澄田範奈 (Hanna SUMITA)

Journal Papers

• Y. Kawase, K. Kimura, K. Makino, and H. Sumita: Optimal Matroid Partitioning Problems.
  Algorithmica (2021), online first, 2021. [LINK]
• Y. Kawase, H. Sumita, and T. Fukunaga: Submodular Maximization with Uncertain Knapsack Capacity.
  SIAM Journal on Discrete Mathematics, 33(3), pp. 1121-1145, 2019. [LINK]
• H. Sumita, N. Kakimura and K. Makino: Total Dual Integrality of the Linear Complementarity Problem.
  Annals of Operations Research, 274(1–2), pp. 531–553, 2019. [LINK]
• H. Sumita, N. Kakimura and K. Makino: Parameterized Complexity of Sparse Linear Complementarity Problems.
  Algorithmica, 79(1), pp. 42-65, 2017. [LINK]
• H. Sumita, N. Kakimura and K. Makino: The Linear Complementarity Problems with a Few Variables per Constraint.
  Mathematics of Operations Research, 40(4), pp. 1015-1026, 2015. [LINK]

Refereed Conference Proceedings

• K. Takemura, S. Ito, D. Hatano, H. Sumita, T. Fukunaga, N. Kakimura, and K. Kawarabayashi: A Parameter-Free Algorithm for Misspecified Linear Contextual Bandits.
  Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS 2021), 130:3367-3375.
• K. Takemura, S. Ito, D. Hatano, H. Sumita, T. Fukunaga, N. Kakimura, and K. Kawarabayashi: Near-Optimal Regret Bounds for Contextual Combinatorial Semi-Bandits with Linear Payoff Functions.
  Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-21).
• S. Ito, D. Hatano, H. Sumita, K. Takemura, T. Fukunaga, N. Kakimura, and K. Kawarabayashi: Delay and Cooperation in Nonstochastic Linear Bandits.
  Proceedings of the 34th Annual Conference on Neural Information Processing Systems (NeurIPS 2020).
• Y. Kawase and H. Sumita: On the Max-min Fair Stochastic Allocation of Indivisible Goods.
  Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-20), 2070-2078. [LINK]
• S. Ito, D. Hatano, H. Sumita, K. Takemura, T. Fukunaga, N. Kakimura, and K. Kawarabayashi: Oracle-Efficient Algorithms for Online Linear Optimization with Bandit Feedback.
  Proceedings of the 33rd Annual Conference on Neural Information Processing Systems (NeurIPS 2019), 10589-10598.
• S. Ito, D. Hatano, H. Sumita, K. Takemura, T. Fukunaga, N. Kakimura, and K. Kawarabayashi: Improved Regret Bounds for Bandit Combinatorial Optimization.
  Proceedings of the 33rd Annual Conference on Neural Information Processing Systems (NeurIPS 2019), 12027-12036.
• D. Hatano, Y. Kuroki, Y. Kawase, H. Sumita, N. Kakimura, and K. Kawarabayashi: Non-zero-sum Stackelberg Budget Allocation Game for Computational Advertising.
  Proceedings of the 16th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2019), 568-582 .
• Y. Kawase and H. Sumita: Randomized Strategies for Robust Combinatorial Optimization.
  Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-19), 7876-7883. (acceptance ratio 1,150/7,095 = 16.2%)
• S. Ito, D. Hatano, H. Sumita, A. Yabe, T. Fukunaga, N. Kakimura, K. Kawarabayashi: Regret Bounds for Online Portfolio Selection with a Cardinality Constraint.
  Proceedings of the 32nd Annual Conference on Neural Information Processing Systems (NeurIPS 2018), 10588-10597.
• A. Yabe, D. Hatano, H. Sumita, S. Ito, N. Kakimura, T. Fukunaga, K. Kawarabayashi: Causal Bandits with Propagating Inference.
  Proceedings of the 35th International Conference on Machine Learning (ICML 2018), 5512-5520. [LINK]
• S. Ito, D. Hatano, H. Sumita, A. Yabe, T. Fukunaga, N. Kakimura, K. Kawarabayashi: Online Regression with Partial Information: Generalization and Linear Projection.
  Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS 2018), 1599-1607. [LINK]
• Y. Kawase, H. Sumita and T. Fukunaga: Submodular maximization with uncertain knapsack capacity.
  Proceedings of the 13th Latin American Theoretical Informatics (LATIN 2018), 653-668. [LINK]
• Y. Kawase, K. Kimura, K. Makino and H. Sumita: Optimal Matroid Partitioning Problems.
  Proceedings of the 28th International Symposium on Algorithms and Computation (ISAAC 2017), 51:1-51:13. [LINK]
• S. Ito, D. Hatano, H. Sumita, A. Yabe, T. Fukunaga, N. Kakimura and K. Kawarabayashi: Efficient Sublinear-Regret Algorithms for Online Sparse Linear Regression with Limited Observation.
  Proceedings of the 31st Annual Conference on Neural Information Processing Systems (NIPS 2017), 4102-4111. [LINK]
• H. Sumita, Y. Yonebayashi, N. Kakimura and K. Kawarabayashi: An Improved Approximation Algorithm for the Subpath Planning Problem and Its Generalization.
  Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), 4412-4418. [LINK]
• H. Sumita, Y. Kawase, S. Fujita and T. Fukunaga: Online Optimization of Video-Ad Allocation.
  Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), 423-429. [LINK]
• Y. Kawase, K. Kimura, K. Makino and H. Sumita: Min-sum-max matroid partitioning problem.
  Proceedings of the 10th Japanese-Hungarian Symposium on Discrete Mathematics and Its Applications, 2017, 335-344.
• T. Maehara, Y. Kawase, H. Sumita, K. Tono and K. Kawarabayashi: Optimal Pricing for Submodular Valuations with Bounded Curvature.
  Proceedings of the 31st AAAI Conference on Artificial Intelligence (AAAI-17), 622-628. [LINK]
• H. Sumita, N. Kakimura and K. Makino: Parameterized Complexity of Sparse Linear Complementarity Problems.
  Proceedings of the 10th International Symposium on Parameterized and Exact Computation (IPEC 2015), 2015, 355-364.
• H. Sumita, N. Kakimura and K. Makino: Total Dual Integrality of the Linear Complementarity Problem.
  Proceedings of the 9th Hungarian-Japanese Symposium on Discrete Mathematics and Its Applications, 2015, 342-351.
• H. Sumita, N. Kakimura and K. Makino: Sparse Linear Complementarity Problems.
  Proceedings of the 8th Japanese-Hungarian Symposium on Discrete Mathematics and Its Applications, 2013, 453-462.
• H. Sumita, N. Kakimura and K. Makino: Sparse Linear Complementarity Problems.
  Proceedings of the 8th International Conference on Algorithms and Complexity (CIAC 2013), LNCS 7878, 2013, 358-369.

