{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T16:35:53Z","timestamp":1775579753459,"version":"3.50.1"},"reference-count":17,"publisher":"IEEE","license":[{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,6,6]],"date-time":"2021-06-06T00:00:00Z","timestamp":1622937600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,6,6]]},"DOI":"10.1109\/icassp39728.2021.9414155","type":"proceedings-article","created":{"date-parts":[[2021,5,13]],"date-time":"2021-05-13T19:53:45Z","timestamp":1620935625000},"page":"8138-8142","source":"Crossref","is-referenced-by-count":74,"title":["Optimizing Coverage and Capacity in Cellular Networks using Machine Learning"],"prefix":"10.1109","author":[{"given":"Ryan M.","family":"Dreifuerst","sequence":"first","affiliation":[]},{"given":"Samuel","family":"Daulton","sequence":"additional","affiliation":[]},{"given":"Yuchen","family":"Qian","sequence":"additional","affiliation":[]},{"given":"Paul","family":"Varkey","sequence":"additional","affiliation":[]},{"given":"Maximilian","family":"Balandat","sequence":"additional","affiliation":[]},{"given":"Sanjay","family":"Kasturia","sequence":"additional","affiliation":[]},{"given":"Anoop","family":"Tomar","sequence":"additional","affiliation":[]},{"given":"Ali","family":"Yazdan","sequence":"additional","affiliation":[]},{"given":"Vish","family":"Ponnampalam","sequence":"additional","affiliation":[]},{"given":"Robert W.","family":"Heath","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","article-title":"BoTorch: Programmable Bayesian Optimization in PyTorch","volume":"33","author":"balandat","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref11","article-title":"Deterministic Policy Gradient Algorithms","author":"silver","year":"2014","journal-title":"ICML"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/EuCAP.2014.6902008"},{"key":"ref13","article-title":"Quadriga-based RF channel and response simulation (data and code)","author":"dreifuerst","year":"0"},{"key":"ref14","first-page":"63","author":"rasmussen","year":"2004","journal-title":"Gaussian Processes in Machine Learning"},{"key":"ref15","article-title":"Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization","volume":"33","author":"daulton","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref16","article-title":"Bayesian Optimization of Risk Measures","author":"cakmak","year":"2020"},{"key":"ref17","first-page":"2866","author":"geibel","year":"2012","journal-title":"Risk-sensitive Reinforcement Learning"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/VETECS.2011.5956497"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/WCNC.2009.4917961"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ACSSC.2017.8335588"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/WTS.2019.8715538"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCCN.2019.2933420"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/PIMRC.2010.5671622"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TVT.2016.2605380"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/SURV.2012.021312.00116"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/s11277-016-3849-9"}],"event":{"name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","location":"Toronto, ON, Canada","start":{"date-parts":[[2021,6,6]]},"end":{"date-parts":[[2021,6,11]]}},"container-title":["ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9413349\/9413350\/09414155.pdf?arnumber=9414155","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T15:41:07Z","timestamp":1652197267000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9414155\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,6,6]]},"references-count":17,"URL":"https:\/\/doi.org\/10.1109\/icassp39728.2021.9414155","relation":{},"subject":[],"published":{"date-parts":[[2021,6,6]]}}}