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Carlo D'Eramo
Carlo D'Eramo
Professor of Reinforcement Learning @ University of Würzburg | Group leader @ hessian.AI
Verified email at uni-wuerzburg.de - Homepage
Title
Cited by
Cited by
Year
Sharing Knowledge in Multi-Task Deep Reinforcement Learning
C D'Eramo, D Tateo, A Bonarini, M Restelli, J Peters
International Conference on Learning Representations (ICLR), 2020
842020
Estimating the Maximum Expected Value through Gaussian Approximation
C D’Eramo, A Nuara, M Restelli
Proceedings of The 33rd International Conference on Machine Learning, 1032-1040, 2016
452016
Mushroomrl: Simplifying reinforcement learning research
C D'Eramo, D Tateo, A Bonarini, M Restelli, J Peters
Journal of Machine Learning Research (JMLR) 22, 1-5, 2020
422020
Boosted Fitted Q-Iteration
S Tosatto, M Pirotta, C D'Eramo, M Restelli
Proceedings of The 34th International Conference on Machine Learning, 3434-3443, 2017
402017
Model Predictive Actor-Critic: Accelerating Robot Skill Acquisition with Deep Reinforcement Learning
AS Morgan, D Nandha, G Chalvatzaki, C D'Eramo, AM Dollar, J Peters
International Conference on Robotics and Automation (ICRA), 2021
30*2021
Self-Paced Deep Reinforcement Learning
P Klink, C D'Eramo, J Peters, J Pajarinen
Advances in Neural Information Processing Systems (NeurIPS), 2020
272020
Estimating the Maximum Expected Value in Continuous Reinforcement Learning Problems
C D'Eramo, A Nuara, M Pirotta, R Marcello
AAAI Conference on Artificial Intelligence, 1840-1846, 2017
232017
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 (JMLR) 22, 1-52, 2021
132021
Multi-channel interactive reinforcement learning for sequential tasks
D Koert, M Kircher, V Salikutluk, C D'Eramo, J Peters
Frontiers in Robotics and AI 7, 97, 2020
122020
Composable Energy Policies for Reactive Motion Generation and Reinforcement Learning
J Urain, A Li, P Liu, C D'Eramo, J Peters
Robotics: Science and Systems (RSS), 2021
112021
Deep reinforcement learning with weighted Q-Learning
A Cini, C D'Eramo, J Peters, C Alippi
arXiv preprint arXiv:2003.09280, 2020
102020
Exploiting Action-Value Uncertainty to Drive Exploration in Reinforcement Learning
C D’Eramo, A Cini, M Restelli
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
92019
Convex regularization in Monte-Carlo tree search
TQ Dam, C D’Eramo, J Peters, J Pajarinen
International Conference on Machine Learning, 2365-2375, 2021
8*2021
Curriculum reinforcement learning via constrained optimal transport
P Klink, H Yang, C D’Eramo, J Peters, J Pajarinen
International Conference on Machine Learning, 11341-11358, 2022
62022
Long-Term Visitation Value for Deep Exploration in Sparse-Reward Reinforcement Learning
S Parisi, D Tateo, M Hensel, C D’eramo, J Peters, J Pajarinen
Algorithms 15 (3), 81, 2022
42022
Generalized Mean Estimation in Monte-Carlo Tree Search
T Dam, P Klink, C D'Eramo, J Peters, J Pajarinen
International Joint Conference on Artificial Intelligence (IJCAI), 2020
42020
Boosted Curriculum Reinforcement Learning
P Klink, C D'Eramo, J Peters, J Pajarinen
International Conference on Learning Representations (ICLR), 2022
32022
Gaussian approximation for bias reduction in Q-learning
C D'Eramo, A Cini, A Nuara, M Pirotta, C Alippi, J Peters, M Restelli
Journal of Machine Learning Research (JMLR) 22, 1-51, 2021
32021
Exploration Driven by an Optimistic Bellman Equation
S Tosatto, C D’Eramo, J Pajarinen, M Restelli, J Peters
2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019
22019
Exploiting structure and uncertainty of Bellman updates in Markov decision processes
D Tateo, C D'Eramo, A Nuara, M Restelli, A Bonarini
Symposium on Adaptive Dynamic Programming and Reinforcement Learning (IEEE …, 2017
22017
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