Publications

Refereed Journal Papers and Conference Proceedings

  1. Towards the Proximity Conjecture on Group-Labeled Matroids

    Dániel Garamvölgyi, Ryuhei Mizutani, Taihei Oki, Tamás Schwarcz, and Yutaro Yamaguchi Alphabetical

    • Proceedings of the 52nd International Colloquium on Automata, Languages and Programming (ICALP ’25), to appear.

    arXiv

  2. Algorithmic aspects of semistability of quiver representations

    Yuni Iwamasa, Taihei Oki, and Tasuku Soma Alphabetical

    • Proceedings of the 52nd International Colloquium on Automata, Languages and Programming (ICALP ’25), to appear.

    arXiv

  3. Fast and numerically stable implementation of rate constant matrix contraction method

    Shinichi Hemmi, Satoru Iwata, and Taihei Oki Alphabetical

    • Proceedings of the 10th International Council for Industrial and Applied Mathematics (ICIAM '23), to appear.

    arXiv

  4. Virtual ligand-assisted optimization: a rational strategy for ligand engineering

    Wataru Matsuoka, Taihei Oki, Ren Yamada, Tomohiko Yokoyama, Shinichi Suda, Carla M. Saunders, Bastian B. Skjelstad, Yu Harabuchi, Natalie Fey, Satoru Iwata, and Satoshi Maeda Contribution-based

    • ACS Catalysis, 14(21):16297–16312, 2024.

    JournalChemRxiv

  5. Algebraic combinatorial optimization on the degree of determinants of noncommutative symbolic matrices

    Hiroshi Hirai, Yuni Iwamasa, Taihei Oki, and Tasuku Soma Alphabetical

    • Mathematical Programming, 2024.

    JournalarXiv

  6. No-regret M${}^\natural$-concave function maximization: stochastic bandit algorithms and NP-hardness of adversarial full-information setting

    Taihei Oki and Shinsaku Sakaue Alphabetical

    • Advances in Neural Information Processing Systems 37 (NeurIPS '24), pp. 57418–57438, 2024.

    ProceedingarXiv

  7. Data-driven projection for reducing dimensionality of linear programs: generalization bound and learning methods

    Shinsaku Sakaue and Taihei Oki Contribution-based

    • Advances in Neural Information Processing Systems 37 (NeurIPS '24), pp. 12825–12846, 2024.

    ProceedingarXiv

  8. Fractional linear matroid matching is in quasi-NC

    Rohit Gurjar, Taihei Oki, and Roshan Raj Alphabetical

    • Proceedings of the 32nd Annual European Symposium on Algorithms (ESA ’24), LIPIcs 308, pp. 63:1–63:14, 2024.

    ProceedingarXivECCC

  9. Structural preprocessing method for nonlinear differential-algebraic equations using linear symbolic matrices

    Taihei Oki and Yujin Song Alphabetical

    • Proceedings of the 49th International Symposium on Symbolic and Algebraic Computation (ISSAC ’24), pp. 143–152, 2024.

    ProceedingarXiv

  10. Online structured prediction with Fenchel–Young losses and improved surrogate regret for online multiclass classification with logistic loss

    Shinsaku Sakaue, Han Bao, Taira Tsuchiya, and Taihei Oki Contribution-based

    • Proceedings of the 37th Conference on Learning Theory (COLT ’24), PMLR 247, pp. 4458–4486, 2024.

    ProceedingarXiv

  11. Problems on group-labeled matroid bases

    Florian Hörsch, András Imolay, Ryuhei Mizutani, Taihei Oki, and Tamás Schwarcz Alphabetical

    • Proceedings of the 51st International Colloquium on Automata, Languages and Programming (ICALP ’24), LIPIcs 297, pp. 86:1–86:20, 2024.

    ProceedingarXiv

  12. Differentiating the yield of chemical reactions using parameters in first-order kinetic equations to identify elementary steps that control the reactivity from complicated reaction path networks

    Yu Harabuchi, Tomohiko Yokoyama, Wataru Matsuoka, Taihei Oki, Satoru Iwata, and Satoshi Maeda Contribution-based

    • The Journal of Physical Chemistry, 128(14):2883–2890, 2024.

    JournalChemRxiv

  13. Faster discrete convex function minimization with predictions: the M-Convex case

    Taihei Oki and Shinsaku Sakaue Contribution-based

    • Advances in Neural Information Processing Systems 36 (NeurIPS '23), pp. 68576–68588, 2023.

    ProceedingarXiv

  14. Rethinking warm-starts with predictions: learning predictions close to sets of optimal solutions for faster $\text{L}$-/$\text{L}^\natural$-convex function minimization

    Shinsaku Sakaue and Taihei Oki Contribution-based

    • Proceedings of the 40th International Conference on Machine Learning (ICML '23), PMLR 202, pp. 29760–29776, 2023.

