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Y. Sogawa, T. Ueno, Y. Kawahara, & T. Washio, Active learning for noisy oracle via density power divergence, Neural Networks, 46: 133-143, 2013.
S. Shimizu, T. Inazumi, Y. Sogawa, A. Hyvärinen, Y. Kawahara, T. Washio, P. O. Hoyer & K. Bollen, DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model, Journal of Machine Learning Research, 12(Apr): 1225-1248, 2011.
Y. Sogawa, S. Shimizu, T. Shimamura, A. Hyvärinen, T. Washio, & S. Imoto, Estimating Exogenous Variables in Data with More Variables than Observations, Neural Networks, 24: 875-880, 2011 (Special Issue: ICANN2010).
Domestic Journal
Yasuhiro Sogawa, Tsuyoshi Ueno, Yoshinobu Kawahara, & Takashi Washio, Active Learning for Regression via Density Power Divergence, Transactions of the Japanese Society for Artificial Intelligence, Vol.28, No.1: 13-21, 2013. (Japanese)
International Conference
Y. Sogawa, Tsuyoshi Ueno, Yoshinobu Kawahara & Takashi Washio, Robust Active Learning for Linear Regression via Density Power Divergence in Proc. International Conference on Neural Information Processing (ICONIP2012), pp.xx-xx, Doha, Qatar, November, 2012. (In press)
. Fujimaki, Y. Sogawa & S. Morinaga, Online Heterogeneous Mixture Modeling with Marginal and Copula Selection, In Proc. the 17th annual ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2011), pp.645-653, San Diego, California, USA, August, 2011.
Y. Sogawa, S. Shimizu, A. Hyvärinen, T. Washio, S. Teppei & S. Imoto, Discovery of Exogenous Variables in Data with More Variables than Observations, in Proc. International Conference on Artificial Neural Networks (ICANN2010), pp.67-76, Thessaloniki, Greece, September, 2010.
Y. Sogawa, S. Shimizu, Y. Kawahara & T. Washio, An experimental comparison of linear non-Gaussian causal discovery methods and their variants, in Proc. International Joint Conference on Neural Networks (IJCNN2010), pp.768-775, Barcelona, Spain, July, 2010.