Joni Pajarinen
Joni Pajarinen
Assistant Professor at Aalto University
Verified email at - Homepage
Cited by
Cited by
An Algorithmic Perspective on Imitation Learning
T Osa, J Pajarinen, G Neumann, JA Bagnell, P Abbeel, J Peters
Foundations and Trends in Robotics 7 (1-2), 1-179, 2018
Partially Observable Markov Decision Processes in Robotics: A Survey
M Lauri, D Hsu, J Pajarinen
IEEE Transactions on Robotics 39 (1), 21-40, 2022
Robotic manipulation of multiple objects as a POMDP
J Pajarinen, V Kyrki
Artificial Intelligence 247, 213-228, 2017
Learning in-contact control strategies from demonstration
M Racca, J Pajarinen, A Montebelli, V Kyrki
2016 IEEE/RSJ international conference on intelligent robots and systems …, 2016
Periodic finite state controllers for efficient POMDP and DEC-POMDP planning
J Pajarinen, J Peltonen
Advances in neural information processing systems 24, 2011
Self-Paced Deep Reinforcement Learning
P Klink, C D'Eramo, J Peters, J Pajarinen
Advances in Neural Information Processing Systems (NeurIPS), 2020
Efficient planning for factored infinite-horizon DEC-POMDPs
J Pajarinen, J Peltonen
IJCAI Proceedings-International Joint Conference on Artificial Intelligence …, 2011
Processing of data packets within a network element cluster
A Kuukankorpi, J Pajarinen, C Jalio, M Nippula
US Patent 7,130,305, 2006
Learning intention aware online adaptation of movement primitives
D Koert, J Pajarinen, A Schotschneider, S Trick, C Rothkopf, J Peters
IEEE Robotics and Automation Letters 4 (4), 3719-3726, 2019
Optimizing spatial and temporal reuse in wireless networks by decentralized partially observable Markov decision processes
J Pajarinen, A Hottinen, J Peltonen
IEEE Transactions on Mobile Computing 13 (4), 866-879, 2013
Curriculum reinforcement learning via constrained optimal transport
P Klink, H Yang, C D’Eramo, J Pajarinen, J Peters
International Conference on Machine Learning (ICML), 11341-11358, 2022
Multi-sensor next-best-view planning as matroid-constrained submodular maximization
M Lauri, J Pajarinen, J Peters, S Frintrop
IEEE Robotics and Automation Letters 5 (4), 5323-5330, 2020
Latent Derivative Bayesian Last Layer Networks
J Watson, JA Lin, P Klink, J Pajarinen, J Peters
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021
Compatible natural gradient policy search
J Pajarinen, HL Thai, R Akrour, J Peters, G Neumann
Machine Learning 108, 1443-1466, 2019
Adaptive behavior cloning regularization for stable offline-to-online reinforcement learning
Y Zhao, R Boney, A Ilin, J Kannala, J Pajarinen
European Symposium on Artificial Neural Networks, Computational Intelligence …, 2022
A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning
P Klink, H Abdulsamad, B Belousov, C D'Eramo, J Peters, J Pajarinen
Journal of Machine Learning Research 22 (182), 1-52, 2021
Redeeming Intrinsic Rewards via Constrained Optimization
E Chen, ZW Hong, J Pajarinen, P Agrawal
Advances in Neural Information Processing Systems (NeurIPS), 2022
Reinforcement learning based underwater wireless optical communication alignment for autonomous underwater vehicles
Y Weng, J Pajarinen, R Akrour, T Matsuda, J Peters, T Maki
IEEE Journal of Oceanic Engineering 47 (4), 1231-1245, 2022
Multi-agent active information gathering in discrete and continuous-state decentralized POMDPs by policy graph improvement
M Lauri, J Pajarinen, J Peters
Autonomous Agents and Multi-Agent Systems 34 (2), 42, 2020
Hybrid control trajectory optimization under uncertainty
J Pajarinen, V Kyrki, M Koval, S Srinivasa, J Peters, G Neumann
2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017
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