rsantana's learning [47 articles] Export

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	Research topics in discrete estimation of distribution algorithms based on factorizations [My Copy] Memetic Computing, Vol. 1, No. 1. (1 March 2009), pp. 35-54. by Roberto Santana, Pedro Larrañaga, Jose Lozano posted to eda-theory edas graphical-models graphs learning by rsantana on 2009-06-25 16:57:15 as along with 1 person and 1 group lmarti estimation_of_distribution_algorithms
	The Cross-Entropy Method: A Unified Approach to Combinatorial Optimization, Monte-Carlo Simulation and Machine Learning (Information Science and Statistics) [My Copy] (28 July 2004) by Reuven Y. Rubinstein, Dirk P. Kroese posted to entropy learning optimization by rsantana on 2009-02-17 23:01:59 as along with 2 people sugarexpletive abellogin
	Combining Pattern Classifiers: Methods and Algorithms [My Copy] (01 July 2004) by Ludmila I. Kuncheva posted to classifiers learning pattern-recognition by rsantana on 2009-02-17 23:01:27 as along with 6 people and 1 group operon sdvillal AbnerCYH napvasconcelos drivard abellogin CSBBGraphTheory
	An Extension on "Statistical Comparisons of Classifiers over Multiple Data Sets" for all Pairwise Comparisons [My Copy] Journal of Machine Learning Research, Vol. 9 (December 2008), pp. 2677-2694. by Salvador García, Francisco Herrera posted to classifiers learning by rsantana on 2009-01-15 14:54:33 as along with 3 people Dori2008 sdvillal jjrodriguez
	Statistical Methods for Eliciting Probability Distributions [My Copy] Journal of the American Statistical Association, Vol. 100, No. 470. (June 2005), pp. 680-701. by Paul H. Garthwaite, Joseph B. Kadane, Anthony O'Hagan posted to bayesian bayesian-networks graphical-models learning by rsantana on 2008-12-08 23:14:40 as along with 2 people mijam mgp28
	The discovery of structural form. [My Copy] Proceedings of the National Academy of Sciences of the United States of America, Vol. 105, No. 31. (5 August 2008), pp. 10687-10692. by Charles Kemp, Joshua B. Tenenbaum posted to data-mining graphs learning by rsantana on 2008-08-13 17:54:01 as along with 30 people and 3 groups briordan lmaurits anon_pl mthomure TRHvidsten ckai1 prydzews qwermish thiagomanel linhares vlachmore stober nojhan stringertheory thefillm amatos markstoehr uhhhhhhhhhhm A_Olympia tmmurali jmchauvet shigepong tbloomf kevinemamy markusd jborn deubel guhjy Zephyrus jago Optimization logics of knowledge Roswell Cancer Crosstalk
	Causation, Prediction, and Search [My Copy] (08 January 2001) by Peter Spirtes, Clark Glymour, Richard Scheines posted to graphical-models learning by rsantana on 2008-08-13 17:50:21 as along with 5 people livingthingdan wnpx chechetka naegele frohike
	Learning Bayesian Networks From Dependency Networks: A Preliminary Study [My Copy] In Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, Jan 3-6, 2003, Key West, FL. (Jan 3-6 2003) by Geoff Hulten, David M. Chickering, David Heckerman edited by Christopher M. Bishop, Brendan J. Frey posted to graphical-models learning by rsantana on 2008-08-13 17:50:00 as along with 1 person naegele
	What is principal component analysis? [My Copy] Nature Biotechnology, Vol. 26, No. 3. (01 March 2008), pp. 303-304. by Markus Ringnér posted to clustering learning by rsantana on 2008-06-10 16:12:25 as along with 69 people and 3 groups singhsh Jporci tnhh ruvido ucbcjbm daforerog Diego_Prada abellogin nguizard thegoose2 arsyed Zephyrus flips svozil VGreiff kaniko ssgong Yanno guhjy operon barry baaic dullhunk Bevan_Weir zeji gareth massivemayhem zwang GustavoLacerda GeeSharpMinor bmaust zambujo mingzhi starz1010101 maralena wchannels sunhwan jennifermbui kdelavega zhouyu sobolevnrm fryanpan kengg rvosa dekay23 adacier hpaces waghsk rchauhan pavanghatty kristgy jfr bibay2004 xingxu quianominorleo craigwilson06 ashko markusd dayjm dimka i-stevenson chrissp100 tharris ale mjoach HugoMarcelo jdiezperezj rrbarb Nici baker-group FAB-lab Bioinformatics
