Jang-Hyun Kim
Hello!
I am a PhD student at Seoul National University, Computer Science department, advised by Hyun Oh Song.
My research interests lie in the field of machine learning, especially in solving challenging
problems from the optimization perspective.
I previously interned at NAVER CLOVA AI in 2018, working on speech enhancement and speaker
verification.
I completed my Bachelors with Mathematics from Seoul National University in 2019.
Email   / 
CV   / 
Scholar   / 
Github   / 
Twitter
|
|
|
Neural Relation Graph: A Unified Framework for Identifying Label Noise and Outlier Data
Jang-Hyun Kim, Sangdoo Yun, Hyun Oh Song
Preprint, 2023
Paper |
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
Code
|
|
Image Mosaic via Mixed Integer Programming
Code
|
Notes
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-)
|
|