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Dan Geiger Vis

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*2009
63EEDan Geiger, Christopher Meek, Ydo Wexler: Speeding up HMM algorithms for genetic linkage analysis via chain reductions of the state space. Bioinformatics 25(12): (2009)
2008
62EEMark Silberstein, Assaf Schuster, Dan Geiger, Anjul Patney, John D. Owens: Efficient computation of sum-products on GPUs through software-managed cache. ICS 2008: 309-318
61EESivan Bercovici, Dan Geiger, Liran Shlush, Karl Skorecki, Alan Templeton: Panel Construction for Mapping in Admixed Populations Via Expected Mutual Information. RECOMB 2008: 435-449
60EEYdo Wexler, Dan Geiger: Variational Upper and Lower Bounds for Probabilistic Graphical Models. Journal of Computational Biology 15(7): 721-735 (2008)
2007
59EEYdo Wexler, Dan Geiger: Variational Upper Bounds for Probabilistic Phylogenetic Models. RECOMB 2007: 226-237
58EERon Zohar, Dan Geiger: Estimation of flows in flow networks. European Journal of Operational Research 176(2): 691-706 (2007)
2006
57EEMark Silberstein, Dan Geiger, Assaf Schuster: A Distributed System for Genetic Linkage Analysis. GCCB 2006: 110-123
56EEMark Silberstein, Dan Geiger, Assaf Schuster, Miron Livny: Scheduling Mixed Workloads in Multi-grids: The Grid Execution Hierarchy. HPDC 2006: 291-302
55EEDan Geiger, Christopher Meek, Ydo Wexler: A Variational Inference Procedure Allowing Internal Structure for Overlapping Clusters and Deterministic Constraints. J. Artif. Intell. Res. (JAIR) 27: 1-23 (2006)
2005
54EEYdo Wexler, Zohar Yakhini, Yechezkel Kashi, Dan Geiger: Finding Approximate Tandem Repeats in Genomic Sequences. Journal of Computational Biology 12(7): 928-942 (2005)
53EEDmitry Rusakov, Dan Geiger: Asymptotic Model Selection for Naive Bayesian Networks. Journal of Machine Learning Research 6: 1-35 (2005)
2004
52EEGideon Greenspan, Dan Geiger: High density linkage disequilibrium mapping using models of haplotype block variation. ISMB/ECCB (Supplement of Bioinformatics) 2004: 137-144
51EEVladimir Jojic, Nebojsa Jojic, Christopher Meek, Dan Geiger, Adam C. Siepel, David Haussler, David Heckerman: Efficient approximations for learning phylogenetic HMM models from data. ISMB/ECCB (Supplement of Bioinformatics) 2004: 161-168
50EEYdo Wexler, Zohar Yakhini, Yechezkel Kashi, Dan Geiger: Finding approximate tandem repeats in genomic sequences. RECOMB 2004: 223-232
49EEMaáyan Fishelson, Dan Geiger: Optimizing Exact Genetic Linkage Computations. Journal of Computational Biology 11(2/3): 263-275 (2004)
48EEGideon Greenspan, Dan Geiger: Model-Based Inference of Haplotype Block Variation. Journal of Computational Biology 11(2/3): 493-504 (2004)
2003
47EEMaáyan Fishelson, Dan Geiger: Optimizing exact genetic linkage computations. RECOMB 2003: 114-121
46EEGideon Greenspan, Dan Geiger: Model-based inference of haplotype block variation. RECOMB 2003: 131-137
45 Ari Frank, Dan Geiger, Zohar Yakhini: A Distance-Based Branch and Bound Feature Selection Algorithm. UAI 2003: 241-248
44 Dmitry Rusakov, Dan Geiger: Automated Analytic Asymptotic Evaluation of the Marginal Likelihood for Latent Models. UAI 2003: 501-508
2002
43 Maáyan Fishelson, Dan Geiger: Exact genetic linkage computations for general pedigrees. ISMB 2002: 189-198
42 Dan Geiger, Christopher Meek, Bernd Sturmfels: Factorization of Discrete Probability Distributions. UAI 2002: 162-169
41 Dmitry Rusakov, Dan Geiger: Asymptotic Model Selection for Naive Bayesian Networks. UAI 2002: 438-445
2001
40EEAnn Becker, Dan Geiger: A sufficiently fast algorithm for finding close to optimal clique trees. Artif. Intell. 125(1-2): 3-17 (2001)
2000
39EEAnn Becker, Dan Geiger, Christopher Meek: Perfect Tree-like Markovian Distributions. UAI 2000: 19-23
38EENir Friedman, Dan Geiger, Noam Lotner: Likelihood Computations Using Value Abstraction. UAI 2000: 192-200
37EEAnn Becker, Reuven Bar-Yehuda, Dan Geiger: Randomized Algorithms for the Loop Cutset Problem. J. Artif. Intell. Res. (JAIR) 12: 219-234 (2000)
1999
36EEKristin P. Bennett, Usama M. Fayyad, Dan Geiger: Density-Based Indexing for Approximate Nearest-Neighbor Queries. KDD 1999: 233-243
