Dan Geiger - RankMe

109 papers A* 4A 33B 6Journal 60Unranked 5

Year	Rank	Type	Title / Venue / Authors
2021	J	`jnl`	Likelihoods and Parameter Priors for Bayesian Networks. CoRR David Heckerman, Dan Geiger
2021	J	`jnl`	Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions. CoRR Dan Geiger, David Heckerman
2016	J	`jnl`	Dependence and Relevance: A probabilistic view. CoRR Dan Geiger, David Heckerman
2014	J	`jnl`	Random Algorithms for the Loop Cutset Problem. CoRR Ann Becker, Reuven Bar-Yehuda, Dan Geiger
2013	J	`jnl`	A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks CoRR Dan Geiger, David Heckerman
2013	J	`jnl`	A Sufficiently Fast Algorithm for Finding Close to Optimal Junction Trees CoRR Ann Becker, Dan Geiger
2013	J	`jnl`	A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees. Bioinform. Mark Silberstein, Omer Weissbrod, Lars Otten, Anna Tzemach, Andrei Anisenia, Oren Shtark, Dvir Tuberg, Eddie Galfrin, Irena Gannon, Adel Shalata, Zvi U. Borochowitz, Rina Dechter, Elizabeth Thompson, Dan Geiger
2013	J	`jnl`	A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees. Bioinform. Mark Silberstein, Omer Weissbrod, Lars Otten, Anna Tzemach, Andrei Anisenia, Oren Shtark, Dvir Tuberg, Eddie Galfrin, Irena Gannon, Adel Shalata, Zvi U. Borochowitz, Rina Dechter, Elizabeth Thompson, Dan Geiger
2013	J	`jnl`	Advances in Probabilistic Reasoning CoRR Dan Geiger, David Heckerman
2013	J	`jnl`	An Entropy-based Learning Algorithm of Bayesian Conditional Trees CoRR Dan Geiger
2013	J	`jnl`	Approximation Algorithms for the Loop Cutset Problem CoRR Ann Becker, Dan Geiger
2013	J	`jnl`	Asymptotic Model Selection for Directed Networks with Hidden Variables CoRR Dan Geiger, David Heckerman, Christopher Meek
2013	J	`jnl`	Asymptotic Model Selection for Naive Bayesian Networks CoRR Dmitry Rusakov, Dan Geiger
2013	J	`jnl`	Factorization of Discrete Probability Distributions CoRR Dan Geiger, Christopher Meek, Bernd Sturmfels
2013	J	`jnl`	Graphical Models and Exponential Families CoRR Dan Geiger, Christopher Meek
2013	J	`jnl`	Inference Algorithms for Similarity Networks CoRR Dan Geiger, David Heckerman
2013	J	`jnl`	Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains CoRR David Heckerman, Dan Geiger
2013	J	`jnl`	Learning Bayesian Networks: The Combination of Knowledge and Statistical Data CoRR David Heckerman, Dan Geiger, David Maxwell Chickering
2013	J	`jnl`	Learning Gaussian Networks CoRR Dan Geiger, David Heckerman
2013	J	`jnl`	Likelihood Computations Using Value Abstractions CoRR Nir Friedman, Dan Geiger, Noam Lotner
2013	J	`jnl`	On Testing Whether an Embedded Bayesian Network Represents a Probability Model CoRR Dan Geiger, Azaria Paz, Judea Pearl
2013	J	`jnl`	On the Logic of Causal Models CoRR Dan Geiger, Judea Pearl
2013	J	`jnl`	Parameter Priors for Directed Acyclic Graphical Models and the Characterization of Several Probability Distributions CoRR Dan Geiger, David Heckerman
2013	J	`jnl`	Perfect Tree-Like Markovian Distributions CoRR Ann Becker, Dan Geiger, Christopher Meek
2013	J	`jnl`	Practical and Theoretical Advances in Knowledge Acquisition of Probabilistic Networks CoRR Dan Geiger, David Heckerman
2013	J	`jnl`	Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (1997) CoRR Dan Geiger, Prakash P. Shenoy
2013	J	`jnl`	Quantifier Elimination for Statistical Problems CoRR Dan Geiger, Christopher Meek
2013	J	`jnl`	d-Separation: From Theorems to Algorithms CoRR Dan Geiger, Tom S. Verma, Judea Pearl
