George Michailidis
17 papers · 2010–2026 · 4 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (31) π Academic Marathon Β· Full π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Gold π£ Hot Topic Early Bird
π
Keyword Champion
ποΈ
Keyword Collector
(101)
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Trend Setter
π
Century Club Β· Bronze
π₯
Unstoppable Β· Bronze
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Renaissance Researcher
(7)
Venues
Top co-authors
Research topics
Machine Learning
(16)
Core Methods
(14)
Mathematics & Optimization
(12)
Mathematics
(8)
Optimization & Theory
(8)
Artificial Intelligence
(6)
Bayesian & Probabilistic Β· Machine Learning
(5)
Optimization
(5)
Data Science & Analytics
(4)
Core AI
(4)
Methods
(4)
Learning Types
(3)
Healthcare & Medicine
(2)
Bayesian & Probabilistic Β· Artificial Intelligence
(2)
Research
(2)
Keywords
vector autoregression
(3)
high-dimensional estimation
(3)
causal inference
(3)
gaussian graphical model
(3)
stochastic block model
(2)
graphical model
(2)
high-dimensional data
(2)
change point detection
(2)
group-penalized regression
(2)
maximum likelihood estimation
(2)
time series analysis
(2)
neighborhood selection
(2)
high-dimensional statistics
(2)
network model
(2)
group lasso
(2)
community detection
(2)
high-dimensional regression
(2)
network analysis
(2)
granger causality
(2)
alternating direction method
(2)
Papers
Model-Agnostic Online Certificate-Driven Calibration for Time Series Forecasting Under Distribution Shift
UAI 2026
Axiomatic effect propagation in structural causal models
JMLR 2024
Logistic Regression Under Network Dependence
JMLR 2024
Bayesian Spiked Laplacian Graphs
JMLR 2023
Inference on the Change Point under a High Dimensional Covariance Shift
JMLR 2023
Low Tree-Rank Bayesian Vector Autoregression Models
JMLR 2023
Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models
JMLR 2022
Regularized and Smooth Double Core Tensor Factorization for Heterogeneous Data
JMLR 2022
Flow-based Attribution in Graphical Models: A Recursive Shapley Approach
ICML 2021
Change Point Estimation in a Dynamic Stochastic Block Model
JMLR 2020
Regularized Estimation of High-dimensional Factor-Augmented Vector Autoregressive (FAVAR) Models
JMLR 2020
Estimation of Graphical Models through Structured Norm Minimization
JMLR 2018
Regularized Estimation and Testing for High-Dimensional Multi-Block Vector-Autoregressive Models
JMLR 2017
Joint Structural Estimation of Multiple Graphical Models
JMLR 2016
Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models
JMLR 2016
Network Granger Causality with Inherent Grouping Structure
JMLR 2015
Penalized Principal Component Regression on Graphs for Analysis of Subnetworks
NeurIPS 2010