Large-Sample Learning of Bayesian Networks is NP-Hard

19 October 2012

Papers citing "Large-Sample Learning of Bayesian Networks is NP-Hard"

50 / 167 papers shown

Title
dotears: Scalable, consistent DAG estimation using observational and interventional data Albert Y Xue Jingyou Rao S. Sankararaman Harold Pimentel OOD CML 16 3 0 30 May 2023
Learning DAGs from Data with Few Root Causes Panagiotis Misiakos Chris Wendler Markus Püschel CML 37 10 0 25 May 2023
Toward Falsifying Causal Graphs Using a Permutation-Based Test Elias Eulig Atalanti A. Mastakouri Patrick Blobaum Michael W. Hardt Dominik Janzing 13 8 0 16 May 2023
Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences Jie Qiao Ruichu Cai Siyu Wu Yu Xiang Keli Zhang Z. Hao CML AI4TS 22 5 0 10 May 2023
Structure Learning with Continuous Optimization: A Sober Look and Beyond Ignavier Ng Biwei Huang Kun Zhang CML 21 21 0 04 Apr 2023
A Guide for Practical Use of ADMG Causal Data Augmentation Audrey Poinsot Alessandro Leite CML 20 2 0 03 Apr 2023
Learning the Finer Things: Bayesian Structure Learning at the Instantiation Level Chase Yakaboski E. Santos 13 2 0 08 Mar 2023
Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting An Zhang Fang Liu Wenchang Ma Zhibo Cai Xiang Wang Tat-Seng Chua CML 26 5 0 06 Mar 2023
Credal Bayesian Deep Learning Michele Caprio Souradeep Dutta Kuk Jin Jang Vivian Lin Radoslav Ivanov O. Sokolsky Insup Lee OOD BDL UQCV 26 18 0 19 Feb 2023
Causal Structural Learning from Time Series: A Convex Optimization Approach S. Wei Yao Xie CML 27 2 0 26 Jan 2023
Data-Driven Estimation of Heterogeneous Treatment Effects Christopher Tran Keith Burghardt Kristina Lerman Elena Zheleva CML 19 1 0 16 Jan 2023
Evaluation of Induced Expert Knowledge in Causal Structure Learning by NOTEARS Jawad Chowdhury Rezaur Rashid G. Terejanu CML 18 9 0 04 Jan 2023
Reinforcement Causal Structure Learning on Order Graph Dezhi Yang Guoxian Yu J. Wang Zhe Wu Maozu Guo BDL CML 26 16 0 22 Nov 2022
Sample-Specific Root Causal Inference with Latent Variables Eric V. Strobl Thomas A. Lasko CML 23 8 0 27 Oct 2022
Combinatorial and algebraic perspectives on the marginal independence structure of Bayesian networks Danai Deligeorgaki Alex Markham Pratik Misra Liam Solus 17 4 0 03 Oct 2022
DAGMA: Learning DAGs via M-matrices and a Log-Determinant Acyclicity Characterization Kevin Bello Bryon Aragam Pradeep Ravikumar 59 78 0 16 Sep 2022
On the Sparse DAG Structure Learning Based on Adaptive Lasso Danru Xu Erdun Gao Wei Huang Menghan Wang Andy Song Mingming Gong CML 10 4 0 07 Sep 2022
Truncated Matrix Power Iteration for Differentiable DAG Learning Zhen Zhang Ignavier Ng Dong Gong Yuhang Liu Ehsan Abbasnejad Mingming Gong Kun Zhang Javen Qinfeng Shi 22 25 0 30 Aug 2022
CausNet : Generational orderings based search for optimal Bayesian networks via dynamic programming with parent set constraints Nand Sharma J. Millstein 7 0 0 18 Jul 2022
Multiscale Causal Structure Learning Gabriele DÁcunto P. Lorenzo Sergio Barbarossa 56 4 0 16 Jul 2022
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure Uncertainty Christopher Tran Elena Zheleva CML 17 4 0 25 Jun 2022
Explanatory causal effects for model agnostic explanations Jiuyong Li Ha Xuan Tran T. Le Lin Liu Kui Yu Jixue Liu CML 17 1 0 23 Jun 2022
Causality Learning With Wasserstein Generative Adversarial Networks H. Petkov Colin Hanley Feng Dong CML GAN OOD 12 0 0 03 Jun 2022
Causal discovery under a confounder blanket David S. Watson Ricardo M. A. Silva CML 13 2 0 11 May 2022
