Jean Honorio
Assistant Professor in the Computer Science Department at Purdue.
Assistant Professor in the Statistics Department (by courtesy) at Purdue.
Lawson Building 2142-J, West Lafayette, IN 47907, phone: 765-496-6757
e-mail: jhonorio at purdue.edu
Through a unifying framework, with the power of convex relaxations and primal-dual certificates, my research group produces novel algorithms for learning and inference in combinatorial problems. Our aim is to generate correct, computationally efficient and statistically efficient algorithms for high dimensional machine learning problems. Our results include algorithms for learning Bayesian networks, graphical games, learning and inference in structured prediction, and community detection. [vita]
Prior to joining Purdue, I was a postdoctoral associate at MIT CSAIL, working with Tommi Jaakkola.
My Erdös number is 3: Jean Honorio → Tommi Jaakkola → Noga Alon → Paul Erdös.
People (my students* and student coauthors)
Current: Adarsh Barik*, Kevin Bello*, Chuyang Ke*, Abi Komanduru, Zitao Li, Yuki Ohnishi, Zhanyu Wang, Qiuling Xu, Xiaochen Yang, Qian Zhang
Past: Abdulrahman Alabdulkareem, Asish Ghoshal*, Longyun Guo, Krishna Kesari, Yu-Jun Li, Meimei Liu, Raphael Meyer, Keehwan Park, Zhaosen Wang, Yixi Xu, Yilin Zheng
Here is a note for prospective students that are considering working with me.
News
9/25/20. Kevin got 1 paper accepted at NeurIPS.
3/31/20. Adarsh got 1 paper accepted at ISIT.
1/6/20. Kevin got 1 paper accepted at AISTATS.
9/3/19. Kevin got 1 paper, Adarsh got 1 paper, Abi got 1 paper accepted at NeurIPS.
8/2/19. Zhaosen got 1 paper accepted at Allerton.
4/21/19. Raphael got 1 paper accepted at ICML.
3/31/19. Longyun got 1 paper accepted at ISIT.
9/5/18. Kevin got 2 papers, Chuyang got 1 paper accepted at NeurIPS.
8/3/18. Meimei got 1 paper accepted at Allerton.
5/11/18. Asish got 1 paper accepted at ICML.
12/22/17. Asish got 2 papers, Yixi got 1 paper accepted at AISTATS.
9/4/17. Asish got 1 paper accepted at NeurIPS.
8/17/17. NSF RI:Small grant awarded to do research on structured prediction.
Teaching
CS 37300: Data Mining and Machine Learning: Spring 2021, also offered on Fall 2019 and Fall 2018
CS 57800: Statistical Machine Learning: Fall 2020, also offered on Spring 2020, Spring 2018, Fall 2017 and Fall 2016
CS 59000-HLT / STAT 59800-HLT: Hands-On Learning Theory: Fall 2020, also offered on Fall 2019, Fall 2018, Fall 2017, Fall 2016 and Fall 2015
CS 69000-SML: Statistical Machine Learning II: Spring 2019, also offered on Spring 2017
CS 52000: Computational Methods In Optimization: Spring 2016
Publications (by year / by topic)
Manuscripts under submission
Information Theoretic Sample Complexity Lower Bound for Feed-Forward Fully-Connected Deep Networks. (Preprint)
Yang X., Honorio J.
(Under submission.)
Fundamental Limits of Adversarial Learning. (Preprint)
Bello K., Xu Q., Honorio J.
(Under submission.)
Support Union Recovery in Meta Learning of Gaussian Graphical Models. (Preprint)
Zhang Q., Zheng Y., Honorio J.
(Under submission.)
Exact Support Recovery in Federated Regression with One-shot Communication. (Preprint)
Barik A., Honorio J.
(Under submission.)
Exact Partitioning of High-order Planted Models with a Tensor Nuclear Norm Constraint. (Preprint)
Ke C., Honorio J.
(Under submission.)
Provable Sample Complexity Guarantees for Learning of Continuous-Action Graphical Games with Nonparametric Utilities. (Preprint)
Barik A., Honorio J.
(Under submission.)
Information-Theoretic Lower Bounds for Zero-Order Stochastic Gradient Estimation. (Preprint)
Alabdulkareem A., Honorio J.
(Under submission.)
First Order Methods take Exponential Time to Converge to Global Minimizers of Non-Convex Functions. (Preprint)
Kesari K., Honorio J.
(Under submission.)
Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation. (Preprint)
Ohnishi Y., Honorio J.
(Under submission.)
The Sample Complexity of Meta Sparse Regression. (Preprint)
Wang Z., Honorio J.
(Under submission.)
Provable Computational and Statistical Guarantees for Efficient Learning of Continuous-Action Graphical Games. (Preprint)
Barik A., Honorio J.
