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Nir Friedman Vis

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*2009
98EEManuel Garber, Mitchell Guttman, Michele E. Clamp, Michael C. Zody, Nir Friedman, Xiaohui Xie: Identifying novel constrained elements by exploiting biased substitution patterns. Bioinformatics 25(12): (2009)
2008
97EEMoran Yassour, Tommy Kaplan, Ariel Jaimovich, Nir Friedman: Nucleosome positioning from tiling microarray data. ISMB 2008: 139-146
96EETal El-Hay, Nir Friedman, Raz Kupferman: Gibbs Sampling in Factorized Continuous-Time Markov Processes. UAI 2008: 169-178
2007
95EEIlan Wapinski, Avi Pfeffer, Nir Friedman, Aviv Regev: Automatic genome-wide reconstruction of phylogenetic gene trees. ISMB/ECCB (Supplement of Bioinformatics) 2007: 549-558
94EEMatan Ninio, Eyal Privman, Tal Pupko, Nir Friedman: Phylogeny reconstruction: increasing the accuracy of pairwise distance estimation using Bayesian inference of evolutionary rates. Bioinformatics 23(2): 136-141 (2007)
2006
93EETal El-Hay, Nir Friedman, Daphne Koller, Raz Kupferman: Continuous Time Markov Networks. UAI 2006
92EENir Friedman, Raz Kupferman: Dimension Reduction in Singularly Perturbed Continuous-Time Bayesian Networks. UAI 2006
91EEAriel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman: Towards an Integrated Protein-Protein Interaction Network: A Relational Markov Network Approach. Journal of Computational Biology 13(2): 145-164 (2006)
90EENoam Slonim, Nir Friedman, Naftali Tishby: Multivariate Information Bottleneck. Neural Computation 18(8): 1739-1789 (2006)
2005
89EEItay Mayrose, Nir Friedman, Tal Pupko: A Gamma mixture model better accounts for among site rate heterogeneity. ECCB/JBI 2005: 158
88EEAriel Jaimovich, Gal Elidan, Hanah Margalit, Nir Friedman: Towards an Integrated Protein-Protein Interaction Network. RECOMB 2005: 14-30
87EETommy Kaplan, Nir Friedman, Hanah Margalit: Predicting Transcription Factor Binding Sites Using Structural Knowledge. RECOMB 2005: 522-537
86EEYoseph Barash, Gal Elidan, Tommy Kaplan, Nir Friedman: Y. Barash, G. Elidan, T. Kaplan, , N. Friedman. Bioinformatics 21(5): 596-600 (2005)
85EEEran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman: Learning Module Networks. Journal of Machine Learning Research 6: 557-588 (2005)
84EEGal Elidan, Nir Friedman: Learning Hidden Variable Networks: The Information Bottleneck Approach. Journal of Machine Learning Research 6: 81-127 (2005)
2004
83EEIftach Nachman, Aviv Regev, Nir Friedman: Inferring quantitative models of regulatory networks from expression data. ISMB/ECCB (Supplement of Bioinformatics) 2004: 248-256
82EEIftach Nachman, Gal Elidan, Nir Friedman: "Ideal Parent" Structure Learning for Continuous Variable Networks. UAI 2004: 400-409
81EEYoseph Barash, Elinor Dehan, Meir Krupsky, Wilbur Franklin, Marc Geraci, Nir Friedman, Naftali Kaminski: Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays. Bioinformatics 20(6): 839-846 (2004)
80EEGill Bejerano, Nir Friedman, Naftali Tishby: Efficient Exact p-Value Computation for Small Sample, Sparse, and Surprising Categorical Data. Journal of Computational Biology 11(5): 867-886 (2004)
2003
79 Nir Friedman: Probabilistic models for identifying regulation networks. ECCB 2003: 57
78EEYoseph Barash, Gal Elidan, Nir Friedman, Tommy Kaplan: Modeling dependencies in protein-DNA binding sites. RECOMB 2003: 28-37
77 Gal Elidan, Nir Friedman: The Information Bottleneck EM Algorithm. UAI 2003: 200-208
76 Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller, Nir Friedman: Learning Module Networks. UAI 2003: 525-534
75EENir Friedman, Joseph Y. Halpern: Modeling Belief in Dynamic Systems, Part I: Foundations CoRR cs.AI/0307070: (2003)
74EENir Friedman, Joseph Y. Halpern: Modeling Belief in Dynamic Systems, Part II: Revisions and Update CoRR cs.AI/0307071: (2003)
