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Efficient Bayesian network structure learning via local Markov boundary search


Oct 12, 2021
Ming Gao, Bryon Aragam

* 30 pages, 3 figures, to appear in NeurIPS 2021 

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Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families


Oct 10, 2021
Goutham Rajendran, Bohdan Kivva, Ming Gao, Bryon Aragam

* 36 pages, 9 figures 

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Uniform Consistency in Nonparametric Mixture Models


Aug 31, 2021
Bryon Aragam, Ruiyi Yang


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Learning latent causal graphs via mixture oracles


Jun 29, 2021
Bohdan Kivva, Goutham Rajendran, Pradeep Ravikumar, Bryon Aragam

* 37 pages 

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Fundamental Limits and Tradeoffs in Invariant Representation Learning


Dec 19, 2020
Han Zhao, Chen Dan, Bryon Aragam, Tommi S. Jaakkola, Geoffrey J. Gordon, Pradeep Ravikumar


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A polynomial-time algorithm for learning nonparametric causal graphs


Jun 22, 2020
Ming Gao, Yi Ding, Bryon Aragam

* 30 pages 

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DYNOTEARS: Structure Learning from Time-Series Data


Feb 02, 2020
Roxana Pamfil, Nisara Sriwattanaworachai, Shaan Desai, Philip Pilgerstorfer, Paul Beaumont, Konstantinos Georgatzis, Bryon Aragam

* 22 pages, 13 figures, accepted to AISTATS 2020 

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Diagnostic Curves for Black Box Models


Dec 02, 2019
David I. Inouye, Liu Leqi, Joon Sik Kim, Bryon Aragam, Pradeep Ravikumar

* Accepted to NeurIPS 2019 Workshop on Safety and Robustness in Decision Making 

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Learning Sample-Specific Models with Low-Rank Personalized Regression


Oct 15, 2019
Benjamin Lengerich, Bryon Aragam, Eric P. Xing

* Accepted at NeurIPS 2019 

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Learning Sparse Nonparametric DAGs


Sep 29, 2019
Xun Zheng, Chen Dan, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

* 17 pages, 5 figures 

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On perfectness in Gaussian graphical models


Sep 03, 2019
Arash A. Amini, Bryon Aragam, Qing Zhou

* This note is based on a result that first appeared in arXiv:1711.00991v1. The original article has now been split into two parts 

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DAGs with NO TEARS: Continuous Optimization for Structure Learning


Nov 03, 2018
Xun Zheng, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

* 22 pages, 8 figures, accepted to NIPS 2018 

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Fault Tolerance in Iterative-Convergent Machine Learning


Oct 17, 2018
Aurick Qiao, Bryon Aragam, Bingjing Zhang, Eric P. Xing


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Sample Complexity of Nonparametric Semi-Supervised Learning


Sep 10, 2018
Chen Dan, Liu Leqi, Bryon Aragam, Pradeep Ravikumar, Eric P. Xing

* 18 pages, 3 figures 

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Identifiability of Nonparametric Mixture Models and Bayes Optimal Clustering


Apr 22, 2018
Bryon Aragam, Chen Dan, Pradeep Ravikumar, Eric P. Xing

* 25 pages, 8 figures, 1 table. Added more experiments 

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Learning Large-Scale Bayesian Networks with the sparsebn Package


Mar 10, 2018
Bryon Aragam, Jiaying Gu, Qing Zhou

* To appear in the Journal of Statistical Software, 39 pages, 7 figures 

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Partial correlation graphs and the neighborhood lattice


Nov 03, 2017
Arash A. Amini, Bryon Aragam, Qing Zhou


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Learning Directed Acyclic Graphs with Penalized Neighbourhood Regression


Oct 02, 2017
Bryon Aragam, Arash A. Amini, Qing Zhou

* 54 pages, 1 figure 

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Concave Penalized Estimation of Sparse Gaussian Bayesian Networks


Jan 04, 2015
Bryon Aragam, Qing Zhou

* Journal of Machine Learning Research 16(Nov):2273-2328, 2015 
* 57 pages 

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