Joong-Ho Won

36 papers A* 8A 2Journal 24Unranked 2
YearRankTypeTitle / Venue / Authors
2024 A* conf
$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence.
ICLR
Juno Kim, Jaehyuk Kwon, Mincheol Cho, Hyunjong Lee, Joong-Ho Won
2024 J jnl
Learning Massive-scale Partial Correlation Networks in Clinical Multi-omics Studies with HP-ACCORD.
CoRR
Sungdong Lee, Joshua Bang, Youngrae Kim, Hyungwon Choi, Sang-Yun Oh, Joong-Ho Won
2024 J jnl
On the Correctness of the Generalized Isotonic Recursive Partitioning Algorithm.
CoRR
Joong-Ho Won, Jihan Jung
2024 A* conf
StrWAEs to Invariant Representations.
ICML
Hyunjong Lee, Yedarm Seong, Sungdong Lee, Joong-Ho Won
2023 J jnl
A unified analysis of convex and non-convex ℓ
Optim. Lett.
Joong-Ho Won, Kenneth Lange, Jason Xu
2023 J jnl
Wasserstein Geodesic Generator for Conditional Distributions.
CoRR
Young-geun Kim, Kyungbok Lee, Youngwon Choi, Joong-Ho Won, Myunghee Cho Paik
2023 J jnl
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CoRR
Juno Kim, Jaehyuk Kwon, Mincheol Cho, Hyunjong Lee, Joong-Ho Won
2022 J jnl
Impact of Diffusion-Perfusion Mismatch on Predicting Final Infarction Lesion Using Deep Learning.
IEEE Access
Sungdong Lee, Leonard Sunwoo, Youngwon Choi, Jae Hyup Jung, Seung Chai Jung, Joong-Ho Won
2022 J jnl
Orthogonal Trace-Sum Maximization: Tightness of the Semidefinite Relaxation and Guarantee of Locally Optimal Solutions.
SIAM J. Optim.
Joong-Ho Won, Teng Zhang, Hua Zhou
2022 A* conf
Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert.
ICML
Yoonhyung Lee, Sungdong Lee, Joong-Ho Won
2022 J jnl
Statistical inference with implicit SGD: proximal Robbins-Monro vs. Polyak-Ruppert.
CoRR
Yoonhyung Lee, Sungdong Lee, Joong-Ho Won
2021 J jnl
Computationally scalable regression modeling for ultrahigh-dimensional omics data with ParProx.
Briefings Bioinform.
Seyoon Ko, Ginny X. Li, Hyungwon Choi, Joong-Ho Won
2021 A* conf
Learning from Nested Data with Ornstein Auto-Encoders.
ICML
Youngwon Choi, Sungdong Lee, Joong-Ho Won
2021 J jnl
Orthogonal Trace-Sum Maximization: Applications, Local Algorithms, and Global Optimality.
SIAM J. Matrix Anal. Appl.
Joong-Ho Won, Hua Zhou, Kenneth Lange
2020 J jnl
A real-time 3D video analyzer for enhanced 3D audio-visual systems.
Multim. Syst.
Sangoh Jeong, Hyun-Soo Kim, KyuWoon Kim, Byeong-Moon Jeon, Joong-Ho Won
2020 J jnl
DistStat.jl: Towards Unified Programming for High-Performance Statistical Computing Environments in Julia.
CoRR
Seyoon Ko, Hua Zhou, Jin Zhou, Joong-Ho Won
2020 J jnl
Principled Learning Method for Wasserstein distributionally robust optimization with local perturbations.
CoRR
Yongchan Kwon, Wonyoung Kim, Joong-Ho Won, Myunghee Cho Paik
2020 A* conf
Principled learning method for Wasserstein distributionally robust optimization with local perturbations.
ICML
Yongchan Kwon, Wonyoung Kim, Joong-Ho Won, Myunghee Cho Paik
2020 A* conf
Proximity Operator of the Matrix Perspective Function and its Applications.
