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Sang-Yun Oh
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Sang-Yun Oh12 visible / 12 total nodes / 21 links

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Co-authorshipCo-authorshipCo-authorshipAuthorshipAuthorshipWorks onWorks onWorks onAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipTopic signalTopic signalTopic signalTopic signalTopic signalAuthorshipSang-Yun OhASang-Yun OhResearcherRelaxed Sparsest-Permutation Formulation for Causal Discovery at ScaleWRelaxed Sparsest-Permut...preprint / 2026Sunmin OhASunmin OhResearcherGunwoong ParkAGunwoong ParkResearcherOptimization Methods for Sparse Pseudo-Likelihood Graphical Model SelectionWOptimization Methods fo...preprint / 2014Towards a sparse, scalable, and stably positive definite (inverse) covariance estimatorWTowards a sparse, scala...preprint / 2016Machine LearningTMachine Learning49008 worksPartial Separability and Functional Graphical Models for Multivariate Gaussian ProcessesWPartial Separability an...preprint / 2022A convex pseudo-likelihood framework for high dimensional partial correlation estimation with convergence guaranteesWA convex pseudo-likelih...preprint / 2014Family-wise error rate control in Gaussian graphical model selection via Distributionally Robust OptimizationWFamily-wise error rate ...preprint / 2022Generalized Pseudolikelihood Methods for Inverse Covariance EstimationWGeneralized Pseudolikel...preprint / 2016Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance EstimationWCommunication-Avoiding ...preprint / 2018
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Sang-Yun Oh

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PaperRelaxed Sparsest-Permutation Formulation for Causal Discovery at ScaleAuthorship / preprint / 2026PersonSunmin OhCo-authorship / ResearcherPersonGunwoong ParkCo-authorship / ResearcherPaperOptimization Methods for Sparse Pseudo-Likelihood Graphical Model SelectionAuthorship / preprint / 2014PaperTowards a sparse, scalable, and stably positive definite (inverse) covariance estimatorAuthorship / preprint / 2016TopicMachine LearningWorks on / 49008 worksPaperPartial Separability and Functional Graphical Models for Multivariate Gaussian ProcessesAuthorship / preprint / 2022PaperA convex pseudo-likelihood framework for high dimensional partial correlation estimation with convergence guaranteesAuthorship / preprint / 2014

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