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- Publications
- Influence
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
- D. Heckerman, D. Geiger, David Maxwell Chickering
- Computer Science, Mathematics
- Machine Learning
- 31 July 1994
TLDR
Optimal Structure Identification With Greedy Search
- David Maxwell Chickering
- Mathematics, Computer Science
- J. Mach. Learn. Res.
- 1 March 2003
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… Expand
Learning Equivalence Classes of Bayesian-Network Structures
- David Maxwell Chickering
- Computer Science, Mathematics
- J. Mach. Learn. Res.
- 1 August 1996
TLDR
Learning Bayesian Networks is NP-Complete
- David Maxwell Chickering
- Computer Science
- AISTATS
- 28 December 2016
TLDR
Dependency Networks for Inference, Collaborative Filtering, and Data Visualization
- D. Heckerman, David Maxwell Chickering, Christopher Meek, Robert Rounthwaite, C. Kadie
- Computer Science
- J. Mach. Learn. Res.
- 1 September 2001
TLDR
A Transformational Characterization of Equivalent Bayesian Network Structures
- David Maxwell Chickering
- Computer Science, Mathematics
- UAI
- 18 August 1995
TLDR
Counterfactual reasoning and learning systems: the example of computational advertising
- L. Bottou, J. Peters, +6 authors Ed Snelson
- Computer Science
- J. Mach. Learn. Res.
- 2013
TLDR
A Bayesian Approach to Learning Bayesian Networks with Local Structure
- David Maxwell Chickering, D. Heckerman, Christopher Meek
- Computer Science, Mathematics
- UAI
- 1 August 1997
TLDR
Large-Sample Learning of Bayesian Networks is NP-Hard
- David Maxwell Chickering, D. Heckerman, Christopher Meek
- Computer Science, Mathematics
- J. Mach. Learn. Res.
- 7 August 2002
TLDR
Efficient Approximations for the Marginal Likelihood of Bayesian Networks with Hidden Variables
- David Maxwell Chickering, D. Heckerman
- Mathematics, Computer Science
- Machine Learning
- 1 November 1997
TLDR