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Patient-Specific Seizure Detection from Intra-cranial EEG Using High Dimensional Clustering.

H. Dutta, D. Waltz, K. Ramasamy, P. Gross, A. Salleb-Aouissi, H. Diab, M. Pooleery, C. Schevon, and R. Emerson. ICMLA, page 782-787. IEEE Computer Society, (2010)

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Vers des Machines à Vecteurs Support Äctionnables" : Une Approche Fondée sur le Classement.A. Salleb-Aouissi, B. Huang, and D. Waltz. EGC, volume RNTI-E-11 of Revue des Nouvelles Technologies de l'Information, page 285-296. Cépaduès-Éditions, (2008)Application of Sentiment and Topic Analysis to Teacher Evaluation Policy in the U.S.A. Moretti, K. McKnight, and A. Salleb-Aouissi. EDM, page 628-629. International Educational Data Mining Society (IEDMS), (2015)Making Sense of Word Sense Variation.R. Passoneau, A. Salleb-Aouissi, and N. Ide. SEW@NAACL-HLT, page 2-9. Association for Computational Linguistics, (2009)Machine Learning for theNew York City Power Grid.C. Rudin, D. Waltz, R. Anderson, A. Boulanger, A. Salleb-Aouissi, M. Chow, H. Dutta, P. Gross, B. Huang, and S. Ierome. IEEE Trans. Pattern Anal. Mach. Intell., 34 (2): 328-345 (2012)Alive on Back-feed Culprit Identification via Machine Learning.B. Huang, A. Salleb-Aouissi, and P. Gross. ICMLA, page 725-730. IEEE Computer Society, (2009)Learning Characteristic Rules in Geographic Information Systems.A. Salleb-Aouissi, C. Vrain, and D. Cassard. RuleML, volume 9202 of Lecture Notes in Computer Science, page 431-444. Springer, (2015)QuantMiner: A Genetic Algorithm for Mining Quantitative Association Rules.A. Salleb-Aouissi, C. Vrain, and C. Nortet. IJCAI, page 1035-1040. (2007)Word Sense Annotation of Polysemous Words by Multiple Annotators.R. Passonneau, A. Salleb-Aouissi, V. Bhardwaj, and N. Ide. LREC, European Language Resources Association, (2010)Automated Symbolic Law Discovery: A Computer Vision Approach.H. Xing, A. Salleb-Aouissi, and N. Verma. AAAI, page 660-668. AAAI Press, (2021)Sequential event prediction with association rulesC. Rudin, B. Letham, A. Salleb-Aouissi, E. Kogan, and D. Madigan. (2011)

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Patient-Specific Seizure Detection from Intra-cranial EEG Using High Dimensional Clustering.

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Patient-Specific Seizure Detection from Intra-cranial EEG Using High Dimensional Clustering.

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Patient-Specific Seizure Detection from Intra-cranial EEG Using High Dimensional Clustering.