Jaehong Yoon
jaehong.yoon [at] kaist [dot] ac [dot] kr
Latest Updated
News
May 2022
(NEW!) Two papers got accepted to
ICML 2022.
Jan 2022
Two papers got accepted to
ICLR 2022
including one
oral presentation (acceptance rate = 54/3391 = 1.6%).
Introduction
I’m a Ph.D. student in the
Machine Learning and Artificial Intelligence (MLAI)
Lab at KAIST, under the supervision of Prof. Sung Ju Hwang.
I finished the B.S. and M.S. degree at UNIST in 2016 and 2018, respectively.
My expected graduation date is February 2023.
I'm eager to build lifelong and meta-cognitive learning algorithms for non-stationary problems or environments, towards real-world artificial general intelligence. Recently, I've been focusing on bridging my research experience to relevant research areas, such as open-world problems, online/streaming learning, reinforcement learning, multimodal, and language models.
Publications
[C9] Forgetting-free Continual Learning with Winning Subnetworks
ICML 2022 (To appear)Paper Code BibTeX
[C8] Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization
ICML 2022 (To appear)Paper Code
@article{yoon2022bitwidth,
title = {Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization},
author = {Jaehong Yoon and Geon Park and Wonyong Jeong and Sung Ju Hwang},
journal = {CoRR},
volume = {abs/2022.11453},
eprint={2022.11453},
archivePrefix={arXiv},
year = {2022},
}
title = {Bitwidth Heterogeneous Federated Learning with Progressive Weight Dequantization},
author = {Jaehong Yoon and Geon Park and Wonyong Jeong and Sung Ju Hwang},
journal = {CoRR},
volume = {abs/2022.11453},
eprint={2022.11453},
archivePrefix={arXiv},
year = {2022},
}
[C7] Representational Continuity for Unsupervised Continual Learning
ICLR 2022 Oral Presentation (Acceptance Rate = 1.6%)Paper Code
@inproceedings{madaan2022rethinking,
title={Rethinking the Representational Continuity: Towards Unsupervised Continual Learning},
author={Divyam Madaan and Jaehong Yoon and Yuanchun Li and Yunxin Liu and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=9Hrka5PA7LW}
}
title={Rethinking the Representational Continuity: Towards Unsupervised Continual Learning},
author={Divyam Madaan and Jaehong Yoon and Yuanchun Li and Yunxin Liu and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=9Hrka5PA7LW}
}
[C6] Online Coreset Selection for Rehearsal-based Continual Learning
ICLR 2022
Paper Code
@inproceedings{yoon2022online,
title={Online Coreset Selection for Rehearsal-based Continual Learning},
author={Jaehong Yoon and Divyam Madaan and Eunho Yang and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=f9D-5WNG4Nv}
}
title={Online Coreset Selection for Rehearsal-based Continual Learning},
author={Jaehong Yoon and Divyam Madaan and Eunho Yang and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=f9D-5WNG4Nv}
}
[C5] Federated Continual Learning with Weighted Inter-client Transfer
ICML 2020 Workshop in Lifelong Machine LearningICML 2021
Paper Code
@inproceedings{yoon2021federated,
title={Federated continual learning with weighted inter-client transfer},
author={Yoon, Jaehong and Jeong, Wonyong and Lee, Giwoong and Yang, Eunho and Hwang, Sung Ju},
booktitle={International Conference on Machine Learning},
pages={12073--12086},
year={2021},
organization={PMLR}
}
title={Federated continual learning with weighted inter-client transfer},
author={Yoon, Jaehong and Jeong, Wonyong and Lee, Giwoong and Yang, Eunho and Hwang, Sung Ju},
booktitle={International Conference on Machine Learning},
pages={12073--12086},
year={2021},
organization={PMLR}
}
[C4] Federated Semi-supervised Learning with Inter-Client Consistency & Disjoint Learning
ICML 2020 Workshop in Federated Learning (Long Presentation) (Best Student Paper Award)ICLR 2021
Paper Code
@inproceedings{jeong2021federated,
title={Federated Semi-Supervised Learning with Inter-Client Consistency \& Disjoint Learning},
author={Wonyong Jeong and Jaehong Yoon and Eunho Yang and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=ce6CFXBh30h}
