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Dan Geiger: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Kristin P. Bennett, Usama M. Fayyad, Dan Geiger
    Density-Based Indexing for Approximate Nearest-Neighbor Queries. [Citation Graph (1, 0)][DBLP]
    KDD, 1999, pp:233-243 [Conf]
  2. David Heckerman, Dan Geiger, David Maxwell Chickering
    Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. [Citation Graph (1, 0)][DBLP]
    Machine Learning, 1995, v:20, n:3, pp:197-243 [Journal]
  3. Dan Geiger, Jeffrey A. Barnett
    Optimal Satisficing Tree Searches. [Citation Graph (0, 0)][DBLP]
    AAAI, 1991, pp:441-445 [Conf]
  4. Dan Geiger, Azaria Paz, Judea Pearl
    Learning Causal Trees from Dependence Information. [Citation Graph (0, 0)][DBLP]
    AAAI, 1990, pp:770-776 [Conf]
  5. Kirill Shoikhet, Dan Geiger
    A Practical Algorithm for Finding Optimal Triangulations. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1997, pp:185-190 [Conf]
  6. Gideon Greenspan, Dan Geiger
    High density linkage disequilibrium mapping using models of haplotype block variation. [Citation Graph (0, 0)][DBLP]
    ISMB/ECCB (Supplement of Bioinformatics), 2004, pp:137-144 [Conf]
  7. Maáyan Fishelson, Dan Geiger
    Exact genetic linkage computations for general pedigrees. [Citation Graph (0, 0)][DBLP]
    ISMB, 2002, pp:189-198 [Conf]
  8. Vladimir Jojic, Nebojsa Jojic, Christopher Meek, Dan Geiger, Adam C. Siepel, David Haussler, David Heckerman
    Efficient approximations for learning phylogenetic HMM models from data. [Citation Graph (0, 0)][DBLP]
    ISMB/ECCB (Supplement of Bioinformatics), 2004, pp:161-168 [Conf]
  9. David Heckerman, Dan Geiger, David Maxwell Chickering
    Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. [Citation Graph (0, 0)][DBLP]
    KDD Workshop, 1994, pp:85-96 [Conf]
  10. Maáyan Fishelson, Dan Geiger
    Optimizing exact genetic linkage computations. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2003, pp:114-121 [Conf]
  11. Gideon Greenspan, Dan Geiger
    Model-based inference of haplotype block variation. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2003, pp:131-137 [Conf]
  12. Ydo Wexler, Zohar Yakhini, Yechezkel Kashi, Dan Geiger
    Finding approximate tandem repeats in genomic sequences. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2004, pp:223-232 [Conf]
  13. Ydo Wexler, Dan Geiger
    Variational Upper Bounds for Probabilistic Phylogenetic Models. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2007, pp:226-237 [Conf]
  14. Reuven Bar-Yehuda, Dan Geiger, Joseph Naor, Ron M. Roth
    Approximation Algorithms for the Vertex Feedback Set Problem with Applications to Constraint Satisfaction and Bayesian Inference. [Citation Graph (0, 0)][DBLP]
    SODA, 1994, pp:344-354 [Conf]
  15. Ann Becker, Dan Geiger, Christopher Meek
    Perfect Tree-like Markovian Distributions. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:19-23 [Conf]
  16. Ann Becker, Reuven Bar-Yehuda, Dan Geiger
    Random Algorithms for the Loop Cutset Problem. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:49-56 [Conf]
  17. Ann Becker, Dan Geiger
    Approximation Algorithms for the Loop Cutset Problem. [Citation Graph (0, 0)][DBLP]
    UAI, 1994, pp:60-68 [Conf]
  18. Ann Becker, Dan Geiger
    A sufficiently fast algorithm for finding close to optimal junction trees. [Citation Graph (0, 0)][DBLP]
    UAI, 1996, pp:81-89 [Conf]
  19. Ari Frank, Dan Geiger, Zohar Yakhini
    A Distance-Based Branch and Bound Feature Selection Algorithm. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:241-248 [Conf]
  20. Nir Friedman, Dan Geiger, Noam Lotner