	Embracing Statistical Challenges in the Information Technology Age [My Copy] Technometrics, Vol. 49, No. 3. (August 2007), pp. 237-248. by Yu, Bin posted to graphical-models learning by rsantana on 2008-03-14 16:56:28 as along with 1 person davidr
	Information theory, multivariate dependence, and genetic network inference [My Copy] (7 June 2004) by Ilya Nemenman posted to graphical-models inference interactions learning by rsantana on 2008-01-06 23:26:09 as along with 4 people and 1 group nettraq cantupaz dcoates markusd Philosophy_of_Information
	Incorporating non-local information into information extraction systems by Gibbs sampling [My Copy] In ACL '05: Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics (2005), pp. 363-370. by Jenny R. Finkel, Trond Grenager, Christopher Manning posted to gibbs-sampling learning sampling by rsantana on 2007-12-24 21:39:00 as along with 7 people arafalov mehrbod julianpan bhaddow eegilbert vlachmore markusd
	Estimation of Entropy and Mutual Information [My Copy] Neural Comp., Vol. 15, No. 6. (1 June 2003), pp. 1191-1253. by Liam Paninski posted to entropy learning by rsantana on 2007-12-24 21:27:36 as along with 8 people and 1 group rpadams xlli xtizon bayesian phung superflunky dpf aresjung impca
	Bayesian Substructure Learning - Approximate Learning of Very Large Network Structures [My Copy] In Machine Learning: ECML 2007. 18th European Conference on Machine Learning (September 2007) by Andreas Nägele, Mathäus Dejori, Martin Stetter edited by Dunja Mladenič, Andrzej Skowron posted to bayesian-networks learning by rsantana on 2007-11-01 21:35:59 as along with 1 person and 2 groups naegele ic4 generif_paper
	On the Convergence of an Estimation of Distribution Algorithm Based on Linkage Discovery and Factorization [My Copy] by Alden H. Wright, Sandeep posted to eda-theory edas learning by rsantana on 2007-06-05 07:58:31 as
	Learning with mixtures of trees [My Copy] (1999) by Meila M. Predoviciu posted to clustering learning mixtures tree by rsantana on 2007-05-30 12:17:33 as
	Random Forests [My Copy] Machine Learning, Vol. 45, No. 1. (October 2001), pp. 5-32. by Leo Breiman posted to graphical-models learning random-forests by rsantana on 2007-04-17 10:29:06 as along with 1 person rabio
	A Simple Approach for Finding [My Copy] by The G. Optimal posted to bayesian bayesian-networks graphical-models learning by rsantana on 2007-03-28 16:03:50 as along with 2 people and 1 group jrw lmarti estimation_of_distribution_algorithms
	The structure and function of complex networks [My Copy] (2003) by M. Newman posted to graphs learning network by rsantana on 2007-03-27 11:57:00 as along with 27 people and 7 groups rrbarb thegoose conservatism dylanwalker aalves orahcio camster korakot arkas Borelli jhammerb cmm scis0000001 bigbossman merazzle fuzzy7761 cerkut rchauhan graphminer xinian dowlingj ltabourier sparikh ransombriggs pprett paulovn pdlug complex networks Philosophy_of_Information dbk-lab Blog_and_Wiki_Research UoA_ODT FAB-lab contact-id
	Generalized Belief Propagation [My Copy] In NIPS (2000), pp. 689-695. by Jonathan S. Yedidia, William T. Freeman, Yair Weiss posted to factor-graphs graphical-models kikuchi-approximations learning region-graphs by rsantana on 2007-03-09 11:03:26 as along with 4 people yaroslavvb lcigler markusd roys
	Dimensionality reduction using genetic algorithms [My Copy] Evolutionary Computation, IEEE Transactions on, Vol. 4, No. 2. (2000), pp. 164-171. by M. L. Raymer, W. F. Punch, E. D. Goodman, L. A. Kuhn, A. K. Jain posted to ga-theory learning by rsantana on 2007-03-09 10:24:41 as along with 1 person kutabar
