Dan Geiger

发表

Word-level recognition of small sets of hand-written words

Amir Eliaz, Dan Geiger, 1995, Pattern Recognit. Lett..

Approximation Algorithms for the Feedback Vertex Set Problem with Applications to Constraint Satisfaction and Bayesian Inference

Reuven Bar-Yehuda, Joseph Naor, Ron M. Roth, 1998, SIAM J. Comput..

Randomized Algorithms for the Loop Cutset Problem

Reuven Bar-Yehuda, Dan Geiger, Ann Becker, 2000, J. Artif. Intell. Res..

Advances in Probabilistic Reasoning pdf

David Heckerman, Dan Geiger, D. Geiger, 1994, Conference on Uncertainty in Artificial Intelligence.

Learning Bayesian networks: The combination of knowledge and statistical data

David Maxwell Chickering, David Heckerman, Dan Geiger, 1995, Mach. Learn..

A Characterization of the Dirichlet Distribution Through Global and Local Independence

David Heckerman, Dan Geiger, D. Geiger, 1994, UAI 1994.

Likelihood Computations Using Value Abstraction

Nir Friedman, Dan Geiger, Noam Lotner, 2000, UAI.

Maximum Likelihood Haplotyping for General Pedigrees

Dan Geiger, Ma'ayan Fishelson, Nickolay Dovgolevsky, 2005, Human Heredity.

Probabilistic relevance relations

David Heckerman, Dan Geiger, D. Geiger, 1998, IEEE Trans. Syst. Man Cybern. Part A.

GridBot: execution of bags of tasks in multiple grids

Assaf Schuster, Mark Silberstein, Dan Geiger, 2009, Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis.

Efficient computation of sum-products on GPUs through software-managed cache

Anjul Patney, John D. Owens, Assaf Schuster, 2008, ICS '08.

Optimizing Exact Genetic Linkage Computations

Dan Geiger, Maáyan Fishelson, 2004, J. Comput. Biol..

Factorization of Discrete Probability Distributions pdf

Bernd Sturmfels, Christopher Meek, Dan Geiger, 2002, UAI.

Approximation algorithms for the vertex feedback set problem with applications to constraint satisfaction and Bayesian inference

Reuven Bar-Yehuda, Joseph Naor, Ron M. Roth, 1994, SODA '94.

Scheduling Mixed Workloads in Multi-grids: The Grid Execution Hierarchy

Miron Livny, Assaf Schuster, Mark Silberstein, 2006, 2006 15th IEEE International Conference on High Performance Distributed Computing.

Integration of SNP genotyping confidence scores in IBD inference

Dan Geiger, Barak Markus, Ohad S. Birk, 2011, Bioinform..

Structured Variational Inference Procedures and their Realizations

Christopher Meek, Dan Geiger, D. Geiger, 2005, AISTATS.

Optimization of Pearl's Method of Conditioning and Greedy-Like Approximation Algorithms for the Vertex Feedback Set Problem

Dan Geiger, Ann Becker, D. Geiger, 1996, Artif. Intell..

Learning Bayesian Networks: Search Methods and Experimental Results

David Heckerman, Dan Geiger, Max Chickering, 1995 .

Graphical Models and Exponential Families pdf

Dan Geiger, D. Geiger, 1998, UAI.

Variational Upper Bounds for Probabilistic Phylogenetic Models

Dan Geiger, Ydo Wexler, D. Geiger, 2007, RECOMB.

A sufficiently fast algorithm for finding close to optimal junction trees

Dan Geiger, Ann Becker, D. Geiger, 1996, UAI.

Approximation Algorithms for the Loop Cutset Problem

Dan Geiger, Ann Becker, D. Geiger, 1994, UAI.

Finding approximate tandem repeats in genomic sequences.

Dan Geiger, Zohar Yakhini, Ydo Wexler, 2005, Journal of computational biology : a journal of computational molecular cell biology.

Finding approximate tandem repeats in genomic sequences

Dan Geiger, Zohar Yakhini, Ydo Wexler, 2004, RECOMB.

Learning Causal Trees from Dependence Information

Dan Geiger, Judea Pearl, Azaria Paz, 1990, AAAI.

Learning Gaussian Networks

David Heckerman, Dan Geiger, D. Geiger, 1994, UAI.

An Entropy-based Learning Algorithm of Bayesian Conditional Trees

Dan Geiger, D. Geiger, 1992, UAI.

Axioms and Algorithms for Inferences Involving Probabilistic Independence

Dan Geiger, Judea Pearl, Azaria Paz, 1991, Inf. Comput..

Probabilistic Reactive Disassembly Planning

Dan Geiger, E. Lenz, E. Zussmann, 1996 .

