Sung-En Chang

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 16

Top Topics

Main Contribution

Multiple Layers

Norm Regularization

Top Venues

Publications

Yanyue Xie, Peiyan Dong, Geng Yuan, Zhengang Li, Masoud Zabihi, Chao Wu, Sung-En Chang, Xufeng Zhang, Xue Lin, Caiwen Ding, Nobuyuki Yoshikawa, Olivia Chen, Yanzhi Wang
SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum- Flux - Parametron Superconducting Circuits. DATE (2024)
Yanyue Xie, Peiyan Dong, Geng Yuan, Zhengang Li, Masoud Zabihi, Chao Wu, Sung-En Chang, Xufeng Zhang, Xue Lin, Caiwen Ding, Nobuyuki Yoshikawa, Olivia Chen, Yanzhi Wang
SuperFlow: A Fully-Customized RTL-to-GDS Design Automation Flow for Adiabatic Quantum-Flux-Parametron Superconducting Circuits. CoRR (2024)
Sung-En Chang, Geng Yuan, Alec Lu, Mengshu Sun, Yanyu Li, Xiaolong Ma, Zhengang Li, Yanyue Xie, Minghai Qin, Xue Lin, Zhenman Fang, Yanzhi Wang
ESRU: Extremely Low-Bit and Hardware-Efficient Stochastic Rounding Unit Design for Low-Bit DNN Training. DATE (2023)
Mengshu Sun, Zhengang Li, Alec Lu, Yanyu Li, Sung-En Chang, Xiaolong Ma, Xue Lin, Zhenman Fang
FILM-QNN: Efficient FPGA Acceleration of Deep Neural Networks with Intra-Layer, Mixed-Precision Quantization. FPGA (2022)
Sung-En Chang, Geng Yuan, Alec Lu, Mengshu Sun, Yanyu Li, Xiaolong Ma, Zhengang Li, Yanyue Xie, Minghai Qin, Xue Lin, Zhenman Fang, Yanzhi Wang
Hardware-efficient stochastic rounding unit design for DNN training: late breaking results. DAC (2022)
Geng Yuan, Sung-En Chang, Qing Jin, Alec Lu, Yanyu Li, Yushu Wu, Zhenglun Kong, Yanyue Xie, Peiyan Dong, Minghai Qin, Xiaolong Ma, Xulong Tang, Zhenman Fang, Yanzhi Wang
You Already Have It: A Generator-Free Low-Precision DNN Training Framework Using Stochastic Rounding. ECCV (12) (2022)
Shaoyi Huang, Dongkuan Xu, Ian En-Hsu Yen, Yijue Wang, Sung-En Chang, Bingbing Li, Shiyang Chen, Mimi Xie, Sanguthevar Rajasekaran, Hang Liu, Caiwen Ding
Sparse Progressive Distillation: Resolving Overfitting under Pretrain-and-Finetune Paradigm. ACL (1) (2022)
Sung-En Chang, Yanyu Li, Mengshu Sun, Runbin Shi, Hayden K. H. So, Xuehai Qian, Yanzhi Wang, Xue Lin
Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework. HPCA (2021)
Sung-En Chang, Yanyu Li, Mengshu Sun, Yanzhi Wang, Xue Lin
ILMPQ : An Intra-Layer Multi-Precision Deep Neural Network Quantization framework for FPGA. CoRR (2021)
Sung-En Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Sijia Liu, Yanzhi Wang, Xue Lin
RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions. CoRR (2021)
Sung-En Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Sijia Liu, Yanzhi Wang, Xue Lin
RMSMP: A Novel Deep Neural Network Quantization Framework with Row-wise Mixed Schemes and Multiple Precisions. ICCV (2021)
Sung-En Chang, Yanyu Li, Mengshu Sun, Runbin Shi, Hayden Kwok-Hay So, Xuehai Qian, Yanzhi Wang, Xue Lin
Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework. CoRR (2020)
Sung-En Chang, Yanyu Li, Mengshu Sun, Weiwen Jiang, Runbin Shi, Xue Lin, Yanzhi Wang
MSP: An FPGA-Specific Mixed-Scheme, Multi-Precision Deep Neural Network Quantization Framework. CoRR (2020)
Sung-En Chang, Xun Zheng, Ian En-Hsu Yen, Pradeep Ravikumar, Rose Yu
Learning Tensor Latent Features. CoRR (2018)
Ian En-Hsu Yen, Wei-Cheng Lee, Kai Zhong, Sung-En Chang, Pradeep Ravikumar, Shou-De Lin
MixLasso: Generalized Mixed Regression via Convex Atomic-Norm Regularization. NeurIPS (2018)
Ian En-Hsu Yen, Wei-Cheng Lee, Sung-En Chang, Arun Sai Suggala, Shou-De Lin, Pradeep Ravikumar
Latent Feature Lasso. ICML (2017)