Making tree ensembles interpretable: A Bayesian model selection approach S Hara, K Hayashi Proceedings of the 21th International Conference on Artificial Intelligence …, 2016 | 244 | 2016 |

Fairwashing: the risk of rationalization U Aïvodji, H Arai, O Fortineau, S Gambs, S Hara, A Tapp Proceedings of the 36th International Conference on Machine Learning (ICML …, 0 | 172* | |

Data Cleansing for Models Trained with SGD S Hara, A Nitanda, T Maehara Advances in Neural Information Processing Systems 32 (NeurIPS'19), 2019 | 82 | 2019 |

Separation of stationary and non-stationary sources with a generalized eigenvalue problem S Hara, Y Kawahara, T Washio, P Von BüNau, T Tokunaga, K Yumoto Neural networks 33, 7-20, 2012 | 68 | 2012 |

Enumerate lasso solutions for feature selection S Hara, T Maehara Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 64 | 2017 |

Exploration of flow reaction conditions using machine-learning for enantioselective organocatalyzed Rauhut–Currier and [3+ 2] annulation sequence M Kondo, HDP Wathsala, M Sako, Y Hanatani, K Ishikawa, S Hara, ... Chemical Communications 56 (8), 1259-1262, 2020 | 57 | 2020 |

Quantile regression approach to conditional mode estimation H Ota, K Kato, S Hara | 56 | 2019 |

Evaluation of similarity-based explanations K Hanawa, S Yokoi, S Hara, K Inui arXiv preprint arXiv:2006.04528, 2020 | 48 | 2020 |

Learning a common substructure of multiple graphical Gaussian models S Hara, T Washio Neural Networks 38, 23-38, 2012 | 40 | 2012 |

Characterizing the risk of fairwashing U Aïvodji, H Arai, S Gambs, S Hara Advances in Neural Information Processing Systems 34, 14822-14834, 2021 | 31 | 2021 |

Energy-, time-, and labor-saving synthesis of α-ketiminophosphonates: Machine-learning-assisted simultaneous multiparameter screening for electrochemical oxidation M Kondo, A Sugizaki, MI Khalid, HDP Wathsala, K Ishikawa, S Hara, ... Green Chemistry 23 (16), 5825-5831, 2021 | 25 | 2021 |

Stationary subspace analysis as a generalized eigenvalue problem S Hara, Y Kawahara, T Washio, P Von Bünau Neural Information Processing. Theory and Algorithms: 17th International …, 2010 | 24 | 2010 |

Bayesian optimization-driven parallel-screening of multiple parameters for the flow synthesis of biaryl compounds M Kondo, HDP Wathsala, MSH Salem, K Ishikawa, S Hara, T Takaai, ... Communications Chemistry 5 (1), 148, 2022 | 20 | 2022 |

Synthesis of computer simulation and machine learning for achieving the best material properties of filled rubber T Kojima, T Washio, S Hara, M Koishi Scientific reports 10 (1), 18127, 2020 | 19 | 2020 |

Interpretable companions for black-box models D Pan, T Wang, S Hara International conference on artificial intelligence and statistics, 2444-2454, 2020 | 17 | 2020 |

Faking Fairness via Stealthily Biased Sampling K Fukuchi, S Hara, T Maehara arXiv preprint arXiv:1901.08291, 2019 | 16* | 2019 |

Approximate and exact enumeration of rule models S Hara, M Ishihata Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 16 | 2018 |

Anomaly Detection in Reconstructed Quantum States Using a Machine-Learning Technique Satoshi Hara, Takafumi Ono, Ryo Okamoto, Takashi Washio, Shigeki Takeuchi Physical Review A 89 (2), 022104, 2014 | 16 | 2014 |

A Consistent Method for Graph Based Anomaly Localization Satoshi Hara, Tetsuro Morimura, Toshihiro Takahashi, Hiroki Yanagisawa ... Proceedings of the Eighteenth International Conference on Artificial …, 2015 | 13* | 2015 |

Discounted average degree density metric and new algorithms for the densest subgraph problem H Yanagisawa, S Hara Networks 71 (1), 3-15, 2018 | 11 | 2018 |