2012	J	`jnl`	A Distance-Based Branch and Bound Feature Selection Algorithm CoRR Ari Frank, Dan Geiger, Zohar Yakhini
2012	J	`jnl`	Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models CoRR Dmitry Rusakov, Dan Geiger
2012	J	`jnl`	Importance Sampling via Variational Optimization CoRR Ydo Wexler, Dan Geiger
2011	J	`jnl`	Admixture Aberration Analysis: Application to Mapping in Admixed Population Using Pooled DNA. J. Comput. Biol. Sivan Bercovici, Dan Geiger
2011	J	`jnl`	Automatic boosting of cross-product coverage using Bayesian networks. Int. J. Softw. Tools Technol. Transf. Dorit Baras, Shai Fine, Laurent Fournier, Dan Geiger, Avi Ziv
2011	J	`jnl`	Integration of SNP genotyping confidence scores in IBD inference. Bioinform. Barak Markus, Ohad S. Birk, Dan Geiger
2011	J	`jnl`	Randomized Algorithms for the Loop Cutset Problem CoRR Reuven Bar-Yehuda, Ann Becker, Dan Geiger
2010	B	`conf`	Admixture Aberration Analysis: Application to Mapping in Admixed Population Using Pooled DNA. RECOMB Sivan Bercovici, Dan Geiger
2010	J	`jnl`	Estimating genome-wide IBD sharing from SNP data via an efficient hidden Markov model of LD with application to gene mapping. Bioinform. Sivan Bercovici, Christopher Meek, Ydo Wexler, Dan Geiger
2009	A	`conf`	GridBot: execution of bags of tasks in multiple grids. SC Mark Silberstein, Artyom Sharov, Dan Geiger, Assaf Schuster
2009	J	`jnl`	Inferring Ancestries Efficiently in Admixed Populations with Linkage Disequilibrium. J. Comput. Biol. Sivan Bercovici, Dan Geiger
2009	J	`jnl`	Speeding up HMM algorithms for genetic linkage analysis via chain reductions of the state space. Bioinform. Dan Geiger, Christopher Meek, Ydo Wexler
2008	A	`conf`	Efficient computation of sum-products on GPUs through software-managed cache. ICS Mark Silberstein, Assaf Schuster, Dan Geiger, Anjul Patney, John D. Owens
2008	B	`conf`	Panel Construction for Mapping in Admixed Populations Via Expected Mutual Information. RECOMB Sivan Bercovici, Dan Geiger, Liran Shlush, Karl Skorecki, Alan A. Templeton
2008	J	`jnl`	Variational Upper and Lower Bounds for Probabilistic Graphical Models. J. Comput. Biol. Ydo Wexler, Dan Geiger
2007	J	`jnl`	Estimation of flows in flow networks. Eur. J. Oper. Res. Ron Zohar, Dan Geiger
2007	A	`conf`	Importance Sampling via Variational Optimization. UAI Ydo Wexler, Dan Geiger
2007	B	`conf`	Variational Upper Bounds for Probabilistic Phylogenetic Models. RECOMB Ydo Wexler, Dan Geiger
2006	—	`conf`	A Distributed System for Genetic Linkage Analysis. GCCB Mark Silberstein, Dan Geiger, Assaf Schuster
2006	J	`jnl`	A Variational Inference Procedure Allowing Internal Structure for Overlapping Clusters and Deterministic Constraints. J. Artif. Intell. Res. Dan Geiger, Christopher Meek, Ydo Wexler
2006	A	`conf`	Scheduling Mixed Workloads in Multi-grids: The Grid Execution Hierarchy. HPDC Mark Silberstein, Dan Geiger, Assaf Schuster, Miron Livny
2005	J	`jnl`	Asymptotic Model Selection for Naive Bayesian Networks. J. Mach. Learn. Res. Dmitry Rusakov, Dan Geiger
2005	J	`jnl`	Finding Approximate Tandem Repeats in Genomic Sequences. J. Comput. Biol. Ydo Wexler, Zohar Yakhini, Yechezkel Kashi, Dan Geiger
2005	A	`conf`	Structured Variational Inference Procedures and their Realizations. AISTATS Dan Geiger, Christopher Meek