    ProceedingarXiv

  15. Improved generalization bound and learning of sparsity patterns for data-driven low-rank approximation

    Shinsaku Sakaue and Taihei Oki Contribution-based

    • Proceedings of the 26th International Conference on Artificial Intelligence and Statistics (AISTATS '23), PMLR 206, pp. 1–10, 2023.

    ProceedingarXiv

  16. Algebraic algorithms for fractional linear matroid parity via noncommutative rank

    Taihei Oki and Tasuku Soma Alphabetical

    • SIAM Journal on Computing, 54(1):134–162, 2025.

    • Proceedings of the 34th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA '23), pp. 4188–4204, 2023. (Under the title of “Algebraic algorithms for fractional linear matroid parity via non-commutative rank”)

    JournalProceedingarXiv

  17. Discrete-convex-analysis-based framework for warm-starting algorithms with predictions

    Shinsaku Sakaue and Taihei Oki Contribution-based

    • Advances in Neural Information Processing Systems 35 (NeurIPS '22), pp. 20988–21000, 2022.

    ProceedingarXiv

  18. Sample complexity of learning heuristic functions for greedy-best-first and A* search

    Shinsaku Sakaue and Taihei Oki Contribution-based

    • Advances in Neural Information Processing Systems 35 (NeurIPS '22), pp. 2889–2901, 2022.

    ProceedingarXiv

  19. Lazy and fast greedy MAP inference for determinantal point process

    Shinichi Hemmi, Taihei Oki, Shinsaku Sakaue, Kaito Fujii, and Satoru Iwata Contribution-based

    • Advances in Neural Information Processing Systems 35 (NeurIPS '22), pp. 2776–2789, 2022.

    ProceedingarXivMETR

  20. Pfaffian pairs and parities: counting on linear matroid intersection and parity problems

    Kazuki Matoya and Taihei Oki Alphabetical

    • SIAM Journal on Discrete Mathematics, 36(3):2121–2158, 2022.

    • Proceedings of the 22nd Conference on Integer Programming and Combinatorial Optimization (IPCO '21), LNCS 12707, pp. 223–237, 2021.

    JournalProceedingarXivMETR

  21. Computing valuations of the Dieudonné determinants

    Taihei Oki

    • Journal of Symbolic Computation, 116:284–323, 2023.

    • Proceedings of the 46th International Symposium on Symbolic and Algebraic Computation (ISSAC ’21), pp. 321–328, 2021.

    • Proceedings of the 47th International Colloquium on Automata, Languages and Programming (ICALP ’20), LIPIcs 168, pp. 89:1–89:14, 2020. (Under the title of “On solving (non)commutative weighted Edmonds’ problem”)

    JournalProceeding (ISSAC)Proceeding (ICALP)arXivMETR

  22. Dynamic programming approach to the generalized minimum Manhattan network problem

    Yuya Masumura, Taihei Oki, and Yutaro Yamaguchi Alphabetical

    • Algorithmica, 83(12):3681–3714, 2021.

    • Proceedings of the 6th International Symposium on Combinatorial Optimization (ISCO ’20), LNCS 12176, pp. 237–248, 2020.

    JournalProceedingarXiv

  23. Improved structural methods for nonlinear differential-algebraic equations via combinatorial relaxation

    Taihei Oki

    • IMA Journal of Numerical Analysis, 43(1):357–386, 2023.

    • Proceedings of the 44th International Symposium on Symbolic and Algebraic Computation (ISSAC ’19), pp. 315–322, 2019.

    JournalProceedingarXivMETR

  24. Index reduction for differential-algebraic equations with mixed matrices

    Satoru Iwata, Taihei Oki, and Mizuyo Takamatsu Alphabetical

    • Journal of the ACM, 66(5), 2019.

    • Proceedings of the 8th SIAM Workshop on Combinatorial Scientific Computing (CSC ’18), pp. 45–55, 2018.

    JournalProceedingarXivMETR

  25. A compact representation for minimizers of $k$-submodular functions

    Hiroshi Hirai and Taihei Oki Alphabetical

    • Journal of Combinatorial Optimization, 36(3):45–55, 2018.

    • Proceedings of the 4th International Symposium on Combinatorial Optimization (ISCO ’16), LNCS 9849, pp. 45–55, 2018.

