%0 Conference Paper %1 conf/uai/GoI22 %A Go, Jinwoo %A Isaac, Tobin %B UAI %D 2022 %E Cussens, James %E Zhang, Kun %I PMLR %K dblp %P 728-737 %T Robust expected information gain for optimal Bayesian experimental design using ambiguity sets. %U http://dblp.uni-trier.de/db/conf/uai/uai2022.html#GoI22 %V 180

@inproceedings{conf/uai/GoI22, added-at = {2022-10-15T00:00:00.000+0200}, author = {Go, Jinwoo and Isaac, Tobin}, biburl = {https://www.bibsonomy.org/bibtex/28575c5bffe4b5727b1861894a08511dc/dblp}, booktitle = {UAI}, crossref = {conf/uai/2022}, editor = {Cussens, James and Zhang, Kun}, ee = {https://proceedings.mlr.press/v180/go22a.html}, interhash = {4493cf5f3ab6f507ceb021cb40d5c400}, intrahash = {8575c5bffe4b5727b1861894a08511dc}, keywords = {dblp}, pages = {728-737}, publisher = {PMLR}, series = {Proceedings of Machine Learning Research}, timestamp = {2024-04-09T13:32:27.000+0200}, title = {Robust expected information gain for optimal Bayesian experimental design using ambiguity sets.}, url = {http://dblp.uni-trier.de/db/conf/uai/uai2022.html#GoI22}, volume = 180, year = 2022 }