Won, Joong-Ho

12 publications

NeurIPS 2025 Partial Correlation Network Estimation by Semismooth Newton Methods DongWon Kim, Sungdong Lee, Joong-Ho Won

ICLR 2024 $t^3$-Variational Autoencoder: Learning Heavy-Tailed Data with Student's T and Power Divergence Juno Kim, Jaehyuk Kwon, Mincheol Cho, Hyunjong Lee, Joong-Ho Won

ICML 2024 StrWAEs to Invariant Representations Hyunjong Lee, Yedarm Seong, Sungdong Lee, Joong-Ho Won

ICML 2022 Statistical Inference with Implicit SGD: Proximal Robbins-Monro vs. Polyak-Ruppert Yoonhyung Lee, Sungdong Lee, Joong-Ho Won

ICML 2021 Learning from Nested Data with Ornstein Auto-Encoders Youngwon Choi, Sungdong Lee, Joong-Ho Won

ICML 2020 Principled Learning Method for Wasserstein Distributionally Robust Optimization with Local Perturbations Yongchan Kwon, Wonyoung Kim, Joong-Ho Won, Myunghee Cho Paik

NeurIPS 2020 Proximity Operator of the Matrix Perspective Function and Its Applications Joong-Ho Won

AISTATS 2019 Optimal Minimization of the Sum of Three Convex Functions with a Linear Operator Seyoon Ko, Joong-Ho Won

IJCAI 2019 Ornstein Auto-Encoders Youngwon Choi, Joong-Ho Won

ICML 2019 Projection onto Minkowski Sums with Application to Constrained Learning Joong-Ho Won, Jason Xu, Kenneth Lange

AISTATS 2018 Nonparametric Sharpe Ratio Function Estimation in Heteroscedastic Regression Models via Convex Optimization Seung-Jean Kim, Johan Lim, Joong-Ho Won

MLJ 2012 ROC Convex Hull and Nonparametric Maximum Likelihood Estimation Johan Lim, Joong-Ho Won