M.Sc. (Tech.), Researcher
My research interests include artificial intelligence, decision
making under uncertainty, multi-agent systems, machine learning, and
applying AI and machine learning techniques to real world problems
(robotics, wireless networks).
2011 |
| Joni Pajarinen and Jaakko Peltonen. Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning. In Proceedings of the 25th Annual Conference on Neural Information Processing Systems (NIPS), pages 2636–2644, December 2011. |
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| Joni Pajarinen and Jaakko Peltonen. Efficient Planning for Factored Infinite-Horizon DEC-POMDPs. In Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI), pages 325–331. AAAI Press, July 2011. |
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| Joni Pajarinen, Jaakko Peltonen, and Mikko A. Uusitalo. Fault tolerant machine learning for nanoscale cognitive radio. Neurocomputing, 74(5):753 – 764, 2011. |
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2010 |
| Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, and Mikko Uusitalo. Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations. In J. Balcázar, F. Bonchi, A. Gionis, and M. Sebag, editors, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), volume 6323 of Lecture Notes in Computer Science, pages 1–16. Springer Berlin / Heidelberg, 2010. |
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2009 |
| Joni Pajarinen, Jaakko Peltonen, Mikko A. Uusitalo, and Ari Hottinen. Latent state models of primary user behavior for opportunistic spectrum access. In Proceedings of IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Tokyo, Japan, September 2009. |
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2008 |
| Jaakko Peltonen, Mikko A. Uusitalo, and Joni Pajarinen. Nano-scale fault tolerant machine learning for cognitive radio. In Jose C. Principe, Deniz Erdogmus, and Tülay Adali, editors, Proceedings of IEEE International Workshop on Machine Learning for Signal Processing (MLSP), pages 163–168, Cancún, Mexico, October 2008. |
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