| 2024 | AAAI | Mixed-Effects Contextual Bandits. | Kyungbok Lee, Myunghee Cho Paik, Min-hwan Oh, Gi-Soo Kim |
| 2023 | AAAI | Double Doubly Robust Thompson Sampling for Generalized Linear Contextual Bandits. | Wonyoung Kim, Kyungbok Lee, Myunghee Cho Paik |
| 2023 | AISTATS | Squeeze All: Novel Estimator and Self-Normalized Bound for Linear Contextual Bandits. | Wonyoung Kim, Myunghee Cho Paik, Min-hwan Oh |
| 2023 | ICML | Semi-Parametric Contextual Pricing Algorithm using Cox Proportional Hazards Model. | Young-Geun Choi, Gi-Soo Kim, Yunseo Choi, Wooseong Cho, Myunghee Cho Paik, Min-hwan Oh |
| 2021 | AAAI | Kernel-convoluted Deep Neural Networks with Data Augmentation. | Minjin Kim, Young-geun Kim, Dongha Kim, Yongdai Kim, Myunghee Cho Paik |
| 2020 | AISTATS | Lipschitz Continuous Autoencoders in Application to Anomaly Detection. | Young-geun Kim, Yongchan Kwon, Hyunwoong Chang, Myunghee Cho Paik |
| 2020 | ICML | Principled learning method for Wasserstein distributionally robust optimization with local perturbations. | Yongchan Kwon, Wonyoung Kim, Joong-Ho Won, Myunghee Cho Paik |
| 2019 | ICML | Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model. | Gi-Soo Kim, Myunghee Cho Paik |
| 2016 | MICCAI | Ensemble of Deep Convolutional Neural Networks for Prognosis of Ischemic Stroke. | Youngwon Choi, Yongchan Kwon, Han-Byul Lee, Beomjoon Kim, Myunghee Cho Paik, Joong-Ho Won |