{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:56:38Z","timestamp":1750308998529,"version":"3.41.0"},"reference-count":27,"publisher":"Association for Computing Machinery (ACM)","issue":"6","license":[{"start":{"date-parts":[[2018,11,6]],"date-time":"2018-11-06T00:00:00Z","timestamp":1541462400000},"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":["ACM Trans. Des. Autom. Electron. Syst."],"published-print":{"date-parts":[[2018,11,30]]},"abstract":"<jats:p>We consider a generalized model of learning from expert advice in which experts could abstain from participating at some rounds. Our proposed online algorithm falls into the class of weighted average predictors and uses a time-varying multiplicative weight update rule. This update rule changes the weight of an expert based on his or her relative performance compared to the average performance of available experts at the current round. This makes the algorithm suitable for recommendation systems in the presence of an adversary with many potential applications in the new emerging area of the Internet of Things. We prove the convergence of our algorithm to the best expert, defined in terms of both availability and accuracy, in the stochastic setting. In particular, we show the applicability of our definition of best expert through convergence analysis of another well-known algorithm in this setting. Finally, through simulation results on synthetic and real datasets, we justify the out-performance of our proposed algorithms compared to the existing ones in the literature.<\/jats:p>","DOI":"10.1145\/3236617","type":"journal-article","created":{"date-parts":[[2018,11,6]],"date-time":"2018-11-06T13:36:47Z","timestamp":1541511407000},"page":"1-18","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Learning From Sleeping Experts"],"prefix":"10.1145","volume":"23","author":[{"given":"Anh","family":"Truong","sequence":"first","affiliation":[{"name":"University of Illinois at Urbana\u2013Champaign, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S. Rasoul","family":"Etesami","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Negar","family":"Kiyavash","sequence":"additional","affiliation":[{"name":"University of Illinois at Urbana-Champaign, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,11,6]]},"reference":[{"volume-title":"Proceedings of the 45th Asilomar Conference on Signals, Systems and Computers (ASILOMAR\u201911)","author":"Agrawal K.","key":"e_1_2_1_1_1","unstructured":"K. Agrawal , A. Vempaty , H. Chen , and P. K. Varshney . 2011. Target localization in wireless sensor networks with quantized data in the presence of byzantine attacks . In Proceedings of the 45th Asilomar Conference on Signals, Systems and Computers (ASILOMAR\u201911) . 1669--1673. K. Agrawal, A. Vempaty, H. Chen, and P. K. Varshney. 2011. Target localization in wireless sensor networks with quantized data in the presence of byzantine attacks. In Proceedings of the 45th Asilomar Conference on Signals, Systems and Computers (ASILOMAR\u201911). 1669--1673."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1016\/0191-2607(91)90146-H"},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/WI-IAT.2010.63"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/1007352.1007367"},{"key":"e_1_2_1_5_1","unstructured":"N. C. Bianchi and G. Lugosi. 2006. Prediction Learning and Games. Cambridge University Press Cambridge.   N. C. Bianchi and G. Lugosi. 2006. Prediction Learning and Games. Cambridge University Press Cambridge."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.2140\/pjm.1956.6.1"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/267460.267475"},{"volume-title":"Proceedings of the 40th Annual Symposium on Foundations of Computer Science. 450--457","author":"Blum A.","key":"e_1_2_1_8_1","unstructured":"A. Blum , C. Burch , and A. Kalai . 1999. Finely-competitive paging . In Proceedings of the 40th Annual Symposium on Foundations of Computer Science. 450--457 . A. Blum, C. Burch, and A. Kalai. 1999. Finely-competitive paging. In Proceedings of the 40th Annual Symposium on Foundations of Computer Science. 450--457."},{"key":"e_1_2_1_9_1","unstructured":"A. Blum and Y. Mansour. 2007. From external to internal regret. J. Mach. Learn. Res. 8 (Dec. 2007) 1307--1324.   A. Blum and Y. Mansour. 2007. From external to internal regret. J. Mach. Learn. Res. 8 (Dec. 2007) 1307--1324."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-93-86279-38-5"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/258533.258616"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1093\/comjnl\/bxh168"},{"key":"e_1_2_1_13_1","volume-title":"Approximation to bayes risk in repeated play. Contributions to the Theory of Games 3","author":"Hannan J.","year":"1957","unstructured":"J. Hannan . 1957. Approximation to bayes risk in repeated play. Contributions to the Theory of Games 3 ( 1957 ), 97--139. J. Hannan. 1957. Approximation to bayes risk in repeated play. Contributions to the Theory of Games 3 (1957), 97--139."