Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
A Guide to the Literature on Learning Probabilistic Networks from Data
IEEE Transactions on Knowledge and Data Engineering
Equivalence and synthesis of causal models
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
Enumerating Markov Equivalence Classes of Acyclic Digraph Models
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
On characterizing Inclusion of Bayesian Networks
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Learning equivalence classes of bayesian-network structures
The Journal of Machine Learning Research
Finding optimal bayesian networks
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
A transformational characterization of equivalent Bayesian network structures
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Causal inference and causal explanation with background knowledge
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
On inclusion-driven learning of bayesian networks
The Journal of Machine Learning Research
Characterization of essential graphs by means of the operation of legal merging of components
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems - New trends in probabilistic graphical models
Exact Bayesian Structure Discovery in Bayesian Networks
The Journal of Machine Learning Research
Large-Sample Learning of Bayesian Networks is NP-Hard
The Journal of Machine Learning Research
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
New d-separation identification results for learning continuous latent variable models
ICML '05 Proceedings of the 22nd international conference on Machine learning
Learning dynamic Bayesian network models via cross-validation
Pattern Recognition Letters
The dynamics of viral marketing
ACM Transactions on the Web (TWEB)
Web projections: learning from contextual subgraphs of the web
Proceedings of the 16th international conference on World Wide Web
Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation
The Journal of Machine Learning Research
Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm
The Journal of Machine Learning Research
A kernel-based causal learning algorithm
Proceedings of the 24th international conference on Machine learning
Towards efficient variables ordering for Bayesian networks classifier
Data & Knowledge Engineering
A heuristic algorithm for pattern-to-DAG conversion
AIAP'07 Proceedings of the 25th conference on Proceedings of the 25th IASTED International Multi-Conference: artificial intelligence and applications
Machine learning: a review of classification and combining techniques
Artificial Intelligence Review
Detection of Unfaithfulness and Robust Causal Inference
Minds and Machines
Search for Additive Nonlinear Time Series Causal Models
The Journal of Machine Learning Research
Two Evolutionary Methods for Learning Bayesian Network Structures
Computational Intelligence and Security
Using Markov Blankets for Causal Structure Learning
The Journal of Machine Learning Research
Causal Reasoning with Ancestral Graphs
The Journal of Machine Learning Research
Parallell interacting MCMC for learning of topologies of graphical models
Data Mining and Knowledge Discovery
Learning Causal Bayesian Networks from Incomplete Observational Data and Interventions
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A Fast Hill-Climbing Algorithm for Bayesian Networks Structure Learning
ECSQARU '07 Proceedings of the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
A reconstruction algorithm for the essential graph
International Journal of Approximate Reasoning
Automatic Boosting of Cross-Product Coverage Using Bayesian Networks
HVC '08 Proceedings of the 4th International Haifa Verification Conference on Hardware and Software: Verification and Testing
Structure learning of Bayesian networks using constraints
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Structure learning with independent non-identically distributed data
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Optimizing Student Models for Causality
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Approximation Methods for Efficient Learning of Bayesian Networks
Proceedings of the 2008 conference on Approximation Methods for Efficient Learning of Bayesian Networks
Supervised Machine Learning: A Review of Classification Techniques
Proceedings of the 2007 conference on Emerging Artificial Intelligence Applications in Computer Engineering: Real Word AI Systems with Applications in eHealth, HCI, Information Retrieval and Pervasive Technologies
Learning Behaviors Models for Robot Execution Control
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Integrating Ontological Knowledge for Iterative Causal Discovery and Visualization
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
On the classification performance of TAN and general Bayesian networks
Knowledge-Based Systems
Incremental Bayesian Network Learning for Scalable Feature Selection
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
A comparison of novel and state-of-the-art polynomial Bayesian network learning algorithms
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
Learning Bayesian network equivalence classes with Ant Colony optimization
Journal of Artificial Intelligence Research
Mind change optimal learning of Bayes net structure from dependency and independency data
Information and Computation
Impact of censoring on learning Bayesian networks in survival modelling
Artificial Intelligence in Medicine
A conditional independence algorithm for learning undirected graphical models
Journal of Computer and System Sciences
An Expert System Based Approach to Modeling and Selecting Requirement Engineering Techniques
WISM '09 Proceedings of the International Conference on Web Information Systems and Mining
Characterization of inclusion neighbourhood in terms of the essential graph
International Journal of Approximate Reasoning
Strong Limit Theorems for the Bayesian Scoring Criterion in Bayesian Networks
The Journal of Machine Learning Research
Bayesian Network Structure Learning by Recursive Autonomy Identification
The Journal of Machine Learning Research
The Journal of Machine Learning Research
Mind change optimal learning of Bayes net structure
