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Journal Articles
- 2023
[j2]Ke Wang
, Alexander Franks, Sang-Yun Oh:
Learning Gaussian graphical models with latent confounders. J. Multivar. Anal. 198: 105213 (2023)- 2019
- [j1]Kshitij Khare, Sang-Yun Oh, Syed Rahman, Bala Rajaratnam:
A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data. Mach. Learn. 108(12): 2061-2086 (2019)
Conference and Workshop Papers
- 2020
- [c6]Pedro Cisneros-Velarde, Alexander Petersen, Sang-Yun Oh:
Distributionally Robust Formulation and Model Selection for the Graphical Lasso. AISTATS 2020: 756-765 - 2018
- [c5]Penporn Koanantakool, Alnur Ali, Ariful Azad, Aydin Buluç, Dmitriy Morozov, Leonid Oliker, Katherine A. Yelick, Sang-Yun Oh:
Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation. AISTATS 2018: 1376-1386 - 2017
- [c4]Alnur Ali, Kshitij Khare, Sang-Yun Oh, Bala Rajaratnam:
Generalized Pseudolikelihood Methods for Inverse Covariance Estimation. AISTATS 2017: 280-288 - 2016
- [c3]Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat:
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks. ICMLA 2016: 892-897 - [c2]Penporn Koanantakool, Ariful Azad, Aydin Buluç, Dmitriy Morozov, Sang-Yun Oh, Leonid Oliker, Katherine A. Yelick:
Communication-Avoiding Parallel Sparse-Dense Matrix-Matrix Multiplication. IPDPS 2016: 842-853 - 2014
- [c1]Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam:
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. NIPS 2014: 667-675
Informal and Other Publications
- 2019
- [i4]Pedro Cisneros-Velarde, Sang-Yun Oh, Alexander Petersen:
Distributionally Robust Formulation and Model Selection for the Graphical Lasso. CoRR abs/1905.08975 (2019) - 2017
- [i3]Penporn Koanantakool, Alnur Ali, Ariful Azad, Aydin Buluç, Dmitriy Morozov, Sang-Yun Oh, Leonid Oliker, Katherine A. Yelick:
Communication-Avoiding Optimization Methods for Massive-Scale Graphical Model Structure Learning. CoRR abs/1710.10769 (2017) - 2016
- [i2]Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat:
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks. CoRR abs/1601.07621 (2016) - 2014
- [i1]Sang-Yun Oh, Onkar Dalal, Kshitij Khare, Bala Rajaratnam:
Optimization Methods for Sparse Pseudo-Likelihood Graphical Model Selection. CoRR abs/1409.3768 (2014)
Coauthor Index
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