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
A Functional Model for Structure Learning and Parameter Estimation in Continuous Time Bayesian Network: An Application in Identifying Patterns of Multiple Chronic Conditions Syed Hasib Akhter Faruqui A. Alaeddini Jing Wang C. Jaramillo CML 6 6 0 31 Jul 2020
Instrument variable detection with graph learning : an application to high dimensional GIS-census data for house pricing Ning Xu Timothy C. G. Fisher Jian Hong 13 0 0 30 Jul 2020
Accuracy and stability of solar variable selection comparison under complicated dependence structures Ning Xu Timothy C. G. Fisher Jian Hong 13 0 0 30 Jul 2020
Solving Bayesian Network Structure Learning Problem with Integer Linear Programming Ronald Seoh 8 1 0 06 Jul 2020
Causal Discovery from Incomplete Data using An Encoder and Reinforcement Learning Xiaoshui Huang Fujin Zhu Lois Holloway Ali Haidar CML 9 10 0 09 Jun 2020
Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains James Bannon Bradford T. Windsor Wenbo Song Tao Li CML OOD OffRL 18 20 0 03 Jun 2020
Graphical Normalizing Flows Antoine Wehenkel Gilles Louppe TPM BDL 10 36 0 03 Jun 2020
Causal Modeling of Twitter Activity During COVID-19 O. Gencoglu M. Gruber CML 22 49 0 16 May 2020
Graphical modeling of stochastic processes driven by correlated errors Søren Wengel Mogensen N. Hansen 17 18 0 15 May 2020
Learning Bayesian Networks that enable full propagation of evidence Anthony C. Constantinou 22 17 0 09 Apr 2020
Graph Learning Under Partial Observability Vincenzo Matta A. Santos A. H. Sayed 11 0 0 18 Dec 2019
Causality-based Feature Selection: Methods and Evaluations Kui Yu Xianjie Guo Lin Liu Jiuyong Li Hao Wang Zhaolong Ling Xindong Wu CML 18 92 0 17 Nov 2019
Scaling structural learning with NO-BEARS to infer causal transcriptome networks Hao-Chih Lee M. Danieletto Riccardo Miotto S. Cherng J. Dudley CML 6 44 0 31 Oct 2019
Beyond DAGs: Modeling Causal Feedback with Fuzzy Cognitive Maps Osonde A. Osoba B. Kosko 6 9 0 26 Jun 2019
Bayesian Network Models for Incomplete and Dynamic Data M. Scutari SyDa 16 0 0 15 Jun 2019
Causal Discovery with Reinforcement Learning Shengyu Zhu Ignavier Ng Zhitang Chen CML 8 236 0 11 Jun 2019
On Pruning for Score-Based Bayesian Network Structure Learning Alvaro H. C. Correia James Cussens Cassio de Campos 15 14 0 23 May 2019
Learning Functional Dependencies with Sparse Regression Zhihan Guo Theodoros Rekatsinas 6 1 0 04 May 2019
Learning big Gaussian Bayesian networks: partition, estimation, and fusion J. Gu Qing Zhou GNN 19 19 0 24 Apr 2019
DAG-GNN: DAG Structure Learning with Graph Neural Networks Yue Yu Jie Chen Tian Gao Mo Yu BDL CML GNN 11 476 0 22 Apr 2019
Graph Learning over Partially Observed Diffusion Networks: Role of Degree Concentration Vincenzo Matta A. Santos A. H. Sayed 14 2 0 05 Apr 2019
Efficient and Robust Machine Learning for Real-World Systems Franz Pernkopf Wolfgang Roth Matthias Zöhrer Lukas Pfeifenberger Günther Schindler Holger Froening Sebastian Tschiatschek Robert Peharz Matthew Mattina Zoubin Ghahramani OOD 13 1 0 05 Dec 2018
Generalization in anti-causal learning Niki Kilbertus Giambattista Parascandolo Bernhard Schölkopf OOD CML 6 53 0 03 Dec 2018
Probabilistic Causal Analysis of Social Influence Francesco Bonchi Francesco Gullo B. Mishra Daniele Ramazzotti CML 35 4 0 06 Aug 2018
Semantically Enhanced Dynamic Bayesian Network for Detecting Sepsis Mortality Risk in ICU Patients with Infection Tony Wang Tom Velez Emilia Apostolova Tim Tschampel T. Ngo Joy Hardison 11 5 0 26 Jun 2018
Who Learns Better Bayesian Network Structures: Accuracy and Speed of Structure Learning Algorithms M. Scutari C. E. Graafland J. Gutiérrez CML 28 53 0 30 May 2018
