Bryon Aragam
Title
Cited by
Cited by
Year
Concave penalized estimation of sparse Gaussian Bayesian networks
B Aragam, Q Zhou
Journal of Machine Learning Research 16, 2273-2328, 2015
472015
DAGs with NO TEARS: Continuous Optimization for Structure Learning
X Zheng, B Aragam, PK Ravikumar, EP Xing
Advances in Neural Information Processing Systems, 9472-9483, 2018
28*2018
Precision lasso: Accounting for correlations and linear dependencies in high-dimensional genomic data
H Wang, BJ Lengerich, B Aragam, EP Xing
Bioinformatics, 2017
182017
Learning Large-Scale Bayesian Networks with the sparsebn Package
B Aragam, J Gu, Q Zhou
Journal of Statistical Software 91 (11), 2019
172019
Learning directed acyclic graphs with penalized neighbourhood regression
B Aragam, AA Amini, Q Zhou
arXiv preprint arXiv:1511.08963, 2015
142015
Variable selection in heterogeneous datasets: a truncated-rank sparse linear mixed model with applications to genome-wide association studies
H Wang, B Aragam, EP Xing
Methods 145, 2-9, 2018
122018
Personalized Regression Enables Sample-Specific Pan-Cancer Analysis
B Lengerich, B Aragam, EP Xing
Bioinformatics 34 (13), i178--i186, 2018
52018
Fault Tolerance in Iterative-Convergent Machine Learning
A Qiao, B Aragam, B Zhang, EP Xing
International Conference on Machine Learning, 5220-5230, 2019
42019
Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering
B Aragam, C Dan, P Ravikumar, EP Xing
arXiv preprint arXiv:1802.04397, 2018
42018
Partial correlation graphs and the neighborhood lattice
AA Amini, B Aragam, Q Zhou
arXiv preprint arXiv:1711.00991, 2017
42017
Concave penalized estimation of sparse Bayesian networks
B Aragam, Q Zhou
arXiv preprint arXiv:1401.0852, 2014
42014
DYNOTEARS: Structure Learning from Time-Series Data
R Pamfil, N Sriwattanaworachai, S Desai, P Pilgerstorfer, P Beaumont, ...
arXiv preprint arXiv:2002.00498, 2020
2020
Diagnostic Curves for Black Box Models
DI Inouye, L Leqi, JS Kim, B Aragam, P Ravikumar
arXiv preprint arXiv:1912.01108, 2019
2019
Learning Sparse Nonparametric DAGs
X Zheng, C Dan, B Aragam, P Ravikumar, EP Xing
arXiv preprint arXiv:1909.13189, 2019
2019
On perfectness in Gaussian graphical models
AA Amini, B Aragam, Q Zhou
arXiv preprint arXiv:1909.01978, 2019
2019
Globally optimal score-based learning of directed acyclic graphs in high-dimensions
B Aragam, A Amini, Q Zhou
Advances in Neural Information Processing Systems, 4452-4464, 2019
2019
Learning Sample-Specific Models with Low-Rank Personalized Regression
B Lengerich, B Aragam, EP Xing
Advances in Neural Information Processing Systems, 3570-3580, 2019
2019
The Sample Complexity of Semi-Supervised Learning with Nonparametric Mixture Models
C Dan, L Leqi, B Aragam, PK Ravikumar, EP Xing
Advances in Neural Information Processing Systems, 9321-9332, 2018
2018
Collaborative Development in R
B Aragam
2017
Structure Learning of Linear Bayesian Networks in High-Dimensions
NB Aragam
UCLA, 2015
2015
The system can't perform the operation now. Try again later.
Articles 1–20