{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T00:31:30Z","timestamp":1787013090952,"version":"build-2736575974"},"reference-count":32,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2018,6,1]],"date-time":"2018-06-01T00:00:00Z","timestamp":1527811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"}],"funder":[{"DOI":"10.13039\/100006168","name":"Consortium for Verification Technology under Department of Energy National Nuclear Security Administration Award","doi-asserted-by":"publisher","award":["DE-NA0002534"],"award-info":[{"award-number":["DE-NA0002534"]}],"id":[{"id":"10.13039\/100006168","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007270","name":"University of Michigan ECE Departmental Fellowship","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100007270","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004284","name":"Xerox University Grant","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100004284","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2018,6]]},"DOI":"10.1109\/tifs.2018.2790580","type":"journal-article","created":{"date-parts":[[2018,1,8]],"date-time":"2018-01-08T17:32:15Z","timestamp":1515432735000},"page":"1446-1459","source":"Crossref","is-referenced-by-count":9,"title":["Latent Laplacian Maximum Entropy Discrimination for Detection of High-Utility Anomalies"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8100-6206","authenticated-orcid":false,"given":"Elizabeth","family":"Hou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kumar","family":"Sricharan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alfred O.","family":"Hero","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2014.05.011"},{"key":"ref31","year":"2015","journal-title":"I Have Every Publicly Available Reddit Comment for Research 1 7 Billion Comments 250 GB Compressed Any Interest in This?"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/1143844.1143874"},{"key":"ref10","first-page":"57","article-title":"Semi-supervised classification by low density separation","author":"chapelle","year":"2005","journal-title":"Proc Int Workshop Artif Intell Statist (AISTATS)"},{"key":"ref11","author":"jebara","year":"2004","journal-title":"Machine Learning Discriminative and Generative"},{"key":"ref12","first-page":"49","article-title":"Ai2: Training a big data machine to defend","author":"veeramachaneni","year":"2016","journal-title":"Proc IEEE 2nd Int Conf Big Data Security (BigDataSecurity)"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2016.0102"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2010.091510.100315"},{"key":"ref15","first-page":"470","article-title":"Maximum entropy discrimination","volume":"12","author":"jaakkola","year":"2000","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2014.6854029"},{"key":"ref17","first-page":"617","article-title":"Infinite SVM: A Dirichlet process mixture of large-margin kernel machines","author":"zhu","year":"2011","journal-title":"Proc 28th Int Conf Mach Learn (ICML)"},{"key":"ref18","first-page":"2531","article-title":"Maximum entropy discrimination Markov networks","volume":"10","author":"zhu","year":"2009","journal-title":"J Mach Learn Res"},{"key":"ref19","first-page":"69","article-title":"Support vector machines, reproducing kernel Hilbert spaces and the randomized GACV","volume":"6","author":"wahba","year":"1999","journal-title":"Adv Kernel Methods-Support Vector Learn"},{"key":"ref28","author":"grant","year":"2014","journal-title":"CVX Matlab software for disciplined convex programming version 2 0 beta"},{"key":"ref4","first-page":"665","article-title":"Learning minimum volume sets","volume":"7","author":"scott","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-84800-155-8_7"},{"key":"ref3","first-page":"585","article-title":"Geometric entropy minimization (GEM) for anomaly detection and localization","volume":"19","author":"hero","year":"2007","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref6","first-page":"1073","article-title":"Active learning for anomaly and rare-category detection","volume":"17","author":"pelleg","year":"2005","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref29","author":"franc","year":"2009","journal-title":"Library for Quadratic Programming"},{"key":"ref5","first-page":"478","article-title":"Efficient anomaly detection using bipartite k-NN graphs","volume":"24","author":"sricharan","year":"2011","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"ref7","article-title":"Aladin: Active learning of anomalies to detect intrusions","author":"stokes","year":"2008"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1613\/jair.3623","article-title":"Toward supervised anomaly detection","volume":"46","author":"g\u00f6rnitz","year":"2013","journal-title":"J Artif Intell Res"},{"key":"ref9","first-page":"2399","article-title":"Manifold regularization: A geometric framework for learning from labeled and unlabeled examples","volume":"7","author":"belkin","year":"2006","journal-title":"J Mach Learn Res"},{"key":"ref1","first-page":"582","article-title":"Support vector method for novelty detection","volume":"12","author":"sch\u00f6lkopf","year":"2000","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref20","article-title":"Probabilistic kernel regression models","author":"jaakkola","year":"1999","journal-title":"Proc Int'l Workshop Artificial Intelligence and Statistics (AISTATS)"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1162\/089976600300014881"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/S0893-6080(98)00032-X"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1090\/conm\/398\/07486"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1023\/A:1012489924661"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/1102351.1102455"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10206\/8283858\/08248782.pdf?arnumber=8248782","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,12]],"date-time":"2022-01-12T11:17:56Z","timestamp":1641986276000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8248782\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,6]]},"references-count":32,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tifs.2018.2790580","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"value":"1556-6013","type":"print"},{"value":"1556-6021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,6]]}}}