Learning Bayesian Networks from Big Data with Greedy Search: Computational Complexity and Efficient Implementation M. Scutari C. Vitolo A. Tucker 20 99 0 22 Apr 2018
Learning discrete Bayesian networks in polynomial time and sample complexity Adarsh Barik Jean Honorio TPM 13 0 0 12 Mar 2018
DAGs with NO TEARS: Continuous Optimization for Structure Learning Xun Zheng Bryon Aragam Pradeep Ravikumar Eric P. Xing NoLa CML OffRL 10 914 0 04 Mar 2018
EMR-based medical knowledge representation and inference via Markov random fields and distributed representation learning Chao Zhao Jingchi Jiang Y. Guan 10 39 0 20 Sep 2017
Entropy-based Pruning for Learning Bayesian Networks using BIC Cassio P. De Campos Mauro Scanagatta Giorgio Corani Marco Zaffalon 13 34 0 19 Jul 2017
Learning the structure of Bayesian Networks via the bootstrap G. Caravagna Daniele Ramazzotti CML 25 1 0 07 Jun 2017
Learning the structure of Bayesian Networks: A quantitative assessment of the effect of different algorithmic schemes S. Beretta M. Castelli Ivo Gonçalves Roberto Henriques Daniele Ramazzotti CML 17 5 0 27 Apr 2017
Learning Large-Scale Bayesian Networks with the sparsebn Package Bryon Aragam J. Gu Qing Zhou CML 13 55 0 11 Mar 2017
Efficient computational strategies to learn the structure of probabilistic graphical models of cumulative phenomena Daniele Ramazzotti Marco S. Nobile M. Antoniotti Alex Graudenzi CML 14 4 0 08 Mar 2017
Parallel Implementation of Efficient Search Schemes for the Inference of Cancer Progression Models Daniele Ramazzotti Marco S. Nobile P. Cazzaniga G. Mauri M. Antoniotti 11 7 0 08 Mar 2017
Generalization error minimization: a new approach to model evaluation and selection with an application to penalized regression N. Xu Jian Hong Timothy C. G. Fisher 10 2 0 18 Oct 2016
Finite-sample and asymptotic analysis of generalization ability with an application to penalized regression N. Xu Jian Hong Timothy C. G. Fisher 10 0 0 12 Sep 2016
Latent Dependency Forest Models Shanbo Chu Yong-jia Jiang Kewei Tu AI4CE 17 3 0 08 Sep 2016
Model selection consistency from the perspective of generalization ability and VC theory with an application to Lasso N. Xu Jian Hong Timothy C. G. Fisher 23 0 0 01 Jun 2016
A Model of Selective Advantage for the Efficient Inference of Cancer Clonal Evolution Daniele Ramazzotti 16 5 0 15 Feb 2016
Learning Directed Acyclic Graphs with Penalized Neighbourhood Regression Bryon Aragam Arash A. Amini Qing Zhou CML 14 42 0 29 Nov 2015
From Observational Studies to Causal Rule Mining Jiuyong Li T. Le Lin Liu Jixue Liu Zhou Jin Bing-Yu Sun Saisai Ma CML 18 50 0 16 Aug 2015
Causal Decision Trees Jiuyong Li Saisai Ma T. Le Lin Liu Jixue Liu CML 11 59 0 16 Aug 2015
A hybrid algorithm for Bayesian network structure learning with application to multi-label learning Maxime Gasse A. Aussem H. Elghazel 21 88 0 18 Jun 2015
Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks Using a Polynomial Number of Score Evaluations D. M. Chickering Christopher Meek 33 27 0 06 Jun 2015
Incorporating Type II Error Probabilities from Independence Tests into Score-Based Learning of Bayesian Network Structure Eliot Brenner David Sontag 25 0 0 12 May 2015
A Greedy, Flexible Algorithm to Learn an Optimal Bayesian Network Structure Amir Arsalan Soltani TPM 43 1 0 24 Nov 2014
Fast Learning of Relational Dependency Networks Oliver Schulte Zhensong Qian A. Kirkpatrick Xiaoqian Yin Yan Lindsay Sun GNN 17 12 0 28 Oct 2014
Cognitive Learning of Statistical Primary Patterns via Bayesian Network Weijia Han H. Sang Min Sheng Jiandong Li Shuguang Cui 24 1 0 28 Sep 2014