Geiger, Dan

35 publications

UAI 2007 Importance Sampling via Variational Optimization Ydo Wexler, Dan Geiger

JAIR 2006 A Variational Inference Procedure Allowing Internal Structure for Overlapping Clusters and Deterministic Constraints Dan Geiger, Christopher Meek, Ydo Wexler

JMLR 2005 Asymptotic Model Selection for Naive Bayesian Networks Dmitry Rusakov, Dan Geiger

AISTATS 2005 Structured Variational Inference Procedures and Their Realizations Dan Geiger, Chris Meek

UAI 2003 A Distance-Based Branch and Bound Feature Selection Algorithm Ari Frank, Dan Geiger, Zohar Yakhini

UAI 2003 Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models Dmitry Rusakov, Dan Geiger

UAI 2002 Asymptotic Model Selection for Naive Bayesian Networks Dmitry Rusakov, Dan Geiger

UAI 2002 Factorization of Discrete Probability Distributions Dan Geiger, Christopher Meek, Bernd Sturmfels

AISTATS 2001 On Parameter Priors for Discrete DAG Models Dmitry Rusakov, Dan Geiger

UAI 2000 Likelihood Computations Using Value Abstraction Nir Friedman, Dan Geiger, Noam Lotner

UAI 2000 Perfect Tree-like Markovian Distributions Ann Becker, Dan Geiger, Christopher Meek

JAIR 2000 Randomized Algorithms for the Loop Cutset Problem Ann Becker, Reuven Bar-Yehuda, Dan Geiger

AISTATS 1999 On the Geometry of DAG Models with Hidden Variables Dan Geiger, David Heckerman, Henry King, Christopher Meek

UAI 1999 Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions Dan Geiger, David Heckerman

UAI 1999 Quantifier Elimination for Statistical Problems Dan Geiger, Christopher Meek

UAI 1999 Random Algorithms for the Loop Cutset Problem Ann Becker, Reuven Bar-Yehuda, Dan Geiger

UAI 1998 Graphical Models and Exponential Families Dan Geiger

AAAI 1997 A Practical Algorithm for Finding Optimal Triangulations Kirill Shoikhet, Dan Geiger

MLJ 1997 Bayesian Network Classifiers Nir Friedman, Dan Geiger, Moisés Goldszmidt

UAI 1997 UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, Brown University, Providence, Rhode Island, USA, August 1-3, 1997 Dan Geiger, Prakash P. Shenoy

UAI 1996 A Sufficiently Fast Algorithm for Finding Close to Optimal Junction Trees Ann Becker, Dan Geiger

UAI 1996 Asymptotic Model Selection for Directed Networks with Hidden Variables Dan Geiger, David Heckerman, Christopher Meek

UAI 1995 A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks Dan Geiger, David Heckerman

UAI 1995 Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains David Heckerman, Dan Geiger

AISTATS 1995 Learning Bayesian Networks: Search Methods and Experimental Results David Maxwell Chickering, Dan Geiger, David Heckerman

MLJ 1995 Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman, Dan Geiger, David Maxwell Chickering

UAI 1994 Approximation Algorithms for the Loop Cutset Problem Ann Becker, Dan Geiger

UAI 1994 Learning Bayesian Networks: The Combination of Knowledge and Statistical Data David Heckerman, Dan Geiger, David Maxwell Chickering

UAI 1994 Learning Gaussian Networks Dan Geiger, David Heckerman

UAI 1994 On Testing Whether an Embedded Bayesian Network Represents a Probability Model Dan Geiger, Azaria Paz, Judea Pearl

UAI 1993 Inference Algorithms for Similarity Networks Dan Geiger, David Heckerman

UAI 1992 An Entropy-Based Learning Algorithm of Bayesian Conditional Trees Dan Geiger

AAAI 1991 Optimal Satisficing Tree Searches Dan Geiger, Jeffrey A. Barnett

AAAI 1990 Learning Causal Trees from Dependence Information Dan Geiger, Azaria Paz, Judea Pearl

UAI 1990 Separable and Transitive Graphoids Dan Geiger, David Heckerman