| Higher-order factorization machines M Blondel, A Fujino, N Ueda, M Ishihata arXiv preprint arXiv:1607.07195, 2016 | 160* | 2016 |
| Polynomial networks and factorization machines: New insights and efficient training algorithms M Blondel, M Ishihata, A Fujino, N Ueda International Conference on Machine Learning, 850-858, 2016 | 78 | 2016 |
| Evaluating abductive hypotheses using an EM algorithm on BDDs K Inoue, T Sato, M Ishihata, Y Kameya, H Nabeshima Twenty-First International Joint Conference on Artificial Intelligence, 2009 | 58 | 2009 |
| Propositionalizing the EM algorithm by BDDs M Ishihata, Y Kameya, T Sato, S Minato Transactions of the Japanese Society for Artificial Intelligence 25 (3), 475-484, 2010 | 50 | 2010 |
| Propositionalizing the EM algorithm by BDDs M Ishihata, Y Kameya, T Sato, S Minato Transactions of the Japanese Society for Artificial Intelligence 25 (3), 475-484, 2010 | 50 | 2010 |
| Exact computation of influence spread by binary decision diagrams T Maehara, H Suzuki, M Ishihata Proceedings of the 26th International Conference on World Wide Web, 947-956, 2017 | 26 | 2017 |
| Statistical emerging pattern mining with multiple testing correction J Komiyama, M Ishihata, H Arimura, T Nishibayashi, S Minato Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge …, 2017 | 17 | 2017 |
| Kinetic models and qualitative abstraction for relational learning in systems biology G Synnaeve, K Inoue, A Doncescu, H Nabeshima, Y Kameya, M Ishihata, ... BIOSTEC Bioinformatics 2011, 2011 | 13 | 2011 |
| Efficient bandit combinatorial optimization algorithm with zero-suppressed binary decision diagrams S Sakaue, M Ishihata, S Minato International Conference on Artificial Intelligence and Statistics, 585-594, 2018 | 12 | 2018 |
| Accelerated best-first search with upper-bound computation for submodular function maximization S Sakaue, M Ishihata Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 10 | 2018 |
| An EM algorithm on BDDs with order encoding for logic-based probabilistic models M Ishihata, Y Kameya, T Sato, S Minato Proceedings of 2nd Asian Conference on Machine Learning, 161-176, 2010 | 10 | 2010 |
| Approximate and exact enumeration of rule models S Hara, M Ishihata Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 7 | 2018 |
| Bayesian inference for statistical abduction using Markov chain Monte Carlo M Ishihata, T Sato Asian Conference on Machine Learning, 81-96, 2011 | 7 | 2011 |
| Constraint-based probabilistic modeling for statistical abduction T Sato, M Ishihata, K Inoue Machine learning 83 (2), 241-264, 2011 | 4 | 2011 |
| Algorithmic meta-theorems for monotone submodular maximization M Ishihata, T Maehara, T Rigaux arXiv preprint arXiv:1807.04575, 2018 | 3 | 2018 |
| Compiling bayesian networks for parameter learning based on shared bdds M Ishihata, T Sato, S Minato Australasian Joint Conference on Artificial Intelligence, 203-212, 2011 | 3 | 2011 |
| Variational Bayes inference for logic-based probabilistic models on BDDs M Ishihata, Y Kameya, T Sato International Conference on Inductive Logic Programming, 189-203, 2011 | 3 | 2011 |
| Exact computation of strongly connected reliability by binary decision diagrams H Suzuki, M Ishihata, S Minato International Conference on Combinatorial Optimization and Applications, 281-295, 2018 | 2 | 2018 |
| Enumeration of nonequivalent substitutional structures using advanced data structure of binary decision diagram K Shinohara, A Seko, T Horiyama, M Ishihata, J Honda, I Tanaka The Journal of Chemical Physics 153 (10), 104109, 2020 | 1 | 2020 |
| Designing Survivable Networks with Zero-Suppressed Binary Decision Diagrams H Suzuki, M Ishihata, S Minato International Workshop on Algorithms and Computation, 273-285, 2020 | 1 | 2020 |
Taisuke SatoAIST/NIIVerified email at aist.go.jp
