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Position: PhD Student Unit: Alumni Schölkopf

Articles (2):
•	Hachiya H , Peters J and Sugiyama M (November-2011) Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning Neural Computation 23(11) 2798-2832.
•	Hachiya H , Akiyama T , Sugiyama M and Peters J (December-2009) Adaptive Importance Sampling for Value Function Approximation in Off-policy Reinforcement Learning Neural Networks 22(10) 1399-1410.
Conference papers (3):
•	Hachiya H , Peters J and Sugiyama M (September-2009) Efficient Sample Reuse in EM-Based Policy Search In: ECML PKDD 2009, 16th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Springer, Berlin, Germany, 469-484.
•	Hachiya H , Akiyama T , Sugiyama M and Peters J (May-2009) Efficient data reuse in value function approximation In: IEEE ADPRL 2009, 2009 IEEE International Symposium on Adaptive Dynamic Programming and Reinforcement Learning, IEEE Service Center, Piscataway, NJ, USA, 8-15.
•	Hachiya H , Akiyama T , Sugiyama M and Peters J (July-2008) Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation In: AAAI 2008, Twenty-Third Conference on Artificial Intelligence, AAAI Press, Menlo Park, CA, USA, 1351-1356.