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Nir Friedman: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Nir Friedman, Joseph Y. Halpern
    A Knowledge-Based Framework for Belief Change, Part II: Revision and Update. [Citation Graph (1, 0)][DBLP]
    KR, 1994, pp:190-201 [Conf]
  2. Craig Boutilier, Nir Friedman, Joseph Y. Halpern
    Belief Revision with Unreliable Observations. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1998, pp:127-134 [Conf]
  3. Richard Dearden, Nir Friedman, Stuart J. Russell
    Bayesian Q-Learning. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1998, pp:761-768 [Conf]
  4. Gal Elidan, Matan Ninio, Nir Friedman, Dale Shuurmans
    Data Perturbation for Escaping Local Maxima in Learning. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2002, pp:132-139 [Conf]
  5. Nir Friedman, Moisés Goldszmidt
    Building Classifiers Using Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 2, 1996, pp:1277-1284 [Conf]
  6. Nir Friedman, Joseph Y. Halpern
    Conditional Logics of Belief Change. [Citation Graph (0, 0)][DBLP]
    AAAI, 1994, pp:915-921 [Conf]
  7. Nir Friedman, Joseph Y. Halpern
    Plausibility Measures and Default Reasoning. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 2, 1996, pp:1297-1304 [Conf]
  8. Nir Friedman, Joseph Y. Halpern, Daphne Koller
    First-Order Conditional Logic Revisited. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, Vol. 2, 1996, pp:1305-1312 [Conf]
  9. Nir Friedman, Daphne Koller, Avi Pfeffer
    Structured Representation of Complex Stochastic Systems. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1998, pp:157-164 [Conf]
  10. Itay Mayrose, Nir Friedman, Tal Pupko
    A Gamma mixture model better accounts for among site rate heterogeneity. [Citation Graph (0, 0)][DBLP]
    ECCB/JBI, 2005, pp:158- [Conf]
  11. Nir Friedman
    Probabilistic models for identifying regulation networks. [Citation Graph (0, 0)][DBLP]
    ECCB, 2003, pp:57- [Conf]
  12. Nir Friedman
    Learning Belief Networks in the Presence of Missing Values and Hidden Variables. [Citation Graph (0, 0)][DBLP]
    ICML, 1997, pp:125-133 [Conf]
  13. Nir Friedman, Moisés Goldszmidt
    Discretizing Continuous Attributes While Learning Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    ICML, 1996, pp:157-165 [Conf]
  14. Nir Friedman, Moisés Goldszmidt, Thomas J. Lee
    Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:179-187 [Conf]
  15. Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar
    Learning Probabilistic Models of Relational Structure. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:170-177 [Conf]
  16. Ronen I. Brafman, Nir Friedman
    On Decision-Theoretic Foundations for Defaults. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1995, pp:1458-1465 [Conf]
  17. Nir Friedman, Moisés Goldszmidt, David Heckerman, Stuart J. Russell
    Challenge: What is the Impact of Bayesian Networks on Learning? [Citation Graph (0, 0)][DBLP]
    IJCAI (1), 1997, pp:10-15 [Conf]
  18. Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer
    Learning Probabilistic Relational Models. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1999, pp:1300-1309 [Conf]
  19. Iftach Nachman, Aviv Regev, Nir Friedman
    Inferring quantitative models of regulatory networks from expression data. [Citation Graph (0, 0)][DBLP]
    ISMB/ECCB (Supplement of Bioinformatics), 2004, pp:248-256 [Conf]
  20. Dana Pe'er, Aviv Regev, Gal Elidan, Nir Friedman
    Inferring subnetworks from perturbed expression profiles. [Citation Graph (0, 0)][DBLP]
    ISMB (Supplement of Bioinformatics), 2001, pp:215-224 [Conf]
  21. Eran Segal, Benjamin Taskar, Audrey Gasch, Nir Friedman, Daphne Koller
    Rich probabilistic models for gene expression. [Citation Graph (0, 0)][DBLP]
    ISMB (Supplement of Bioinformatics), 2001, pp:243-252 [Conf]
  22. Nir Friedman, Joseph Y. Halpern
    On the Complexity of Conditional Logics. [Citation Graph (0, 0)][DBLP]
    KR, 1994, pp:202-213 [Conf]
  23. Nir Friedman, Joseph Y. Halpern
    Belief Revision: A Critique. [Citation Graph (0, 0)][DBLP]
    KR, 1996, pp:421-431 [Conf]
  24. Joseph Y. Halpern, Nir Friedman
    Plausibility Measures and Default Reasoning: An Overview. [Citation Graph (0, 0)][DBLP]