2004	—	`conf`	Efficient approximations for learning phylogenetic HMM models from data. ISMB/ECCB (Supplement of Bioinformatics) Vladimir Jojic, Nebojsa Jojic, Christopher Meek, Dan Geiger, Adam C. Siepel, David Haussler, David Heckerman
2004	B	`conf`	Finding approximate tandem repeats in genomic sequences. RECOMB Ydo Wexler, Zohar Yakhini, Yechezkel Kashi, Dan Geiger
2004	—	`conf`	High density linkage disequilibrium mapping using models of haplotype block variation. ISMB/ECCB (Supplement of Bioinformatics) Gideon Greenspan, Dan Geiger
2004	J	`jnl`	Model-Based Inference of Haplotype Block Variation. J. Comput. Biol. Gideon Greenspan, Dan Geiger
2004	J	`jnl`	Optimizing Exact Genetic Linkage Computations. J. Comput. Biol. Maáyan Fishelson, Dan Geiger
2003	A	`conf`	A Distance-Based Branch and Bound Feature Selection Algorithm. UAI Ari Frank, Dan Geiger, Zohar Yakhini
2003	A	`conf`	Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models. UAI Dmitry Rusakov, Dan Geiger
2003	B	`conf`	Model-based inference of haplotype block variation. RECOMB Gideon Greenspan, Dan Geiger
2003	B	`conf`	Optimizing exact genetic linkage computations. RECOMB Maáyan Fishelson, Dan Geiger
2002	A	`conf`	Asymptotic Model Selection for Naive Bayesian Networks. UAI Dmitry Rusakov, Dan Geiger
2002	A	`conf`	Exact genetic linkage computations for general pedigrees. ISMB Maáyan Fishelson, Dan Geiger
2002	A	`conf`	Factorization of Discrete Probability Distributions. UAI Dan Geiger, Christopher Meek, Bernd Sturmfels
2001	J	`jnl`	A sufficiently fast algorithm for finding close to optimal clique trees. Artif. Intell. Ann Becker, Dan Geiger
2001	A	`conf`	On Parameter Priors for Discrete DAG Models. AISTATS Dmitry Rusakov, Dan Geiger
2000	A	`conf`	Likelihood Computations Using Value Abstraction. UAI Nir Friedman, Dan Geiger, Noam Lotner
2000	A	`conf`	Perfect Tree-like Markovian Distributions. UAI Ann Becker, Dan Geiger, Christopher Meek
2000	J	`jnl`	Randomized Algorithms for the Loop Cutset Problem. J. Artif. Intell. Res. Ann Becker, Reuven Bar-Yehuda, Dan Geiger
1999	A*	`conf`	Density-Based Indexing for Approximate Nearest-Neighbor Queries. KDD Kristin P. Bennett, Usama M. Fayyad, Dan Geiger
1999	J	`jnl`	Mass Estimation of DNA Molecules and Extraction of Ordered Restriction Maps in Optical Mapping Imagery. Algorithmica Laxmi Parida, Dan Geiger
1999	A	`conf`	On the geometry of DAG models with hidden variables. AISTATS Dan Geiger, David Heckerman, Henry King, Christopher Meek
1999	A	`conf`	Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions. UAI Dan Geiger, David Heckerman
1999	A	`conf`	Quantifier Elimination for Statistical Problems. UAI Dan Geiger, Christopher Meek
1999	A	`conf`	Random Algorithms for the Loop Cutset Problem. UAI Ann Becker, Reuven Bar-Yehuda, Dan Geiger
1998	J	`jnl`	Approximation Algorithms for the Feedback Vertex Set Problem with Applications to Constraint Satisfaction and Bayesian Inference. SIAM J. Comput. Reuven Bar-Yehuda, Dan Geiger, Joseph Naor, Ron M. Roth
1998	—	`ch.`	Asymptotic Model Selection for Directed Networks with Hidden Variables. Learning in Graphical Models Dan Geiger, David Heckerman, Christopher Meek
1998	A	`conf`	Graphical Models and Exponential Families. UAI Dan Geiger
1998	J	`jnl`	Probabilistic relevance relations. IEEE Trans. Syst. Man Cybern. Part A Dan Geiger, David Heckerman
1997	—	`conf`	A Practical Algorithm for Finding Optimal Triangulations. AAAI/IAAI Kirill Shoikhet, Dan Geiger
