Empirical Inference Conference Paper 2025

Active Fine-Tuning of Multi-Task Policies

arXiv
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Empirical Inference
  • Doctoral Researcher
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Empirical Inference, Autonomous Learning
Senior Research Scientist

Author(s): Bagatella, M. and Hübotter, J. and Martius, G. and Krause, A.
Links:
Book Title: Proceedings of the 42nd International Conference on Machine Learning (ICML)
Volume: 267
Pages: 2409--2441
Year: 2025
Month: July
Series: Proceedings of Machine Learning Research
Editors: Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry
Publisher: PMLR
BibTeX Type: Conference Paper (inproceedings)
Event Name: International Conference on Machine Learning
Event Place: Vancouver Convention Center
State: Published
URL: https://proceedings.mlr.press/v267/bagatella25a.html

BibTeX

@inproceedings{BagHubMarKra25,
  title = {Active Fine-Tuning of Multi-Task Policies},
  booktitle = {Proceedings of the 42nd International Conference on Machine Learning (ICML)},
  volume = {267},
  pages = {2409--2441},
  series = {Proceedings of Machine Learning Research},
  editors = {Singh, Aarti and Fazel, Maryam and Hsu, Daniel and Lacoste-Julien, Simon and Berkenkamp, Felix and Maharaj, Tegan and Wagstaff, Kiri and Zhu, Jerry},
  publisher = {PMLR},
  month = jul,
  year = {2025},
  author = {Bagatella, M. and H{\"u}botter, J. and Martius, G. and Krause, A.},
  url = {https://proceedings.mlr.press/v267/bagatella25a.html},
  month_numeric = {7}
}