{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T10:05:04Z","timestamp":1764842704393,"version":"3.41.0"},"reference-count":5,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2022,12,30]],"date-time":"2022-12-30T00:00:00Z","timestamp":1672358400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGMETRICS Perform. Eval. Rev."],"published-print":{"date-parts":[[2022,12,30]]},"abstract":"<jats:p>Brief Biography: Jessica Maghakian is a final-year PhD candidate in Operations Research at Stony Brook University. She has collaborated with several industry partners and interned at Microsoft Research NYC. Jessica's research combines data-driven decision making with traditional online algorithms approaches to solve challenging resource allocation problems that arise in IT infrastructure systems. Her work has been awarded an NSF Graduate Research Fellowship, a Stony Brook University STRIDE Fellowship for excellence in visualization, science communication and decision-support, and a Best Paper Nomination at ACM e-Energy. She received her Bachelors of Science from the Massachusetts Institute of Technology (MIT) with a double major in Mathematics and Brain and Cognitive Sciences.<\/jats:p>","DOI":"10.1145\/3579342.3579349","type":"journal-article","created":{"date-parts":[[2023,1,6]],"date-time":"2023-01-06T05:22:00Z","timestamp":1672982520000},"page":"24-27","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Online Resource Allocation with Noisy Predictions"],"prefix":"10.1145","volume":"50","author":[{"given":"Jessica","family":"Maghakian","sequence":"first","affiliation":[{"name":"Stony Brook University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,1,5]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Two Untrusted Predictors are Better than One: Minimizing Bandwidth Cost with Multiple Noisy Predictors (Under review) with J. Maghakian R. Lee M. Hajiesmaili J. Li Z. 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Liu"}],"container-title":["ACM SIGMETRICS Performance Evaluation Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3579342.3579349","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3579342.3579349","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:49:27Z","timestamp":1750182567000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3579342.3579349"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,30]]},"references-count":5,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2022,12,30]]}},"alternative-id":["10.1145\/3579342.3579349"],"URL":"https:\/\/doi.org\/10.1145\/3579342.3579349","relation":{},"ISSN":["0163-5999"],"issn-type":[{"type":"print","value":"0163-5999"}],"subject":[],"published":{"date-parts":[[2022,12,30]]},"assertion":[{"value":"2023-01-05","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}