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Recent papers classified by the tag structure_learning.

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	MinReg: A Scalable Algorithm for Learning Parsimonious Regulatory Networks in Yeast and Mammals [My Copy] J. Mach. Learn. Res., Vol. 7 (2006), pp. 167-189. by Dana Pe'er, Amos Tanay, Aviv Regev posted to structure_learning regulatory_networks gene_expression_data bayesian_networks by roys on 2009-11-24 21:53:02 as
	A Stochastic Grammar of Images [My Copy] (2007) by Song C. Zhu, David Mumford posted to visual_grammars structure_learning review machine_learning grammars bayesian by markstoehr to the group Statistical Machine Learning on 2009-09-03 01:18:42 as
	Using MDL for Grammar Induction [My Copy] Grammatical Inference: Algorithms and Applications (2006), pp. 293-306. by Pieter Adriaans, Ceriel Jacobs posted to structure_learning mdl machine_learning learning_theory kolmogorov_complexity grammars formal_languages dfa by markstoehr on 2009-08-31 23:06:38 as
	A stochastic grammar of images [My Copy] Found. Trends. Comput. Graph. Vis., Vol. 2, No. 4. (2006), pp. 259-362. by Song C. Zhu, David Mumford posted to vision structure_learning sparse_coding probability object_detection mrfs markov_models machine_learning hierarchical_learning graphical_models grammars computer_vision appearance_models ai by markstoehr on 2009-08-29 20:04:25 as along with 5 people alexander_bauer forefinger brandyn mthomure pwais
	Efficient Stepwise Selection in Decomposable Models [My Copy] In UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence (2001), pp. 128-135. by Amol Deshpande, Minos N. Garofalakis, Michael I. Jordan posted to decomposable mrf structure_learning by roys on 2009-08-11 07:23:44 as
	A Bayesian method for the induction of probabilistic networks from data [My Copy] Machine Learning, Vol. 9, No. 4. (1 October 1992), pp. 309-347. by Gregory F. Cooper, Edward Herskovits posted to bn k2 structure_learning by kennedie on 2009-07-13 09:58:03 as along with 4 people arturdnt oconnonp tessaverhoef czeller
	A Hybrid Anytime Algorithm for the Construction of Causal Models From Sparse Data [My Copy] In Proceedings of the fifteenth international conference on uncertainty in artificial intelligence (1999), pp. 142-149. by Denver Dash, Marek J. Druzdzel posted to bn egs structure_learning by kennedie on 2009-06-19 14:59:53 as
	Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery [My Copy] In Proceedings of the International Conference on Mathematics and Engineering Techniques in Medicine and Biological Scienes, METMBS '03, June 23 - 26, 2003, Las Vegas, Nevada, USA (2003), pp. 371-376. by Constantin F. Aliferis, Ioannis Tsamardinos, Alexander R. Statnikov, Laura E. Brown edited by Faramarz Valafar, Homayoun Valafar, Faramarz Valafar, Homayoun Valafar posted to bayesian_networks causality software structure_learning by roys on 2009-05-26 22:52:13 as along with 1 person naegele
	Searching for Bayesian network structures in the space of restricted acyclic partially directed graphs [My Copy] Journal of Artificial Intelligence Research, Vol. 18 (2003), pp. 445-490. by Luis M. De Campos posted to graphical_models pdags structure_learning by roys on 2009-03-29 19:52:17 as
	Algorithms for Large Scale Markov Blanket Discovery [My Copy] In In The 16th International FLAIRS Conference, St (2003), pp. 376-380. by Ioannis Tsamardinos, Constantin F. Aliferis, Er Statnikov posted to causality markov_boundary markov_networks structure_learning by roys on 2009-03-03 04:36:33 as
	"Ideal Parent" structure learning for continuous variable networks [My Copy] In AUAI '04: Proceedings of the 20th conference on Uncertainty in artificial intelligence (2004), pp. 400-409. by Iftach Nachman, Gal Elidan, Nir Friedman posted to bnet structure_learning by roys on 2008-12-11 05:57:15 as along with 1 person espriggs
	Sequential update of Bayesian network structure [My Copy] In Proceedings of the Thirteenth Conference on Uncertainty in Artificial Intelligence (1997), pp. 165-174. by Nir Friedman, Moises Goldszmidt posted to bayesian_network sequential structure_learning by naegele on 2008-11-01 15:58:00 as