(Under submission.)
Exact Partitioning of High-order Models with a Novel Convex Tensor Cone Relaxation. (Preprint)
Ke C., Honorio J.
(Under submission.)
Direct Estimation of Difference Between Structural Equation Models in High Dimensions. (Preprint)
Ghoshal A., Honorio J.
(Under submission.)
Exact Inference with Latent Variables in an Arbitrary Domain. (Preprint)
Ke C., Honorio J.
(Under submission.)
Information Theoretic Limits for Standard and One-Bit Compressed Sensing with Graph-Structured Sparsity. (Preprint)
Barik A., Honorio J.
(Under submission.)
Regularized Loss Minimizers with Local Data Perturbation: Consistency and Data Irrecoverability. (Preprint)
Li Z., Honorio J.
(Under submission.)
The Error Probability of Random Fourier Features is Dimensionality Independent. (Preprint)
Li Y., Honorio J.
(Under submission.)
2021
Randomized Deep Structured Prediction for Discourse-Level Processing.
Widmoser M., Pacheco M., Honorio J., Goldwasser D.
European Association for Computational Linguistics Conference. Ukraine.
PrivSyn: Differentially Private Data Synthesis.
Zhang Z., Wang T., Honorio J., Li N., Backes M., He S., Chen J. Zhang Y.
USENIX Security Symposium. Vancouver/Canada.
2020
Fairness Constraints can Help Exact Inference in Structured Prediction.
Bello K., Honorio J.
Neural Information Processing Systems. Vancouver/Canada.
Provable Efficient Skeleton Learning of Encodable Discrete Bayes Nets in Poly-Time and Sample Complexity.
Barik A., Honorio J.
IEEE International Symposium on Information Theory. California.
Minimax Bounds for Structured Prediction Based on Factor Graphs.
Bello K., Ghoshal A., Honorio J.
Artificial Intelligence and Statistics. Palermo/Italy.
2019
Exact Inference in Structured Prediction.
Bello K., Honorio J.
Neural Information Processing Systems. Vancouver/Canada.
Learning Bayesian Networks with Low Rank Conditional Probability Tables.
Barik A., Honorio J.
Neural Information Processing Systems. Vancouver/Canada.
On the Correctness and Sample Complexity of Inverse Reinforcement Learning.
Komanduru A., Honorio J.
Neural Information Processing Systems. Vancouver/Canada.
Reconstructing a Bounded-Degree Directed Tree Using Path Queries.
Wang Z., Honorio J.
IEEE Allerton Conference on Communication, Control and Computing. Illinois.
Optimality Implies Kernel Sum Classifiers are Statistically Efficient.
Meyer R., Honorio J.
International Conference on Machine Learning. California.
Cost-Aware Learning for Improved Identifiability with Multiple Experiments.
Guo L., Honorio J., Morgan J.
IEEE International Symposium on Information Theory. Paris/France.
2018
Learning Latent Variable Structured Prediction Models with Gaussian Perturbations.
Bello K., Honorio J.
Neural Information Processing Systems. Montreal/Canada.
Computationally and Statistically Efficient Learning of Causal Bayes Nets Using Path Queries.
Bello K., Honorio J.
Neural Information Processing Systems. Montreal/Canada.
Information-Theoretic Limits for Community Detection in Network Models.
Ke C., Honorio J.
Neural Information Processing Systems. Montreal/Canada.
Statistically and Computationally Efficient Variance Estimator for Kernel Ridge Regression.
Liu M., Honorio J., Cheng G.
IEEE Allerton Conference on Communication, Control and Computing. Illinois.
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time.
Ghoshal A., Honorio J.
International Conference on Machine Learning. Stockholm/Sweden.
Learning Linear Structural Equation Models in Polynomial Time and Sample Complexity.
Ghoshal A., Honorio J.
Artificial Intelligence and Statistics. Canary Islands/Spain.
Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity.
Ghoshal A., Honorio J.
Artificial Intelligence and Statistics. Canary Islands/Spain.
On the Statistical Efficiency of Compositional Nonparametric Prediction.
Xu Y., Honorio J., Wang X.
Artificial Intelligence and Statistics. Canary Islands/Spain.
2017
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity.
Ghoshal A., Honorio J.
Neural Information Processing Systems. California.
On the Sample Complexity of Learning Graphical Games.
Honorio J.
IEEE Allerton Conference on Communication, Control and Computing. Illinois.
Information Theoretic Limits for Linear Prediction with Graph-Structured Sparsity.
Barik A., Honorio J., Tawarmalani M.
IEEE International Symposium on Information Theory. Aachen/Germany.
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions.
Ghoshal A., Honorio J.
Artificial Intelligence and Statistics. Florida.
