Seyoung Kim
12 papers · 2006–2023 · 4 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (38) π Academic Marathon Β· Full π Conference Polyglot Β· Bronze π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Keyword Trendsetter Combo
(5)
π§
Keyword Pioneer
π
Keyword Champion
π
Trend Setter
π
Conference Pioneer
π
Renaissance Researcher
(6)
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Century Club Β· Bronze
ποΈ
Keyword Collector
(89)
Venues
Top co-authors
Research topics
Machine Learning
(12)
Core Methods
(12)
Optimization & Theory
(10)
Artificial Intelligence
(7)
Mathematics & Optimization
(6)
Bayesian & Probabilistic Β· Artificial Intelligence
(6)
Bayesian & Probabilistic Β· Machine Learning
(6)
Optimization
(4)
Healthcare & Medicine
(3)
Research
(3)
Interdisciplinary
(2)
Learning Types
(2)
Science
(2)
Computer Science
(1)
Deep Learning
(1)
Keywords
sparse regression
(4)
gaussian graphical model
(4)
structure learning
(3)
graphical model
(3)
sparse estimation
(2)
inverse covariance
(2)
matrix-variate gaussian
(2)
convex optimization
(2)
random effect
(2)
newton method
(2)
variational inference
(1)
sparse learning
(1)
gaussian processes
(1)
logistic regression
(1)
probabilistic modeling
(1)
semi-supervised learning
(1)
hierarchical modeling
(1)
markov chain monte carlo
(1)
hierarchical dirichlet processes
(1)
bayesian nonparametrics
(1)
Papers
Factorial SDE for Multi-Output Gaussian Process Regression
AISTATS 2023
Doubly Mixed-Effects Gaussian Process Regression
AISTATS 2022
EiGLasso for Scalable Sparse Kronecker-Sum Inverse Covariance Estimation
JMLR 2022
EiGLasso: Scalable Estimation of Cartesian Product of Sparse Inverse Covariance Matrices
UAI 2020
Multi-level Gaussian Graphical Models Conditional on Covariates
AISTATS 2020
Large-Scale Optimization Algorithms for Sparse Conditional Gaussian Graphical Models
AISTATS 2016
On Sparse Gaussian Chain Graph Models
NeurIPS 2014
A* Lasso for Learning a Sparse Bayesian Network Structure for Continuous Variables
NeurIPS 2013
Joint Estimation of Structured Sparsity and Output Structure in Multiple-Output Regression via Inverse-Covariance Regularization
AISTATS 2012
Heterogeneous multitask learning with joint sparsity constraints
NeurIPS 2009
Hierarchical Dirichlet Processes with Random Effects
NeurIPS 2006
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
JMLR 2006