| Journal Papers |
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- Dam, T.; D'Eramo, C.; Peters, J.; Pajarinen, J. (submitted). A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search, Submitted to the Journal of Artificial Intelligence Research (JAIR).
- Klink, P.; Wolf, F.; Ploeger, K.; Peter, J.; Pajarinen, J. (submitted). Tracking Control for a Spherical Pendulum via Curriculum Reinforcement Learning, Submitted to the IEEE Transactions on Robotics (T-Ro).
- Klink, P.; D'Eramo, C.; Peters, J.; Pajarinen, J. (in press). On the Benefit of Optimal Transport for Curriculum Reinforcement Learning, Submitted to the IEEE Transaction on Pattern Analysis and Machine Intelligence (PAMI).
- Weng, Y.; Chun, S.; Ohashi, M.; Matsuda, T.; Sekimoria, Y.; Pajarinen, J.; Peters, J.; Maki, T. (in press). Autonomous Underwater Vehicle Link Alignment Control in Unknown Environments Using Reinforcement Learning, Journal of Field Robotics.
- Parisi, S.; Tateo, D.; Hensel, M.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2022). Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning, Algorithms, 15, 3, pp.81.
- Weng, Y.; Pajarinen, J.; Akrour, R.; Matsuda, T.; Peters, J.; Maki, T. (2022). Reinforcement Learning Based Underwater Wireless Optical Communication Alignment for Multiple Autonomous Underwater Vehicles, IEEE Journal of Oceanic Engineering, 47, 4, pp.1231-1245.
- Weng, Y.; Matsuda, T.; Sekimuri, Y.; Pajarinen, J.; Peters, J.; Maki, T. (2022). Pointing Error Control of Underwater Wireless Optical Communication on Mobile Platform, IEEE Photonics Technology Letters, 34, 13, pp.699-702.
- Weng, Y.; Matsuda, T.; Sekimoria, Y.; Pajarinen, J.; Peters, J.; Maki, T. (2022). Establishment of Line-of-Sight Optical Links Between Autonomous Underwater Vehicles: Field Experiment and Performance Validation, Applied Ocean Research, 129.
- Klink, P.; Abdulsamad, H.; Belousov, B.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2021). A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning, Journal of Machine Learning Research (JMLR).
- Pajarinen, J.; Arenz, O.; Peters, J.; Neumann, N. (2020). Probabilistic approach to physical object disentangling, IEEE Robotics and Automation Letters (RA-L).
- Lauri, M.; Pajarinen, J.; Peters, J.; Frintrop, S. (2020). Multi-Sensor Next-Best-View Planning as Matroid-Constrained Submodular Maximization, IEEE Robotics and Automation Letters (RA-L), 5, 4, pp.5323-5330.
- Pajarinen, J.; Thai, H.L.; Akrour, R.; Peters, J.; Neumann, G. (2019). Compatible natural gradient policy search, Machine Learning (MLJ), 108, 8, pp.1443--1466, Springer.
- Koert, D.; Pajarinen, J.; Schotschneider, A.; Trick, S., Rothkopf, C.; Peters, J. (2019). Learning Intention Aware Online Adaptation of Movement Primitives, IEEE Robotics and Automation Letters (RA-L), with presentation at the IEEE International Conference on Intelligent Robots and Systems (IROS).
- Osa, T.; Pajarinen, J.; Neumann, G.; Bagnell, J.A.; Abbeel, P.; Peters, J. (2018). An Algorithmic Perspective on Imitation Learning, Foundations and Trends in Robotics.
- Pajarinen, J.; Kyrki, V. (2015). Robotic manipulation of multiple objects as a POMDP, Artificial Intelligence.
- Pajarinen, J.; Hottinen, A.; Peltonen, J. (2013). Optimizing Spatial and Temporal Reuse in Wireless Networks by Decentralized Partially Observable Markov Decision Processes, IEEE Transactions on Mobile Computing.
- Pajarinen, J.; Peltonen, J.; Uusitalo, M.A. (2011). Fault tolerant machine learning for nanoscale cognitive radio, Neurocomputing.
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| Conference Papers |
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- Klink, P.; D`Eramo, C.; Peters, J.; Pajarinen, J. (2022). Boosted Curriculum Reinforcement Learning, International Conference on Learning Representations (ICLR).
- Klink, P.; Yang, H.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2022). Curriculum Reinforcement Learning via Constrained Optimal Transport, International Conference on Machine Learning (ICML).