Information-Theoretic Limits of Bayesian Network Structure Learning.
Ghoshal A., Honorio J.
Artificial Intelligence and Statistics. Florida.
2016
From Behavior to Sparse Graphical Games: Efficient Recovery of Equilibria.
Ghoshal A., Honorio J.
IEEE Allerton Conference on Communication, Control and Computing. Illinois.
Structured Prediction: From Gaussian Perturbations to Linear-Time Principled Algorithms.
Honorio J., Jaakkola T.
Uncertainty in Artificial Intelligence. New York.
Information-Theoretic Lower Bounds for Recovery of Diffusion Network Structures.
Park K., Honorio J.
IEEE International Symposium on Information Theory. Barcelona/Spain.
Variable Selection in Gaussian Markov Random Fields.
Honorio J., Samaras D., Rish I., Cecchi G.
Invited book chapter in Log-Linear Models, Extensions and Applications.
Edited by Aravkin A., Deng L., Heigold G., Jebara T., Kanevski D., Wright S. (to be published on December, 2016)
2015
Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data.
Honorio J., Ortiz L.
Journal of Machine Learning Research, 16(Jun): pp. 1157-1210 [code]
On the Statistical Efficiency of L1,p Multi-Task Learning of Gaussian Graphical Models.
Honorio J., Jaakkola T., Samaras D.
Technical report. [code]
Predictive Sparse Modeling of fMRI Data for Improved Classification, Regression, and Visualization Using the k-Support Norm.
Belilovsky E., Gkirtzou K., Misyrlis M., Konova A., Honorio J., Alia-Klein N., Goldstein R., Samaras D., Blaschko M.
Computerized Medical Imaging and Graphics, 46(1): pp. 40-46
Integration of PCA with a Novel Machine Learning Method for Reparameterization and Assisted History Matching Geologically Complex Reservoirs.
Honorio J., Chen C., Gao G., Du K., Jaakkola T.
Society of Petroleum Engineers: 91th Annual Technical Conference and Exhibition. Houston.
2014
A Unified Framework for Consistency of Regularized Loss Minimizers.
Honorio J., Jaakkola T.
International Conference on Machine Learning. Beijing/China.
Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees.
Honorio J., Jaakkola T.
Artificial Intelligence and Statistics. Reykjavik/Iceland.
Classification on Brain Functional Magnetic Resonance Imaging: Dimensionality, Sample Size, Subject Variability and Noise.
Honorio J.
Invited book chapter in Frontiers of Medical Imaging.
Edited by Chen C., World Scientific Publishing Company.
Improving Interpretability of Graphical Models in fMRI Analysis via Variable-Selection.
Honorio J., Samaras D., Rish I., Cecchi G.
Organization for Human Brain Mapping, Anual Meeting. Hamburg/Germany.
Predicting Cross-task Behavioral Variables from
fMRI Data Using the k-Support Norm. (Best paper award)
Misyrlis M., Konova A., Blaschko M., Honorio J., Alia-Klein N., Goldstein R., Samaras D.
Medical Image Computing and Computer-Assisted Intervention. Workshop on Sparsity Techniques in Medical Imaging. Boston.
Methylphenidate Enhances Executive Function and Optimizes Prefrontal Function in Both Health and Cocaine Addiction.
Moeller S., Honorio J., Tomasi D., Parvaz M., Woicik P., Volkow N., Goldstein R.
Cerebral Cortex, 24(3): pp. 643-653
Integration of Principal Component Analysis and Streamline Information for the History Matching of Channelized Reservoirs.
Chen C., Gao G., Honorio J., Gelderblom P., Jimenez E., Jaakkola T.
Society of Petroleum Engineers: 90th Annual Technical Conference and Exhibition. Amsterdam/The Netherlands.
2013
Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models.
Honorio J., Jaakkola T.
Uncertainty in Artificial Intelligence. Washington. [code]
Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy.
Honorio J., Jaakkola T.
International Conference on Machine Learning. Atlanta.
fMRI Analysis of Cocaine Addiction Using k-Support Sparsity.
Gkirtzou K., Honorio J., Samaras D., Goldstein R., Blaschko M.
IEEE International Symposium on Biomedical Imaging. California. [code]
fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics.
Gkirtzou K., Honorio J., Samaras D., Goldstein R., Blaschko M.
Medical Image Computing and Computer-Assisted Intervention, Workshop on Machine Learning in Medical Imaging. Nagoya/Japan. [code]
2012
Convergence Rates of Biased Stochastic Optimization for Learning Sparse Ising Models.
Honorio J.
International Conference on Machine Learning. Edinburgh/Scotland. [code]
Variable Selection for Gaussian Graphical Models.
Honorio J., Samaras D., Rish I., Cecchi G.
