Satoshi Hara
Satoshi Hara
Assistant Professor, Osaka University
Verified email at
Cited by
Cited by
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
Making tree ensembles interpretable: A Bayesian model selection approach
S Hara, K Hayashi
Proceedings of the 21th International Conference on Artificial Intelligence …, 2016
Making Tree Ensembles Interpretable
S Hara, K Hayashi
2016 Workshop on Human Interpretability in Machine Learning, 81-85, 2016
Enumerate lasso solutions for feature selection
S Hara, T Maehara
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
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
Data Cleansing for Models Trained with SGD
S Hara, A Nitanda, T Maehara
Advances in Neural Information Processing Systems 32 (NeurIPS'19), 2019
Quantile regression approach to conditional mode estimation
H Ota, K Kato, S Hara
Learning a common substructure of multiple graphical Gaussian models
S Hara, T Washio
Neural Networks 38, 23-38, 2012
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
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
Faking Fairness via Stealthily Biased Sampling
K Fukuchi, S Hara, T Maehara
arXiv preprint arXiv:1901.08291, 2019
Approximate and exact enumeration of rule models
S Hara, M Ishihata
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
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
Discounted average degree density metric and new algorithms for the densest subgraph problem
H Yanagisawa, S Hara
Networks 71 (1), 3-15, 2018
Common substructure learning of multiple graphical gaussian models
S Hara, T Washio
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011
Finding alternate features in lasso
S Hara, T Maehara
arXiv preprint arXiv:1611.05940, 2016
Maximally invariant data perturbation as explanation
S Hara, K Ikeno, T Soma, T Maehara
arXiv preprint arXiv:1806.07004, 2018
Quantum-state anomaly detection for arbitrary errors using a machine-learning technique
S Hara, T Ono, R Okamoto, T Washio, S Takeuchi
Physical Review A 94 (4), 042341, 2016
Maximizing invariant data perturbation with stochastic optimization
K Ikeno, S Hara
arXiv preprint arXiv:1807.05077, 2018
Consistent and Efficient Nonparametric Different-Feature Selection
ST Satoshi Hara, Takayuki Katsuki, Hiroki Yanagisawa, Takafumi Ono, Ryo Okamoto
Proceedings of the 20th International Conference on Artificial Intelligence …, 2017
The system can't perform the operation now. Try again later.
Articles 1–20