論文

• Zhao, T., Hachiya, H., Tangkaratt, V., Morimoto, J., & Sugiyama, M.. Efficient sample reuse inpolicy gradients with parameter-based exploration, Neural Computation, vol. 25, no. 6, pp. 1512-1547, 2013.
• Zhao, T., Hachiya, H., Niu, G., Sugiyama, M.. Analysis and improvement of policy gradient estimation, Neural Networks, vol. 26, pp. 118-129, 2012.

国際会議発表 (査読有り)

• Zhao, T., Hachiya, H., Sugiyama, M.. Importance-weighted policy gradients with parameter-based exploration., IBISML2011, IEICE Technical Report, IBISML2011-95, pp. 55-62, Mar. 2012.

国際会議発表 (査読なし・不明)

• Zhao, T., Hachiya, H., Niu, G., Sugiyama, M. Analysis and improvement of policy gradient estimation., Neural Information Processing Systems (NIPS2011),, Advances in Neural Information Processing Systems 24, J. Shawe-Taylor, R. S. Zemel, P. Bartlett, F. C. N. Pereira, and K. Q. Weinberger, pp. 262-270, Dec. 2011.

国内会議発表 (査読なし・不明)

• Mori, S., Tangkaratt, V., Zhao, T., Morimoto, J., &Sugiyama, M.. Model-based policy gradients with parameter-based exploration by least-squares conditional density estimation, IBISML2012-95, IEICE Technical Report, pp. 17-24, 2013.
• Zhao, T., Hachiya, H., Niu, G., Sugiyama, M.. Analysis and improvement of policy gradient estimation., IBISML2011, IEICE Technical Report, IBISML2011-12, pp. .83-89,, Feb. 2012.
• Zhao, T., Hachiya, H., & Sugiyama, M.. Efficient data reuse in robot control learning via importnace sampling, 2nd Institute of Mathematical Statistics Asia Pacific Rim Meeting, 2012.

学位論文

• Statistical Theory of Reinforcement Learning with Applications to Robot Control,  Exam Summary,  Doctor (Engineering),  Tokyo Institute of Technology,  2014/03/26,   
• Statistical Theory of Reinforcement Learning with Applications to Robot Control,  Thesis,  Doctor (Engineering),  Tokyo Institute of Technology,  2014/03/26,   
• Statistical Theory of Reinforcement Learning with Applications to Robot Control,  Summary,  Doctor (Engineering),  Tokyo Institute of Technology,  2014/03/26,   

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