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Decrypting "Cryptogenic" Epilepsy: Semi-supervised Hierarchical Conditional Random Fields For Detecting Cortical Lesions In MRI-Negative Patients., , , , , and . J. Mach. Learn. Res., (2016)Hierarchical Conditional Random Fields for Outlier Detection: An Application to Detecting Epileptogenic Cortical Malformations., , , , , , and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 1080-1088. JMLR.org, (2014)Parahippocampal and Entorhinal Resection Extent Predicts Verbal Memory Decline in an Epilepsy Surgery Cohort., , , , , , , , , and 1 other author(s). J. Cognitive Neuroscience, 29 (5): 869-880 (2017)Phonetically irregular word pronunciation and cortical thickness in the adult brain., , , , , , , , , and 4 other author(s). NeuroImage, 51 (4): 1453-1458 (2010)A Non-parametric Approach to Detect Epileptogenic Lesions using Restricted Boltzmann Machines., , , , , , , and . KDD, page 373-382. ACM, (2016)Multi-task Learning with Weak Class Labels: Leveraging iEEG to Detect Cortical Lesions in Cryptogenic Epilepsy., , , , , , and . MLHC, volume 56 of JMLR Workshop and Conference Proceedings, page 115-133. JMLR.org, (2016)