Ghassen Jerfel, Serena Wang, Clara Wong-Fannjiang, Katherine A. Heller, Yian Ma, Michael I. Jordan. Variational refinement for importance sampling using the forward Kullback-Leibler divergence. In Cassio P. de Campos, Marloes H. Maathuis, Erik Quaeghebeur, editors, Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, UAI 2021, Virtual Event, 27-30 July 2021. Volume 161 of Proceedings of Machine Learning Research, pages 1819-1829, AUAI Press, 2021. [doi]
@inproceedings{JerfelWWHMJ21,
title = {Variational refinement for importance sampling using the forward Kullback-Leibler divergence},
author = {Ghassen Jerfel and Serena Wang and Clara Wong-Fannjiang and Katherine A. Heller and Yian Ma and Michael I. Jordan},
year = {2021},
url = {https://proceedings.mlr.press/v161/jerfel21a.html},
researchr = {https://researchr.org/publication/JerfelWWHMJ21},
cites = {0},
citedby = {0},
pages = {1819-1829},
booktitle = {Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, UAI 2021, Virtual Event, 27-30 July 2021},
editor = {Cassio P. de Campos and Marloes H. Maathuis and Erik Quaeghebeur},
volume = {161},
series = {Proceedings of Machine Learning Research},
publisher = {AUAI Press},
}