	A tutorial on learning with Bayesian networks [My Copy] (1999), pp. 301-354. by David Heckerman posted to bayesian learning by rsantana on 2007-03-09 10:17:21 as along with 10 people and 1 group birte yaroslavvb JoSeK mjt abhik garyfeng grimm balicea wnpx slygent ReadingLab
	Machine learning in bioinformatics: A brief survey and recommendations for practitioners [My Copy] Computers in Biology and Medicine In Intelligent Technologies in Medicine and Bioinformatics, Vol. 36, No. 10. (October 2006), pp. 1104-1125. by Harish Bhaskar, David C. Hoyle, Sameer Singh posted to learning bioinformatics by rsantana on 2007-02-08 17:20:08 as along with 3 people svozil drmabuse xili03
	An overview of statistical learning theory [My Copy] Neural Networks, IEEE Transactions on, Vol. 10, No. 5. (1999), pp. 988-999. by V. N. Vapnik posted to learning by rsantana on 2007-02-08 17:18:37 as along with 18 people and 9 groups makni thefillm sourada A_Olympia yaroslavvb anoopsarkar gangli eme garyfeng arsyed yish sdvillal gane5h dwf atbrew d_burfoot balduzzi fredguilloux Philosophy_of_Information Blog_and_Wiki_Research tulip ReadingLab astro mathgamespatterns dtl vds-arg eni
	Learning Factor Graphs in Polynomial Time and Sample Complexity [My Copy] JMLR (2006) by Pieter Abbeel, Daphne Koller, Andrew Y. Ng posted to learning graphical-models factor-graphs by rsantana on 2007-01-25 13:44:17 as along with 4 people and 4 groups rsabbadin mhay feasel chechetka Modèles Graphiques UBIAT kdl unc_cs_eve UNC-FPM
	Probabilistic modeling for continuous EDA with Boltzmann selection and Kullback-Leibeler divergence [My Copy] In GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation (2006), pp. 389-396. by Cai Yunpeng, Sun Xiaomin, Jia Peifa posted to selection learning edas continuous-edas by rsantana on 2007-01-19 19:43:41 as along with 2 people and 4 groups nojhan lmarti EvolutionaryComputation Metaheuristics Optimization estimation_of_distribution_algorithms
	Algorithms for learning decomposable models and chordal graphs [My Copy] No. DECSAI 970213. (1997) by Luis, J. F. Huete posted to chordal-graphs graphical-models learning by rsantana on 2006-12-20 19:22:38 as
	Independency relationship and learning algorithms for singly connected networks [My Copy] Journal of Experimental and Theoretical Artificial Intelligence (1998), pp. 511-549. by Luis posted to graphical-models learning by rsantana on 2006-12-20 19:22:38 as
	Bayesian Evolutionary Algorithms for Learning and Optimization [My Copy] In Proceedings of the Genetic and Evolutionary Computation Conference {GECCO}-2000, Workshop on Optimization by Building and Using Probabilistic Models (OBUPM) (2000), pp. 220-222. by B. T. Zhang posted to bayesian-edas edas learning by rsantana on 2006-12-20 19:22:37 as
	Constructing Free Energy Approximations and Generalized Belief Propagation Algorithms [My Copy] IEEE Transactions on Information Theory, Vol. 51, No. 7. (2005), pp. 2282-2312. by J. S. Yedidia, W. T. Freeman, Y. Weiss posted to graphical-models inference kikuchi-approximations learning propagation region-graphs by rsantana on 2006-12-20 19:22:37 as
	A microscopic study of minimum entropy search in learning decomposable Markov networks [My Copy] Machine Learning, Vol. 26, No. 1. (1997), pp. 65-92. by Y. Xiang, S. K. M. Wong, N. Cercone posted to markov-network learning inference entropy by rsantana on 2006-12-20 19:22:37 as
	Tree approximations to Markov Fields [My Copy] IEEE transactions on pattern analysis and Machine Intelligence, Vol. 17, No. 4. (1995), pp. 391-401. by Chi H. Wu, Peter C. Doerschuk posted to tree markov-fields learning approximations by rsantana on 2006-12-20 19:22:37 as
