| 2026 | COLT | A Tight Lower Bound for Non-stochastic Multi-armed Bandits with Expert Advice. | Zachary Chase, Shinji Ito, Idan Mehalel |
| 2026 | COLT | Adversarial Learning in Games with Bandit Feedback: Logarithmic Pure-Strategy Maximin Regret. | Shinji Ito, Haipeng Luo, Arnab Maiti, Taira Tsuchiya, Yue Wu |
| 2026 | COLT | Adaptive Learning Rates with Surrogate Probability for Follow-the-Perturbed-Leader. | Jongyeong Lee, Junya Honda, Shinji Ito, Chansoo Kim |
| 2025 | AISTATS | LC-Tsallis-INF: Generalized Best-of-Both-Worlds Linear Contextual Bandits. | Masahiro Kato, Shinji Ito |
| 2025 | COLT | Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback. | Shinji Ito, Haipeng Luo, Taira Tsuchiya, Yue Wu |
| 2025 | COLT | Data-dependent Bounds with T-Optimal Best-of-Both-Worlds Guarantees in Multi-Armed Bandits using Stability-Penalty Matching. | Quan M. Nguyen, Shinji Ito, Junpei Komiyama, Nishant A. Mehta |
| 2025 | COLT | Corrupted Learning Dynamics in Games. | Taira Tsuchiya, Shinji Ito, Haipeng Luo |
| 2024 | AAAI | New Classes of the Greedy-Applicable Arm Feature Distributions in the Sparse Linear Bandit Problem. | Koji Ichikawa, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi |
| 2024 | COLT | Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds. | Shinji Ito, Taira Tsuchiya, Junya Honda |
| 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 |
| 2024 | ICML | Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring. | Taira Tsuchiya, Shinji Ito, Junya Honda |
| 2024 | IJCAI | Learning with Posterior Sampling for Revenue Management under Time-varying Demand. | Kazuma Shimizu, Junya Honda, Shinji Ito, Shinji Nakadai |
| 2023 | ACML | Maximization of Minimum Weighted Hamming Distance between Set Pairs. | Tatsuya Matsuoka, Shinji Ito |
| 2023 | AISTATS | Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits. | Taira Tsuchiya, Shinji Ito, Junya Honda |
| 2023 | ALT | Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems. | Junya Honda, Shinji Ito, Taira Tsuchiya |
| 2023 | ALT | Best-of-Both-Worlds Algorithms for Partial Monitoring. | Taira Tsuchiya, Shinji Ito, Junya Honda |
| 2023 | COLT | Best-of-Three-Worlds Linear Bandit Algorithm with Variance-Adaptive Regret Bounds. | Shinji Ito, Kei Takemura |
| 2022 | AAAI | Online Task Assignment Problems with Reusable Resources. | Hanna Sumita, Shinji Ito, Kei Takemura, Daisuke Hatano, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi |
| 2022 | COLT | Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds. | Shinji Ito, Taira Tsuchiya, Junya Honda |
| 2022 | ICML | Revisiting Online Submodular Minimization: Gap-Dependent Regret Bounds, Best of Both Worlds and Adversarial Robustness. | Shinji Ito |
| 2021 | AAAI | Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions. | Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi |
| 2021 | AISTATS | Tracking Regret Bounds for Online Submodular Optimization. | Tatsuya Matsuoka, Shinji Ito, Naoto Ohsaka |
| 2021 | AISTATS | A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits. | Kei Takemura, Shinji Ito, Daisuke Hatano, Hanna Sumita, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi |
| 2021 | COLT | Parameter-Free Multi-Armed Bandit Algorithms with Hybrid Data-Dependent Regret Bounds. | Shinji Ito |
| 2020 | AISTATS | An Optimal Algorithm for Bandit Convex Optimization with Strongly-Convex and Smooth Loss. | Shinji Ito |
| 2019 | ICDM | An Arm-Wise Randomization Approach to Combinatorial Linear Semi-Bandits. | Kei Takemura, Shinji Ito |
| 2018 | AISTATS | Online Regression with Partial Information: Generalization and Linear Projection. | Shinji Ito, Daisuke Hatano, Hanna Sumita, Akihiro Yabe, Takuro Fukunaga, Naonori Kakimura, Ken-ichi Kawarabayashi |
| 2018 | ICML | Unbiased Objective Estimation in Predictive Optimization. | Shinji Ito, Akihiro Yabe, Ryohei Fujimaki |
| 2018 | ICML | Causal Bandits with Propagating Inference. | Akihiro Yabe, Daisuke Hatano, Hanna Sumita, Shinji Ito, Naonori Kakimura, Takuro Fukunaga, Ken-ichi Kawarabayashi |
| 2017 | IJCAI | Robust Quadratic Programming for Price Optimization. | Akihiro Yabe, Shinji Ito, Ryohei Fujimaki |
| 2017 | KDD | Optimization Beyond Prediction: Prescriptive Price Optimization. | Shinji Ito, Ryohei Fujimaki |
| 2016 | KES | Supporting System for Descriptive Quiz in Large Class - Effectiveness of the Three-step-view System -. | Shinji Ito, Tomoya Oba, Haruhiko Takase, Hiroharu Kawanaka, Shinji Tsuruoka |
| 2002 | VLSID | A Parallel and Accelerated Circuit Simulator with Precise Accuracy. | Peter M. Lee, Shinji Ito, Takeaki Hashimoto, Junji Sato, Tomomasa Touma, Goichi Yokomizo |