Taira Tsuchiya

Japanese version is here

I am a third-year Ph.D. student at Kyoto University, advised by Prof. Junya Honda, and a member of Mathematical System Theory group. My research interest includes a wide range of statistical learning theories, especially on the theory of online decision making.

I am looking for a research position in the Kanto area (mainly Tokyo) starting in the fall of 2023.

[Google Scholar] [GitHub] [dblp] [researchmap]

** Contact: scse.taira [at] gmail.com (tsuchiya [at] ms.k.u-tokyo.ac.jp is NOT available.)

News

Publications

Preprints

  1. Taira Tsuchiya, Shinji Ito, and Junya Honda,
    "Best-of-Both-Worlds Algorithms for Partial Monitoring,"
    arXiv:2207.14550, 2022.
    [arXiv]

Conference Proceedings (peer-reviewed)

  1. Shinji Ito, Taira Tsuchiya, and Junya Honda,
    "Nearly Optimal Best-of-Both-Worlds Algorithms for Online Learning with Feedback Graphs,"
    In Advances in Neural Information Processing Systems 35 (NeurIPS 2022), pp.xxx–xxx, 2022.
    [arXiv]
  2. Junpei Komiyama, Taira Tsuchiya, and Junya Honda,
    "Globally Optimal Algorithms for Fixed-Budget Best Arm Identification,"
    In Advances in Neural Information Processing Systems 35 (NeurIPS 2022), pp.xxx–xxx, 2022.
    [arXiv]
  3. Shinji Ito, Taira Tsuchiya, and Junya Honda,
    "Adversarially Robust Multi-Armed Bandit Algorithm with Variance-Dependent Regret Bounds,"
    In Proceedings of Thirty Fifth Conference on Learning Theory (COLT 2022), pp.1421–1422, 2022.
    (Presented at Conference on Learning Theory (COLT 2022), London, UK, July 2–5, 2022)
    [proceeding (extended abstract)] [full paper on arXiv] [slide]
  4. Taira Tsuchiya, Junya Honda, and Masashi Sugiyama,
    "Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring,"
    In Advances in Neural Information Processing Systems 33 (NeurIPS 2020), pp.8861–8871, 2020.
    (Presented at Neural Information Processing Systems (NeurIPS2020), online, Dec. 6–12, 2020)
    [proceeding] [full paper (pdf)] [arXiv] [poster]
  5. Taira Tsuchiya, Naohiro Tawara, Tetsuji Ogawa, and Tetsunori Kobayashi,
    "Speaker Invariant Feature Extraction for Zero-Resource Languages with Adversarial Learning,"
    In Proceedings of 2018 IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP 2018), pp.2381–2385, 2018.
    (Presented at International Conference on Acoustic, Speech, and Signal Processing (ICASSP 2018), Calgary, Canada, Apr. 15–20, 2018)
    [preprint] [paper]

Journal Papers (peer-reviewed)

  1. Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, and Masashi Sugiyama,
    "Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization,"
    Neural Computation, 33(12):3361-3412, 2021.
    [arXiv] [paper]

Others (invited talks / domestic conferences / domestic proceedings / workshops)

  1. Taira Tsuchiya
    "Towards Practical Algorithms for Online Decision-Making,"
    Seminar talk at INRIA Lille Scool group, July 8, 2022.
    [slide]
  2. Junta Fujinaga, Taira Tsuchiya, and Junya Honda,
    "On DC Relaxation of Information-directed Sampling in Combinatorial Multi-armed Bandit Problem,"
    In Proceedings of Information-Based Induction Sciences and Machine Learning Workshop, vol.122, no.90, pp.129–136, June 2022.
  3. Taira Tsuchiya
    "Thompson Sampling for Partial Monitoring,"
    Toshiba Sympsium 2020, Dec. 22, 2020.
  4. Taira Tsuchiya, Junya Honda, and Masashi Sugiyama,
    "Analysis and Design of Thompson Sampling for Stochastic Partial Monitoring,"
    Presented at 23rd Information-Based Induction Sciences Workshop (IBIS 2020), Nov. 23–26, 2020.
    Recieved outstanding presentation award.
  5. Taira Tsuchiya, Nontawat Charoenphakdee, Issei Sato, and Masashi Sugiyama,
    "Semi-Supervised Ordinal Regression Based on Empirical Risk Minimization,"
    Presented at 22nd Information-Based Induction Sciences Workshop (IBIS 2019), Nov. 20–23, 2019.
  6. Taira Tsuchiya, Tomoharu Iwata, and Tetsuji Ogawa,
    "Transformed Multiple Matrix Factorization: Towards Utilizing Heterogeneous Auxiliary Information,"
    In Proceedings of Information-Based Induction Sciences and Machine Learning Workshop, vol.117, no.475, pp.41–48, March 2018.
  7. Naohiro Tawara, Taira Tsuchiya, Tetsuji Ogawa, and Tetsunori Kobayashi,
    "Speaker Feature Extraction using Adversarial Training,"
    In Proceedings of 2018 Spring Meeting of Acoustic Society of Japan (ASJ 2018), pp.141–144, March 2018.
  8. Taira Tsuchiya, Naohiro Tawara, Tetsuji Ogawa, and Tetsunori Kobayashi,
    "Adversarial Multi-Task Learning for Extracting Speaker Invariant Feature for Zero-Resource Languages,"
    In Proceedings of 2018 Spring Meeting of Acoustic Society of Japan (ASJ 2018), pp.9–12, March 2018.

Grants

  1. ACT-X, JST [link]
  2. JSPS Research Fellowship for Young Scientists (DC1), JSPS [link]
  3. AIP Challenge Program, JST (Aug. 2019 – Mar. 2020)

Awards

  1. Outstanding Presentation Award, IBIS2020, 2020 [link]
  2. Travel Award, NeurIPS 2020
  3. UTokyo Toyota-Dwango AI Scholarship (Apr. 2020 – Mar. 2021)
  4. UTokyo Toyota-Dwango AI Scholarship (Apr. 2019 – Mar. 2020)
  5. JEES-Softbank AI Scholarship (Apr. 2019 – Mar. 2020)
  6. Department Award, Waseda University, 2018

Professional Activities (Reviewer)

Contact

© Taira Tsuchiya, Oct 15, 2022