
Juyoung Yun
In the field of deep learning, the prevalence of models initially trained with 32-bit precision is a testament to its robustness and accuracy. However, the continuous evolution of…
cs.LG2023
Stochastic Gradient Sampling for Enhancing Neural Networks Training
Juyoung Yun
In this paper, we introduce StochGradAdam, a novel optimizer designed as an extension of the Adam algorithm, incorporating stochastic gradient sampling techniques to improve comput…