Preprints

• Y. Kawase and H. Sumita: Randomized Strategies for Robust Combinatorial Optimization.
  arXiv:1805.07809, 2018. [LINK]
• Y. Kawase, H. Sumita and T. Fukunaga: Submodular maximization with uncertain knapsack capacity.
  arXiv:1803.02565, 2018. [LINK]
• Y. Kawase, K. Kimura, K. Makino and H. Sumita: Optimal Matroid Partitioning Problems.
  arXiv:1710.00950, 2017. [LINK]
• T. Maehara, Y. Kawase, H. Sumita, K. Tono and K. Kawarabayashi: Optimal Pricing for Submodular Valuations with Bounded Curvature.
  arXiv:1611.07605, 2016. [LINK]
• H. Sumita, N. Kakimura and K. Makino: Total Dual Integrality of the Linear Complementarity Problem.
  Mathematical Engineering Technical Reports METR 2014-25, 2014. [PDF]
• H. Sumita, N. Kakimura and K. Makino: Sparse Linear Complementarity Problems.
  Mathematical Engineering Technical Reports METR 2013-02, 2013. [PDF]

Talks in International Conferences

• Y. Kawase and H. Sumita: Randomized Strategies for Robust Combinatorial Optimization. (highlight and poster)
  The 33rd AAAI Conference on Artificial Intelligence (AAAI 2019), Honolulu, USA, January 2019.
• H. Sumita, Y. Yonebayashi, N. Kakimura and K. Kawarabayashi: An Improved Approximation Algorithm for the Subpath Planning Problem and Its Generalization.
  The 26th International Joint Conference on Artificial Intelligence (IJCAI 2017), Melbourne, Australia, August 2017.
• Y. Kawase, K. Kimura, K. Makino and H. Sumita: Min-sum-max matroid partitioning problem.
  The 10th Japanese-Hungarian Symposium on Discrete Mathematics and Its Applications, Budapest, Hungary, May 2017.
• H. Sumita, N. Kakimura and K. Makino: Parameterized Complexity of Sparse Linear Complementarity Problems.
  The 10th International Symposium on Parameterized and Exact Computation (IPEC 2015), Patras, Greece, September 2015.
• H. Sumita, N. Kakimura and K. Makino: Total Dual Integrality of the Linear Complementarity Problem.
  The 22nd International Symposium on Mathematical Programming (ISMP 2015), Pittsburgh, USA, July 2015.
• H. Sumita, N. Kakimura and K. Makino: Total Dual Integrality of the Linear Complementarity Problem.
  The 9th Hungarian-Japanese Symposium on Discrete Mathematics and Its Applications, Fukuoka, Japan, June 2015.
• H. Sumita, N. Kakimura and K. Makino: Sparse Linear Complementarity Problems.
  The 8th Japanese-Hungarian Symposium on Discrete Mathematics and Its Applications, Veszprem, Hungary, June 2013.
• H. Sumita, N. Kakimura and K. Makino: Sparse Linear Complementarity Problems.
  The 8th International Conference on Algorithms and Complexity (CIAC 2013), Barcelona, Spain, May 2013.