73 Nir Friedman, Daphne Koller: Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks. Machine Learning 50(1-2): 95-125 (2003)
2002
72 Adnan Darwiche, Nir Friedman: UAI '02, Proceedings of the 18th Conference in Uncertainty in Artificial Intelligence, University of Alberta, Edmonton, Alberta, Canada, August 1-4, 2002 Morgan Kaufmann 2002
71 Gal Elidan, Matan Ninio, Nir Friedman, Dale Shuurmans: Data Perturbation for Escaping Local Maxima in Learning. AAAI/IAAI 2002: 132-139
70EEEran Segal, Yoseph Barash, Itamar Simon, Nir Friedman, Daphne Koller: From promoter sequence to expression: a probabilistic framework. RECOMB 2002: 263-272
69EENoam Slonim, Nir Friedman, Naftali Tishby: Unsupervised document classification using sequential information maximization. SIGIR 2002: 129-136
68EEShai Shalev-Shwartz, Shlomo Dubnov, Nir Friedman, Yoram Singer: Robust temporal and spectral modeling for query By melody. SIGIR 2002: 331-338
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. Bioinformatics 18(8): 1116-1123 (2002)
66 Yoseph Barash, Nir Friedman: Context-Specific Bayesian Clustering for Gene Expression Data. Journal of Computational Biology 9(2): 169-191 (2002)
65 Nir Friedman, Matan Ninio, Itsik Pe'er, Tal Pupko: A Structural EM Algorithm for Phylogenetic Inference. Journal of Computational Biology 9(2): 331-353 (2002)
64EELise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar: Learning Probabilistic Models of Link Structure. Journal of Machine Learning Research 3: 679-707 (2002)
2001
63 Lise Getoor, Nir Friedman, Daphne Koller, Benjamin Taskar: Learning Probabilistic Models of Relational Structure. ICML 2001: 170-177
62 Dana Pe'er, Aviv Regev, Gal Elidan, Nir Friedman: Inferring subnetworks from perturbed expression profiles. ISMB (Supplement of Bioinformatics) 2001: 215-224
61 Eran Segal, Benjamin Taskar, Audrey Gasch, Nir Friedman, Daphne Koller: Rich probabilistic models for gene expression. ISMB (Supplement of Bioinformatics) 2001: 243-252
60EENoam Slonim, Nir Friedman, Naftali Tishby: Agglomerative Multivariate Information Bottleneck. NIPS 2001: 929-936
59EEYoseph Barash, Nir Friedman: Context-specific Bayesian clustering for gene expression data. RECOMB 2001: 12-21
58EENir Friedman, Matan Ninio, Itsik Pe'er, Tal Pupko: A structural EM algorithm for phylogenetic inference. RECOMB 2001: 132-140
57EEAmir Ben-Dor, Nir Friedman, Zohar Yakhini: Class discovery in gene expression data. RECOMB 2001: 31-38
56EETal El-Hay, Nir Friedman: Incorporating Expressive Graphical Models in VariationalApproximations: Chain-graphs and Hidden Variables. UAI 2001: 136-143
55EEGal Elidan, Nir Friedman: Learning the Dimensionality of Hidden Variables. UAI 2001: 144-151
54EENir Friedman, Ori Mosenzon, Noam Slonim, Naftali Tishby: Multivariate Information Bottleneck. UAI 2001: 152-161
53EEYoseph Barash, Gill Bejerano, Nir Friedman: A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites. WABI 2001: 278-293
52EERonen I. Brafman, Nir Friedman: On decision-theoretic foundations for defaults. Artif. Intell. 133(1-2): 1-33 (2001)
51EENir Friedman, Joseph Y. Halpern: Belief Revision: A Critique CoRR cs.AI/0103020: (2001)
50EENir Friedman, Joseph Y. Halpern: Plausibility measures and default reasoning. J. ACM 48(4): 648-685 (2001)
2000
49 Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koller: Discovering Hidden Variables: A Structure-Based Approach. NIPS 2000: 479-485
48EENir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er: Using Bayesian networks to analyze expression data. RECOMB 2000: 127-135
47EEAmir Ben-Dor, Laurakay Bruhn, Nir Friedman, Iftach Nachman, Michèl Schummer, Zohar Yakhini: Tissue classification with gene expression profiles. RECOMB 2000: 54-64
