%0 Conference Paper %1 conf/icml/0001VC23 %A Liu, Fanghui %A Viano, Luca %A Cevher, Volkan %B ICML %D 2023 %E Krause, Andreas %E Brunskill, Emma %E Cho, Kyunghyun %E Engelhardt, Barbara %E Sabato, Sivan %E Scarlett, Jonathan %I PMLR %K dblp %P 22063-22091 %T What can online reinforcement learning with function approximation benefit from general coverage conditions? %U http://dblp.uni-trier.de/db/conf/icml/icml2023.html#0001VC23 %V 202

@inproceedings{conf/icml/0001VC23, added-at = {2023-08-28T00:00:00.000+0200}, author = {Liu, Fanghui and Viano, Luca and Cevher, Volkan}, biburl = {https://www.bibsonomy.org/bibtex/2b8bfa4da85bda19e9e8e445134d33820/dblp}, booktitle = {ICML}, crossref = {conf/icml/2023}, editor = {Krause, Andreas and Brunskill, Emma and Cho, Kyunghyun and Engelhardt, Barbara and Sabato, Sivan and Scarlett, Jonathan}, ee = {https://proceedings.mlr.press/v202/liu23aj.html}, interhash = {47243e1f53af6de7258e5468ac732571}, intrahash = {b8bfa4da85bda19e9e8e445134d33820}, keywords = {dblp}, pages = {22063-22091}, publisher = {PMLR}, series = {Proceedings of Machine Learning Research}, timestamp = {2024-04-10T01:43:32.000+0200}, title = {What can online reinforcement learning with function approximation benefit from general coverage conditions?}, url = {http://dblp.uni-trier.de/db/conf/icml/icml2023.html#0001VC23}, volume = 202, year = 2023 }