35EEDan Geiger, James Cussens: Parameter Priors for Directed Acyclic Graphical Models and the Characteriration of Several Probability Distributions. UAI 1999: 216-225
34EEDan Geiger, Christopher Meek: Quantifier Elimination for Statistical Problems. UAI 1999: 226-235
33EEAnn Becker, Reuven Bar-Yehuda, Dan Geiger: Random Algorithms for the Loop Cutset Problem. UAI 1999: 49-56
32EELaxmi Parida, Dan Geiger: Mass Estimation of DNA Molecules and Extraction of Ordered Restriction Maps in Optical Mapping Imagery. Algorithmica 25(2-3): 295-310 (1999)
1998
31EEDan Geiger: Graphical Models and Exponential Families. UAI 1998: 156-165
30 Dan Geiger, David Heckerman: Probabilistic relevance relations. IEEE Transactions on Systems, Man, and Cybernetics, Part A 28(1): 17-25 (1998)
29EEReuven 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. SIAM J. Comput. 27(4): 942-959 (1998)
1997
28 Dan Geiger, Prakash P. Shenoy: UAI '97: Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence, August 1-3, 1997, Brown University, Providence, Rhode Island, USA Morgan Kaufmann 1997
27 Kirill Shoikhet, Dan Geiger: A Practical Algorithm for Finding Optimal Triangulations. AAAI/IAAI 1997: 185-190
26 Nir Friedman, Dan Geiger, Moisés Goldszmidt: Bayesian Network Classifiers. Machine Learning 29(2-3): 131-163 (1997)
1996
25EEDan Geiger, David Heckerman, Christopher Meek: Asymptotic Model Selection for Directed Networks with Hidden Variables. UAI 1996: 283-290
24EEAnn Becker, Dan Geiger: A sufficiently fast algorithm for finding close to optimal junction trees. UAI 1996: 81-89
23EEDan Geiger, David Heckerman: Knowledge Representation and Inference in Similarity Networks and Bayesian Multinets. Artif. Intell. 82(1-2): 45-74 (1996)
22EEAnn Becker, Dan Geiger: Optimization of Pearl's Method of Conditioning and Greedy-Like Approximation Algorithms for the Vertex Feedback Set Problem. Artif. Intell. 83(1): 167-188 (1996)
1995
21EEDan Geiger, David Heckerman: A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks. UAI 1995: 196-207
20EEDavid Heckerman, Dan Geiger: Learning Bayesian Networks: A Unification for Discrete and Gaussian Domains. UAI 1995: 274-284
19EEDavid Maxwell Chickering, Dan Geiger, David Heckerman: On Finding a Cycle Basis with a Shortest Maximal Cycle. Inf. Process. Lett. 54(1): 55-58 (1995)
18 David Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. Machine Learning 20(3): 197-243 (1995)
17EEAmir Eliaz, Dan Geiger: Word-level recognition of small sets of hand-written words. Pattern Recognition Letters 16(10): 999-1009 (1995)
1994
16 David Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. KDD Workshop 1994: 85-96
15 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. SODA 1994: 344-354
14EEDan Geiger, David Heckerman: Learning Gaussian Networks. UAI 1994: 235-243
13EEDan Geiger, Azaria Paz, Judea Pearl: On Testing Whether an Embedded Bayesian Network Represents a Probability Model. UAI 1994: 244-252
12EEDavid Heckerman, Dan Geiger, David Maxwell Chickering: Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. UAI 1994: 293-301
11EEAnn Becker, Dan Geiger: Approximation Algorithms for the Loop Cutset Problem. UAI 1994: 60-68
1993
10EEDan Geiger, David Heckerman: Inference Algorithms for Similarity Networks. UAI 1993: 326-334
1992
9EEDan Geiger: An Entropy-based Learning Algorithm of Bayesian Conditional Trees. UAI 1992: 92-97
1991
8 Dan Geiger, Jeffrey A. Barnett: Optimal Satisficing Tree Searches. AAAI 1991: 441-445
7EEDan Geiger, David Heckerman: Advances in Probabilistic Reasoning. UAI 1991: 118-126
6 Dan Geiger, Azaria Paz, Judea Pearl: Axioms and Algorithms for Inferences Involving Probabilistic Independence Inf. Comput. 91(1): 128-141 (1991)
1990
5 Dan Geiger, Azaria Paz, Judea Pearl: Learning Causal Trees from Dependence Information. AAAI 1990: 770-776
4EEDan Geiger, David Heckerman: separable and transitive graphoids. UAI 1990: 65-76
3 Dan Geiger, Judea Pearl: Logical and algorithmic properties of independence and their application to Bayesian networks. Ann. Math. Artif. Intell. 2: 165-178 (1990)
1989
2EEDan Geiger, Thomas Verma, Judea Pearl: d-Separation: From Theorems to Algorithms. UAI 1989: 139-148
1988
1EEDan Geiger, Judea Pearl: On the logic of causal models. UAI 1988: 3-14

