Sang-Yun Oh - RankMe

13 papers A 4C 1Journal 7Unranked 1

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Learning Massive-scale Partial Correlation Networks in Clinical Multi-omics Studies with HP-ACCORD. CoRR Sungdong Lee, Joshua Bang, Youngrae Kim, Hyungwon Choi, Sang-Yun Oh, Joong-Ho Won
2023	J	`jnl`	Learning Gaussian graphical models with latent confounders. J. Multivar. Anal. Ke Wang, Alexander Franks, Sang-Yun Oh
2020	A	`conf`	Distributionally Robust Formulation and Model Selection for the Graphical Lasso. AISTATS Pedro Cisneros-Velarde, Alexander Petersen, Sang-Yun Oh
2019	J	`jnl`	A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data. Mach. Learn. Kshitij Khare, Sang-Yun Oh, Syed Rahman, Bala Rajaratnam
2019	J	`jnl`	Distributionally Robust Formulation and Model Selection for the Graphical Lasso. CoRR Pedro Cisneros-Velarde, Sang-Yun Oh, Alexander Petersen
2018	A	`conf`	Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation. AISTATS Penporn Koanantakool, Alnur Ali, Ariful Azad, Aydin Buluç, Dmitriy Morozov, Leonid Oliker, Katherine A. Yelick, Sang-Yun Oh
2017	J	`jnl`	Communication-Avoiding Optimization Methods for Massive-Scale Graphical Model Structure Learning. CoRR Penporn Koanantakool, Alnur Ali, Ariful Azad, Aydin Buluç, Dmitriy Morozov, Sang-Yun Oh, Leonid Oliker, Katherine A. Yelick
2017	A	`conf`	Generalized Pseudolikelihood Methods for Inverse Covariance Estimation. AISTATS Alnur Ali, Kshitij Khare, Sang-Yun Oh, Bala Rajaratnam
2016	A	`conf`	Communication-Avoiding Parallel Sparse-Dense Matrix-Matrix Multiplication. IPDPS Penporn Koanantakool, Ariful Azad, Aydin Buluç, Dmitriy Morozov, Sang-Yun Oh, Leonid Oliker, Katherine A. Yelick
2016	C	`conf`	Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks. ICMLA Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat
2016	J	`jnl`	Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks. CoRR Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat
2014	—	`conf`	Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. NIPS Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam
2014	J	`jnl`	Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. CoRR Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam