O-2A: Low Overhead DNN Compression with Outlier-Aware Approximation. - Nguyen-Dong Ho; Minh-Son Le; Ik-Joon Chang (DAC, 2020)

TCL: an ANN-to-SNN Conversion with Trainable Clipping Layers. - Nguyen-Dong Ho; Ik-Joon Chang (DAC, 2021)

O-2A: Outlier-Aware Compression for 8-bit Post-Training Quantization Model. - Nguyen-Dong Ho; Ik-Joon Chang (IEEE Access, 2023)

MiCE: An ANN-to-SNN Conversion Technique to Enable High Accuracy and Low Latency. - Nguyen-Dong Ho; Ik-Joon Chang (IEEE J. Emerg. Sel. Topics Circuits Syst., 2023)

MERSIT: A Hardware-Efficient 8-bit Data Format with Enhanced Post-Training Quantization DNN Accuracy. - Nguyen-Dong Ho; Gyujun Jeong; Cheol-Min Kang; Seungkyu Choi; Ik-Joon Chang (DAC, 2024)

SAPIENS: Towards Energy-efficient Deep Spiking Neural Networks via the Approximation of Power-expensive Neurons. - Cheol-Min Kang; Nguyen-Dong Ho; Dongyoung Lee; Yonghwan Kwon; Donghyun Kim; Inhan Kang; Ik Joon Chang (AICAS, 2025)