Personal Information
Seungkyu Choi
research interestshttps://sites.google.com/view/seungkyuchoi
International Journal Papers
Youngbeom Jung, Hyeonuk Kim, Seungkyu Choi, Jaekang Shin, Lee-Sup Kim
Energy-Efficient CNN Personalized Training by Adaptive Data Reformation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2023
 
Seungkyu Choi, Jaekang Shin, Lee-Sup Kim
Accelerating On-Device DNN Training Workloads via Runtime Convergence Monitoring
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022
 
Seungkyu Choi, Jaekang Shin, Lee-Sup Kim
A Deep Neural Network Training Architecture with Inference-aware Heterogeneous Data-type
IEEE Transactions on Computers, 2022
 
Kangkyu Park, Seungkyu Choi, Yeongjae Choi, Lee-Sup Kim
Rare Computing: Removing Redundant Multiplications from Sparse and Repetitive Data in Deep Neural Networks
IEEE Transactions on Computers, 2022
 
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 Journal of Solid-State Circuits, 2020
 
Yeongjae Choi, Dongmyung Bae, Jaehyeong Sim, Seungkyu Choi, Minhye Kim, Lee-Sup Kim
Energy-efficient design of processing element for convolutional neural network
IEEE Transactions on Circuits and Systems II, 2017
 
International Conference Papers
Jaekang Shin, Seungkyu Choi, Jongwoo Ra, Lee-Sup Kim
Algorithm/Architecture Co-Design for Energy-Efficient Acceleration of Multi-Task DNN
IEEE/ACM Design Automation Conference, 2022
 
Seungkyu Choi, Jaekang Shin, Lee-Sup Kim
A Convergence Monitoring Method for DNN Training of On-Device Task Adaptation
IEEE/ACM International Conference On Computer Aided Design, 2021
 
Jaekang Shin, Seungkyu Choi, Yeongjae Choi, Lee-Sup Kim
A Pragmatic Approach to On-device Incremental Learning System with Selective Weight Updates
IEEE/ACM Design Automation Conference , 2020
 
Seungkyu Choi, Jaehyeong Sim, Myeonggu Kang, Yeongjae Choi, Hyeonuk Kim, Lee-Sup Kim
A 47.4uJ/epoch Trainable Deep Convolutional Neural Network Accelerator for In-Situ Personalization on Smart Devices
IEEE Asian Solid-State Circuits Conference, 2019
 
Hyeonwook Wi, Hyeonuk Kim, Seungkyu Choi, Lee-Sup Kim
Compressing Sparse Ternary Weight Convolutional Neural Networks for Efficient Hardware Acceleration
ACM/IEEE International Symposium on Low Power Electronics and Design, 2019
 
Seungkyu Choi, Jaekang Shin, Yeongjae Choi, Lee-Sup Kim
An Optimized Design Technique of Low-bit Neural Network Training for Personalization on IoT Devices
IEEE/ACM Design Automation Conference, 2019
 
Seungkyu Choi, Jaehyeong Sim, Myeonggu Kang, Lee-Sup Kim
TrainWare: A Memory Optimized Weight Update Architecture for On-Device Convolutional Neural Network Training
ACM/IEEE International Symposium on Low Power Electronics and Design, 2018
 
Myunghoon Choi, Seungkyu Choi, Jaehyeong Sim, Lee-Sup Kim
SENIN: An Energy-Efficient Sparse Neuromorphic System
The International Symposium on Low Power Electronics and Design , 2017