COLT'07 Proceedings of the 20th annual conference on Learning theory
ICNC'09 Proceedings of the 5th international conference on Natural computation
Learning locally minimax optimal Bayesian networks
International Journal of Approximate Reasoning
A geometric view on learning Bayesian network structures
International Journal of Approximate Reasoning
Learning Bayesian networks from survival data using weighting censored instances
Journal of Biomedical Informatics
Introduction to Causal Inference
The Journal of Machine Learning Research
Learning an L1-regularized Gaussian Bayesian network in the equivalence class space
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Automatic model adaptation for complex structured domains
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
Data Mining and Knowledge Discovery
Efficient Algorithms for Conditional Independence Inference
The Journal of Machine Learning Research
On open questions in the geometric approach to structural learning Bayesian nets
International Journal of Approximate Reasoning
Graphical Methods, Inductive Causal Inference, and Econometrics: A Literature Review
Computational Economics
Efficient Structure Learning of Bayesian Networks using Constraints
The Journal of Machine Learning Research
DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model
The Journal of Machine Learning Research
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
ECSQARU'11 Proceedings of the 11th European conference on Symbolic and quantitative approaches to reasoning with uncertainty
Incorporating expert knowledge when learning Bayesian network structure: A medical case study
Artificial Intelligence in Medicine
Model-based multidimensional clustering of categorical data
Artificial Intelligence
Learning bayesian network equivalence classes from incomplete data
DS'06 Proceedings of the 9th international conference on Discovery Science
Variable construction for predictive and causal modeling of online education data
Proceedings of the 1st International Conference on Learning Analytics and Knowledge
Large-sample learning of bayesian networks is NP-hard
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
On local optima in learning bayesian networks
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Constrained score+(local)search methods for learning bayesian networks
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Review: learning bayesian networks: Approaches and issues
The Knowledge Engineering Review
The IMAP hybrid method for learning gaussian bayes nets
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
AI'04 Proceedings of the 17th Australian joint conference on Advances in Artificial Intelligence
Causal discovery with prior information
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
The role of operation granularity in search-based learning of latent tree models
JSAI-isAI'10 Proceedings of the 2010 international conference on New Frontiers in Artificial Intelligence
Finding consensus Bayesian network structures
Journal of Artificial Intelligence Research
Multimedia Tools and Applications
Conservative independence-based causal structure learning in absence of adjacency faithfulness
International Journal of Approximate Reasoning
Characteristic imsets for learning Bayesian network structure
International Journal of Approximate Reasoning
An experimental comparison of hybrid algorithms for bayesian network structure learning
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
Maximum Likelihood Estimation Over Directed Acyclic Gaussian Graphs
Statistical Analysis and Data Mining
The problem of finding the sparsest bayesian network for an input data set is NP-Hard
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
International Journal of Approximate Reasoning
DemocraticOP: A Democratic way of aggregating Bayesian network parameters
International Journal of Approximate Reasoning
Identifying significant edges in graphical models of molecular networks
Artificial Intelligence in Medicine
The Journal of Machine Learning Research
Learning linear cyclic causal models with latent variables
The Journal of Machine Learning Research
Adaptive thresholding in structure learning of a Bayesian network
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Bayesian probabilities for constraint-based causal discovery
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
An efficient node ordering method using the conditional frequency for the K2 algorithm
Pattern Recognition Letters
Profit optimizing customer churn prediction with Bayesian network classifiers
Intelligent Data Analysis - Business Analytics and Intelligent Optimization
Learning Bayesian network structure: Towards the essential graph by integer linear programming tools
International Journal of Approximate Reasoning
Two optimal strategies for active learning of causal models from interventional data
International Journal of Approximate Reasoning
Learning AMP chain graphs and some marginal models thereof under faithfulness
International Journal of Approximate Reasoning
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In this paper we prove the so-called "Meek Conjecture". In particular, we show that if a DAG H is an independence map of another DAG G, then there exists a finite sequence of edge additions and covered edge reversals in G such that (1) after each edge modification H remains an independence map of G and (2) after all modifications G =H. As shown by Meek (1997), this result has an important consequence for Bayesian approaches to learning Bayesian networks from data: in the limit of large sample size, there exists a two-phase greedy search algorithm that---when applied to a particular sparsely-connected search space---provably identifies a perfect map of the generative distribution if that perfect map is a DAG. We provide a new implementation of the search space, using equivalence classes as states, for which all operators used in the greedy search can be scored efficiently using local functions of the nodes in the domain. Finally, using both synthetic and real-world datasets, we demonstrate that the two-phase greedy approach leads to good solutions when learning with finite sample sizes.