Jang-Hyun Kim

Hello! I am a PhD student in computer science at Seoul National University, advised by Hyun Oh Song. I am currently at New York University as a visiting scholar, hosted by Kyunghyun Cho (~2024.08). I previously interned at NAVER AI in 2018. I completed BSc with Mathematics at Seoul National University in 2019. My PhD studies are supported by the Korea Foundation for Advanced Studies (KFAS).

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My research focuses on developing a robust and efficient machine learning system with a data-centric approach, particularly leveraging the interplay between data and a model. Across various domains including image, speech, and language, I address real-world challenges.

My key research observations are:
  • [Compression] Trained models can compress datasets or contexts, enhancing the efficiency of training and inference processes. [Context Memory, Data Condensation, Principal Curve].
  • [Identification] We can infer relationships within data by leveraging trained models, facilitating the characterization of problematic data in large datasets. [Neural Relation Graph].
  • [Generation] During training, models learn to locate informative parts of the data for inference. Saliency-guided data augmentation can reinforce the training. [Puzzle Mix, Co-Mixup].

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

Google's Speaker Verification
Code | Kaggle

Caricature Generation

Image Mosaic via Mixed Integer Programming


Mathematical Backgrounds for Machine Learning, An undergraduate dissertation (in Korean, 2018), Paper

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-)

Template based on Jon Barron's website.