Jean Honorio
Jean Honorio
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Cited by
Cited by
Two-person interaction detection using body-pose features and multiple instance learning
K Yun, J Honorio, D Chattopadhyay, TL Berg, D Samaras
2012 IEEE Computer Society Conference on Computer Vision and Pattern …, 2012
Anterior cingulate cortex hypoactivations to an emotionally salient task in cocaine addiction
RZ Goldstein, N Alia-Klein, D Tomasi, J Honorio, T Maloney, PA Woicik, ...
Proceedings of the National Academy of Sciences 106 (23), 9453-9458, 2009
Oral methylphenidate normalizes cingulate activity in cocaine addiction during a salient cognitive task
RZ Goldstein, PA Woicik, T Maloney, D Tomasi, N Alia-Klein, J Shan, ...
Proceedings of the National Academy of Sciences 107 (38), 16667-16672, 2010
Disrupted functional connectivity with dopaminergic midbrain in cocaine abusers
D Tomasi, ND Volkow, R Wang, J Honorio, T Maloney, N Alia-Klein, ...
PloS one 5 (5), e10815, 2010
Dopaminergic response to drug words in cocaine addiction
RZ Goldstein, D Tomasi, N Alia-Klein, J Honorio, T Maloney, PA Woicik, ...
The Journal of Neuroscience 29 (18), 6001-6006, 2009
Multi-task learning of Gaussian graphical models
J Honorio, D Samaras
2010 International Conference on Machine Learning (ICML), 2010
Methylphenidate enhances executive function and optimizes prefrontal function in both health and cocaine addiction
SJ Moeller, J Honorio, D Tomasi, MA Parvaz, PA Woicik, ND Volkow, ...
Cerebral cortex 24 (3), 643-653, 2014
Dopaminergic involvement during mental fatigue in health and cocaine addiction
SJ Moeller, D Tomasi, J Honorio, ND Volkow, RZ Goldstein
Translational psychiatry 2 (10), e176-e176, 2012
Enhanced midbrain response at 6‐month follow‐up in cocaine addiction, association with reduced drug‐related choice
SJ Moeller, D Tomasi, PA Woicik, T Maloney, N Alia‐Klein, J Honorio, ...
Addiction biology 17 (6), 1013-1025, 2012
Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data
J Honorio, L Ortiz
Journal of Machine Learning Research. (accepted, pending publication.), 2012
Sparse and locally constant Gaussian graphical models
J Honorio, D Samaras, N Paragios, R Goldstein, LE Ortiz
Advances in Neural Information Processing Systems 22, 745-753, 2009
Learning linear structural equation models in polynomial time and sample complexity
A Ghoshal, J Honorio
2018 Artificial Intelligence and Statistics (AISTATS), 2018
Learning identifiable gaussian bayesian networks in polynomial time and sample complexity
A Ghoshal, J Honorio
arXiv preprint arXiv:1703.01196, 2017
Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees
J Honorio, T Jaakkola
Proceedings of the Seventeenth International Conference on Artificial …, 2014
Can a single brain region predict a disorder?
J Honorio, D Tomasi, RZ Goldstein, HC Leung, D Samaras
IEEE Transactions on Medical Imaging 31 (11), 2062-2072, 2012
Integration of principal-component-analysis and streamline information for the history matching of channelized reservoirs
C Chen, G Gao, J Honorio, P Gelderblom, E Jimenez, T Jaakkola
SPE Annual Technical Conference and Exhibition, 2014
Variable selection for gaussian graphical models
J Honorio, D Samaras, I Rish, G Cecchi
Artificial Intelligence and Statistics, 538-546, 2012
Information-theoretic limits of Bayesian network structure learning
A Ghoshal, J Honorio
2017 Artificial Intelligence and Statistics (AISTATS), 2017
Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models
J Honorio, TS Jaakkola
Uncertainty in Artificial Intelligence 2013, 2013
Predictive sparse modeling of fMRI data for improved classification, regression, and visualization using the k-support norm
E Belilovsky, K Gkirtzou, M Misyrlis, AB Konova, J Honorio, N Alia-Klein, ...
Computerized Medical Imaging and Graphics 46, 40-46, 2015
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