Jang-Hyun Kim
Hello!
I am a PhD student in computer science at Seoul National University, advised by Hyun Oh Song.
I was a visiting scholar at New York University in 2024, hosted by Kyunghyun Cho.
Before that, I interned at NAVER
AI in 2018, where I worked on speech enhancement.
I completed BSc with Mathematics at Seoul National University in 2019. My PhD studies are
supported by the Korea Foundation for Advanced Studies (KFAS).
Email   / 
CV   / 
Scholar   / 
Github   / 
Twitter
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Research
(Research Statement)
My research focuses on optimizing data usage in AI systems to develop sustainable systems capable of
(1) efficient memory management during inference and (2) effective learning from limited human-labeled
data.
This goal entails leveraging model feedback to compress data, generate synthetic data,
and identify relationships among data—ultimately reducing reliance on human intervention.
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Targeted Cause Discovery with Data-Driven Learning
Jang-Hyun Kim, Claudia Skok Gibbs, Sangdoo Yun, Hyun Oh Song, Kyunghyun Cho
arXiv, 2024
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Code |
LM podcast |
Bibtex
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Compressed Context Memory For Online Language Model Interaction
Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun†, Hyun Oh
Song†
ICLR, 2024
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Code |
Project Page |
Bibtex
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Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data
Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song
NeurIPS, 2023
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Code |
Bibtex
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Dataset Condensation via Efficient Synthetic-Data Parameterization
Jang-Hyun Kim, Jinuk Kim, Seong Joon Oh, Sangdoo Yun, Hwanjun Song, Joonhyun
Jeong, Jung-Woo Ha, Hyun Oh Song
ICML, 2022
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Code |
Bibtex
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Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
Gaon An*, Seungyong Moon*, Jang-Hyun Kim, Hyun Oh Song
NeurIPS, 2021
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Code |
Bibtex
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Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity
Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song
ICLR (
Oral Presentation
), 2021
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Code |
Bibtex
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Spherical Principal Curves
Jongmin Lee*, Jang-Hyun Kim*, Hee-Seok Oh (*: equal contribution)
TPAMI, 2021 | R Journal, 2022
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R Journal |
Code |
Bibtex
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Puzzle Mix: Exploiting Saliency and Local statistics for Optimal Mixup
Jang-Hyun Kim, Wonho Choo, Hyun Oh Song
ICML, 2020
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Code |
Bibtex
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Phase-Aware Speech Enhancement with Deep Complex U-Net
Hyeong-Seok Choi, Jang-Hyun Kim, Jaesung Huh, Adrian Kim, Jung-Woo Ha, Kyogu Lee
arxiv, 2019
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Bibtex
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Multi-Domain Processing via Hybrid Denoising Networks for Speech Enhancement
Jang-Hyun Kim*, Jaejun Yoo*, Sanghyuk Chun, Adrian Kim, Jung-Woo Ha
arxiv, 2018
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Bibtex |
Demo
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Google's Speaker Verification
Code |
Kaggle
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Caricature Generation
Code
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Image Mosaic via Mixed Integer Programming
Code
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Notes
Mathematical Backgrounds for Machine Learning,
An undergraduate dissertation (in Korean, 2018), Paper
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Academic Services
Workshop Program Committee
- First Workshop on Interpolation Regularizers and Beyond (NeurIPS 2022), Website
- Workshop on ImageNet: Past, Present, and Future (NeurIPS 2021), Website
Reviewing Activities
- NeurIPS (2021-), ICLR (2022-), ICML (2022-), TMLR (2022-)
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