Talks in Domestic Conferences (in Japanese)

• 河瀬康志，澄田範奈，福永拓郎: 不確実なナップサック制約をもつ劣モジュラ関数最大化，
  電子情報通信学会, 東京電機大学, 2018年3月. 招待講演
• 前原貴憲，河瀬康志，澄田範奈，東野克哉，河原林健一: 劣モジュラ評価関数をもつ最適価格付け問題，
  2017年日本オペレーションズ・リサーチ学会春季研究発表会，沖縄県市町村自治会館，2017年3月.
• 澄田範奈，河瀬康志，藤田澄男，福永拓郎: 動画広告割当のオンライン最適化，
  日本応用数理学会2016年年会，北九州国際会議場，2016年9月.
• 澄田範奈，河瀬康志，藤田澄男，福永拓郎: 動画広告割当のオンライン最適化，
  日本オペレーションズ・リサーチ学会関西支部研究講演会，常翔学園大阪センター，2016年7月.
• 澄田範奈，垣村尚徳，牧野和久: 線形相補性問題のパラメータ化計算量，
  2015年日本オペレーションズ・リサーチ学会春季研究発表会，東京理科大学，2015年3月.
• 澄田範奈，垣村尚徳，牧野和久: 線形相補性問題のパラメータ化計算量，
  電子情報通信学会, 立命館大学, 2015年3月. 最優秀論文賞
• 澄田範奈，垣村尚徳，牧野和久: 方向つき線形相補性問題の計算複雑度，
  2014年日本オペレーションズ・リサーチ学会秋季研究発表会，北海道科学大学，2014年8月.
• 澄田範奈，垣村尚徳，牧野和久: 線形相補性問題の完全双対整数性，
  日本オペレーションズ・リサーチ学会「最適化の理論と応用」研究部会SOTA，筑波大学，2014年6月.
• 澄田範奈，垣村尚徳，牧野和久: 線形相補性問題の整数性，
  研究集会「最適化：モデリングとアルゴリズム」, 政策研究大学院大学, 2014年3月.
• 澄田範奈，垣村尚徳，牧野和久: 線形相補性問題の完全双対整数性，
  電子情報通信学会, 新潟大学, 2014年3月.
• 澄田範奈，垣村尚徳，牧野和久: 線形相補性問題の完全双対整数性，
  2014年日本オペレーションズ・リサーチ学会春季研究発表会，大阪大学，2014年3月.
• 澄田範奈，垣村尚徳，牧野和久: 疎な線形相補性問題に対する組合せ的アルゴリズム，
  電子情報通信学会, 岐阜大学, 2013年3月.
• 澄田範奈，垣村尚徳，牧野和久: 疎な線形相補性問題に対する組合せ的アルゴリズム，
  2012年日本オペレーションズ・リサーチ学会秋季研究発表会，ウインクあいち，2012年9月.
• 澄田範奈，垣村尚徳，牧野和久: 疎な線形相補性問題の計算複雑度，
  日本オペレーションズ・リサーチ学会「最適化の理論と応用」研究部会SOTA，筑波大学，2012年6-7月.

Talks in Seminars

• Y. Kawase and H. Sumita: Randomized Strategies for Robust Combinatorial Optimization.
  NeurIPS Meetup Japan 2020, online, December 9, 2020. Invited talk
• 澄田範奈，河瀬康志，藤田澄男，福永拓郎: Online Optimization of Video-Ad Allocation.
  ERATO感謝祭 SeasonIV，学術総合センター，2017年8月4日. (in Japanese)
• H. Sumita, N. Kakimura and K. Makino: The Linear Complementarity Problem: Sparsity and Integrality.
  Mittagsseminar, ETH Zurich, March 19, 2015.

Award

• COMP-ELC学生シンポジウム(電子情報通信学会2015年総合大会) 最優秀論文賞

所属学会

• 日本オペレーションズ・リサーチ学会
• 電子情報通信学会

活動実績

• 日本オペレーションズ・リサーチ学会「離散アルゴリズムの応用と理論」研究部会　幹事（2016〜2018年度） [LINK]
• NeurIPS 2019 Top Reviewers [LINK ]
• Program Commitee or reviewer of international conferences such as NeurIPS, AAAI, IJCAI

Degrees

• March 2010, Bachelor of Engineering from Faculty of Engineering, University of Tokyo.
• March 2012, Master of Information Science and Technology from Graduate School of Information Science and Technology, University of Tokyo.
• March 2015, Doctor of Information Science and Technology from Graduate School of Information Science and Technology, University of Tokyo.
  • advisor: Prof. Kazuhisa Makino (moved to Kyoto University in 2013)

Career

• April 2014 - March 2015, Research Fellow of the Japan Society for the Promotion of Science (DC2).
• April 2015 - March 2018, Project researcher, National Institute of Informatics and JST, ERATO, Kawarabayashi Large Graph Project.
• April 2018 - March 2020, Assistant Professor, Faculty of Economics and Business Administration, Tokyo Metropolitan University.
• Since April 2020, Associate Professor (Lecturer), Department of Mathematical and Computing Science, School of Computing, Tokyo Institute of Technology.


• 2016 - 2019(Academic year), Part-time Lecturer, Department of Computer Science, Tokyo Institute of Technology.