← Authors

Seyoung Kim

12 papers · 2006–2023 · 4 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (17) πŸ—ΊοΈ Taxonomy Completionist (17) 🌍 Conference Polyglot (4) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (4) πŸ† Keyword Champion 🌱 Topic Pioneer πŸ’Ž Century Club (12) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (84) πŸš€ Conference Pioneer

Conferences

AISTATS (5) NIPS (4) JMLR (2) UAI (1)

Top co-authors

Jun Ho Yoon (3) Calvin McCarter (2) Padhraic Smyth (2) Daniel P. Jeong (2) Xiaolin Yang (1) Gi Bum Kim (1) Kyung-ah Sohn (1) Jing Xiang (1) Eric P. Xing (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) multitask learning (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 NIPS 2014
A* Lasso for Learning a Sparse Bayesian Network Structure for Continuous Variables NIPS 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 NIPS 2009
Hierarchical Dirichlet Processes with Random Effects NIPS 2006
Segmental Hidden Markov Models with Random Effects for Waveform Modeling JMLR 2006