| 2025 | ICASSP | Partial Inference in Structured Prediction. | Chuyang Ke, Deepak Maurya, Jean Honorio |
| 2025 | ICASSP | Exact Solutions of the Inner Optimization Problem of Adversarial Robustness. | Deepak Maurya, Adarsh Barik, Jean Honorio |
| 2024 | AAAI | Federated X-armed Bandit. | Wenjie Li, Qifan Song, Jean Honorio, Guang Lin |
| 2024 | AISTATS | Personalized Federated X-armed Bandit. | Wenjie Li, Qifan Song, Jean Honorio |
| 2024 | UAI | Support Recovery in Sparse PCA with General Missing Data. | Hanbyul Lee, Qifan Song, Jean Honorio |
| 2024 | UAI | Identifying Causal Changes Between Linear Structural Equation Models. | Vineet Malik, Kevin Bello, Asish Ghoshal, Jean Honorio |
| 2023 | CVPR | MEDIC: Remove Model Backdoors via Importance Driven Cloning. | Qiuling Xu, Guanhong Tao, Jean Honorio, Yingqi Liu, Shengwei An, Guangyu Shen, Siyuan Cheng, Xiangyu Zhang |
| 2023 | ICASSP | Provable Computational and Statistical Guarantees for Efficient Learning of Continuous-Action Graphical Games. | Adarsh Barik, Jean Honorio |
| 2023 | ICML | Exact Inference in High-order Structured Prediction. | Chuyang Ke, Jean Honorio |
| 2022 | AISTATS | A View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy. | Kevin Bello, Chuyang Ke, Jean Honorio |
| 2022 | AISTATS | Federated Myopic Community Detection with One-shot Communication. | Chuyang Ke, Jean Honorio |
| 2022 | ICASSP | Provable Sample Complexity Guarantees For Learning Of Continuous-Action Graphical Games With Nonparametric Utilities. | Adarsh Barik, Jean Honorio |
| 2022 | ICASSP | Information Theoretic Limits For Standard and One-Bit Compressed Sensing with Graph-Structured Sparsity. | Adarsh Barik, Jean Honorio |
| 2022 | ICASSP | Exact Partitioning of High-Order Planted Models with A Tensor Nuclear Norm Constraint. | Chuyang Ke, Jean Honorio |
| 2022 | ICML | Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex Relaxation. | Adarsh Barik, Jean Honorio |
| 2022 | ICML | A Simple Unified Framework for High Dimensional Bandit Problems. | Wenjie Li, Adarsh Barik, Jean Honorio |
| 2022 | ISIT | On the Fundamental Limits of Exact Inference in Structured Prediction. | Hanbyul Lee, Kevin Bello, Jean Honorio |
| 2021 | AISTATS | Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation. | Yuki Ohnishi, Jean Honorio |
| 2021 | AISTATS | The Sample Complexity of Meta Sparse Regression. | Zhanyu Wang, Jean Honorio |
| 2021 | EACL | Randomized Deep Structured Prediction for Discourse-Level Processing. | Manuel Widmoser, Maria Leonor Pacheco, Jean Honorio, Dan Goldwasser |
| 2021 | ICML | A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning. | Abi Komanduru, Jean Honorio |
| 2021 | ICML | Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation. | Qian Zhang, Yilin Zheng, Jean Honorio |
| 2021 | ISIT | Information-Theoretic Bounds for Integral Estimation. | Donald Q. Adams, Adarsh Barik, Jean Honorio |
| 2021 | ISIT | Information-theoretic lower bounds for zero-order stochastic gradient estimation. | Abdulrahman Alabdulkareem, Jean Honorio |
| 2021 | ISIT | First Order Methods take Exponential Time to Converge to Global Minimizers of Non-Convex Functions. | Krishna Reddy Kesari, Jean Honorio |
| 2021 | ISIT | Information Theoretic Limits of Exact Recovery in Sub-hypergraph Models for Community Detection. | Jiajun Liang, Chuyang Ke, Jean Honorio |
