Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Fundamental concepts of qualitative probabilistic networks
Artificial Intelligence
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Maximum Likelihood Bounded Tree-Width Markov Networks
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Optimal structure identification with greedy search
The Journal of Machine Learning Research
Finding a path is harder than finding a tree
Journal of Artificial Intelligence Research
UAI'99 Proceedings of the Fifteenth 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
On local optima in learning bayesian networks
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
On the incompatibility of faithfulness and monotone DAG faithfulness
Artificial Intelligence
Consistent Feature Selection for Pattern Recognition in Polynomial Time
The Journal of Machine Learning Research
Strategies for improving the modeling and interpretability of Bayesian networks
Data & Knowledge Engineering
A chain-model genetic algorithm for Bayesian network structure learning
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Evolved bayesian networks as a versatile alternative to partin tables for prostate cancer management
Proceedings of the 10th annual conference on Genetic and evolutionary computation
A Recursive Method for Structural Learning of Directed Acyclic Graphs
The Journal of Machine Learning Research
Distribution-Free Learning of Bayesian Network Structure
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
BAIS: A Bayesian Artificial Immune System for the effective handling of building blocks
Information Sciences: an International Journal
Bayesian network structure learning using cooperative coevolution
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Graph-Based Analysis of Nasopharyngeal Carcinoma with Bayesian Network Learning Methods
GbRPR '09 Proceedings of the 7th IAPR-TC-15 International Workshop on Graph-Based Representations in Pattern Recognition
Learning Bayesian network equivalence classes with Ant Colony optimization
Journal of Artificial Intelligence Research
On the incompatibility of faithfulness and monotone DAG faithfulness
Artificial Intelligence
Mind change optimal learning of Bayes net structure from dependency and independency data
Information and Computation
CI '07 Proceedings of the Third IASTED International Conference on Computational Intelligence
Probabilistic Graphical Markov Model Learning: An Adaptive Strategy
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
Averaged Naive Bayes Trees: A New Extension of AODE
ACML '09 Proceedings of the 1st Asian Conference on Machine Learning: Advances in Machine Learning
Learning Bayesian networks to perform feature selection
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Bayesian Network Structure Learning by Recursive Autonomy Identification
The Journal of Machine Learning Research
A parallel algorithm for learning Bayesian networks
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Mind change optimal learning of Bayes net structure
COLT'07 Proceedings of the 20th annual conference on Learning theory
A hybrid approach for learning Markov equivalence classes of Bayesian network
KSEM'07 Proceedings of the 2nd international conference on Knowledge science, engineering and management
Algorithm for graphical Bayesian modeling based on multiple regressions
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
Using Bayesian network and AIS to perform feature subset selection
ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
Supporting scalable Bayesian networks using configurable discretizer actuators
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Integrated importance measures of multi-state systems under uncertainty
Computers and Industrial Engineering
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
Artificial Intelligence Review
Influence of Prior Knowledge in Constraint-Based Learning of Gene Regulatory Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
An Efficient Algorithm for Learning Bayesian Networks from Data
Fundamenta Informaticae - From Mathematical Beauty to the Truth of Nature: to Jerzy Tiuryn on his 60th Birthday
Using Qualitative Probability in Reverse-Engineering Gene Regulatory Networks
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Discriminative Learning of Bayesian Networks via Factorized Conditional Log-Likelihood
The Journal of Machine Learning Research
Pure high-order word dependence mining via information geometry
ICTIR'11 Proceedings of the Third international conference on Advances in information retrieval theory
Analysis of nasopharyngeal carcinoma risk factors with Bayesian networks
Artificial Intelligence in Medicine
Learning bayesian networks does not have to be NP-Hard
MFCS'06 Proceedings of the 31st international conference on Mathematical Foundations of Computer Science
Review: learning bayesian networks: Approaches and issues
The Knowledge Engineering Review
The Journal of Machine Learning Research
Finding consensus Bayesian network structures
Journal of Artificial Intelligence Research
A network intrusion detection system based on a Hidden Naïve Bayes multiclass classifier
Expert Systems with Applications: An International Journal
Analysis of Markov Boundary Induction in Bayesian Networks: A New View From Matroid Theory
Fundamenta Informaticae
Learning bayesian networks from Markov random fields: An efficient algorithm for linear models
ACM Transactions on Knowledge Discovery from Data (TKDD)
A review on probabilistic graphical models in evolutionary computation
Journal of Heuristics
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
A review on evolutionary algorithms in Bayesian network learning and inference tasks
Information Sciences: an International Journal
Improving naive Bayes classifier using conditional probabilities
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Mining pure high-order word associations via information geometry for information retrieval
ACM Transactions on Information Systems (TOIS)
Finding optimal Bayesian networks using precedence constraints
The Journal of Machine Learning Research
Incremental causal network construction over event streams
Information Sciences: an International Journal
Sub-local constraint-based learning of Bayesian networks using a joint dependence criterion
The Journal of Machine Learning Research
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In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a scoring criterion that favors the simplest structure for which the model is able to represent the generative distribution exactly. Our results therefore hold whenever the learning algorithm uses a consistent scoring criterion and is applied to a sufficiently large dataset. We show that identifying high-scoring structures is NP-hard, even when any combination of one or more of the following hold: the generative distribution is perfect with respect to some DAG containing hidden variables; we are given an independence oracle; we are given an inference oracle; we are given an information oracle; we restrict potential solutions to structures in which each node has at most k parents, for all k=3.Our proof relies on a new technical result that we establish in the appendices. In particular, we provide a method for constructing the local distributions in a Bayesian network such that the resulting joint distribution is provably perfect with respect to the structure of the network.