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2020 – today
- 2024
[j8]Hyeonuk Kim
, Youngbeom Jung, Lee-Sup Kim:
ADC-Free ReRAM-Based In-Situ Accelerator for Energy-Efficient Binary Neural Networks. IEEE Trans. Computers 73(2): 353-365 (2024)- 2023
- [j7]Youngbeom Jung, Hyeonuk Kim, Seungkyu Choi, Jaekang Shin, Lee-Sup Kim:
Energy-Efficient CNN Personalized Training by Adaptive Data Reformation. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42(1): 332-336 (2023) - 2022
- [j6]Myeonggu Kang, Hyeonuk Kim, Hyein Shin, Jaehyeong Sim, Kyeonghan Kim, Lee-Sup Kim:
S-FLASH: A NAND Flash-Based Deep Neural Network Accelerator Exploiting Bit-Level Sparsity. IEEE Trans. Computers 71(6): 1291-1304 (2022) - [j5]Youngbeom Jung, Hyeonuk Kim, Yeongjae Choi, Lee-Sup Kim:
Quantization-Error-Robust Deep Neural Network for Embedded Accelerators. IEEE Trans. Circuits Syst. II Express Briefs 69(2): 609-613 (2022) - 2021
- [j4]Hyeonuk Kim, Kyunghyun Park, Junkee Jeon, Changhoon Song, Jungwoo Bae, Yongsik Kim, Myungjoo Kang:
Candidate point selection using a self-attention mechanism for generating a smooth volatility surface under the SABR model. Expert Syst. Appl. 173: 114640 (2021) - 2020
- [j3]Seungkyu Choi, Jaehyeong Sim, Myeonggu Kang, Yeongjae Choi, Hyeonuk Kim, Lee-Sup Kim:
An Energy-Efficient Deep Convolutional Neural Network Training Accelerator for In Situ Personalization on Smart Devices. IEEE J. Solid State Circuits 55(10): 2691-2702 (2020)
2010 – 2019
- 2019
- [j2]Hyeonuk Kim, Heejae Han, Dalhyeon Gwon, Myungjoo Kang:
High order face-offsetting method for interface tracking problem using WENO schemes. J. Comput. Phys. 376: 863-893 (2019) - [c4]Seungkyu Choi, Jaehyeong Sim, Myeonggu Kang, Yeongjae Choi, Hyeonuk Kim, Lee-Sup Kim:
A 47.4µJ/epoch Trainable Deep Convolutional Neural Network Accelerator for In-Situ Personalization on Smart Devices. A-SSCC 2019: 57-60 - [c3]Hyeonuk Kim, Jaehyeong Sim, Yeongjae Choi, Lee-Sup Kim:
NAND-Net: Minimizing Computational Complexity of In-Memory Processing for Binary Neural Networks. HPCA 2019: 661-673 - [c2]Hyeonwook Wi, Hyeonuk Kim, Seungkyu Choi, Lee-Sup Kim:
Compressing Sparse Ternary Weight Convolutional Neural Networks for Efficient Hardware Acceleration. ISLPED 2019: 1-6 - 2017
- [c1]Hyeonuk Kim, Jaehyeong Sim, Yeongjae Choi, Lee-Sup Kim:
A Kernel Decomposition Architecture for Binary-weight Convolutional Neural Networks. DAC 2017: 60:1-60:6 - 2016
- [j1]Junkee Jeon, Heejae Han, Hyeonuk Kim, Myungjoo Kang:
An integral equation representation approach for valuing Russian options with a finite time horizon. Commun. Nonlinear Sci. Numer. Simul. 36: 496-516 (2016)
Coauthor Index
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