Speaker Invariant Feature Extraction for Zero-Resource Languages with Adversarial Learning. - Taira Tsuchiya; Naohiro Tawara; Tetsuji Ogawa; Tetsunori Kobayashi (ICASSP, 2018)

Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization. - Taira Tsuchiya; Nontawat Charoenphakdee; Issei Sato; Masashi Sugiyama (CoRR, 2019)

Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring. - Taira Tsuchiya; Junya Honda; Masashi Sugiyama (NeurIPS, 2020)

Semisupervised Ordinal Regression Based on Empirical Risk Minimization. - Taira Tsuchiya; Nontawat Charoenphakdee; Issei Sato; Masashi Sugiyama (Neural Comput., 2021)

Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds. - Shinji Ito; Taira Tsuchiya; Junya Honda (COLT, 2022)

Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs. - Shinji Ito; Taira Tsuchiya; Junya Honda (NeurIPS, 2022)

Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification. - Junpei Komiyama; Taira Tsuchiya; Junya Honda (NeurIPS, 2022)

Globally Optimal Algorithms for Fixed-Budget Best Arm Identification. - Junpei Komiyama; Taira Tsuchiya; Junya Honda (CoRR, 2022)

Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits. - Taira Tsuchiya; Shinji Ito; Junya Honda (AISTATS, 2023)

Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems. - Junya Honda; Shinji Ito; Taira Tsuchiya (ALT, 2023)

Best-of-Both-Worlds Algorithms for Partial Monitoring. - Taira Tsuchiya; Shinji Ito; Junya Honda (ALT, 2023)

Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds. - Taira Tsuchiya; Shinji Ito; Junya Honda (NeurIPS, 2023)

Best-of-Both-Worlds Algorithms for Linear Contextual Bandits. - Yuko Kuroki; Alberto Rumi; Taira Tsuchiya; Fabio Vitale; Nicolò Cesa-Bianchi (AISTATS, 2024)

Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds. - Shinji Ito; Taira Tsuchiya; Junya Honda (COLT, 2024)

Online Structured Prediction with Fenchel-Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss. - Shinsaku Sakaue; Han Bao 002; Taira Tsuchiya; Taihei Oki (COLT, 2024)

Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring. - Taira Tsuchiya; Shinji Ito; Junya Honda (ICML, 2024)

A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $ Theta(T^{2/3})$ and its Application to Best-of-Both-Worlds. - Taira Tsuchiya; Shinji Ito (NeurIPS, 2024)

Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets. - Taira Tsuchiya; Shinji Ito (NeurIPS, 2024)

Online Control of Linear Systems with Unbounded and Degenerate Noise. - Kaito Ito; Taira Tsuchiya (CoRR, 2024)

Fast Rates in Online Convex Optimization by Exploiting the Curvature of Feasible Sets. - Taira Tsuchiya; Shinji Ito (CoRR, 2024)

A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of θ(T2/3) and its Application to Best-of-Both-Worlds. - Taira Tsuchiya; Shinji Ito (CoRR, 2024)

Revisiting Online Learning Approach to Inverse Linear Optimization: A Fenchel-Young Loss Perspective and Gap-Dependent Regret Analysis. - Shinsaku Sakaue; Han Bao 002; Taira Tsuchiya (AISTATS, 2025)

Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback. - Shinji Ito; Haipeng Luo; Taira Tsuchiya; Yue Wu (COLT, 2025)

Corrupted Learning Dynamics in Games. - Taira Tsuchiya; Shinji Ito; Haipeng Luo (COLT, 2025)

Online Inverse Linear Optimization: Improved Regret Bound, Robustness to Suboptimality, and Toward Tight Regret Analysis. - Shinsaku Sakaue; Taira Tsuchiya; Han Bao 002; Taihei Oki (CoRR, 2025)

Bandit and Delayed Feedback in Online Structured Prediction. - Yuki Shibukawa; Taira Tsuchiya; Shinsaku Sakaue; Kenji Yamanishi (CoRR, 2025)

Reinforcement Learning from Adversarial Preferences in Tabular MDPs. - Taira Tsuchiya; Shinji Ito; Haipeng Luo (CoRR, 2025)