46EENir Friedman, Dan Geiger, Noam Lotner: Likelihood Computations Using Value Abstraction. UAI 2000: 192-200
45EENir Friedman, Daphne Koller: Being Bayesian about Network Structure. UAI 2000: 201-210
44EENir Friedman, Iftach Nachman: Gaussian Process Networks. UAI 2000: 211-219
43EENir Friedman, Joseph Y. Halpern, Daphne Koller: First-order conditional logic for default reasoning revisited. ACM Trans. Comput. Log. 1(2): 175-207 (2000)
42 Amir Ben-Dor, Laurakay Bruhn, Nir Friedman, Iftach Nachman, Michèl Schummer, Zohar Yakhini: Tissue Classification with Gene Expression Profiles. Journal of Computational Biology 7(3-4): 559-583 (2000)
41 Nir Friedman, Michal Linial, Iftach Nachman, Dana Pe'er: Using Bayesian Networks to Analyze Expression Data. Journal of Computational Biology 7(3-4): 601-620 (2000)
1999
40 Nir Friedman, Lise Getoor, Daphne Koller, Avi Pfeffer: Learning Probabilistic Relational Models. IJCAI 1999: 1300-1309
39EEJoseph Y. Halpern, Nir Friedman: Plausibility Measures and Default Reasoning: An Overview. LICS 1999: 130-135
38EERichard Dearden, Nir Friedman, David Andre: Model based Bayesian Exploration. UAI 1999: 150-159
37EENir Friedman, Moisés Goldszmidt, Abraham Wyner: Data Analysis with Bayesian Networks: A Bootstrap Approach. UAI 1999: 196-205
36EENir Friedman, Iftach Nachman, Dana Pe'er: Learning Bayesian Network Structure from Massive Datasets: The "Sparse Candidate" Algorithm. UAI 1999: 206-215
35EEXavier Boyen, Nir Friedman, Daphne Koller: Discovering the Hidden Structure of Complex Dynamic Systems. UAI 1999: 91-100
34EENir Friedman, Joseph Y. Halpern: Modeling Belief in Dynamic Systems, Part II: Revision and Update CoRR cs.AI/9903016: (1999)
33EENir Friedman, Joseph Y. Halpern: Modeling Belief in Dynamic Systems, Part II: Revision and Update. J. Artif. Intell. Res. (JAIR) 10: 117-167 (1999)
32 Nir Friedman, Joseph Y. Halpern: Belief Revision: A Critique. Journal of Logic, Language and Information 8(4): 401-420 (1999)
1998
31 Craig Boutilier, Nir Friedman, Joseph Y. Halpern: Belief Revision with Unreliable Observations. AAAI/IAAI 1998: 127-134
30 Nir Friedman, Daphne Koller, Avi Pfeffer: Structured Representation of Complex Stochastic Systems. AAAI/IAAI 1998: 157-164
29 Richard Dearden, Nir Friedman, Stuart J. Russell: Bayesian Q-Learning. AAAI/IAAI 1998: 761-768
28 Nir Friedman, Moisés Goldszmidt, Thomas J. Lee: Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting. ICML 1998: 179-187
27EENir Friedman, Yoram Singer: Efficient Bayesian Parameter Estimation in Large Discrete Domains. NIPS 1998: 417-423
26EENir Friedman: The Bayesian Structural EM Algorithm. UAI 1998: 129-138
25EENir Friedman, Kevin P. Murphy, Stuart J. Russell: Learning the Structure of Dynamic Probabilistic Networks. UAI 1998: 139-147
24EENir Friedman, Joseph Y. Halpern, Daphne Koller: First-Order Conditional Logic Revisited CoRR cs.AI/9808005: (1998)
23EENir Friedman, Joseph Y. Halpern: Plausibility Measures and Default Reasoning CoRR cs.AI/9808007: (1998)
1997
22 Nir Friedman: Learning Belief Networks in the Presence of Missing Values and Hidden Variables. ICML 1997: 125-133
21 Nir Friedman, Moisés Goldszmidt, David Heckerman, Stuart J. Russell: Challenge: What is the Impact of Bayesian Networks on Learning? IJCAI (1) 1997: 10-15
20 David Andre, Nir Friedman, Ronald Parr: Generalized Prioritized Sweeping. NIPS 1997
19EENir Friedman, Moisés Goldszmidt: Sequential Update of Bayesian Network Structure. UAI 1997: 165-174
18EENir Friedman, Stuart J. Russell: Image Segmentation in Video Sequences: A Probabilistic Approach. UAI 1997: 175-181
17EENir Friedman, Joseph Y. Halpern: Modeling Belief in Dynamic Systems, Part I: Foundations. Artif. Intell. 95(2): 257-316 (1997)
16 Nir Friedman, Dan Geiger, Moisés Goldszmidt: Bayesian Network Classifiers. Machine Learning 29(2-3): 131-163 (1997)
1996
