Taira Tsuchiya

According to our database, Taira Tsuchiya authored at least 18 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Adaptive Learning Rate for Follow-the-Regularized-Leader: Competitive Analysis and Best-of-Both-Worlds.

Shinji Ito, Taira Tsuchiya, Junya Honda

CoRR, 2024

Fast Rates in Online Convex Optimization by Exploiting the Curvature of Feasible Sets.

Taira Tsuchiya, Shinji Ito

CoRR, 2024

Online Control of Linear Systems with Unbounded and Degenerate Noise.

Kaito Ito, Taira Tsuchiya

CoRR, 2024

Exploration by Optimization with Hybrid Regularizers: Logarithmic Regret with Adversarial Robustness in Partial Monitoring.

Taira Tsuchiya, Shinji Ito, Junya Honda

CoRR, 2024

Online Structured Prediction with Fenchel-Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss.

Shinsaku Sakaue, Han Bao, Taira Tsuchiya, Taihei Oki

CoRR, 2024

2023

Best-of-Both-Worlds Algorithms for Linear Contextual Bandits.

Yuko Kuroki, Alberto Rumi, Taira Tsuchiya, Fabio Vitale, Nicolò Cesa-Bianchi

CoRR, 2023

Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds.

Taira Tsuchiya, Shinji Ito, Junya Honda

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Best-of-Both-Worlds Algorithms for Partial Monitoring.

Taira Tsuchiya, Shinji Ito, Junya Honda

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Follow-the-Perturbed-Leader Achieves Best-of-Both-Worlds for Bandit Problems.

Junya Honda, Shinji Ito, Taira Tsuchiya

Proceedings of the International Conference on Algorithmic Learning Theory, 2023

Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits.

Taira Tsuchiya, Shinji Ito, Junya Honda

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Globally Optimal Algorithms for Fixed-Budget Best Arm Identification.

Junpei Komiyama, Taira Tsuchiya, Junya Honda

CoRR, 2022

Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification.

Junpei Komiyama, Taira Tsuchiya, Junya Honda

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs.

Shinji Ito, Taira Tsuchiya, Junya Honda

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds.

Shinji Ito, Taira Tsuchiya, Junya Honda

Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022

2021

Semisupervised Ordinal Regression Based on Empirical Risk Minimization.

Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama

Neural Comput., 2021

2020

Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring.

Taira Tsuchiya, Junya Honda, Masashi Sugiyama

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization.

Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, Masashi Sugiyama

CoRR, 2019

2018

Speaker Invariant Feature Extraction for Zero-Resource Languages with Adversarial Learning.

Taira Tsuchiya, Naohiro Tawara, Tetsuji Ogawa, Tetsunori Kobayashi

Proceedings of the 2018 IEEE International Conference on Acoustics, 2018