Jang-Hyun Kim

Hello! I am a PhD student in computer science at Seoul National University, advised by Hyun Oh Song. I am currently a visiting scholar at New York University, hosted by Kyunghyun Cho. I previously interned at NAVER AI, where I worked on speech enhancement research. I completed BSc with Mathematics at Seoul National University. My PhD studies are supported by Korea Foundation for Advanced Studies.

Email / CV / Scholar / Github / Twitter

Research

My research aims at developing efficient and robust AI systems through the co-optimization of machine learning models and data. My key research observations are:

[Compression] Trained neural networks have a capability to compress datasets or contexts, enhancing the efficiency of training and inference processes. [Context Memory, Data Condensation, Principal Curve].
[Identification] Trained models encode a relational structure among data, facilitating the characterization of problematic data in large datasets. [Neural Relation Graph].
[Generation] Throughout training, models learn to locate informative parts of data for inference. Saliency-guided data augmentation can reinforce the training. [Puzzle Mix, Co-Mixup].

Publications

	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