Tsuchiya, Taira

1. Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
   2023/05/26 by Taira Tsuchiya, Tsuchiya, Taira, Shinji Ito +3 · 4 citations
   Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Reinforcement Learning in Robotics #Stochastic Gradient Optimization Techniques
2. Best-of-Both-Worlds Algorithms for Linear Contextual Bandits
   2023/12/24 by Yuko Kuroki, Alberto Rumi, Kuroki, Yuko +7 · 4 citations
   Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
3. Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs
   2022/06/02 by Ito, Shinji, Tsuchiya, Taira, Honda, Junya · 3 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG)
4. Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds
   2024/03/01 by Shinji Ito, Taira Tsuchiya, Ito, Shinji +3 · 4 citations
   Computer Science · #Distributed Sensor Networks and Detection Algorithms
5. Best-of-Both-Worlds Algorithms for Partial Monitoring
   2022/07/29 by Taira Tsuchiya, Tsuchiya, Taira, Shinji Ito +3 · 2 citations
   Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms #Reinforcement Learning in Robotics
6. Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring
   2020/06/17 by Tsuchiya, Taira, Honda, Junya, Sugiyama, Masashi · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
7. Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification
   2022/06/09 by Komiyama, Junpei, Tsuchiya, Taira, Honda, Junya · 1 citation
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
8. Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds
   2022/06/14 by Shinji Ito, Ito, Shinji, Taira Tsuchiya +3 · 1 citation
   Computer Science · Decision Sciences · #Advanced Bandit Algorithms Research #Adversarial Robustness in Machine Learning #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
9. Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring
   2024/02/13 by Tsuchiya, Taira, Ito, Shinji, Honda, Junya · 2 citations
   #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
10. A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of Θ(T^2/3) and its Application to Best-of-Both-Worlds
    2024/05/30 by Taira Tsuchiya, Shinji Ito, Tsuchiya, Taira +1 · 2 citations
    Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning and Algorithms
11. Corrupted Learning Dynamics in Games
    2024/12/10 by Tsuchiya, Taira, Ito, Shinji, Luo, Haipeng · 2 citations
    #Computer Science and Game Theory (cs.GT) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
12. Online Inverse Linear Optimization: Efficient Logarithmic-Regret Algorithm, Robustness to Suboptimality, and Lower Bound
    2025/01/24 by Sakaue, Shinsaku, Tsuchiya, Taira, Bao, Han +1 · 1 citation
    #FOS: Computer and information sciences #Machine Learning (cs.LG)
13. Instance-Dependent Regret Bounds for Learning Two-Player Zero-Sum Games with Bandit Feedback
    2025/02/24 by Shinji Ito, Ito, Shinji, Haipeng Luo +5 · 2 citations
    Decision Sciences · Computer Science · #Advanced Bandit Algorithms Research #Auction Theory and Applications #Data Stream Mining Techniques