Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Ayfer Ozgur"'
Autor:
Geoffrey Y. Li, Walid Saad, Ayfer Ozgur, Peter Kairouz, Zhijin Qin, Jakob Hoydis, Zhu Han, Deniz Gunduz, Jaafar Elmirghani
Publikováno v:
IEEE Journal on Selected Areas in Communications. 40:2251-2253
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d285c6576f7249dedfb87f8e643aa57
https://doi.org/10.1109/jsac.2022.3181863
https://doi.org/10.1109/jsac.2022.3181863
Publikováno v:
IEEE Transactions on Information Theory. 67:8248-8263
We consider parameter estimation in distributed networks, where each sensor in the network observes an independent sample from an underlying distribution and has $k$ bits to communicate its sample to a centralized processor which computes an estimate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0dd652b7d91db4639224d0d7ba1e3205
https://doi.org/10.1109/tit.2021.3108952
https://doi.org/10.1109/tit.2021.3108952
Autor:
Geoffrey Y. Li, Walid Saad, Ayfer Ozgur, Peter Kairouz, Zhijin Qin, Jakob Hoydis, Zhu Han, Deniz Gunduz, Jaafar Elmirghani
Publikováno v:
IEEE Journal on Selected Areas in Communications. 39:2267-2270
The Second Call for Papers of the Series on Machine Learning in Communications and Networks has continued to receive a great number of high-quality papers covering various aspects of intelligent communication systems. In addition to those already pub
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0430b078325dfc89289816f0bc7e9c26
https://doi.org/10.1109/jsac.2021.3087366
https://doi.org/10.1109/jsac.2021.3087366
Publikováno v:
2022 IEEE International Symposium on Information Theory (ISIT).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::463ee3fb9c58cdf9c66c60d56085ab07
https://doi.org/10.1109/isit50566.2022.9834610
https://doi.org/10.1109/isit50566.2022.9834610
Publikováno v:
IEEE Transactions on Information Theory. 66:7929-7938
The classical problem of supervised learning is to infer an accurate estimate of a target variable $Y$ from a measured variable $X$ using a set of labeled training samples. Motivated by the increasingly distributed nature of data and decision making,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17a57d79702f363e990b173e90a090ed
https://doi.org/10.1109/tit.2020.3029182
https://doi.org/10.1109/tit.2020.3029182
Publikováno v:
IEEE Journal on Selected Areas in Information Theory. 1:660-668
In this work, we consider the deterministic optimization using random projections as a statistical estimation problem, where the squared distance between the predictions from the estimator and the true solution is the error metric. In approximately s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d693d07f15dc5edbcb035a7cb78e184
https://doi.org/10.1109/jsait.2020.3039509
https://doi.org/10.1109/jsait.2020.3039509
Autor:
Geoffrey Y. Li, Walid Saad, Ayfer Ozgur, Peter Kairouz, Zhijin Qin, Jakob Hoydis, Zhu Han, Deniz Gunduz, Jaafar Elmirghani
The third call for papers of the Series on Machine Learning in Communications and Networks has continued to receive a great number of high-quality papers covering various aspects of intelligent communications, from which we have included 26 original
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ec807cd95d4f526ae74e52ad7e72a50
https://hdl.handle.net/11380/1280099
https://hdl.handle.net/11380/1280099
Publikováno v:
2021 IEEE Global Communications Conference (GLOBECOM).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1b86612fa81c2970f832672217ed101
https://doi.org/10.1109/globecom46510.2021.9685768
https://doi.org/10.1109/globecom46510.2021.9685768
Autor:
Ayfer Ozgur, Cem Kalkanli
Publikováno v:
2021 IEEE International Symposium on Information Theory (ISIT).
We study the asymptotic performance of the Thompson sampling algorithm in the batched multi-armed bandit setting where the time horizon $T$ is divided into batches, and the agent is not able to observe the rewards of her actions until the end of each
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d6a6f415ff07fb3c528a3e7339f822f3
https://doi.org/10.1109/isit45174.2021.9517843
https://doi.org/10.1109/isit45174.2021.9517843