    Likelihood Computations Using Value Abstraction. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:192-200 [Conf]
  21. Dan Geiger
    An Entropy-based Learning Algorithm of Bayesian Conditional Trees. [Citation Graph (0, 0)][DBLP]
    UAI, 1992, pp:92-97 [Conf]
  22. Dan Geiger
    Graphical Models and Exponential Families. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:156-165 [Conf]
  23. Dan Geiger, James Cussens
    Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:216-225 [Conf]
  24. Dan Geiger, David Heckerman
    separable and transitive graphoids. [Citation Graph (0, 0)][DBLP]
    UAI, 1990, pp:65-76 [Conf]
  25. Dan Geiger, David Heckerman
    Advances in Probabilistic Reasoning. [Citation Graph (0, 0)][DBLP]
    UAI, 1991, pp:118-126 [Conf]
  26. Dan Geiger, David Heckerman
    Inference Algorithms for Similarity Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1993, pp:326-334 [Conf]
  27. Dan Geiger, David Heckerman
    Learning Gaussian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1994, pp:235-243 [Conf]
  28. Dan Geiger, David Heckerman
    A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1995, pp:196-207 [Conf]
  29. Dan Geiger, David Heckerman, Christopher Meek
    Asymptotic Model Selection for Directed Networks with Hidden Variables. [Citation Graph (0, 0)][DBLP]
    UAI, 1996, pp:283-290 [Conf]
  30. Dan Geiger, Christopher Meek
    Quantifier Elimination for Statistical Problems. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:226-235 [Conf]
  31. Dan Geiger, Christopher Meek, Bernd Sturmfels
    Factorization of Discrete Probability Distributions. [Citation Graph (0, 0)][DBLP]
    UAI, 2002, pp:162-169 [Conf]
  32. Dan Geiger, Judea Pearl
    On the logic of causal models. [Citation Graph (0, 0)][DBLP]
    UAI, 1988, pp:3-14 [Conf]
  33. Dan Geiger, Azaria Paz, Judea Pearl
    On Testing Whether an Embedded Bayesian Network Represents a Probability Model. [Citation Graph (0, 0)][DBLP]
    UAI, 1994, pp:244-252 [Conf]
  34. Dan Geiger, Thomas Verma, Judea Pearl
    d-Separation: From Theorems to Algorithms. [Citation Graph (0, 0)][DBLP]
    UAI, 1989, pp:139-148 [Conf]
  35. David Heckerman, Dan Geiger, David Maxwell Chickering
    Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. [Citation Graph (0, 0)][DBLP]
    UAI, 1994, pp:293-301 [Conf]
  36. David Heckerman, Dan Geiger
    Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains. [Citation Graph (0, 0)][DBLP]
    UAI, 1995, pp:274-284 [Conf]
  37. Dmitry Rusakov, Dan Geiger
    Asymptotic Model Selection for Naive Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2002, pp:438-445 [Conf]
  38. Dmitry Rusakov, Dan Geiger
    Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:501-508 [Conf]
  39. Mark Silberstein, Dan Geiger, Assaf Schuster
    A Distributed System for Genetic Linkage Analysis. [Citation Graph (0, 0)][DBLP]
    GCCB, 2006, pp:110-123 [Conf]
  40. Ann Becker, Dan Geiger
    A sufficiently fast algorithm for finding close to optimal clique trees. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2001, v:125, n:1-2, pp:3-17 [Journal]
  41. Ann Becker, Dan Geiger
    Optimization of Pearl's Method of Conditioning and Greedy-Like Approximation Algorithms for the Vertex Feedback Set Problem. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1996, v:83, n:1, pp:167-188 [Journal]
  42. Dan Geiger, David Heckerman
    Knowledge Representation and Inference in Similarity Networks and Bayesian Multinets. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1996, v:82, n:1-2, pp:45-74 [Journal]
  43. Laxmi Parida, Dan Geiger
    Mass Estimation of DNA Molecules and Extraction of Ordered Restriction Maps in Optical Mapping Imagery. [Citation Graph (0, 0)][DBLP]