}
title={Federated Semi-Supervised Learning with Inter-Client Consistency \& Disjoint Learning},
author={Wonyong Jeong and Jaehong Yoon and Eunho Yang and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2021},
url={https://openreview.net/forum?id=ce6CFXBh30h}
}
[C3] Scalable and Order-robust Continual Learning with Additive Parameter Decomposition
ICLR 2020
Paper Code
@inproceedings{Yoon2020Scalable,
title={Scalable and Order-robust Continual Learning with Additive Parameter Decomposition},
author={Jaehong Yoon and Saehoon Kim and Eunho Yang and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2020},
url={https://openreview.net/forum?id=r1gdj2EKPB}
}
title={Scalable and Order-robust Continual Learning with Additive Parameter Decomposition},
author={Jaehong Yoon and Saehoon Kim and Eunho Yang and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2020},
url={https://openreview.net/forum?id=r1gdj2EKPB}
}
[C2] Lifelong Learning with Dynamically Expandable Networks
ICLR 2018
Paper Code
@inproceedings{yoon2018lifelong,
title={Lifelong Learning with Dynamically Expandable Networks},
author={Jaehong Yoon and Eunho Yang and Jeongtae Lee and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2018},
url={https://openreview.net/forum?id=Sk7KsfW0-},
}
title={Lifelong Learning with Dynamically Expandable Networks},
author={Jaehong Yoon and Eunho Yang and Jeongtae Lee and Sung Ju Hwang},
booktitle={International Conference on Learning Representations},
year={2018},
url={https://openreview.net/forum?id=Sk7KsfW0-},
}
[C1] Combined Group and Exclusive Sparsity for Deep Neural Networks
ICML 2017
Paper Code
@inproceedings{yoon2017combined,
title={Combined group and exclusive sparsity for deep neural networks},
author={Yoon, Jaehong and Hwang, Sung Ju},
booktitle={International Conference on Machine Learning},
pages={3958--3966},
year={2017},
organization={PMLR}
}
title={Combined group and exclusive sparsity for deep neural networks},
author={Yoon, Jaehong and Hwang, Sung Ju},
booktitle={International Conference on Machine Learning},
pages={3958--3966},
year={2017},
organization={PMLR}
}
Preprints
[P4] Personalized Subgraph Federated Learning
Preprint, 2022
Paper BibTeX
[P3] BiTAT: Neural Network Binarization with Task-dependent Aggregated Transformation
Preprint, 2022
Paper BibTeX
[P2] Rapid Structural Pruning of Neural Networks with Set-based Task-Adaptive Meta-Pruning
arXiv:2006.12130, 2020
Paper
@article{song2020rapid,
title = {Rapid Structural Pruning of Neural Networks with Set-based Task-Adaptive Meta-Pruning},
author = {Minyoung Song and Jaehong Yoon and Eunho Yang and Sung Ju Hwang},
journal = {CoRR},
volume = {abs/2006.12139},
eprint={2006.12139},
archivePrefix={arXiv},
year = {2020},
}
title = {Rapid Structural Pruning of Neural Networks with Set-based Task-Adaptive Meta-Pruning},
author = {Minyoung Song and Jaehong Yoon and Eunho Yang and Sung Ju Hwang},
journal = {CoRR},
volume = {abs/2006.12139},
eprint={2006.12139},
archivePrefix={arXiv},
year = {2020},
}
[P1] Adaptive Network Sparsification with Dependent Variational Beta-Bernoulli Dropout
arXiv:1805.10896, 2018
Paper
@article{lee2019adaptive,
title = {Adaptive Network Sparsification with Dependent Variational Beta-Bernoulli Dropout},
author = {Juho Lee and Saehoon Kim and Jaehong Yoon and Hae Beom Lee and Eunho Yang and Sung Ju Hwang},
journal = {CoRR},
volume = {abs/1805.10896},
eprint={1805.10896},
archivePrefix={arXiv},
year = {2017},
}
title = {Adaptive Network Sparsification with Dependent Variational Beta-Bernoulli Dropout},
author = {Juho Lee and Saehoon Kim and Jaehong Yoon and Hae Beom Lee and Eunho Yang and Sung Ju Hwang},
journal = {CoRR},
volume = {abs/1805.10896},
eprint={1805.10896},
archivePrefix={arXiv},
year = {2017},
}
Experience
Nov 2021 - Apr 2022
Microsoft Research, Research Intern (Advisor: Yue Cao)
Mar 2018 - May 2018
AITRICS, Research Intern