Models for data-efficient reinforcement learning on real-world applications.

Andreas Doerr Andreas Doerr Models for data-efficient reinforcement learning on real-world applications. 2021 University of Stuttgart, Germany https://nbn-resolving.org/urn:nbn:de:bsz:93-opus-ds-119257 https://d-nb.info/1250244099 Michael Volpp Lukas P. Fröhlich Kirsten Fischer Andreas Doerr Stefan Falkner Frank Hutter Christian Daniel Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization. 2020 ICLR https://openreview.net/forum?id=ryeYpJSKwr conf/iclr/2020 db/conf/iclr/iclr2020.html#VolppFFDFHD20 Andreas Doerr Michael Volpp Marc Toussaint Sebastian Trimpe Christian Daniel Trajectory-Based Off-Policy Deep Reinforcement Learning. 1636-1645 2019 ICML http://proceedings.mlr.press/v97/doerr19a.html conf/icml/2019 db/conf/icml/icml2019.html#DoerrVTTD19

Michael Volpp Lukas P. Fröhlich Andreas Doerr Frank Hutter Christian Daniel Meta-Learning Acquisition Functions for Bayesian Optimization. 2019 abs/1904.02642 CoRR http://arxiv.org/abs/1904.02642 db/journals/corr/corr1904.html#abs-1904-02642

Andreas Doerr Michael Volpp Marc Toussaint Sebastian Trimpe Christian Daniel Trajectory-Based Off-Policy Deep Reinforcement Learning. 2019 abs/1905.05710 CoRR http://arxiv.org/abs/1905.05710 db/journals/corr/corr1905.html#abs-1905-05710

Andreas Doerr Christian Daniel Martin Schiegg Duy Nguyen-Tuong Stefan Schaal Marc Toussaint Sebastian Trimpe Probabilistic Recurrent State-Space Models. 1279-1288 2018 ICML http://proceedings.mlr.press/v80/doerr18a.html conf/icml/2018 db/conf/icml/icml2018.html#DoerrDSNSTT18 David Reeb Andreas Doerr Sebastian Gerwinn Barbara Rakitsch Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds. 3341-3351 2018 NeurIPS https://proceedings.neurips.cc/paper/2018/hash/d43ab110ab2489d6b9b2caa394bf920f-Abstract.html http://papers.nips.cc/paper/7594-learning-gaussian-processes-by-minimizing-pac-bayesian-generalization-bounds conf/nips/2018 db/conf/nips/nips2018.html#ReebDGR18

David Reeb Andreas Doerr Sebastian Gerwinn Barbara Rakitsch Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds. 2018 abs/1810.12263 CoRR http://arxiv.org/abs/1810.12263 db/journals/corr/corr1810.html#abs-1810-12263

Andreas Doerr Christian Daniel Duy Nguyen-Tuong Alonso Marco Stefan Schaal Marc Toussaint Sebastian Trimpe Optimizing Long-term Predictions for Model-based Policy Search. 227-238 2017 CoRL http://proceedings.mlr.press/v78/doerr17a.html conf/corl/2017 db/conf/corl/corl2017.html#DoerrDNMSTT17 Andreas Doerr Duy Nguyen-Tuong Alonso Marco Stefan Schaal Sebastian Trimpe Model-based policy search for automatic tuning of multivariate PID controllers. 5295-5301 2017 ICRA https://doi.org/10.1109/ICRA.2017.7989622 conf/icra/2017 db/conf/icra/icra2017.html#DoerrNMST17

Andreas Doerr Duy Nguyen-Tuong Alonso Marco Stefan Schaal Sebastian Trimpe Model-Based Policy Search for Automatic Tuning of Multivariate PID Controllers. 2017 abs/1703.02899 CoRR http://arxiv.org/abs/1703.02899 db/journals/corr/corr1703.html#DoerrNMST17

Andreas Doerr Nathan D. Ratliff Jeannette Bohg Marc Toussaint Stefan Schaal Direct Loss Minimization Inverse Optimal Control. 2015 Robotics: Science and Systems http://www.roboticsproceedings.org/rss11/p13.html https://doi.org/10.15607/RSS.2015.XI.013 conf/rss/2015 db/conf/rss/rss2015.html#DoerrRBTS15 Jeannette Bohg Christian Daniel Stefan Falkner Kirsten Fischer Lukas P. Fröhlich Sebastian Gerwinn Frank Hutter Alonso Marco Duy Nguyen-Tuong Barbara Rakitsch Nathan D. Ratliff David Reeb Stefan Schaal Martin Schiegg Marc Toussaint Sebastian Trimpe Michael Volpp