Do-Yeon Kim

11 papers A* 7Journal 3Unranked 1
YearRankTypeTitle / Venue / Authors
2025 A* conf
Adaptive Energy Alignment for Accelerating Test-Time Adaptation.
ICLR
Wonjeong Choi, Do-Yeon Kim, Jungwuk Park, Jungmoon Lee, Younghyun Park, Dong-Jun Han, Jaekyun Moon
2024 A* conf
Achieving Lossless Gradient Sparsification via Mapping to Alternative Space in Federated Learning.
ICML
Do-Yeon Kim, Dong-Jun Han, Jun Seo, Jaekyun Moon
2024 J jnl
Federated Split Learning With Joint Personalization-Generalization for Inference-Stage Optimization in Wireless Edge Networks.
IEEE Trans. Mob. Comput.
Dong-Jun Han, Do-Yeon Kim, Minseok Choi, David R. Nickel, Jaekyun Moon, Mung Chiang, Christopher G. Brinton
2023 A* conf
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning.
NeurIPS
Mohammad Mahdi Rahimi, Hasnain Irshad Bhatti, Younghyun Park, Humaira Kousar, Do-Yeon Kim, Jaekyun Moon
2023 A* conf
SplitGP: Achieving Both Generalization and Personalization in Federated Learning.
INFOCOM
Dong-Jun Han, Do-Yeon Kim, Minseok Choi, Christopher G. Brinton, Jaekyun Moon
2023 A* conf
Warping the Space: Weight Space Rotation for Class-Incremental Few-Shot Learning.
ICLR
Do-Yeon Kim, Dong-Jun Han, Jun Seo, Jaekyun Moon
2022 — conf
Deep Neural Network Compression for Image Inpainting.
ECCV Workshops (7)
Soyeong Kim, Do-Yeon Kim, Jaekyun Moon
2022 J jnl
SplitGP: Achieving Both Generalization and Personalization in Federated Learning.
CoRR
Dong-Jun Han, Do-Yeon Kim, Minseok Choi, Christopher G. Brinton, Jaekyun Moon
2021 A* conf
Few-Round Learning for Federated Learning.
NeurIPS
Younghyun Park, Dong-Jun Han, Do-Yeon Kim, Jun Seo, Jaekyun Moon
2020 A* conf
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning.
ICML
Sung Whan Yoon, Do-Yeon Kim, Jun Seo, Jaekyun Moon
2020 J jnl
XtarNet: Learning to Extract Task-Adaptive Representation for Incremental Few-Shot Learning.
CoRR
Sung Whan Yoon, Do-Yeon Kim, Jun Seo, Jaekyun Moon