	Network inference using informative priors [My Copy] Proceedings of the National Academy of Sciences, Vol. 105, No. 38. (2008), pp. 14313-14318. by Sach Mukherjee, Terence P. Speed posted to bayesian_networks biological_networks structure_learning structured_prior by roys on 2008-09-24 06:04:46 as along with 10 people and 1 group zufar bertelsen ggallone guhjy Borelli ptrobajo jfr markstoehr stringertheory tmmurali Jarman Lab
	Structure Learning on Large Scale Common Sense Statistical Models of Human State [My Copy] In AAAI (2008), pp. 1389-1395. by William Pentney, Matthai Philipose, Jeff A. Bilmes edited by Dieter Fox, Carla P. Gomes, Dieter Fox, Carla P. Gomes posted to mrf structure_learning by roys on 2008-08-29 18:13:02 as along with 1 person hawkes
	Being Bayesian About Network Structure. A Bayesian Approach to Structure Discovery in Bayesian Networks [My Copy] Machine Learning, Vol. V50, No. 1. (1 January 2003), pp. 95-125. by Nir Friedman, Daphne Koller posted to bayesian_network mcmc structure_learning by naegele on 2008-08-11 14:36:56 as along with 5 people and 1 group garyfeng Borelli wnpx chechetka quianominorleo ReadingLab
	Bayes net graphs to understand co-authorship networks? [My Copy] In LinkKDD '05: Proceedings of the 3rd international workshop on Link discovery (2005), pp. 1-8. by Anna Goldenberg, Andrew W. Moore posted to bayesian_network coauthorship graphical_model structure_learning by naegele on 2008-07-30 10:20:22 as along with 1 person Repton
	Learning Equivalence Classes of Bayesian-Network Structures [My Copy] Journal of Machine Learning Research, Vol. 2 (2002), pp. 445-498. by David M. Chickering posted to bayesian_network equivalence_class structure_learning by naegele on 2008-07-02 12:14:38 as along with 2 people and 1 group ible helsley VivesMinions
	Being Bayesian about Network Structure [My Copy] In UAI '00: Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence (2000), pp. 201-210. by Nir Friedman, Daphne Koller posted to bayesian_networks graphical_models structure_learning by roys on 2008-03-14 02:23:21 as
	Data Analysis with Bayesian Networks: A Bootstrap Approach [My Copy] In UAI '99: Proceedings of the Fifteenth Conference on Uncertainty in Artificial Intelligence (1999), pp. 196-205. by Nir Friedman, Moises Goldszmidt, Abraham Wyner edited by Kathryn B. Laskey, Henri Prade posted to bayesian_network bootstrap structure_learning by naegele on 2007-12-20 10:03:00 as along with 1 person luispedro
	Learning Bayesian Network Structure from Massive Datasets: The ”Sparse Candidate” Algorithm [My Copy] pp. 206-215. by Nir Friedman, Iftach Nachman, Dana Pe'er posted to bayesian_networks sparse_candidate structure_learning by roys on 2007-12-14 17:52:10 as along with 4 people ldfu wnpx famoreira dimatura
	Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical Gaussian models and Bayesian networks. [My Copy] Bioinformatics (14 July 2006) by Adriano V V. Werhli, Marco Grzegorczyk, Dirk Husmeier posted to bnet causality structure_learning by roys on 2007-12-14 02:15:42 as along with 3 people wnpx frohike edwardmorrissey
	The max-min hill-climbing Bayesian network structure learning algorithm [My Copy] Machine Learning, Vol. 65, No. 1. (October 2006), pp. 31-78. by Ioannis Tsamardinos, Laura E. Brown, Constantin Aliferis posted to bayesian_network graphical_models machine_learning structure_learning by naegele on 2007-11-28 14:38:58 as along with 2 people pliz dhein1030
	Convex optimization techniques for fitting sparse Gaussian graphical models [My Copy] In ICML '06: Proceedings of the 23rd international conference on Machine learning (2006), pp. 89-96. by Onureena Banerjee, Laurent E. Ghaoui, Alexandre D'Aspremont, Georges Natsoulis posted to graphical_models machine_learning math optimization structure_learning by hcs on 2007-11-15 05:57:15 as along with 1 person daniel51
