Publications (26)
Asymptotic Model Selection for Directed Networks with Hidden Variables
Dan Geiger, David Heckerman, Christopher Meek
On the Logic of Causal Models
Dan Geiger, Judea Pearl
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
David Heckerman, Dan Geiger, David Maxwell Chickering
Accurate Liability Estimation Improves Power in Ascertained Case Control Studies
Omer Weissbrod, Christoph Lippert, Dan Geiger +1
Importance Sampling via Variational Optimization
Ydo Wexler, Dan Geiger
Advances in Probabilistic Reasoning
Dan Geiger, David Heckerman
Quantifier Elimination for Statistical Problems
Dan Geiger, Christopher Meek
On Testing Whether an Embedded Bayesian Network Represents a Probability Model
Dan Geiger, Azaria Paz, Judea Pearl
A Distance-Based Branch and Bound Feature Selection Algorithm
Ari Frank, Dan Geiger, Zohar Yakhini
d-Separation: From Theorems to Algorithms
Dan Geiger, Tom S. Verma, Judea Pearl
On the toric algebra of graphical models
Dan Geiger, Christopher Meek, Bernd Sturmfels
Approximation Algorithms for the Loop Cutset Problem
Ann Becker, Dan Geiger
Separable and transitive graphoids
Dan Geiger, David Heckerman
Graphical Models and Exponential Families
Dan Geiger, Christopher Meek
Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models
Dmitry Rusakov, Dan Geiger
A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks
Dan Geiger, David Heckerman
A Sufficiently Fast Algorithm for Finding Close to Optimal Junction Trees
Ann Becker, Dan Geiger
Random Algorithms for the Loop Cutset Problem
Ann Becker, Reuven Bar-Yehuada, Dan Geiger
Likelihood Computations Using Value Abstractions
Nir Friedman, Dan Geiger, Noam Lotner
Perfect Tree-Like Markovian Distributions
Ann Becker, Dan Geiger, Christopher Meek
Factorization of Discrete Probability Distributions
Dan Geiger, Christopher Meek, Bernd Sturmfels
Dependence and Relevance: A probabilistic view
Dan Geiger, David Heckerman
Asymptotic Model Selection for Naive Bayesian Networks
Dmitry Rusakov, Dan Geiger
Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (1997)
Dan Geiger, Prakash Shenoy
An Entropy-based Learning Algorithm of Bayesian Conditional Trees
Dan Geiger
Inference Algorithms for Similarity Networks
Dan Geiger, David Heckerman