4 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.LG2024
One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training
Lianbo Ma, Yuee Zhou, Jianlun Ma +2
Weight quantization is an effective technique to compress deep neural networks for their deployment on edge devices with limited resources. Traditional loss-aware quantization meth…
cs.NE2022★ 4 cited
Survey on Evolutionary Deep Learning: Principles, Algorithms, Applications and Open Issues
Nan Li, Lianbo Ma, Guo Yu +3
Over recent years, there has been a rapid development of deep learning (DL) in both industry and academia fields. However, finding the optimal hyperparameters of a DL model often n…