| 2026 | COLT | Adaptive Learning Rates with Surrogate Probability for Follow-the-Perturbed-Leader. | Jongyeong Lee, Junya Honda, Shinji Ito, Chansoo Kim |
| 2025 | ICML | Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit Problems. | Botao Chen, Jongyeong Lee, Junya Honda |
| 2024 | AAAI | The Choice of Noninformative Priors for Thompson Sampling in Multiparameter Bandit Models. | Jongyeong Lee, Chao-Kai Chiang, Masashi Sugiyama |
| 2024 | COLT | Follow-the-Perturbed-Leader with Frchet-type Tail Distributions: Optimality in Adversarial Bandits and Best-of-Both-Worlds. | Jongyeong Lee, Junya Honda, Shinji Ito, Min-hwan Oh |
| 2023 | ACML | Thompson Exploration with Best Challenger Rule in Best Arm Identification. | Jongyeong Lee, Junya Honda, Masashi Sugiyama |
| 2023 | ICML | Optimality of Thompson Sampling with Noninformative Priors for Pareto Bandits. | Jongyeong Lee, Junya Honda, Chao-Kai Chiang, Masashi Sugiyama |
| 2019 | EMNLP | Learning Only from Relevant Keywords and Unlabeled Documents. | Nontawat Charoenphakdee, Jongyeong Lee, Yiping Jin, Dittaya Wanvarie, Masashi Sugiyama |
| 2019 | ICML | On Symmetric Losses for Learning from Corrupted Labels. | Nontawat Charoenphakdee, Jongyeong Lee, Masashi Sugiyama |