1997	J	`jnl`	Bayesian Network Classifiers. Mach. Learn. Nir Friedman, Dan Geiger, Moisés Goldszmidt
1997	A	`ed.`	UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, Brown University, Providence, Rhode Island, USA, August 1-3, 1997 UAI Dan Geiger, Prakash P. Shenoy
1996	A	`conf`	A sufficiently fast algorithm for finding close to optimal junction trees. UAI Ann Becker, Dan Geiger
1996	A	`conf`	Asymptotic Model Selection for Directed Networks with Hidden Variables. UAI Dan Geiger, David Heckerman, Christopher Meek
1996	J	`jnl`	Knowledge Representation and Inference in Similarity Networks and Bayesian Multinets. Artif. Intell. Dan Geiger, David Heckerman
1996	J	`jnl`	Optimization of Pearl's Method of Conditioning and Greedy-Like Approximation Algorithms for the Vertex Feedback Set Problem. Artif. Intell. Ann Becker, Dan Geiger
1995	A	`conf`	A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks. UAI Dan Geiger, David Heckerman
1995	A	`conf`	Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains. UAI David Heckerman, Dan Geiger
1995	J	`jnl`	Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. Mach. Learn. David Heckerman, Dan Geiger, David Maxwell Chickering
1995	J	`jnl`	On Finding a Cycle Basis with a Shortest Maximal Cycle. Inf. Process. Lett. David Maxwell Chickering, Dan Geiger, David Heckerman
1995	J	`jnl`	Word-level recognition of small sets of hand-written words. Pattern Recognit. Lett. Amir Eliaz, Dan Geiger
1994	A	`conf`	Approximation Algorithms for the Loop Cutset Problem. UAI Ann Becker, Dan Geiger
1994	A*	`conf`	Approximation Algorithms for the Vertex Feedback Set Problem with Applications to Constraint Satisfaction and Bayesian Inference. SODA Reuven Bar-Yehuda, Dan Geiger, Joseph Naor, Ron M. Roth
1994	—	`conf`	Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. KDD Workshop David Heckerman, Dan Geiger, David Maxwell Chickering
1994	A	`conf`	Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. UAI David Heckerman, Dan Geiger, David Maxwell Chickering
1994	A	`conf`	Learning Gaussian Networks. UAI Dan Geiger, David Heckerman
1994	A	`conf`	On Testing Whether an Embedded Bayesian Network Represents a Probability Model. UAI Dan Geiger, Azaria Paz, Judea Pearl
1993	A	`conf`	Inference Algorithms for Similarity Networks. UAI Dan Geiger, David Heckerman
1992	A	`conf`	An Entropy-based Learning Algorithm of Bayesian Conditional Trees. UAI Dan Geiger
1991	A	`conf`	Advances in Probabilistic Reasoning. UAI Dan Geiger, David Heckerman
1991	J	`jnl`	Axioms and Algorithms for Inferences Involving Probabilistic Independence Inf. Comput. Dan Geiger, Azaria Paz, Judea Pearl
1991	A*	`conf`	Optimal Satisficing Tree Searches. AAAI Dan Geiger, Jeffrey A. Barnett
1990	J	`jnl`	Identifying independence in bayesian networks. Networks Dan Geiger, Thomas Verma, Judea Pearl
1990	A*	`conf`	Learning Causal Trees from Dependence Information. AAAI Dan Geiger, Azaria Paz, Judea Pearl
1990	J	`jnl`	Logical and algorithmic properties of independence and their application to Bayesian networks. Ann. Math. Artif. Intell. Dan Geiger, Judea Pearl
1990	A	`conf`	separable and transitive graphoids. UAI Dan Geiger, David Heckerman
1989	J	`jnl`	Conditional independence and its representations. Kybernetika Judea Pearl, Dan Geiger, Thomas Verma
1989	A	`conf`	d-Separation: From Theorems to Algorithms. UAI Dan Geiger, Thomas Verma, Judea Pearl
1988	A	`conf`	On the logic of causal models. UAI Dan Geiger, Judea Pearl