    LICS, 1999, pp:130-135 [Conf]
  25. David Andre, Nir Friedman, Ronald Parr
    Generalized Prioritized Sweeping. [Citation Graph (0, 0)][DBLP]
    NIPS, 1997, pp:- [Conf]
  26. Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller
    Discovering Hidden Variables: A Structure-Based Approach. [Citation Graph (0, 0)][DBLP]
    NIPS, 2000, pp:479-485 [Conf]
  27. Nir Friedman, Yoram Singer
    Efficient Bayesian Parameter Estimation in Large Discrete Domains. [Citation Graph (0, 0)][DBLP]
    NIPS, 1998, pp:417-423 [Conf]
  28. Noam Slonim, Nir Friedman, Naftali Tishby
    Agglomerative Multivariate Information Bottleneck. [Citation Graph (0, 0)][DBLP]
    NIPS, 2001, pp:929-936 [Conf]
  29. Amir Ben-Dor, Laurakay Bruhn, Nir Friedman, Iftach Nachman, Michèl Schummer, Zohar Yakhini
    Tissue classification with gene expression profiles. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2000, pp:54-64 [Conf]
  30. Amir Ben-Dor, Nir Friedman, Zohar Yakhini
    Class discovery in gene expression data. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2001, pp:31-38 [Conf]
  31. Yoseph Barash, Gal Elidan, Nir Friedman, Tommy Kaplan
    Modeling dependencies in protein-DNA binding sites. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2003, pp:28-37 [Conf]
  32. Yoseph Barash, Nir Friedman
    Context-specific Bayesian clustering for gene expression data. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2001, pp:12-21 [Conf]
  33. Ariel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman
    Towards an Integrated Protein-Protein Interaction Network. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2005, pp:14-30 [Conf]
  34. Tommy Kaplan, Nir Friedman, Hanah Margalit
    Predicting Transcription Factor Binding Sites Using Structural Knowledge. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2005, pp:522-537 [Conf]
  35. Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er
    Using Bayesian networks to analyze expression data. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2000, pp:127-135 [Conf]
  36. Nir Friedman, Matan Ninio, Itsik Pe'er, Tal Pupko
    A structural EM algorithm for phylogenetic inference. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2001, pp:132-140 [Conf]
  37. Eran Segal, Yoseph Barash, Itamar Simon, Nir Friedman, Daphne Koller
    From promoter sequence to expression: a probabilistic framework. [Citation Graph (0, 0)][DBLP]
    RECOMB, 2002, pp:263-272 [Conf]
  38. Shai Shalev-Shwartz, Shlomo Dubnov, Nir Friedman, Yoram Singer
    Robust temporal and spectral modeling for query By melody. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2002, pp:331-338 [Conf]
  39. Noam Slonim, Nir Friedman, Naftali Tishby
    Unsupervised document classification using sequential information maximization. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2002, pp:129-136 [Conf]
  40. Nir Friedman, Joseph Y. Halpern
    A Knowledge-Based Framework for Belief change, Part I: Foundations. [Citation Graph (0, 0)][DBLP]
    TARK, 1994, pp:44-64 [Conf]
  41. Xavier Boyen, Nir Friedman, Daphne Koller
    Discovering the Hidden Structure of Complex Dynamic Systems. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:91-100 [Conf]
  42. Craig Boutilier, Nir Friedman, Moisés Goldszmidt, Daphne Koller
    Context-Specific Independence in Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1996, pp:115-123 [Conf]
  43. Richard Dearden, Nir Friedman, David Andre
    Model based Bayesian Exploration. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:150-159 [Conf]
  44. Tal El-Hay, Nir Friedman
    Incorporating Expressive Graphical Models in VariationalApproximations: Chain-graphs and Hidden Variables. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:136-143 [Conf]
  45. Gal Elidan, Nir Friedman
    Learning the Dimensionality of Hidden Variables. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:144-151 [Conf]
  46. Gal Elidan, Nir Friedman
    The Information Bottleneck EM Algorithm. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:200-208 [Conf]
  47. Nir Friedman
    The Bayesian Structural EM Algorithm. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:129-138 [Conf]
  48. Nir Friedman, Moisés Goldszmidt
    Learning Bayesian Networks with Local Structure. [Citation Graph (0, 0)][DBLP]