	Modularized learning of genetic interaction networks from biological annotations and mRNA expression data [My Copy] Bioinformatics, Vol. 21, No. 11. (1 June 2005), pp. 2739-2747. by Phil H. Lee, Doheon Lee posted to bayesian_network gene_expression genetic_network graphical_models machine_learning microarray regulatory_network structure_learning systems_biology by naegele on 2007-11-14 13:20:21 as along with 7 people frohike verdicchio beete saman_vp patrycja_missiuro roys tvdbulck
	Improving Markov Chain Monte Carlo Model Search for Data Mining [My Copy] Machine Learning, Vol. 50, No. 1. (1 January 2003), pp. 127-158. by Paolo Giudici, Robert Castelo posted to bayesian_network graphical_models machine_learning mcmc structure_learning by naegele on 2007-11-14 09:10:51 as along with 1 person helsley
	A hybrid Bayesian network learning method for constructing gene networks. [My Copy] Comput Biol Chem, Vol. 31, No. 5--6. (19 August 2007), pp. 361-372. by Mingyi Wang, Zuozhou Chen, Sylvie Cloutier posted to bayesian_network genetic_network graphical_models machine_learning regulatory_network structure_learning systems_biology by naegele on 2007-11-12 09:10:05 as along with 2 people ramakris julianjonker
	Growing Bayesian network models of gene networks from seed genes. [My Copy] Bioinformatics, Vol. 21 Suppl 2 (1 September 2005) by J. M. Peña, J. Björkegren, J. Tegnér posted to bayesian_network gene_expression genetic_network graphical_models machine_learning microarray regulatory_network structure_learning systems_biology by naegele to the group ic4 on 2007-10-19 15:44:48 as along with 6 people frohike abhik imouthesmp wnpx ramakris heliopais
	A novel algorithm for scalable and accurate Bayesian network learning. [My Copy] Medinfo, Vol. 11, No. Pt 1. (2004), pp. 711-715. by L. E. Brown, I. Tsamardinos, C. F. Aliferis posted to structure_learning machine_learning graphical_models bayesian_network by naegele to the group ic4 on 2007-09-06 10:26:16 as along with 2 people and 1 group gangli ramakris tulip
	Identifying interventional and pathogenic mechanisms by generative inverse modeling of gene expression profiles. [My Copy] J Comput Biol, Vol. 11, No. 6. (2004), pp. 1135-1148. by M. Dejori, M. Stetter posted to structure_learning own_publication microarray graphical_model by dejori to the group generif_paper on 2007-09-05 12:23:19 as
	Hunting drug targets by systems-level modeling of gene expression profiles. [My Copy] IEEE Trans Nanobioscience, Vol. 3, No. 3. (September 2004), pp. 180-191. by M. Dejori, B. Schuermann, M. Stetter posted to structure_learning own_publication microarray graphical_model by dejori to the group ic4 on 2007-09-05 12:22:39 as along with 1 person and 1 group frohike generif_paper
	Mining Functional Modules in Genetic Networks with Decomposable Graphical Models [My Copy] OMICS: A Journal of Integrative Biology, Vol. 8, No. 2. (July 2004), pp. 176-188. by Mathaus Dejori, Anton Schwaighofer, Volker Tresp, Martin Stetter posted to structure_learning own_publication microarray graphical_model by dejori to the group generif_paper on 2007-09-05 12:21:55 as along with 3 people and 1 group tjtaylor rsantana DavidEdwards ic4
	Learning Bayesian Networks with Local Structure [My Copy] pp. 252-262. by Nir Friedman, Moises Goldszmidt posted to structure_learning graphical_models by hcs on 2007-02-03 23:45:38 as along with 1 person wnpx

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bayesian_network	13
graphical_models	13
machine_learning	13
microarray	12
graphical_model	10
own_publication	9
bayesian_networks	6
regulatory_network	5
systems_biology	5
causality	4
genetic_network	4
grammars	4
bnet	3
gene_expression	3
mrf	3
bayesian	2
bn	2
mcmc	2
review	2
software	2
sparse_candidate	2
visual_grammars	2
ai	1
appearance_models	1
biological_networks	1
block_regularization	1
bootstrap	1
coauthorship	1
computer_vision	1
decomposable	1
dfa	1
egs	1
equivalence_class	1
feature_selection	1
formal_languages	1
gene_expression_data	1
hierarchical_learning	1
k2	1
kolmogorov_complexity	1
l1_regularization	1
learning_theory	1
markov_boundary	1
markov_models	1
markov_networks	1
math	1
mdl	1
mrfs	1
network	1
object_detection	1
optimization	1
pdags	1
probability	1
regulatory_networks	1
sequential	1
sparse_coding	1
structured_prior	1
vision	1

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