Search results

Journal Article (2)

1.
Journal Article
Hachiya, H.; Peters, J.; Sugiyama, M.: Reward-Weighted Regression with Sample Reuse for Direct Policy Search in Reinforcement Learning. Neural computation 23 (11), pp. 2798 - 2832 (2011)
2.
Journal Article
Hachiya, H.; Akiyama, T.; Sugiyama, M.; Peters, J.: Adaptive Importance Sampling for Value Function Approximation in Off-policy Reinforcement Learning. Neural networks 22 (10), pp. 1399 - 1410 (2009)

Conference Paper (3)

3.
Conference Paper
Hachiya, H.; Peters, J.; Sugiyama, M.: Efficient Sample Reuse in EM-Based Policy Search. In: Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2009, Bled, Slovenia, September 7-11, 2009, pp. 469 - 484 (Eds. Buntine, W.; Grobelnik, M.; Mladenic, D.; Shaw-Taylor, J.). 16th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2009), Bled, Slovenia, September 07, 2009 - September 11, 2009. Springer, Berlin, Germany (2009)
4.
Conference Paper
Hachiya, H.; Akiyama, T.; Sugiyama, M.; Peters, J.: Efficient data reuse in value function approximation. In: 2009 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, pp. 8 - 15. 2009 IEEE International Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL 2009), Nashville, TN, USA, March 30, 2009 - April 02, 2009. IEEE Service Center, Piscataway, NJ, USA (2009)
5.
Conference Paper
Hachiya, H.; Akiyama, T.; Sugiyama, M.; Peters, J.: Adaptive Importance Sampling with Automatic Model Selection in Value Function Approximation. In: Twenty-Third Conference on Artificial Intelligence 2008, pp. 1351 - 1356 (Eds. Fox, D.; Gomes, C.). Twenty-Third Conference on Artificial Intelligence 2008, Chicago, IL, USA, July 13, 2008 - July 17, 2008. AAAI Press, Menlo Park, CA, USA (2008)
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