1 code implementation • 9 Aug 2023 • Jue Chen, Huan Yuan, Jianchao Tan, Bin Chen, Chengru Song, Di Zhang
We propose an improved end-to-end Minimax optimization method for this sparse learning problem to better balance the model performance and the computation efficiency.
no code implementations • 30 Jun 2023 • Yuan Zhang, Jian Cao, Ling Zhang, Jue Chen, Wenyu Sun, YuAn Wang
The event streams generated by dynamic vision sensors (DVS) are sparse and non-uniform in the spatial domain, while still dense and redundant in the temporal domain.
no code implementations • 25 Apr 2022 • Yu Qian, Jian Cao, Xiaoshuang Li, Jie Zhang, Hufei Li, Jue Chen
To address this challenge, we propose a novel method that first linearly over-parameterizes the compact layers in pruned networks to enlarge the number of fine-tuning parameters and then re-parameterizes them to the original layers after fine-tuning.