Jeongyoun Ahn

According to our database, Jeongyoun Ahn authored at least 22 papers between 2006 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2026

On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists.

Seungone Kim, Dongkeun Yoon, Kiril Gashteovski, Juyoung Suk, Jinheon Baek, Pranjal Aggarwal, Ian Wu, Viktor Zaverkin, Spase Petkoski, Daniel R. Schrider, Ilija Dukovski, Francesco Santini, Biljana Mitreska, Yong Jeong, Kyeongha Kwon, Young Min Sim, Dragana Manasova, Arthur Porto, Biljana Mojsoska, Makoto Takamoto, Marko Shuntov, Ruoqi Liu, Hyunjoo Jenny Lee, Niyazi Ulas Dinç, Yehhyun Jo, Sunkyu Han, Chungwoo Lee, Huishan Li, Esther H. R. Tsai, Ergun Simsek, Khushboo Shafi, Yeonseung Chung, Jihye Park, Aleksandar Shulevski, Henrik Christiansen, Yoosang Son, Elly Knight, Amanda Montoya, Jeongyoun Ahn, Christian Langkammer, Heera Moon, Changwon Yoon, Nikola Stikov, Mooseok Jang, Edward Choi, Junhan Kim, Yeon Sik Jung, Woo Youn Kim, Jae Kyoung Kim, Ishraq Md Anjum, Hyun Uk Kim, Drew Bridges, Carolin Lawrence, Xiang Yue, Alice Oh, Akari Asai, Sean Welleck, Graham Neubig

CoRR, May, 2026

2025

Optimal differentially private kernel learning with random projection.

Bonwoo Lee, Cheolwoo Park, Jeongyoun Ahn

CoRR, July, 2025

Variable Selection and Basis Learning for Ordinal Classification.

Minwoo Kim, Sangil Han, Jeongyoun Ahn, Sungkyu Jung

J. Comput. Graph. Stat., 2025

Kernel density estimation for compositional data with zeros via hypersphere mapping.

Changwon Yoon, Hyunbin Choi, Jeongyoun Ahn

Comput. Stat. Data Anal., 2025

2024

Differential Privacy in Scalable General Kernel Learning via $K$-means Nystr{\"o}m Random Features.

Bonwoo Lee, Jeongyoun Ahn, Cheolwoo Park

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

Reproducing Kernels and New Approaches in Compositional Data Analysis.

Binglin Li, Changwon Yoon, Jeongyoun Ahn

J. Mach. Learn. Res., 2023

Minimax Risks and Optimal Procedures for Estimation under Functional Local Differential Privacy.

Bonwoo Lee, Jeongyoun Ahn, Cheolwoo Park

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Kernel Sufficient Dimension Reduction and Variable Selection for Compositional Data via Amalgamation.

Junyoung Park, Jeongyoun Ahn, Cheolwoo Park

Proceedings of the International Conference on Machine Learning, 2023

2022

Low-rank, Orthogonally Decomposable Tensor Regression With Application to Visual Stimulus Decoding of fMRI Data.

J. C. Poythress, Jeongyoun Ahn, Cheolwoo Park

J. Comput. Graph. Stat., 2022

Reproducing Kernels and New Approaches in Compositional Data Analysis.

Binglin Li, Jeongyoun Ahn

CoRR, 2022

Kernel Methods for Radial Transformed Compositional Data with Many Zeros.

Junyoung Park, Changwon Yoon, Cheolwoo Park, Jeongyoun Ahn

Proceedings of the International Conference on Machine Learning, 2022

2021

Subspace rotations for high-dimensional outlier detection.

Hee Cheol Chung, Jeongyoun Ahn

J. Multivar. Anal., 2021

Trace Ratio Optimization for High-Dimensional Multi-Class Discrimination.

Jeongyoun Ahn, Hee Cheol Chung, Yongho Jeon

J. Comput. Graph. Stat., 2021

Feature-weighted ordinal classification for predicting drug response in multiple myeloma.

Ziyang Ma, Jeongyoun Ahn

Bioinform., 2021

2020

Grouped variable screening for ultra-high dimensional data for linear model.

Debin Qiu, Jeongyoun Ahn

Comput. Stat. Data Anal., 2020

2016

General sparse multi-class linear discriminant analysis.

Sandra E. Safo, Jeongyoun Ahn

Comput. Stat. Data Anal., 2016

2015

A Nonparametric Kernel Approach to Interval-Valued Data Analysis.

Yongho Jeon, Jeongyoun Ahn, Cheolwoo Park

Technometrics, 2015

Sparse HDLSS discrimination with constrained data piling.

Jeongyoun Ahn, Yongho Jeon

Comput. Stat. Data Anal., 2015

2012

A resampling approach for interval-valued data regression.

Jeongyoun Ahn, Muliang Peng, Cheolwoo Park, Yongho Jeon

Stat. Anal. Data Min., 2012

2010

A stable hyperparameter selection for the Gaussian RBF kernel for discrimination.

Jeongyoun Ahn

Stat. Anal. Data Min., 2010

2007

Support vector machines with adaptive L_q penalty.

Yufeng Liu, Hao Helen Zhang, Cheolwoo Park, Jeongyoun Ahn

Comput. Stat. Data Anal., 2007

2006

Gene selection using support vector machines with non-convex penalty.

Hao Helen Zhang, Jeongyoun Ahn, Xiaodong Lin, Cheolwoo Park

Bioinform., 2006