NeurIPS
Joong-Ho Won
2020 J jnl
Splitting with Near-Circulant Linear Systems: Applications to Total Variation CT and PET.
SIAM J. Sci. Comput.
Ernest K. Ryu, Seyoon Ko, Joong-Ho Won
2020 J jnl
Uncertainty quantification using Bayesian neural networks in classification: Application to biomedical image segmentation.
Comput. Stat. Data Anal.
Yongchan Kwon, Joong-Ho Won, Beomjoon Kim, Myunghee Cho Paik
2019 A conf
Optimal Minimization of the Sum of Three Convex Functions with a Linear Operator.
AISTATS
Seyoon Ko, Joong-Ho Won
2019 A* conf
Ornstein Auto-Encoders.
IJCAI
Youngwon Choi, Joong-Ho Won
2019 A* conf
Projection onto Minkowski Sums with Application to Constrained Learning.
ICML
Joong-Ho Won, Jason Xu, Kenneth Lange
2018 J jnl
A peeling algorithm for multiple testing on a random field.
Comput. Stat.
Joungyoun Kim, Donghyeon Yu, Johan Lim, Joong-Ho Won
2018 J jnl
Comparative study of computational algorithms for the Lasso with high-dimensional, highly correlated data.
Appl. Intell.
Baekjin Kim, Donghyeon Yu, Joong-Ho Won
2018 J jnl
Correction to: HiComet: a high-throughput comet analysis tool for large-scale DNA damage assessment.
BMC Bioinform.
Taehoon Lee, Sungmin Lee, Woo Young Sim, Yu Mi Jung, Sunmi Han, Joong-Ho Won, Hyeyoung Min, Sungroh Yoon
2018 J jnl
HiComet: a high-throughput comet analysis tool for large-scale DNA damage assessment.
BMC Bioinform.
Taehoon Lee, Sungmin Lee, Woo Young Sim, Yu Mi Jung, Sunmi Han, Joong-Ho Won, Hyeyoung Min, Sungroh Yoon
2018 A conf
Nonparametric Sharpe Ratio Function Estimation in Heteroscedastic Regression Models via Convex Optimization.
AISTATS
Seung-Jean Kim, Johan Lim, Joong-Ho Won
2018 J jnl
hc-OTU: A Fast and Accurate Method for Clustering Operational Taxonomic Units Based on Homopolymer Compaction.
IEEE ACM Trans. Comput. Biol. Bioinform.
Seunghyun Park, Hyun-Soo Choi, Byunghan Lee, Jongsik Chun, Joong-Ho Won, Sungroh Yoon
2017 J jnl
Cross-sectional design with a short-term follow-up for prognostic imaging biomarkers.
Comput. Stat. Data Anal.
Joong-Ho Won, Xiao Wu, Sang Han Lee, Ying Lu
2016 — conf
Ensemble of Deep Convolutional Neural Networks for Prognosis of Ischemic Stroke.
BrainLes@MICCAI
Youngwon Choi, Yongchan Kwon, Han-Byul Lee, Beomjoon Kim, Myunghee Cho Paik, Joong-Ho Won
2013 J jnl
Massively Parallel Energy Space Exploration for Uncluttered Visualization of Vascular Structures.
IEEE Trans. Biomed. Eng.
Yongkweon Jeon, Joong-Ho Won, Sungroh Yoon
2013 J jnl
Uncluttered Single-Image Visualization of Vascular Structures Using GPU and Integer Programming.
IEEE Trans. Vis. Comput. Graph.
Joong-Ho Won, Yongkweon Jeon, Jarrett Rosenberg, Sungroh Yoon, Geoffrey D. Rubin, Sandy Napel
2012 J jnl
ROC convex hull and nonparametric maximum likelihood estimation.
Mach. Learn.
Johan Lim, Joong-Ho Won
2006 — conf
Flattening the Abdominal Aortic Tree for Effective Visualization.
EMBC
Joong-Ho Won, Geoffrey D. Rubin, Sandy Napel