Bayesian Inference of Temporal Task Specifications from Demonstrations. Shah, A., Kamath, P., Shah, J. A., & Li, S. In Bengio, S., Wallach, H. M., Larochelle, H., Grauman, K., Cesa-Bianchi, N., & Garnett, R., editors, Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, NeurIPS 2018, 3-8 December 2018, Montréal, Canada, pages 3808–3817, 2018. Paper bibtex @inproceedings{DBLP:conf/nips/ShahKSL18,
author = {Ankit Shah and
Pritish Kamath and
Julie A. Shah and
Shen Li},
editor = {Samy Bengio and
Hanna M. Wallach and
Hugo Larochelle and
Kristen Grauman and
Nicol{\`{o}} Cesa{-}Bianchi and
Roman Garnett},
title = {Bayesian Inference of Temporal Task Specifications from Demonstrations},
booktitle = {Advances in Neural Information Processing Systems 31: Annual Conference
on Neural Information Processing Systems 2018, NeurIPS 2018, 3-8 December
2018, Montr{\'{e}}al, Canada},
pages = {3808--3817},
year = {2018},
url = {http://papers.nips.cc/paper/7637-bayesian-inference-of-temporal-task-specifications-from-demonstrations},
timestamp = {Fri, 06 Mar 2020 17:00:31 +0100},
biburl = {https://dblp.org/rec/conf/nips/ShahKSL18.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
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