Matilde Gargiani, Andrea Zanelli, Andrea Martinelli, Tyler H. Summers, John Lygeros. PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation. In Kamalika Chaudhuri, Stefanie Jegelka, Le Song, Csaba Szepesvári, Gang Niu 0001, Sivan Sabato, editors, International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA. Volume 162 of Proceedings of Machine Learning Research, pages 7223-7240, PMLR, 2022. [doi]
@inproceedings{GargianiZMSL22,
title = {PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation},
author = {Matilde Gargiani and Andrea Zanelli and Andrea Martinelli and Tyler H. Summers and John Lygeros},
year = {2022},
url = {https://proceedings.mlr.press/v162/gargiani22a.html},
researchr = {https://researchr.org/publication/GargianiZMSL22},
cites = {0},
citedby = {0},
pages = {7223-7240},
booktitle = {International Conference on Machine Learning, ICML 2022, 17-23 July 2022, Baltimore, Maryland, USA},
editor = {Kamalika Chaudhuri and Stefanie Jegelka and Le Song and Csaba Szepesvári and Gang Niu 0001 and Sivan Sabato},
volume = {162},
series = {Proceedings of Machine Learning Research},
publisher = {PMLR},
}