    JournalProceedingarXivMETR

Preprints

  1. Steepest Descent Algorithm for M-convex Function Minimization Using Long Step Length

    Taihei Oki and Akiyoshi Shioura Alphabetical

      arXiv

    • Online Inverse Linear Optimization: Improved Regret Bound, Robustness to Suboptimality, and Toward Tight Regret Analysis

      Shinsaku Sakaue, Taira Tsuchiya, Han Bao, and Taihei Oki Contribution-based

        arXiv

      • Position Fair Mechanisms Allocating Indivisible Goods

        Ryoga Mahara, Ryuhei Mizutani, Taihei Oki, and Tomohiko Yokoyama Alphabetical

          arXiv

        • Rate Constant Matrix Contraction Method for Stiff Master Equations with Detailed Balance

          Satoru Iwata, Taihei Oki, and Shinsaku Sakaue Alphabetical

            arXivMETR

          • Multi-dimensional Graph Fourier Transform

            Takashi Kurokawa, Taihei Oki, and Hiromichi Nagao Contribution-based

              arXivMETR

            International Talks

              • Refereed
              • Poster

              Taihei Oki and Shinsaku Sakaue Alphabetical

              No-regret M${}^\natural$-concave function maximization: stochastic bandit algorithms and NP-hardness of adversarial full-information setting

              The 38th Conference on Neural Information Processing Systems (NeurIPS '24), Vancouver, BC, Canada, Dec. 2024.

              • Refereed
              • Oral

              Florian Hörsch, András Imolay, Ryuhei Mizutani, Taihei Oki, and Tamás Schwarcz Alphabetical

              Problems on Group-labeled Matroid Bases

              The 51st International Colloquium on Automata, Languages and Programming (ICALP ’24), Tallinn, Estonia, July 2024.

              • Refereed
              • Poster

              Taihei Oki and Shinsaku Sakaue Contribution-based

              Faster Discrete Convex Function Minimization with Predictions: the M-Convex Case

              The 37th Conference on Neural Information Processing Systems (NeurIPS '23), New Orleans, LA, United States, Dec. 2023.

              • Non-refereed
              • Oral

              Taihei Oki and Tasuku Soma Alphabetical

              Algebraic Algorithms for Fractional Linear Matroid Parity via Non-commutative Rank

              SIAM Conference on Optimization (OP '23), Seattle, Washington, United States, June 2023.

              • Refereed
              • Oral

              Taihei Oki and Tasuku Soma Alphabetical

              Algebraic Algorithms for Fractional Linear Matroid Parity via Non-commutative Rank

              The 12th Japanese-Hungarian Symposium on Discrete Mathematics and Its Applications (JH '23), Budapest, Hungary, Mar. 2023.

              • Refereed
              • Oral

              Taihei Oki and Tasuku Soma Alphabetical

              Algebraic Algorithms for Fractional Linear Matroid Parity via Non-commutative Rank

              The 34th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA '23), Florence, Italy, Jan. 2023.

              • Refereed
              • Poster

              Shinsaku Sakaue and Taihei Oki Contribution-based

              Discrete-Convex-Analysis-Based Framework for Warm-Starting Algorithms with Predictions

              The 36th Conference on Neural Information Processing Systems (NeurIPS '22), New Orleans, LA, United States, Nov. 2022.

              • Refereed
              • Oral

              Taihei Oki

              Computing Valuations of the Dieudonné Determinants

              The 46th International Symposium on Symbolic and Algebraic Computation (ISSAC ’21), Saint Petersburg, Russia (Online Conference), July 2021.

              • Refereed
              • Oral

              Taihei Oki

              On Solving (Non)commutative Weighted Edmonds’ Problem

              The 47th International Colloquium on Automata, Languages and Programming (ICALP ’20), Saarbrücken, Germany (Online Conference), July 2020.

              • Non-refereed
              • Oral

              Taihei Oki

              Computing the Maximum Degree of Minors in Skew Polynomial Matrices

              Buildings, Varieties, and Applications, Leipzig, Germany, Nov. 2019.

              • Refereed
              • Oral

              Taihei Oki

              Improved Structural Methods for Nonlinear Differential-Algebraic Equations via Combinatorial Relaxation

              The 44th International Symposium on Symbolic and Algebraic Computation (ISSAC ’19), Beijing, China, July 2019.

              • Refereed
              • Oral

              Taihei Oki

              Computing the Maximum Degree of Minors in Polynomial Matrices over Skew Fields

              The 11th Hungarian-Japanese Symposium on Discrete Mathematics and Its Applications (HJ ’19), Tokyo, Japan, May 2019.

              • Non-refereed
              • Oral

              Taihei Oki

              Index Reduction for Nonlinear Differential-Algebraic Equations via Combinatorial Relaxation

              NII Shonan Meeting Seminar 125 “Piecewise Smooth System and Optimization with Piecewise Linearization via Algorithmic Differentiation”, Kanagawa, Japan, June 2018.

              • Refereed
              • Oral

              Satoru Iwata, Taihei Oki, and Mizuyo Takamatsu Alphabetical

              Index Reduction for Differential-Algebraic Equations with Mixed Matrices

              The 8th SIAM Workshop on Combinatorial Scientific Computing (CSC ’18), Bergen, Norway, June 2018.

              • Refereed
              • Oral

              Hiroshi Hirai and Taihei Oki Alphabetical

              A compact representation for minimizers of $k$-submodular functions

              The 4th International Symposium on Combinatorial Optimization (ISCO ’16), Vietri sul Mare, Italy, May 2016.