Admixture Aberration Analysis: Application to Mapping in Admixed Population Using Pooled DNA

Dan Geiger, Sivan Bercovici, 2010, RECOMB.

On the logic of causal models pdf

Dan Geiger, Judea Pearl, J. Pearl, 2013, UAI.

Inference Algorithms for Similarity Networks

David Heckerman, Dan Geiger, D. Geiger, 1993, UAI.

Estimating genome-wide IBD sharing from SNP data via an efficient hidden Markov model of LD with application to gene mapping

Christopher Meek, Dan Geiger, Ydo Wexler, 2010, Bioinform..

Optimizing exact genetic linkage computations

Dan Geiger, Maáyan Fishelson, D. Geiger, 2003, RECOMB '03.

Importance Sampling via Variational Optimization

Dan Geiger, Ydo Wexler, D. Geiger, 2007, UAI.

A Practical Algorithm for Finding Optimal Triangulations

Dan Geiger, Kirill Shoikhet, D. Geiger, 1997, AAAI/IAAI.

Learning Bayesian Networks: The Combination of Knowledge and Statistical Data

David Maxwell Chickering, David Heckerman, Dan Geiger, 1994, Machine Learning.

Random Algorithms for the Loop Cutset Problem pdf

Reuven Bar-Yehuda, Dan Geiger, Ann Becker, 1999, UAI.

Density-based indexing for approximate nearest-neighbor queries

Kristin P. Bennett, Dan Geiger, Usama M. Fayyad, 1999, KDD '99.

Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models

Dan Geiger, Dmitry M. Rusakov, Dmitry Rusakov, 2002, UAI.

Variational Upper and Lower Bounds for Probabilistic Graphical Models

Dan Geiger, Ydo Wexler, D. Geiger, 2008, J. Comput. Biol..

Admixture Aberration Analysis: Application to Mapping in Admixed Population Using Pooled DNA

Dan Geiger, Sivan Bercovici, D. Geiger, 2010, RECOMB.

Model-Based Inference of Haplotype Block Variation

Dan Geiger, Gideon Greenspan, 2004, J. Comput. Biol..

Model-based inference of haplotype block variation

Dan Geiger, Gideon Greenspan, D. Geiger, 2003, RECOMB '03.

Likelihood Computations Using Value Abstractions pdf

Nir Friedman, Dan Geiger, Noam Lotner, 2013, ArXiv.

Practical and Theoretical Advances in Knowledge Acquisition of Probabilistic Networks pdf

David Heckerman, Dan Geiger, 2013, ArXiv.

Speeding up HMM algorithms for genetic linkage analysis via chain reductions of the state space

Christopher Meek, Dan Geiger, Ydo Wexler, 2009, Bioinform..

Optimal Satisficing Tree Searches

Dan Geiger, Jeffrey A. Barnett, D. Geiger, 1991, AAAI.

Efficient approximations for learning phylogenetic HMM models from data

Nebojsa Jojic, David Haussler, David Heckerman, 2004, ISMB/ECCB.

A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees

Lars Otten, Mark Silberstein, Rina Dechter, 2013, Bioinform..

Sci-LMM is an efficient strategy for inferring genetic variance components using population scale family trees

Dan Geiger, Yaniv Erlich, Tal Shor, 2018, bioRxiv.

Separable and Transitive Graphoids

David Heckerman, Dan Geiger, D. Geiger, 1990, UAI.

On Finding a Cycle Basis with a Shortest Maximal Cycle

David Maxwell Chickering, David Heckerman, Dan Geiger, 1995, Inf. Process. Lett..

Dependence and Relevance: A probabilistic view pdf

David Heckerman, Dan Geiger, D. Geiger, 2016, ArXiv.

Knowledge Representation and Inference in Similarity Networks and Bayesian Multinets

David Heckerman, Dan Geiger, D. Geiger, 1996, Artif. Intell..

Inferring Ancestries Efficiently in Admixed Populations with Linkage Disequilibrium

Dan Geiger, Sivan Bercovici, D. Geiger, 2022 .

Sci-LMM is an efficient strategy for inferring genetic variance components using population scale family trees

Dan Geiger, Tal Shor, D. Geiger, 2018, bioRxiv.

Identifying independence in bayesian networks

Dan Geiger, Judea Pearl, Thomas Verma, 1990, Networks.

A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks pdf

David Heckerman, Dan Geiger, D. Geiger, 1995, UAI.

A Distributed System for Genetic Linkage Analysis

Assaf Schuster, Mark Silberstein, Dan Geiger, 2007, GCCB.

Asymptotic Model Selection for Directed Networks with Hidden Variables

David Heckerman, Christopher Meek, Dan Geiger, 1996, UAI.

