iBet uBet web content aggregator. Adding the entire web to your favor.
iBet uBet web content aggregator. Adding the entire web to your favor.



Link to original content: https://api.crossref.org/works/10.1109/ALLERTON.2019.8919758
{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,29]],"date-time":"2024-10-29T09:57:55Z","timestamp":1730195875782,"version":"3.28.0"},"reference-count":37,"publisher":"IEEE","license":[{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2019,9,1]],"date-time":"2019-09-01T00:00:00Z","timestamp":1567296000000},"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":[[2019,9]]},"DOI":"10.1109\/allerton.2019.8919758","type":"proceedings-article","created":{"date-parts":[[2019,12,6]],"date-time":"2019-12-06T04:23:39Z","timestamp":1575606219000},"page":"495-505","source":"Crossref","is-referenced-by-count":36,"title":["Privacy-Preserving Adversarial Networks"],"prefix":"10.1109","author":[{"given":"Ardhendu","family":"Tripathy","sequence":"first","affiliation":[]},{"given":"Ye","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Prakash","family":"Ishwar","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"journal-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"Adam: A method for stochastic optimization","year":"2015","author":"kingma","key":"ref33"},{"journal-title":"Proceedings of Workshop on Machine Learning Systems (LearningSys) in The Twenty-ninth Annual Conference on Neural Information Processing Systems (NIPS)","article-title":"Chainer: a nextgeneration open source framework for deep learning","year":"2015","author":"tokui","key":"ref32"},{"journal-title":"arXiv preprint arXiv 1511 05271","article-title":"Adversarial autoencoders","year":"2015","author":"makhzani","key":"ref31"},{"journal-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"Auto-encoding variational bayes","year":"2014","author":"kingma","key":"ref30"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/ITW.2014.6970882"},{"key":"ref36","first-page":"368","article-title":"The information bottleneck method","author":"tishby","year":"1999","journal-title":"Allerton Conf on Comm Ctrl and Comp"},{"journal-title":"Elements of Information Theory","year":"2012","author":"cover","key":"ref35"},{"key":"ref34","first-page":"914","article-title":"Nonparametric estimation of conditional information and divergences","volume":"22","author":"poczos","year":"2012","journal-title":"Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2013.2253320"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ITA.2016.7888175"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/1989323.1989345"},{"key":"ref13","first-page":"21","article-title":"Dependence makes you vulnberable: Differential privacy under dependent tuples","author":"liu","year":"2016","journal-title":"Symposium on Network and Distributed System Security"},{"journal-title":"arXiv preprint arXiv 1710 09295","article-title":"Privacy-utility tradeoffs under constrained data release mechanisms","year":"2017","author":"wang","key":"ref14"},{"key":"ref15","first-page":"201","article-title":"The IM algorithm: A variational approach to information maximization","author":"barber","year":"2003","journal-title":"Proceedings of the 16th International Conference on Neural Information Processing Systems ser NIPS’03"},{"key":"ref16","first-page":"2672","article-title":"Generative adversarial nets","author":"goodfellow","year":"2014","journal-title":"Advances in neural information processing systems"},{"journal-title":"The gan zoo","year":"2017","author":"hindupur","key":"ref17"},{"journal-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"Censoring representations with an adversary","year":"2015","author":"edwards","key":"ref18"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2017.7953386"},{"journal-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"The concrete distribution: A continuous relaxation of discrete random variables","year":"2017","author":"maddison","key":"ref28"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/1217299.1217302"},{"key":"ref27","first-page":"2172","article-title":"Infogan: Interpretable representation learning by information maximizing generative adversarial nets","author":"chen","year":"2016","journal-title":"Advances in Neural IInformation Processing Systems"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1142\/S0218488502001648"},{"key":"ref6","first-page":"265","article-title":"Calibrating noise to sensitivity in private data analysis","author":"dwork","year":"2006","journal-title":"Theory of Cryptography"},{"journal-title":"Proceedings of the International Conference on Learning Representations (ICLR)","article-title":"Categorical reparameterization with gumbel-softmax","year":"2017","author":"jang","key":"ref29"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2007.367856"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.190"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1983.1056749"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2008.33"},{"key":"ref9","first-page":"1401","article-title":"Privacy against statistical inference","author":"calmon","year":"2012","journal-title":"Allerton Conf on Comm Ctrl and Comp"},{"journal-title":"Simple Demographics Often Identify People Uniquely","year":"2000","author":"sweeney","key":"ref1"},{"key":"ref20","first-page":"4704","article-title":"Minimax filter: Learning to preserve privacy from inference attacks","volume":"18","year":"2017","journal-title":"The Journal of Machine Learning Research"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243855"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICB2018.2018.00023"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.3390\/e19120656"},{"journal-title":"arXiv preprint arXiv 1712 07008","article-title":"Privacy-preserving adversarial networks","year":"2017","author":"tripathy","key":"ref23"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/Allerton.2013.6736724"},{"journal-title":"arXiv preprint arXiv 1807 05306","article-title":"Generative adversarial privacy","year":"2018","key":"ref25"}],"event":{"name":"2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton)","start":{"date-parts":[[2019,9,24]]},"location":"Monticello, IL, USA","end":{"date-parts":[[2019,9,27]]}},"container-title":["2019 57th Annual Allerton Conference on Communication, Control, and Computing (Allerton)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8911248\/8919648\/08919758.pdf?arnumber=8919758","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,17]],"date-time":"2022-07-17T17:46:56Z","timestamp":1658080016000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/8919758\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9]]},"references-count":37,"URL":"https:\/\/doi.org\/10.1109\/allerton.2019.8919758","relation":{},"subject":[],"published":{"date-parts":[[2019,9]]}}}