Jean Honorio
41 papers · 2009–2024 · 8 conferences · across top CS/AI conferences
Achievements
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π§ Keyword Pioneer π Renaissance Researcher (5) π Interdisciplinary Bridge πΊοΈ Taxonomy Completionist (13) π Conference Polyglot (8)
π§
Keyword Pioneer
π
Renaissance Researcher
(5)
π
Conference Polyglot
(8)
π¬
Deep Specialist
(16)
π
Keyword Champion
(4)
ποΈ
Keyword Collector
(169)
π
Conference Pioneer
π
Century Club
(41)
π₯
Unstoppable
(8)
π
Trend Setter
β‘
Prolific Year
(7)
Conferences
AISTATS (13)
NIPS (12)
ICML (9)
JMLR (2)
UAI (2)
AAAI (1)
CVPR (1)
EACL (1)
Top co-authors
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