},{"volume-title":"Proceedings of the North American Chapter of the Association for Computational Linguistics Human Language Technologies Conference.","author":"Joshi M.","key":"e_1_2_1_14_1","unstructured":"M. Joshi , D. Das , K. Gimpel , and N. Smith . 2010. Movie reviews and revenues: An experiment in text regression . In Proceedings of the North American Chapter of the Association for Computational Linguistics Human Language Technologies Conference. M. Joshi, D. Das, K. Gimpel, and N. Smith. 2010. Movie reviews and revenues: An experiment in text regression. In Proceedings of the North American Chapter of the Association for Computational Linguistics Human Language Technologies Conference."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jcss.2004.10.016"},{"volume-title":"Proceedings of the 12th International Conference on Artificial Intelligence and Statistics","author":"Kanade V.","key":"e_1_2_1_16_1","unstructured":"V. Kanade , B. McMahan , and B. Bryan . 2009. Sleeping experts and bandits with stochastic action availability and adversarial rewards . In Proceedings of the 12th International Conference on Artificial Intelligence and Statistics . Florida, USA, 272--279. V. Kanade, B. McMahan, and B. Bryan. 2009. Sleeping experts and bandits with stochastic action availability and adversarial rewards. In Proceedings of the 12th International Conference on Artificial Intelligence and Statistics. Florida, USA, 272--279."},{"volume-title":"Proceedings of the 21st Annual Conference on Learning Theory (COLT\u201908)","author":"Kleinberg R. D.","key":"e_1_2_1_17_1","unstructured":"R. D. Kleinberg , A. Niculescu-Mizil , and Y. Sharma . 2008. Regret bounds for sleeping experts and bandits . In Proceedings of the 21st Annual Conference on Learning Theory (COLT\u201908) . 425--436. R. D. Kleinberg, A. Niculescu-Mizil, and Y. Sharma. 2008. Regret bounds for sleeping experts and bandits. In Proceedings of the 21st Annual Conference on Learning Theory (COLT\u201908). 425--436."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/SFCS.1989.63487"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2013.11.035"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2718488"},{"volume-title":"Proceedings of the 52th IEEE Conference on Decision and Control. Florence, Italia, 7315--7320","author":"Truong A.","key":"e_1_2_1_21_1","unstructured":"A. Truong and N. Kiyavash . 2013. Optimal adversarial strategies in learning with expert advice . In Proceedings of the 52th IEEE Conference on Decision and Control. Florence, Italia, 7315--7320 . A. Truong and N. Kiyavash. 2013. Optimal adversarial strategies in learning with expert advice. In Proceedings of the 52th IEEE Conference on Decision and Control. Florence, Italia, 7315--7320."},{"volume-title":"Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference. 3889--3894","author":"Truong A.","key":"e_1_2_1_22_1","unstructured":"A. Truong , N. Kiyavash , and V. Borkar . 2011. Convergence analysis for an online recommendation system . In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference. 3889--3894 . A. Truong, N. Kiyavash, and V. Borkar. 2011. Convergence analysis for an online recommendation system. In Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference. 3889--3894."},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2012.2236325"},{"volume-title":"Proceedings of 46th Annual Conference on Information Sciences and Systems (CISS\u201912)","author":"Vempaty A.","key":"e_1_2_1_24_1","unstructured":"A. Vempaty , O. Ozdemir , and P. K. Varshney . 2012. Mitigation of byzantine attacks for target location estimation in wireless sensor networks . In Proceedings of 46th Annual Conference on Information Sciences and Systems (CISS\u201912) . 1--6. A. Vempaty, O. Ozdemir, and P. K. Varshney. 2012. Mitigation of byzantine attacks for target location estimation in wireless sensor networks. In Proceedings of 46th Annual Conference on Information Sciences and Systems (CISS\u201912). 1--6."},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.5555\/92571.92672"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2009.26"},{"key":"e_1_2_1_27_1","doi-asserted-by":"publisher","DOI":"10.1109\/WI-IAT.2009.53"}],"container-title":["ACM Transactions on Design Automation of Electronic Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3236617","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3236617","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T21:41:27Z","timestamp":1750282887000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3236617"}},"subtitle":["Rewarding Informative, Available, and Accurate Experts"],"short-title":[],"issued":{"date-parts":[[2018,11,6]]},"references-count":27,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2018,11,30]]}},"alternative-id":["10.1145\/3236617"],"URL":"https:\/\/doi.org\/10.1145\/3236617","relation":{},"ISSN":["1084-4309","1557-7309"],"issn-type":[{"type":"print","value":"1084-4309"},{"type":"electronic","value":"1557-7309"}],"subject":[],"published":{"date-parts":[[2018,11,6]]},"assertion":[{"value":"2017-10-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-06-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2018-11-06","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}