Causal bandits with propagating inference A Yabe, D Hatano, H Sumita, S Ito, N Kakimura, T Fukunaga, ... International Conference on Machine Learning, 5512-5520, 2018 | 34 | 2018 |
DeQED: An efficient divide-and-coordinate algorithm for DCOP D Hatano, K Hirayama Proceedings of the 2013 international conference on Autonomous agents and …, 2013 | 27 | 2013 |
Delay and cooperation in nonstochastic linear bandits S Ito, D Hatano, H Sumita, K Takemura, T Fukunaga, N Kakimura, ... Advances in Neural Information Processing Systems 33, 4872-4883, 2020 | 26 | 2020 |
A parameter-free algorithm for misspecified linear contextual bandits K Takemura, S Ito, D Hatano, H Sumita, T Fukunaga, N Kakimura, ... International Conference on Artificial Intelligence and Statistics, 3367-3375, 2021 | 16 | 2021 |
Adaptive Budget Allocation for Maximizing Influence of Advertisements. D Hatano, T Fukunaga, KI Kawarabayashi IJCAI, 3600-3608, 2016 | 15 | 2016 |
Lagrangian decomposition algorithm for allocating marketing channels D Hatano, T Fukunaga, T Maehara, K Kawarabayashi Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 13 | 2015 |
Oracle-efficient algorithms for online linear optimization with bandit feedback S Ito, D Hatano, H Sumita, K Takemura, T Fukunaga, N Kakimura, ... Advances in Neural Information Processing Systems 32, 2019 | 10 | 2019 |
Dynamic sat with decision change costs: Formalization and solutions D Hatano, K Hirayama Transactions of the Japanese Society for Artificial Intelligence 26 (6), 682-691, 2011 | 10 | 2011 |
Improved regret bounds for bandit combinatorial optimization S Ito, D Hatano, H Sumita, K Takemura, T Fukunaga, N Kakimura, ... Advances in Neural Information Processing Systems 32, 2019 | 9 | 2019 |
Online task assignment problems with reusable resources H Sumita, S Ito, K Takemura, D Hatano, T Fukunaga, N Kakimura, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (5), 5199-5207, 2022 | 8 | 2022 |
Regret bounds for online portfolio selection with a cardinality constraint S Ito, D Hatano, H Sumita, A Yabe, T Fukunaga, N Kakimura, ... Advances in Neural Information Processing Systems 31, 2018 | 8 | 2018 |
Scalable algorithm for higher-order co-clustering via random sampling D Hatano, T Fukunaga, T Maehara, K Kawarabayashi Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 8 | 2017 |
Efficient sublinear-regret algorithms for online sparse linear regression with limited observation S Ito, D Hatano, H Sumita, A Yabe, T Fukunaga, N Kakimura, ... Advances in Neural Information Processing Systems 30, 2017 | 6 | 2017 |
Computing least cores of supermodular cooperative games D Hatano, Y Yoshida Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 4 | 2017 |
Near-optimal regret bounds for contextual combinatorial semi-bandits with linear payoff functions K Takemura, S Ito, D Hatano, H Sumita, T Fukunaga, N Kakimura, ... Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9791-9798, 2021 | 3 | 2021 |
Online regression with partial information: Generalization and linear projection S Ito, D Hatano, H Sumita, A Yabe, T Fukunaga, N Kakimura, ... International Conference on Artificial Intelligence and Statistics, 1599-1607, 2018 | 2 | 2018 |
Computational Aspects of the Preference Cores of Supermodular Two-Scenario Cooperative Games. D Hatano, Y Yoshida IJCAI, 310-316, 2018 | 1 | 2018 |
Distributed multiplicative weights methods for DCOP D Hatano, Y Yoshida Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 1 | 2015 |
値変更コスト付き動的 SAT の定式化とその解法 波多野大督, 平山勝敏 人工知能学会論文誌 26 (6), 682-691, 2011 | 1 | 2011 |
New classes of the greedy-applicable arm feature distributions in the sparse linear bandit problem K Ichikawa, S Ito, D Hatano, H Sumita, T Fukunaga, N Kakimura, ... Proceedings of the AAAI Conference on Artificial Intelligence 38 (11), 12708 …, 2024 | | 2024 |