Bayesian Network Classifiers

Nir Friedman, Dan Geiger, Moisés Goldszmidt, 1997, Machine Learning.

High density linkage disequilibrium mapping using models of haplotype block variation

Dan Geiger, Gideon Greenspan, D. Geiger, 2004, ISMB/ECCB.

Perfect Tree-like Markovian Distributions

Christopher Meek, Dan Geiger, Ann Becker, 2000, UAI.

A Distance-Based Branch and Bound Feature Selection Algorithm

Dan Geiger, Zohar Yakhini, Ari Frank, 2002, UAI.

On Testing Whether an Embedded Bayesian Network Represents a Probability Model

Dan Geiger, Judea Pearl, Azaria Paz, 1994, UAI.

Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains pdf

David Heckerman, Dan Geiger, D. Geiger, 1995, UAI.

Estimation of flows in flow networks

Dan Geiger, Ron Zohar, D. Geiger, 2007, Eur. J. Oper. Res..

Exact genetic linkage computations for general pedigrees

Dan Geiger, Maáyan Fishelson, D. Geiger, 2002, ISMB.

Panel Construction for Mapping in Admixed Populations Via Expected Mutual Information

Dan Geiger, Sivan Bercovici, Liran Shlush, 2008, RECOMB.

Automatic boosting of cross-product coverage using Bayesian networks

Avi Ziv, Laurent Fournier, Dan Geiger, 2009, International Journal on Software Tools for Technology Transfer.

A Variational Inference Procedure Allowing Internal Structure for Overlapping Clusters and Deterministic Constraints

Christopher Meek, Dan Geiger, Ydo Wexler, 2006, J. Artif. Intell. Res..

A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees

Lars Otten, Mark Silberstein, Rina Dechter, 2013, Bioinform..

Discrete Optimization Estimation of flows in flow networks

Dan Geiger, Ron Zohar, 2007 .

On Parameter Priors for Discrete DAG Models

Dan Geiger, Dmitry M. Rusakov, Dmitry Rusakov, 2001, AISTATS.

Logical and algorithmic properties of independence and their application to Bayesian networks

Dan Geiger, Judea Pearl, J. Pearl, 1990, Annals of Mathematics and Artificial Intelligence.

Mass Estimation of DNA Molecules and Extraction of Ordered Restriction Maps in Optical Mapping Imagery

Laxmi Parida, Dan Geiger, Laxmi Parida, 1999, Algorithmica.

Quantifier Elimination for Statistical Problems

Christopher Meek, Dan Geiger, D. Geiger, 1999, UAI.

d-Separation: From Theorems to Algorithms

Dan Geiger, Judea Pearl, Tom S. Verma, 2013, UAI.

Asymptotic Model Selection for Naive Bayesian Networks

Dan Geiger, Dmitry M. Rusakov, Dmitry Rusakov, 2002, J. Mach. Learn. Res..

Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions pdf

David Heckerman, Dan Geiger, D. Geiger, 1999, UAI.

On the geometry of DAG models with hidden variables

David Heckerman, Christopher Meek, Dan Geiger, 1999, AISTATS.

Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (1997) pdf

Prakash P. Shenoy, Dan Geiger, 2013, ArXiv.

A sufficiently fast algorithm for finding close to optimal clique trees

Dan Geiger, Ann Becker, D. Geiger, 2001, Artif. Intell..

Conditional independence and its representations

Dan Geiger, Judea Pearl, Thomas Verma, 1990, Kybernetika.

Stratiied Exponential Families: Graphical Models and Model Selection

David Heckerman, Dan Geiger, D. Geiger, 1998 .

Accurate liability estimation improves power in ascertained case-control studies

David Heckerman, Dan Geiger, Christoph Lippert, 2014, Nature Methods.

Quantitative analysis of population-scale family trees with millions of relatives

Dan Geiger, Yaniv Erlich, Melissa Gymrek, 2017, Science.

Maximum Likelihood Haplotyping through Parallelized Search on a Grid of Computers

Lars Otten, Mark Silberstein, Rina Dechter, 2009 .

A fast algorithm for finding junction trees 81 A sufficientlyfast algorithm for finding close to optimal junction trees

Dan Geiger, Ann Becker, 1996 .

Estimating variance components in population scale family trees

Dan Geiger, Yaniv Erlich, Tal Shor, 2019, PLoS genetics.

A Characterization of the Bivariate Normal-Wishart Distribution

David Heckerman, Dan Geiger, D. Geiger, 1995 .

Iterative Referencing for Improving the Interpretation of DNA Sequence Data

Dan Geiger, Alaa Ghanayim, D. Geiger, 2013 .

Multikernel linear mixed models for complex phenotype prediction

Dan Geiger, Saharon Rosset, Omer Weissbrod, 2016, Genome research.