    Algorithmica, 1999, v:25, n:2-3, pp:295-310 [Journal]
  44. Dan Geiger, Judea Pearl
    Logical and algorithmic properties of independence and their application to Bayesian networks. [Citation Graph (0, 0)][DBLP]
    Ann. Math. Artif. Intell., 1990, v:2, n:, pp:165-178 [Journal]
  45. Dan Geiger, Azaria Paz, Judea Pearl
    Axioms and Algorithms for Inferences Involving Probabilistic Independence [Citation Graph (0, 0)][DBLP]
    Inf. Comput., 1991, v:91, n:1, pp:128-141 [Journal]
  46. David Maxwell Chickering, Dan Geiger, David Heckerman
    On Finding a Cycle Basis with a Shortest Maximal Cycle. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Lett., 1995, v:54, n:1, pp:55-58 [Journal]
  47. Ann Becker, Reuven Bar-Yehuda, Dan Geiger
    Randomized Algorithms for the Loop Cutset Problem. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2000, v:12, n:, pp:219-234 [Journal]
  48. Maáyan Fishelson, Dan Geiger
    Optimizing Exact Genetic Linkage Computations. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2004, v:11, n:2/3, pp:263-275 [Journal]
  49. Gideon Greenspan, Dan Geiger
    Model-Based Inference of Haplotype Block Variation. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2004, v:11, n:2/3, pp:493-504 [Journal]
  50. Dmitry Rusakov, Dan Geiger
    Asymptotic Model Selection for Naive Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:1-35 [Journal]
  51. Nir Friedman, Dan Geiger, Moisés Goldszmidt
    Bayesian Network Classifiers. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1997, v:29, n:2-3, pp:131-163 [Journal]
  52. Amir Eliaz, Dan Geiger
    Word-level recognition of small sets of hand-written words. [Citation Graph (0, 0)][DBLP]
    Pattern Recognition Letters, 1995, v:16, n:10, pp:999-1009 [Journal]
  53. Reuven Bar-Yehuda, Dan Geiger, Joseph Naor, Ron M. Roth
    Approximation Algorithms for the Feedback Vertex Set Problem with Applications to Constraint Satisfaction and Bayesian Inference. [Citation Graph (0, 0)][DBLP]
    SIAM J. Comput., 1998, v:27, n:4, pp:942-959 [Journal]
  54. Dan Geiger, David Heckerman
    Probabilistic relevance relations. [Citation Graph (0, 0)][DBLP]
    IEEE Transactions on Systems, Man, and Cybernetics, Part A, 1998, v:28, n:1, pp:17-25 [Journal]
  55. Ron Zohar, Dan Geiger
    Estimation of flows in flow networks. [Citation Graph (0, 0)][DBLP]
    European Journal of Operational Research, 2007, v:176, n:2, pp:691-706 [Journal]
  56. Dan Geiger, Christopher Meek, Ydo Wexler
    A Variational Inference Procedure Allowing Internal Structure for Overlapping Clusters and Deterministic Constraints. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 2006, v:27, n:, pp:1-23 [Journal]

  57. Scheduling Mixed Workloads in Multi-grids: The Grid Execution Hierarchy. [Citation Graph (, )][DBLP]


  58. Efficient computation of sum-products on GPUs through software-managed cache. [Citation Graph (, )][DBLP]


  59. Panel Construction for Mapping in Admixed Populations Via Expected Mutual Information. [Citation Graph (, )][DBLP]


  60. Admixture Aberration Analysis: Application to Mapping in Admixed Population Using Pooled DNA. [Citation Graph (, )][DBLP]


  61. GridBot: execution of bags of tasks in multiple grids. [Citation Graph (, )][DBLP]


  62. Speeding up HMM algorithms for genetic linkage analysis via chain reductions of the state space. [Citation Graph (, )][DBLP]


  63. Estimating genome-wide IBD sharing from SNP data via an efficient hidden Markov model of LD with application to gene mapping. [Citation Graph (, )][DBLP]


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