
Selective Greedy Equivalence Search: Finding Optimal Bayesian Networks Using a Polynomial Number of Score Evaluations
We introduce Selective Greedy Equivalence Search (SGES), a restricted ve...
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Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
We describe algorithms for learning Bayesian networks from a combination...
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Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network
We discuss Bayesian methods for learning Bayesian networks when data set...
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Learning Equivalence Classes of Bayesian Networks Structures
Approaches to learning Bayesian networks from data typically combine a s...
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A Bayesian Approach to Learning Bayesian Networks with Local Structure
Recently several researchers have investigated techniques for using data...
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Learning Mixtures of DAG Models
We describe computationally efficient methods for learning mixtures in w...
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Fast Learning from Sparse Data
We describe two techniques that significantly improve the running time o...
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Dependency Networks for Collaborative Filtering and Data Visualization
We describe a graphical model for probabilistic relationshipsan alter...
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A Decision Theoretic Approach to Targeted Advertising
A simple advertising strategy that can be used to help increase sales of...
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Using Temporal Data for Making Recommendations
We treat collaborative filtering as a univariate time series estimation ...
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A Bayesian Approach to Tackling Hard Computational Problems
We are developing a general framework for using learned Bayesian models ...
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Finding Optimal Bayesian Networks
In this paper, we derive optimality results for greedy Bayesiannetwork ...
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Practically Perfect
The property of perfectness plays an important role in the theory of Bay...
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LargeSample Learning of Bayesian Networks is NPHard
In this paper, we provide new complexity results for algorithms that lea...
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