Daniel Palomar
7 papers · 2019–2023 · 2 venues · across top CS/AI venues
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Achievements
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🌍
Conference Polyglot · Bronze
🌉
Interdisciplinary Bridge · Bronze
🗺️
Taxonomy Completionist
(14)
🐣
Hot Topic Early Bird
🔥
Unstoppable · Bronze
Venues
Top co-authors
Research topics
Keywords
gaussian graphical model
(3)
precision matrix estimation
(3)
graph learning
(2)
graph laplacian
(2)
precision matrix
(1)
sparse inverse covariance
(1)
maximum likelihood estimation
(1)
adaptive regularization
(1)
graphical lasso
(1)
projected gradient descent
(1)
gaussian markov random field
(1)
graph structure learning
(1)
markov random field
(1)
bipartite graph
(1)
graphical model
(1)
minimax lower bound
(1)
alternating direction method of multiplier
(1)
spectral method
(1)
heavy-tailed distribution
(1)
laplacian constraint
(1)
Papers
Fast Projected Newton-like Method for Precision Matrix Estimation under Total Positivity
NeurIPS 2023
Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition
NeurIPS 2023
Learning Bipartite Graphs: Heavy Tails and Multiple Components
NeurIPS 2022
Graphical Models in Heavy-Tailed Markets
NeurIPS 2021
Minimax Estimation of Laplacian Constrained Precision Matrices
AISTATS 2021
Nonconvex Sparse Graph Learning under Laplacian Constrained Graphical Model
NeurIPS 2020
Structured Graph Learning Via Laplacian Spectral Constraints
NeurIPS 2019