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

Research (Research Statement)

My research focuses on constructing compressed memory and generating training data for deep neural networks. To address these challenges, I have developed optimization frameworks that leverage the feedback mechanisms of neural networks, without the need for direct human intervention:

Leveraging trained models to compress datasets or contexts, enhancing the efficiency of training and inference [Context Memory, Data Condensation, Principal Curve].
Saliency-guided data augmentation to reinforce model training [Puzzle Mix, Co-Mixup].
Large-scale identification of problematic data using relational structures encoded by models [Neural Relation Graph].

Publications

	Targeted Cause Discovery with Data-Driven Learning Jang-Hyun Kim, Claudia Skok Gibbs, Sangdoo Yun, Hyun Oh Song, Kyunghyun Cho arXiv, 2024 Paper \| Code \| LM podcast \| Bibtex
	Compressed Context Memory For Online Language Model Interaction Jang-Hyun Kim, Junyoung Yeom, Sangdoo Yun^†, Hyun Oh Song^† ICLR, 2024 Paper \| Code \| Project Page \| Bibtex
	Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song NeurIPS, 2023 Paper \| Code \| Bibtex
	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 Paper \| Code \| Bibtex
	Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble Gaon An, Seungyong Moon, Jang-Hyun Kim, Hyun Oh Song NeurIPS, 2021 Paper \| Code \| Bibtex
	Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity Jang-Hyun Kim, Wonho Choo, Hosan Jeong, Hyun Oh Song ICLR ( Oral Presentation ), 2021 Paper \| Code \| Bibtex
	Spherical Principal Curves Jongmin Lee, Jang-Hyun Kim, Hee-Seok Oh (: equal contribution) TPAMI, 2021 \| R Journal*, 2022 Paper \| R Journal \| Code \| Bibtex
	Puzzle Mix: Exploiting Saliency and Local statistics for Optimal Mixup Jang-Hyun Kim, Wonho Choo, Hyun Oh Song ICML, 2020 Paper \| Code \| Bibtex
	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 Paper \| Bibtex
	Multi-Domain Processing via Hybrid Denoising Networks for Speech Enhancement Jang-Hyun Kim, Jaejun Yoo, Sanghyuk Chun, Adrian Kim, Jung-Woo Ha arxiv, 2018 Paper \| Code \| Bibtex \| Demo