    UAI, 1996, pp:252-262 [Conf]
  49. Nir Friedman, Moisés Goldszmidt
    Sequential Update of Bayesian Network Structure. [Citation Graph (0, 0)][DBLP]
    UAI, 1997, pp:165-174 [Conf]
  50. Nir Friedman, Dan Geiger, Noam Lotner
    Likelihood Computations Using Value Abstraction. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:192-200 [Conf]
  51. Nir Friedman, Moisés Goldszmidt, Abraham Wyner
    Data Analysis with Bayesian Networks: A Bootstrap Approach. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:196-205 [Conf]
  52. Nir Friedman, Joseph Y. Halpern
    Plausibility Measures: A User's Guide. [Citation Graph (0, 0)][DBLP]
    UAI, 1995, pp:175-184 [Conf]
  53. Nir Friedman, Joseph Y. Halpern
    A Qualitative Markov Assumption and Its Implications for Belief Change. [Citation Graph (0, 0)][DBLP]
    UAI, 1996, pp:263-273 [Conf]
  54. Nir Friedman, Daphne Koller
    Being Bayesian about Network Structure. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:201-210 [Conf]
  55. Nir Friedman, Kevin P. Murphy, Stuart J. Russell
    Learning the Structure of Dynamic Probabilistic Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1998, pp:139-147 [Conf]
  56. Nir Friedman, Ori Mosenzon, Noam Slonim, Naftali Tishby
    Multivariate Information Bottleneck. [Citation Graph (0, 0)][DBLP]
    UAI, 2001, pp:152-161 [Conf]
  57. Nir Friedman, Iftach Nachman
    Gaussian Process Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2000, pp:211-219 [Conf]
  58. Nir Friedman, Iftach Nachman, Dana Pe'er
    Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm. [Citation Graph (0, 0)][DBLP]
    UAI, 1999, pp:206-215 [Conf]
  59. Nir Friedman, Stuart J. Russell
    Image Segmentation in Video Sequences: A Probabilistic Approach. [Citation Graph (0, 0)][DBLP]
    UAI, 1997, pp:175-181 [Conf]
  60. Nir Friedman, Zohar Yakhini
    On the Sample Complexity of Learning Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 1996, pp:274-282 [Conf]
  61. Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
    Learning Module Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:525-534 [Conf]
  62. Yoseph Barash, Gill Bejerano, Nir Friedman
    A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites. [Citation Graph (0, 0)][DBLP]
    WABI, 2001, pp:278-293 [Conf]
  63. Ronen I. Brafman, Nir Friedman
    On decision-theoretic foundations for defaults. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2001, v:133, n:1-2, pp:1-33 [Journal]
  64. Nir Friedman, Joseph Y. Halpern
    Modeling Belief in Dynamic Systems, Part I: Foundations. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 1997, v:95, n:2, pp:257-316 [Journal]
  65. Yoseph Barash, Elinor Dehan, Meir Krupsky, Wilbur Franklin, Marc Geraci, Nir Friedman, Naftali Kaminski
    Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2004, v:20, n:6, pp:839-846 [Journal]
  66. Yoseph Barash, Gal Elidan, Tommy Kaplan, Nir Friedman
    Y. Barash, G. Elidan, T. Kaplan, , N. Friedman. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2005, v:21, n:5, pp:596-600 [Journal]
  67. Tal Pupko, Itsik Pe'er, Masami Hasegawa, Dan Graur, Nir Friedman
    A branch-and-bound algorithm for the inference of ancestral amino-acid sequences when the replacement rate varies among sites: Application to the evolution of five gene families. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2002, v:18, n:8, pp:1116-1123 [Journal]
  68. Matan Ninio, Eyal Privman, Tal Pupko, Nir Friedman
    Phylogeny reconstruction: increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates. [Citation Graph (0, 0)][DBLP]
    Bioinformatics, 2007, v:23, n:2, pp:136-141 [Journal]
  69. Nir Friedman, Joseph Y. Halpern
    Belief Revision: A Critique [Citation Graph (0, 0)][DBLP]
    CoRR, 2001, v:0, n:, pp:- [Journal]
  70. Nir Friedman, Joseph Y. Halpern
    Modeling Belief in Dynamic Systems, Part I: Foundations [Citation Graph (0, 0)][DBLP]
    CoRR, 2003, v:0, n:, pp:- [Journal]
  71. Nir Friedman, Joseph Y. Halpern
    Modeling Belief in Dynamic Systems, Part II: Revisions and Update [Citation Graph (0, 0)][DBLP]
    CoRR, 2003, v:0, n:, pp:- [Journal]
  72. Nir Friedman, Joseph Y. Halpern, Daphne Koller
    First-Order Conditional Logic Revisited [Citation Graph (0, 0)][DBLP]
