Honorio, Jean

52 publications

NeurIPS 2025 A Novel General Framework for Sharp Lower Bounds in Succinct Stochastic Bandits Guo Zeng, Jean Honorio

TMLR 2024 A Theoretical Study of the Effects of Adversarial Attacks on Sparse Regression Deepak Maurya, Jean Honorio

AAAI 2024 Federated X-Armed Bandit Wenjie Li, Qifan Song, Jean Honorio, Guang Lin

UAI 2024 Identifying Causal Changes Between Linear Structural Equation Models Vineet Malik, Kevin Bello, Asish Ghoshal, Jean Honorio

TMLR 2024 Meta Learning for Support Recovery of High-Dimensional Ising Models Huiming Xie, Jean Honorio

TMLR 2024 On the Dual Problem of Convexified Convolutional Neural Networks Site Bai, Chuyang Ke, Jean Honorio

AISTATS 2024 Personalized Federated X-Armed Bandit Wenjie Li, Qifan Song, Jean Honorio

TMLR 2024 Provable Guarantees for Sparsity Recovery with Deterministic Missing Data Patterns Chuyang Ke, Jean Honorio

TMLR 2024 Recovering Exact Support in Federated Lasso Without Optimization Adarsh Barik, Jean Honorio

UAI 2024 Support Recovery in Sparse PCA with General Missing Data Hanbyul Lee, Qifan Song, Jean Honorio

ICML 2023 Exact Inference in High-Order Structured Prediction Chuyang Ke, Jean Honorio

CVPR 2023 MEDIC: Remove Model Backdoors via Importance Driven Cloning Qiuling Xu, Guanhong Tao, Jean Honorio, Yingqi Liu, Shengwei An, Guangyu Shen, Siyuan Cheng, Xiangyu Zhang

AISTATS 2022 A View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy Kevin Bello, Chuyang Ke, Jean Honorio

AISTATS 2022 Federated Myopic Community Detection with One-Shot Communication Chuyang Ke, Jean Honorio

ICML 2022 A Simple Unified Framework for High Dimensional Bandit Problems Wenjie Li, Adarsh Barik, Jean Honorio

JMLR 2022 Exact Partitioning of High-Order Models with a Novel Convex Tensor Cone Relaxation Chuyang Ke, Jean Honorio

ICML 2022 Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex Relaxation Adarsh Barik, Jean Honorio

NeurIPS 2022 Support Recovery in Sparse PCA with Incomplete Data Hanbyul Lee, Qifan Song, Jean Honorio

AISTATS 2021 Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation Yuki Ohnishi, Jean Honorio

AISTATS 2021 The Sample Complexity of Meta Sparse Regression Zhanyu Wang, Jean Honorio

ICML 2021 A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning Abi Komanduru, Jean Honorio

NeurIPS 2021 Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem Adarsh Barik, Jean Honorio

NeurIPS 2021 Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees Gregory Dexter, Kevin Bello, Jean Honorio

ICML 2021 Meta Learning for Support Recovery in High-Dimensional Precision Matrix Estimation Qian Zhang, Yilin Zheng, Jean Honorio

NeurIPS 2020 Fairness Constraints Can Help Exact Inference in Structured Prediction Kevin Bello, Jean Honorio

AISTATS 2020 Minimax Bounds for Structured Prediction Based on Factor Graphs Kevin Bello, Asish Ghoshal, Jean Honorio

NeurIPS 2019 Exact Inference in Structured Prediction Kevin Bello, Jean Honorio

NeurIPS 2019 Learning Bayesian Networks with Low Rank Conditional Probability Tables Adarsh Barik, Jean Honorio

NeurIPS 2019 On the Correctness and Sample Complexity of Inverse Reinforcement Learning Abi Komanduru, Jean Honorio

ICML 2019 Optimality Implies Kernel Sum Classifiers Are Statistically Efficient Raphael Meyer, Jean Honorio

NeurIPS 2018 Computationally and Statistically Efficient Learning of Causal Bayes Nets Using Path Queries Kevin Bello, Jean Honorio

NeurIPS 2018 Information-Theoretic Limits for Community Detection in Network Models Chuyang Ke, Jean Honorio

NeurIPS 2018 Learning Latent Variable Structured Prediction Models with Gaussian Perturbations Kevin Bello, Jean Honorio

AISTATS 2018 Learning Linear Structural Equation Models in Polynomial Time and Sample Complexity Asish Ghoshal, Jean Honorio

ICML 2018 Learning Maximum-a-Posteriori Perturbation Models for Structured Prediction in Polynomial Time Asish Ghoshal, Jean Honorio

AISTATS 2018 Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity Asish Ghoshal, Jean Honorio

AISTATS 2018 On the Statistical Efficiency of Compositional Nonparametric Prediction Yixi Xu, Jean Honorio, Xiao Wang

AISTATS 2017 Information-Theoretic Limits of Bayesian Network Structure Learning Asish Ghoshal, Jean Honorio

AISTATS 2017 Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions Asish Ghoshal, Jean Honorio

NeurIPS 2017 Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity Asish Ghoshal, Jean Honorio

UAI 2016 Structured Prediction: From Gaussian Perturbations to Linear-Time Principled Algorithms Jean Honorio, Tommi S. Jaakkola

JMLR 2015 Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data Jean Honorio, Luis Ortiz

ICML 2014 A Unified Framework for Consistency of Regularized Loss Minimizers Jean Honorio, Tommi Jaakkola

AISTATS 2014 Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees Jean Honorio, Tommi S. Jaakkola

UAI 2013 Inverse Covariance Estimation for High-Dimensional Data in Linear Time and Space: Spectral Methods for Riccati and Sparse Models Jean Honorio, Tommi S. Jaakkola

ICML 2013 Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy Jean Honorio, Jaakkola Tommi

ICML 2012 Convergence Rates of Biased Stochastic Optimization for Learning Sparse Ising Models Jean Honorio

CVPRW 2012 Two-Person Interaction Detection Using Body-Pose Features and Multiple Instance Learning Kiwon Yun, Jean Honorio, Debaleena Chattopadhyay, Tamara L. Berg, Dimitris Samaras

AISTATS 2012 Variable Selection for Gaussian Graphical Models Jean Honorio, Dimitris Samaras, Irina Rish, Guillermo Cecchi

UAI 2011 Lipschitz Parametrization of Probabilistic Graphical Models Jean Honorio

ICML 2010 Multi-Task Learning of Gaussian Graphical Models Jean Honorio, Dimitris Samaras

NeurIPS 2009 Sparse and Locally Constant Gaussian Graphical Models Jean Honorio, Dimitris Samaras, Nikos Paragios, Rita Goldstein, Luis E. Ortiz