Seungkyu Choi

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 15

Top Topics

Incremental Learning

Convolutional Neural Network

Top Venues

IEEE Trans. Computers

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst.

Publications

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) (2023)
Seungkyu Choi, Jaekang Shin, Lee-Sup Kim
Accelerating On-Device DNN Training Workloads via Runtime Convergence Monitor. IEEE Trans. Comput. Aided Des. Integr. Circuits Syst. 42 (5) (2023)
Pierre Abillama, Zichen Fan, Yu Chen, Hyochan An, Qirui Zhang, Seungkyu Choi, David T. Blaauw, Dennis Sylvester, Hun-Seok Kim
SONA: An Accelerator for Transform-Domain Neural Networks with Sparse-Orthogonal Weights. ASAP (2023)
Jaekang Shin, Seungkyu Choi, Jongwoo Ra, Lee-Sup Kim
Algorithm/architecture co-design for energy-efficient acceleration of multi-task DNN. DAC (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 Trans. Computers 71 (4) (2022)
Seungkyu Choi, Jaekang Shin, Lee-Sup Kim
A Deep Neural Network Training Architecture With Inference-Aware Heterogeneous Data-Type. IEEE Trans. Computers 71 (5) (2022)
Seungkyu Choi, Jaekang Shin, Lee-Sup Kim
A Convergence Monitoring Method for DNN Training of On-Device Task Adaptation. ICCAD (2021)
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) (2020)
Jaekang Shin, Seungkyu Choi, Yeongjae Choi, Lee-Sup Kim
A Pragmatic Approach to On-device Incremental Learning System with Selective Weight Updates. DAC (2020)
Seungkyu Choi, Jaekang Shin, Yeongjae Choi, Lee-Sup Kim
An Optimized Design Technique of Low-bit Neural Network Training for Personalization on IoT Devices. DAC (2019)
Hyeonwook Wi, Hyeonuk Kim, Seungkyu Choi, Lee-Sup Kim
Compressing Sparse Ternary Weight Convolutional Neural Networks for Efficient Hardware Acceleration. ISLPED (2019)
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)
Seungkyu Choi, Jaehyeong Sim, Myeonggu Kang, Lee-Sup Kim
TrainWare: A Memory Optimized Weight Update Architecture for On-Device Convolutional Neural Network Training. ISLPED (2018)
Yeongjae Choi, Dongmyung Bae, Jaehyeong Sim, Seungkyu Choi, Minhye Kim, Lee-Sup Kim
Energy-Efficient Design of Processing Element for Convolutional Neural Network. IEEE Trans. Circuits Syst. II Express Briefs (11) (2017)
Myung-Hoon Choi, Seungkyu Choi, Jaehyeong Sim, Lee-Sup Kim
SENIN: An energy-efficient sparse neuromorphic system with on-chip learning. ISLPED (2017)
Seungkyu Choi, Chungyong Lee
Power Allocation Algorithms for GMD or UCD Based Joint Transceiver Designs. Wirel. Pers. Commun. 79 (1) (2014)
Seungkyu Choi, Chungyong Lee
A User Scheduling with Minimum-Rate Requirement for Maximum Sum-Rate in MIMO-BC. IEICE Trans. Commun. (11) (2011)