Artificial Intelligence and Statistics. Canary Islands/Spain. [code]
Can a Single Brain Region Predict a Disorder?
Honorio J., Tomasi D., Goldstein R., Leung H.C., Samaras D.
IEEE Transactions on Medical Imaging, 31(11): pp. 2062-2072 [code]
Two-person Interaction Detection Using Body-Pose Features and Multiple Instance Learning.
Yun K., Honorio J., Chattopadhyay D., Berg T., Samaras D.
IEEE Computer Vision and Pattern Recognition, Workshop on Human Activity Understanding from 3D Data. Rhode Island. [data]
Dopaminergic Involvement During Mental Fatigue in Health and Cocaine Addiction.
Moeller S., Tomasi D., Honorio J., Volkow N., Goldstein R.
Translational Psychiatry, 2: e176
Enhanced Midbrain Response at 6-month Follow-up in Cocaine Addiction, Association with Reduced Drug-related Choice.
Moeller S., Tomasi D., Woicik P., Maloney T., Alia-Klein N., Honorio J., Telang F., Wang G., Wang R., Sinha R., Carise D., Astone-Twerell J., Bolger J., Volkow N., Goldstein R.
Addiction Biology, 17(6): pp. 1013-25
2011
Lipschitz Parametrization of Probabilistic Graphical Models.
Honorio J.
Uncertainty in Artificial Intelligence. Barcelona/Spain.
Digital Analysis and Visualization of Swimming Motion.
Kirmizibayrak C., Honorio J., Jiang X., Mark R., Hahn J.
The International Journal of Virtual Reality, 10(3): pp. 9-16
Digital Analysis and Visualization of Swimming Motion.
Kirmizibayrak C., Honorio J., Jiang X., Mark R., Hahn J.
Conference on Computer Animation and Social Agents, Simulation of Sports Motion Workshop. Chengdu/China.
Dopaminergic contribution to endogenous motivation during cognitive control breakdown.
Moeller S., Tomasi D., Honorio J., Volkow N., Goldstein R.
Society for Neuroscience. Washington DC.
2010
Multi-Task Learning of Gaussian Graphical Models.
Honorio J., Samaras D.
International Conference on Machine Learning. Haifa/Israel. [code]
Simple Fully Automated Group Classification on Brain fMRI.
Honorio J., Samaras D., Tomasi D., Goldstein R.
IEEE International Symposium on Biomedical Imaging. Rotterdam/The Netherlands. [code]
Disrupted Functional Connectivity with Dopaminergic Midbrain in Cocaine Abusers.
Tomasi D., Volkow N., Wang R., Honorio J., Maloney T., Alia-Klein N., Woicik P., Telang F., Goldstein R.
Public Library of Science, PLoS ONE, 5(5): e10815
Oral Methylphenidate Normalizes Cingulate Activity in Cocaine Addiction During a Salient Cognitive Task.
Goldstein R., Woicik P., Maloney T., Tomasi D., Alia-Klein N., Shan J., Honorio J., Samaras D., Ruiliang W., Telang F., Wang G., Volkow N.
Proceedings of the National Academy of Sciences, 107(38): pp. 16667-72
2009
Sparse and Locally Constant Gaussian Graphical Models.
Honorio J., Ortiz L., Samaras D., Paragios N., Goldstein R.
Neural Information Processing Systems. Vancouver/Canada. [code]
Learning Brain fMRI Structure Through Sparseness and Local Constancy.
Honorio J., Ortiz L., Samaras D., Goldstein R.
Neural Information Processing Systems, Workshop on Connectivity Inference in NeuroImaging. Vancouver/Canada.
A Functional Geometry of fMRI BOLD Signal Interactions.
Langs G., Samaras D., Paragios N., Honorio J., Golland P., Alia-Klein N., Tomasi D., Volkow N., Goldstein R.
Neural Information Processing Systems, Workshop on Connectivity Inference in NeuroImaging. Vancouver/Canada.
Dopaminergic Response to Drug Words in Cocaine Addiction.
Goldstein R., Tomasi D., Alia-Klein N., Honorio J., Maloney T., Woicik P., Wang R., Telang F., Volkow N.
Journal of Neuroscience, 29(18): pp. 6001-6
Anterior Cingulate Cortex Hypoactivations to an Emotionally Salient Task in Cocaine Addiction.
Goldstein R., Alia-Klein N., Tomasi D., Honorio J., Maloney T., Woicik P., Wang R., Telang F., Volkow N.
Proceedings of the National Academy of Sciences, 106(23): pp. 9453-8
2008
Task-Specific Functional Brain Geometry from Model Maps.
Langs G., Samaras D., Paragios N., Honorio J., Alia-Klein N., Tomasi D., Volkow N., Goldstein R.
Medical Image Computing and Computer-Assisted Intervention. New York.