    CoRR, 1998, v:0, n:, pp:- [Journal]
  73. Nir Friedman, Joseph Y. Halpern
    Plausibility Measures and Default Reasoning [Citation Graph (0, 0)][DBLP]
    CoRR, 1998, v:0, n:, pp:- [Journal]
  74. Nir Friedman, Joseph Y. Halpern
    Modeling Belief in Dynamic Systems, Part II: Revision and Update [Citation Graph (0, 0)][DBLP]
    CoRR, 1999, v:0, n:, pp:- [Journal]
  75. Nir Friedman, Joseph Y. Halpern
    Plausibility measures and default reasoning. [Citation Graph (0, 0)][DBLP]
    J. ACM, 2001, v:48, n:4, pp:648-685 [Journal]
  76. Nir Friedman, Joseph Y. Halpern
    Modeling Belief in Dynamic Systems, Part II: Revision and Update. [Citation Graph (0, 0)][DBLP]
    J. Artif. Intell. Res. (JAIR), 1999, v:10, n:, pp:117-167 [Journal]
  77. Yoseph Barash, Nir Friedman
    Context-Specific Bayesian Clustering for Gene Expression Data. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2002, v:9, n:2, pp:169-191 [Journal]
  78. Gill Bejerano, Nir Friedman, Naftali Tishby
    Efficient Exact p-Value Computation for Small Sample, Sparse, and Surprising Categorical Data. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2004, v:11, n:5, pp:867-886 [Journal]
  79. Amir Ben-Dor, Laurakay Bruhn, Nir Friedman, Iftach Nachman, Michèl Schummer, Zohar Yakhini
    Tissue Classification with Gene Expression Profiles. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2000, v:7, n:3-4, pp:559-583 [Journal]
  80. Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er
    Using Bayesian Networks to Analyze Expression Data. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2000, v:7, n:3-4, pp:601-620 [Journal]
  81. Nir Friedman, Matan Ninio, Itsik Pe'er, Tal Pupko
    A Structural EM Algorithm for Phylogenetic Inference. [Citation Graph (0, 0)][DBLP]
    Journal of Computational Biology, 2002, v:9, n:2, pp:331-353 [Journal]
  82. Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar
    Learning Probabilistic Models of Link Structure. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2002, v:3, n:, pp:679-707 [Journal]
  83. Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman
    Learning Module Networks. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:557-588 [Journal]
  84. Gal Elidan, Nir Friedman
    Learning Hidden Variable Networks: The Information Bottleneck Approach. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2005, v:6, n:, pp:81-127 [Journal]
  85. Nir Friedman, Joseph Y. Halpern
    Belief Revision: A Critique. [Citation Graph (0, 0)][DBLP]
    Journal of Logic, Language and Information, 1999, v:8, n:4, pp:401-420 [Journal]
  86. 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]
  87. Nir Friedman, Daphne Koller
    Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2003, v:50, n:1-2, pp:95-125 [Journal]
  88. Noam Slonim, Nir Friedman, Naftali Tishby
    Multivariate Information Bottleneck. [Citation Graph (0, 0)][DBLP]
    Neural Computation, 2006, v:18, n:8, pp:1739-1789 [Journal]
  89. Nir Friedman, Joseph Y. Halpern, Daphne Koller
    First-order conditional logic for default reasoning revisited. [Citation Graph (0, 0)][DBLP]
    ACM Trans. Comput. Log., 2000, v:1, n:2, pp:175-207 [Journal]
  90. Nir Friedman, Raz Kupferman
    Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]
  91. Iftach Nachman, Gal Elidan, Nir Friedman
    "Ideal Parent" Structure Learning for Continuous Variable Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:400-409 [Conf]
  92. Tal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman
    Continuous Time Markov Networks. [Citation Graph (0, 0)][DBLP]
    UAI, 2006, pp:- [Conf]

  93. Continuous-Time Belief Propagation. [Citation Graph (, )][DBLP]


  94. Automatic genome-wide reconstruction of phylogenetic gene trees. [Citation Graph (, )][DBLP]


  95. Nucleosome positioning from tiling microarray data. [Citation Graph (, )][DBLP]


  96. Gibbs Sampling in Factorized Continuous-Time Markov Processes. [Citation Graph (, )][DBLP]


  97. Identifying novel constrained elements by exploiting biased substitution patterns. [Citation Graph (, )][DBLP]


  98. Modularity and directionality in genetic interaction maps. [Citation Graph (, )][DBLP]


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