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Jean Honorio

41 papers · 2009–2024 · 8 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (12) πŸƒ Academic Marathon (15) 🐣 Hot Topic Early Bird πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (8) πŸ”¬ Deep Specialist (16) πŸ† Keyword Champion (4) πŸ—ƒοΈ Keyword Collector (169) πŸš€ Conference Pioneer πŸ’Ž Century Club (41) πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter ⚑ Prolific Year (7)

Conferences

AISTATS (13) NIPS (12) ICML (9) JMLR (2) UAI (2) AAAI (1) CVPR (1) EACL (1)

Top co-authors

Asish Ghoshal (8) Kevin Bello (8) Chuyang Ke (5) Adarsh Barik (4) Qifan Song (4) Wenjie Li (3) Tommi Jaakkola (2) Hanbyul Lee (2) Abi Komanduru (2) Dimitris Samaras (2)

Keywords

sample complexity (11) structured prediction (6) structure learning (6) graphical model (4) support recovery (4) sparse regression (4) exact inference (3) federated learning (3) inverse reinforcement learning (3) bayesian network (3) generalization bound (3) graph theory (3) polynomial time (3) exact recovery (3) combinatorial optimization (2) nash equilibrium (2) convex relaxation (2) rademacher complexity (2) information theory (2) community detection (2)

Papers

Personalized Federated X-armed Bandit AISTATS 2024
Support Recovery in Sparse PCA with General Missing Data UAI 2024
Identifying Causal Changes Between Linear Structural Equation Models UAI 2024
Federated X-armed Bandit AAAI 2024
MEDIC: Remove Model Backdoors via Importance Driven Cloning CVPR 2023
Exact Inference in High-order Structured Prediction ICML 2023
Support Recovery in Sparse PCA with Incomplete Data NIPS 2022
A Simple Unified Framework for High Dimensional Bandit Problems ICML 2022
Sparse Mixed Linear Regression with Guarantees: Taming an Intractable Problem with Invex Relaxation ICML 2022
Federated Myopic Community Detection with One-shot Communication AISTATS 2022
A View of Exact Inference in Graphs from the Degree-4 Sum-of-Squares Hierarchy AISTATS 2022
Exact Partitioning of High-order Models with a Novel Convex Tensor Cone Relaxation JMLR 2022
Inverse Reinforcement Learning in a Continuous State Space with Formal Guarantees NIPS 2021
Novel Change of Measure Inequalities with Applications to PAC-Bayesian Bounds and Monte Carlo Estimation AISTATS 2021
Meta Learning for Support Recovery in High-dimensional Precision Matrix Estimation ICML 2021
The Sample Complexity of Meta Sparse Regression AISTATS 2021
Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem NIPS 2021
A Lower Bound for the Sample Complexity of Inverse Reinforcement Learning ICML 2021
Randomized Deep Structured Prediction for Discourse-Level Processing EACL 2021
Minimax Bounds for Structured Prediction Based on Factor Graphs AISTATS 2020
Fairness constraints can help exact inference in structured prediction NIPS 2020
Learning Bayesian Networks with Low Rank Conditional Probability Tables NIPS 2019
On the Correctness and Sample Complexity of Inverse Reinforcement Learning NIPS 2019
Exact inference in structured prediction NIPS 2019
Optimality Implies Kernel Sum Classifiers are Statistically Efficient ICML 2019
On the Statistical Efficiency of Compositional Nonparametric Prediction AISTATS 2018
Learning Sparse Polymatrix Games in Polynomial Time and Sample Complexity AISTATS 2018
Information-theoretic Limits for Community Detection in Network Models NIPS 2018
Computationally and statistically efficient learning of causal Bayes nets using path queries NIPS 2018
Learning latent variable structured prediction models with Gaussian perturbations NIPS 2018
Learning Maximum-A-Posteriori Perturbation Models for Structured Prediction in Polynomial Time ICML 2018
Learning linear structural equation models in polynomial time and sample complexity AISTATS 2018
Learning Identifiable Gaussian Bayesian Networks in Polynomial Time and Sample Complexity NIPS 2017
Learning Graphical Games from Behavioral Data: Sufficient and Necessary Conditions AISTATS 2017
Information-theoretic limits of Bayesian network structure learning AISTATS 2017
Learning the Structure and Parameters of Large-Population Graphical Games from Behavioral Data JMLR 2015
A Unified Framework for Consistency of Regularized Loss Minimizers ICML 2014
Tight Bounds for the Expected Risk of Linear Classifiers and PAC-Bayes Finite-Sample Guarantees AISTATS 2014
Two-Sided Exponential Concentration Bounds for Bayes Error Rate and Shannon Entropy ICML 2013
Variable Selection for Gaussian Graphical Models AISTATS 2012
Sparse and Locally Constant Gaussian Graphical Models NIPS 2009