| 2021 | ISIT | Regularized Loss Minimizers with Local Data Perturbation: Consistency and Data Irrecoverability. | Zitao Li, Jean Honorio |
| 2021 | ISIT | A Le Cam Type Bound for Adversarial Learning and Applications. | Qiuling Xu, Kevin Bello, Jean Honorio |
| 2020 | AISTATS | Minimax Bounds for Structured Prediction Based on Factor Graphs. | Kevin Bello, Asish Ghoshal, Jean Honorio |
| 2020 | ISIT | Provable Efficient Skeleton Learning of Encodable Discrete Bayes Nets in Poly-Time and Sample Complexity. | Adarsh Bank, Jean Honorio |
| 2019 | ICML | Optimality Implies Kernel Sum Classifiers are Statistically Efficient. | Raphael A. Meyer, Jean Honorio |
| 2019 | ISIT | Cost-Aware Learning for Improved Identifiability with Multiple Experiments. | Longyun Guo, Jean Honorio, John Morgan |
| 2018 | AISTATS | Learning linear structural equation models in polynomial time and sample complexity. | Asish Ghoshal, Jean Honorio |
| 2018 | AISTATS | Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity. | Asish Ghoshal, Jean Honorio |
| 2018 | AISTATS | On the Statistical Efficiency of Compositional Nonparametric Prediction. | Yixi Xu, Jean Honorio, Xiao Wang |
| 2018 | ICML | Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time. | Asish Ghoshal, Jean Honorio |
| 2017 | AISTATS | Information-theoretic limits of Bayesian network structure learning. | Asish Ghoshal, Jean Honorio |
| 2017 | AISTATS | Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions. | Asish Ghoshal, Jean Honorio |
| 2017 | ISIT | Information theoretic limits for linear prediction with graph-structured sparsity. | Adarsh Barik, Jean Honorio, Mohit Tawarmalani |
| 2016 | ISIT | Information-theoretic lower bounds for recovery of diffusion network structures. | Keehwan Park, Jean Honorio |
| 2016 | UAI | Structured Prediction: From Gaussian Perturbations to Linear-Time Principled Algorithms. | Jean Honorio, Tommi S. Jaakkola |
| 2014 | AISTATS | Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees. | Jean Honorio, Tommi S. Jaakkola |
| 2014 | ICML | A Unified Framework for Consistency of Regularized Loss Minimizers. | Jean Honorio, Tommi S. Jaakkola |
| 2013 | ICML | Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy. | Jean Honorio, Tommi S. Jaakkola |
| 2013 | MICCAI | fMRI Analysis with Sparse Weisfeiler-Lehman Graph Statistics. | Katerina Gkirtzou, Jean Honorio, Dimitris Samaras, Rita Z. Goldstein, Matthew B. Blaschko |
| 2013 | UAI | Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models. | Jean Honorio, Tommi S. Jaakkola |
| 2012 | CVPR | Two-person interaction detection using body-pose features and multiple instance learning. | Kiwon Yun, Jean Honorio, Debaleena Chattopadhyay, Tamara L. Berg, Dimitris Samaras |
| 2012 | ICML | Convergence Rates of Biased Stochastic Optimization for Learning Sparse Ising Models. | Jean Honorio |
| 2011 | UAI | Lipschitz Parametrization of Probabilistic Graphical Models. | Jean Honorio |
| 2010 | ICML | Multi-Task Learning of Gaussian Graphical Models. | Jean Honorio, Dimitris Samaras |
| 2008 | MICCAI | Task-Specific Functional Brain Geometry from Model Maps. | Georg Langs, Dimitris Samaras, Nikos Paragios, Jean Honorio, Nelly Alia-Klein, Dardo Tomasi, Nora D. Volkow, Rita Z. Goldstein |