15 Nir Friedman, Moisés Goldszmidt: Building Classifiers Using Bayesian Networks. AAAI/IAAI, Vol. 2 1996: 1277-1284
14 Nir Friedman, Joseph Y. Halpern: Plausibility Measures and Default Reasoning. AAAI/IAAI, Vol. 2 1996: 1297-1304
13 Nir Friedman, Joseph Y. Halpern, Daphne Koller: First-Order Conditional Logic Revisited. AAAI/IAAI, Vol. 2 1996: 1305-1312
12 Nir Friedman, Moisés Goldszmidt: Discretizing Continuous Attributes While Learning Bayesian Networks. ICML 1996: 157-165
11 Nir Friedman, Joseph Y. Halpern: Belief Revision: A Critique. KR 1996: 421-431
10EECraig Boutilier, Nir Friedman, Moisés Goldszmidt, Daphne Koller: Context-Specific Independence in Bayesian Networks. UAI 1996: 115-123
9EENir Friedman, Moisés Goldszmidt: Learning Bayesian Networks with Local Structure. UAI 1996: 252-262
8EENir Friedman, Joseph Y. Halpern: A Qualitative Markov Assumption and Its Implications for Belief Change. UAI 1996: 263-273
7EENir Friedman, Zohar Yakhini: On the Sample Complexity of Learning Bayesian Networks. UAI 1996: 274-282
1995
6 Ronen I. Brafman, Nir Friedman: On Decision-Theoretic Foundations for Defaults. IJCAI 1995: 1458-1465
5EENir Friedman, Joseph Y. Halpern: Plausibility Measures: A User's Guide. UAI 1995: 175-184
1994
4 Nir Friedman, Joseph Y. Halpern: Conditional Logics of Belief Change. AAAI 1994: 915-921
3 Nir Friedman, Joseph Y. Halpern: A Knowledge-Based Framework for Belief Change, Part II: Revision and Update. KR 1994: 190-201
2 Nir Friedman, Joseph Y. Halpern: On the Complexity of Conditional Logics. KR 1994: 202-213
1 Nir Friedman, Joseph Y. Halpern: A Knowledge-Based Framework for Belief change, Part I: Foundations. TARK 1994: 44-64

Coauthor Index

1David Andre [20] [38]
2Yoseph Barash [53] [59] [66] [70] [78] [81] [86]
3Gill Bejerano [53] [80]
4Amir Ben-Dor [42] [47] [57]
5Craig Boutilier [10] [31]
6Xavier Boyen [35]
7Ronen I. Brafman [6] [52]
8Laurakay Bruhn [42] [47]
9Michele E. Clamp [98]
10Adnan Darwiche [72]
11Richard Dearden [29] [38]
12Elinor Dehan [81]
13Shlomo Dubnov [68]
14Tal El-Hay [56] [93] [96]
15Gal Elidan [49] [55] [62] [71] [77] [78] [82] [84] [86] [88] [91]
16Wilbur Franklin [81]
17Manuel Garber [98]
18Audrey Gasch [61]
19Dan Geiger [16] [46]
20Marc Geraci [81]
21Lise Getoor [40] [63] [64]
22Moisés Goldszmidt [9] [10] [12] [15] [16] [19] [21] [28] [37]
23Dan Graur [67]
24Mitchell Guttman [98]
25Joseph Y. Halpern [1] [2] [3] [4] [5] [8] [11] [13] [14] [17] [23] [24] [31] [32] [33] [34] [39] [43] [50] [51] [74] [75]
26Masami Hasegawa [67]
27David Heckerman [21]
28Ariel Jaimovich [88] [91] [97]
29Naftali Kaminski [81]
30Tommy Kaplan [78] [86] [87] [97]
31Daphne Koller [10] [13] [24] [30] [35] [40] [43] [45] [49] [61] [63] [64] [70] [73] [76] [85] [93]
32Meir Krupsky [81]
33Raz Kupferman [92] [93] [96]
34Thomas J. Lee [28]
35Michal Linial [41] [48]
36Noam Lotner [46] [49]
37Hanah Margalit [87] [88] [91]
38Itay Mayrose [89]
39Ori Mosenzon [54]
40Kevin P. Murphy [25]
41Iftach Nachman [36] [41] [42] [44] [47] [48] [82] [83]
42Matan Ninio [58] [65] [71] [94]
43Ronald Parr [20]
44Dana Pe'er [36] [41] [48] [62] [76] [85]
45Itsik Pe'er [58] [65] [67]
46Avi Pfeffer [30] [40] [95]
47Eyal Privman [94]
48Tal Pupko [58] [65] [67] [89] [94]
49Aviv Regev [62] [76] [83] [85] [95]
50Stuart J. Russell [18] [21] [25] [29]
51Michèl Schummer [42] [47]
52Eran Segal [61] [70] [76] [85]
53Shai Shalev-Shwartz [68]
54Dale Shuurmans [71]
55Itamar Simon [70]
56Yoram Singer [27] [68]
57Noam Slonim [54] [60] [69] [90]
58Benjamin Taskar (Ben Taskar) [61] [63] [64]
59Naftali Tishby [54] [60] [69] [80] [90]
60Ilan Wapinski [95]
61Abraham Wyner [37]
62Xiaohui Xie [98]
63Zohar Yakhini [7] [42] [47] [57]
64Moran Yassour [97]
65Michael C. Zody [98]

Colors in the list of coauthors

Copyright © Tue Nov 3 08:52:44 2009 by Michael Ley (ley@uni-trier.de)