DAG-WGAN: Causal Structure Learning With Wasserstein Generative Adversarial Networks H. Petkov Colin Hanley Feng Dong GAN OOD CML 27 6 0 01 Apr 2022
A Density Evolution framework for Preferential Recovery of Covariance and Causal Graphs from Compressed Measurements Muralikrishnna G. Sethuraman Hang Zhang Faramarz Fekri 9 0 0 17 Mar 2022
Differentiable DAG Sampling Bertrand Charpentier Simon Kibler Stephan Günnemann 20 41 0 16 Mar 2022
Optimal estimation of Gaussian DAG models Ming Gao W. Tai Bryon Aragam 33 9 0 25 Jan 2022
Learning Bayesian Networks in the Presence of Structural Side Information Ehsan Mokhtarian S. Akbari Fatemeh Jamshidi Jalal Etesami Negar Kiyavash 21 16 0 20 Dec 2021
Feature Selection for Efficient Local-to-Global Bayesian Network Structure Learning Kui Yu Zhaolong Ling Lin Liu Hao Wang Jiuyong Li 28 4 0 20 Dec 2021
The Dual PC Algorithm and the Role of Gaussianity for Structure Learning of Bayesian Networks Enrico Giudice Jack Kuipers G. Moffa CML 67 5 0 16 Dec 2021
Simultaneous Missing Value Imputation and Structure Learning with Groups Pablo Morales-Álvarez Wenbo Gong A. Lamb Simon Woodhead Simon L. Peyton Jones Nick Pawlowski Miltiadis Allamanis Cheng Zhang 9 16 0 15 Oct 2021
Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families Goutham Rajendran Bohdan Kivva Ming Gao Bryon Aragam 27 17 0 10 Oct 2021
Causal Explanations of Structural Causal Models Matej Zevcević D. Dhami Constantin Rothkopf Kristian Kersting LRM 22 2 0 05 Oct 2021
A survey of Bayesian Network structure learning N. K. Kitson Anthony C. Constantinou Zhi-gao Guo Yang Liu Kiattikun Chobtham CML 24 182 0 23 Sep 2021
Transport-based Counterfactual Models Lucas de Lara Alberto González Sanz Nicholas M. Asher Laurent Risser Jean-Michel Loubes 25 21 0 30 Aug 2021
A Stochastic Variance-Reduced Coordinate Descent Algorithm for Learning Sparse Bayesian Network from Discrete High-Dimensional Data Nazanin Shajoonnezhad Amin Nikanjam 19 3 0 21 Aug 2021
Improving Efficiency and Accuracy of Causal Discovery Using a Hierarchical Wrapper Shami Nisimov Yaniv Gurwicz R. Y. Rohekar Gal Novik CML TPM 13 6 0 11 Jul 2021
Benchpress: A Scalable and Versatile Workflow for Benchmarking Structure Learning Algorithms Felix L. Rios G. Moffa Jack Kuipers CML 27 12 0 08 Jul 2021
DAGs with No Curl: An Efficient DAG Structure Learning Approach Yue Yu Tian Gao Naiyu Yin Q. Ji CML 22 59 0 14 Jun 2021
Causal Graph Discovery from Self and Mutually Exciting Time Series S. Wei Yao Xie C. Josef Rishikesan Kamaleswaran CML 27 2 0 04 Jun 2021
Causal Inference in medicine and in health policy, a summary Wenhao Zhang Ramin Ramezani A. Naeim CML OOD 9 6 0 10 May 2021
Any Part of Bayesian Network Structure Learning Zhaolong Ling Kui Yu Hao Wang Lin Liu Jiuyong Li 17 3 0 23 Mar 2021
Partitioned hybrid learning of Bayesian network structures Jireh Huang Qing Zhou TPM 19 8 0 22 Mar 2021
Beware of the Simulated DAG! Causal Discovery Benchmarks May Be Easy To Game Alexander G. Reisach C. Seiler S. Weichwald CML 15 136 0 26 Feb 2021
Integer Programming for Causal Structure Learning in the Presence of Latent Variables Rui Chen S. Dash Tian Gao CML 16 14 0 05 Feb 2021
Efficient Permutation Discovery in Causal DAGs C. Squires Joshua Amaniampong Caroline Uhler CML 14 4 0 06 Nov 2020
A Bregman Method for Structure Learning on Sparse Directed Acyclic Graphs Manon Romain Alexandre d’Aspremont 11 5 0 05 Nov 2020
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks Dennis L. Wei Tian Gao Yue Yu CML 56 71 0 18 Oct 2020
Differentiable TAN Structure Learning for Bayesian Network Classifiers Wolfgang Roth Franz Pernkopf BDL 13 2 0 21 Aug 2020