New IJCAI paper: Contextual CMA-ES

New IJCAI paper: Contextual CMA-ES

A. Abdolmaleki, B. Price, N. Lau, P. Reis, and G. Neumann, “Contextual CMA-ES,” in International Joint Conference on Artificial Intelligence (IJCAI), 2017. [BibTeX] [Abstract] [Download…

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New JMLR paper accepted: "Non-parametric Policy Search with Limited Information Loss."

New JMLR paper accepted: “Non-parametric Policy Search with Limited Information Loss.”

H. van Hoof, G. Neumann, and J. Peters, “Non-parametric policy search with limited information loss,” Journal of Machine Learning Research, vol. 18, iss. 73, pp….

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New IJJR Paper accepted! "Learning Movement Primitive Libraries through Probabilistic Segmentation."

New IJJR Paper accepted! “Learning Movement Primitive Libraries through Probabilistic Segmentation.”

R. Lioutikov, G. Neumann, G. Maeda, and J. Peters, “Learning movement primitive libraries through probabilistic segmentation,” International Journal of Robotics Research (IJRR), vol. 36, iss….

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New ICML Paper: Local Bayesian Optimization

New ICML Paper: Local Bayesian Optimization

R. Akrour, D. Sorokin, J. Peters, and G. Neumann, “Local Bayesian optimization of motor skills,” in International Conference on Machine Learning (ICML), 2017. [BibTeX] [Abstract]…

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New AURO Paper: Using Probabilistic Movement Primitives in Robotics

New AURO Paper: Using Probabilistic Movement Primitives in Robotics

Well deserved, Alex! A. Paraschos, C. Daniel, J. Peters, and G. Neumann, “Using probabilistic movement primitives in robotics,” Autonomous Robots, vol. 42, iss. 3, pp….

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New RAL Paper: "Probabilistic Prioritization of Movement Primitives"

New RAL Paper: “Probabilistic Prioritization of Movement Primitives”

Alex’s last journal paper for his PhD has been accepted! Congratulations! A. Paraschos, R. Lioutikov, J. Peters, and G. Neumann, “Probabilistic prioritization of movement primitives,”…

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