- Watson, J.; Lin J. A.; Klink, P.; Pajarinen, J.; Peters, J. (2021). Latent Derivative Bayesian Last Layer Networks, Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS).
- Dam, T.; Klink, P.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2020). Generalized Mean Estimation in Monte-Carlo Tree Search, Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI).
- Laux, M.; Arenz, O.; Pajarinen, J.; Peters, J. (2020). Deep Adversarial Reinforcement Learning for Object Disentangling, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2020).
- Klink, P.; D'Eramo, C.; Peters, J.; Pajarinen, J. (2020). Self-Paced Deep Reinforcement Learning, Advances in Neural Information Processing Systems (NIPS / NeurIPS).
- Lauri, M.; Pajarinen, J.; Peters, J. (2019). Information gathering in decentralized POMDPs by policy graph improvement, Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS).
- Tosatto, S.; D'Eramo, C.; Pajarinen, J.; Restelli, M.; Peters, J. (2019). Exploration Driven By an Optimistic Bellman Equation, Proceedings of the International Joint Conference on Neural Networks (IJCNN).
- Akrour, R.; Pajarinen, J.; Neumann, G.; Peters, J. (2019). Projections for Approximate Policy Iteration Algorithms, Proceedings of the International Conference on Machine Learning (ICML).
- Hoelscher, J.; Koert, D.; Peters, J.; Pajarinen, J. (2018). Utilizing Human Feedback in POMDP Execution and Specification, Proceedings of the International Conference on Humanoid Robots (HUMANOIDS).
- Pajarinen, J.; Kyrki, V.; Koval, M.; Srinivasa, S; Peters, J.; Neumann, G. (2017). Hybrid Control Trajectory Optimization under Uncertainty, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
- Luck, K.S.; Pajarinen, J.; Berger, E.; Kyrki, V.; Ben Amor, H. (2016). Sparse Latent Space Policy Search, Proceedings of the Thirtieth AAAI Conference On Artificial Intelligence (AAAI).
- Ikkala, A.; Pajarinen, J.; Kyrki, V. (2016). Benchmarking RGB-D Segmentation: Toy Dataset of Complex Crowded Scenes, Proceedings of the 11th International Conference on Computer Vision Theory and Applications (VISAPP).
- Racca, M.; Pajarinen, J.; Montebelli, A.; Kyrki, V. (2016). Learning In-Contact Control Strategies from Demonstration, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
- Pajarinen, J.; Kyrki, V. (2015). Decision Making Under Uncertain Segmentations, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA).
- Pajarinen, J.; Kyrki, V. (2014). Robotic manipulation in object composition space, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
- Kondaxakis, P.; Pajarinen, J.; and Kyrki, V. (2014). Real-Time Recognition of Pointing Gestures for Robot to Robot Interaction, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
- Pajarinen, J.; Peltonen, J. (2013). Expectation Maximization for Average Reward Decentralized POMDPs, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD).
- Pajarinen, J.; Peltonen, J. (2011). Periodic Finite State Controllers for Efficient POMDP and DEC-POMDP Planning, Proceedings of the 25th Annual Conference on Neural Information Processing Systems (NIPS).
- Pajarinen, J.; Peltonen, J. (2011). Efficient Planning for Factored Infinite-Horizon DEC-POMDPs, Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI).
- Pajarinen, J.; Peltonen, J.; Hottinen, A.; Uusitalo, M.A. (2010). Efficient Planning in Large POMDPs through Policy Graph Based Factorized Approximations, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD).
- Pajarinen, J.; Peltonen, J.; Uusitalo, M.A.; Hottinen, A. (2009). Latent state models of primary user behavior for opportunistic spectrum access, Proceedings of the IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC).
- Peltonen J.; Uusitalo, M.A.; Pajarinen, J. (2008). Nano-scale fault tolerant machine learning for cognitive radio, Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing (MLSP).
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| Thesis |
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- Pajarinen, J. (2013). Planning under uncertainty for large-scale problems with applications to wireless networking.
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| Patents |
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- Uusitalo, M.A.; Hottinen, A.; Peltonen, J.; Pajarinen, J. (2014). Forecasting of dynamic environmental parameters to optimize operation of a wireless communication system.
- Kuukankorpi, A.; Pajarinen, J.; Jalio, C.; Nippula, M. (2006). Processing of data packets within a network element cluster.
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