Coauthor Index

1Reuven Bar-Yehuda [15] [29] [33] [37]
2Jeffrey A. Barnett [8]
3Ann Becker [11] [22] [24] [33] [37] [39] [40]
4Kristin P. Bennett [36]
5Sivan Bercovici [61]
6David Maxwell Chickering (Max Chickering) [12] [16] [18] [19]
7James Cussens [35]
8Amir Eliaz [17]
9Usama M. Fayyad [36]
10Maáyan Fishelson [43] [47] [49]
11Ari Frank [45]
12Nir Friedman [26] [38]
13Moisés Goldszmidt [26]
14Gideon Greenspan [46] [48] [52]
15David Haussler [51]
16David Heckerman [4] [7] [10] [12] [14] [16] [18] [19] [20] [21] [23] [25] [30] [51]
17Nebojsa Jojic [51]
18Vladimir Jojic [51]
19Yechezkel Kashi [50] [54]
20Miron Livny [56]
21Noam Lotner [38]
22Christopher Meek [25] [34] [39] [42] [51] [55] [63]
23Joseph Naor (Seffi Naor) [15] [29]
24John D. Owens [62]
25Laxmi Parida [32]
26Anjul Patney [62]
27Azaria Paz [5] [6] [13]
28Judea Pearl [1] [2] [3] [5] [6] [13]
29Ron M. Roth [15] [29]
30Dmitry Rusakov [41] [44] [53]
31Assaf Schuster [56] [57] [62]
32Prakash P. Shenoy [28]
33Liran Shlush [61]
34Kirill Shoikhet [27]
35Adam C. Siepel [51]
36Mark Silberstein [56] [57] [62]
37Karl Skorecki [61]
38Bernd Sturmfels [42]
39Alan Templeton [61]
40Thomas Verma [2]
41Ydo Wexler [50] [54] [55] [59] [60] [63]
42Zohar Yakhini [45] [50] [54]
43Ron Zohar [58]

Colors in the list of coauthors

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