no code implementations • 12 Nov 2023 • Han-Byul Kim, Joo Hyung Lee, Sungjoo Yoo, Hong-Seok Kim
Mixed-precision quantization of efficient networks often suffer from activation instability encountered in the exploration of bit selections.
1 code implementation • 27 Apr 2023 • Joo Hyung Lee, Wonpyo Park, Nicole Mitchell, Jonathan Pilault, Johan Obando-Ceron, Han-Byul Kim, Namhoon Lee, Elias Frantar, Yun Long, Amir Yazdanbakhsh, Shivani Agrawal, Suvinay Subramanian, Xin Wang, Sheng-Chun Kao, Xingyao Zhang, Trevor Gale, Aart Bik, Woohyun Han, Milen Ferev, Zhonglin Han, Hong-Seok Kim, Yann Dauphin, Gintare Karolina Dziugaite, Pablo Samuel Castro, Utku Evci
This paper introduces JaxPruner, an open-source JAX-based pruning and sparse training library for machine learning research.
1 code implementation • ECCV(European Conference on Computer Vision) 2022 • Han-Byul Kim, Eunhyeok Park, Sungjoo Yoo
In this paper, we propose Branch-wise Activation-clipping Search Quantization (BASQ), which is a novel quantization method for low-bit activation.