	Learning Mixtures of Bayesian Networks [My Copy] No. MSR-TR-97-30. (February 1997) by B. Thiesson, C. Meek, D. Chickering, D. Heckerman posted to mixtures learning graphical-models bayesian by rsantana on 2006-12-20 19:22:37 as
	Causation, Prediction and Search [My Copy] Vol. 81 (1993) by P. Spirtes, C. Glymour, R. Scheines posted to learning graphical-models by rsantana on 2006-12-20 19:22:36 as
	Learning Bayesian networks with discrete variables from data [My Copy] In Proceedings of the First International Conference on Knowledge Discovery and Data Mining (1995), pp. 294-299. by P. Spirtes, C. Meek posted to learning graphical-models bayesian-networks by rsantana on 2006-12-20 19:22:36 as
	Using tree-decomposable structures to approximate belief networks [My Copy] IEEE Transactions on Systems, Man, and Cybernetics, No. 24. (1993) by S. Sarkar posted to tree learning graphical-models approximations by rsantana on 2006-12-20 19:22:35 as
	The mixture of trees factorized distribution algorithm [My Copy] No. ICIMAF 2000-129. (January 2001) by R. Santana, A. Ochoa, M. R. Soto posted to mixtures learning fda edas by rsantana on 2006-12-20 19:22:34 as
	Probabilistic Evolution and the Busy Beaver Problem [My Copy] In Late Breaking Papers at the 2000 Genetic and Evolutionary Computation Conference GECCO-2000 (July 2000), pp. 261-268. by Roberto Santana, Francisco B. Pereira, Ernesto Costa, et al.Alberto O. Rodriguez, Penousal Machado, Amilcar Cardoso, Marta R. Soto edited by Darrell Whitley posted to turing-machines learning edas by rsantana on 2006-12-20 19:22:34 as
	The edge incident model [My Copy] In Proceedings of the Second Symposium on Artificial Intelligence (CIMAF-99) (March 1999), pp. 352-359. by R. Santana, Ponce E. de León, A. Ochoa posted to constraints edas fda graphs learning by rsantana on 2006-12-20 19:22:34 as
	The Factorized Distribution Algorithm and the Junction Tree: A Learning Perspective [My Copy] In Proceedings of the Second Symposium on Artificial Intelligence (CIMAF-99) (March 1999), pp. 368-377. by A. Ochoa, M. R. Soto, R. Santana, J. C. Madera, N. Jorge edited by A. Ochoa, M. R. Soto, R. Santana posted to eda-theory edas fda learning optimization by rsantana on 2006-12-20 19:22:25 as
	Learning Bayesian Networks [My Copy] (2003) by R. E. Neapolitan posted to learning bayesian-networks by rsantana on 2006-12-20 19:22:25 as
	Learning with mixtures of trees [My Copy] Journal of Machine Learning Research, Vol. 1 (2000), pp. 1-48. by M. Meila, M. I. Jordan posted to graphical-models learning mixtures tree by rsantana on 2006-12-20 19:22:24 as
	Learning Mixtures of Trees [My Copy] (1999) by Marina Meila posted to graphical-models learning mixtures tree by rsantana on 2006-12-20 19:22:24 as
	Finite Mixture Models [My Copy] (2000) by G. J. Mclachlan, D. Peel posted to graphical-models learning mixtures by rsantana on 2006-12-20 19:22:24 as
	Mixture Models: Inference and Applications to Clustering [My Copy] (1988) by G. J. Mclachlan, K. E. Basford edited by Marcel Dekker posted to graphical-models learning mixtures by rsantana on 2006-12-20 19:22:24 as
	Maximum Entropy Markov Models for Information Extraction and Segmentation [My Copy] In Proc. 17th International Conf. on Machine Learning (2000), pp. 591-598. by Andrew Mccallum, Dayne Freitag, Fernando Pereira posted to entropy graphical-models learning markov-network by rsantana on 2006-12-20 19:22:24 as
	Learning in Graphical Models [My Copy] (1998), pp. 175-204. by D. Mackay edited by M. I. Jordan posted to graphical-models learning by rsantana on 2006-12-20 19:22:23 as

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bibtex-import	329
edas	185
protein	110
genetic-algorithms	92
graphical-models	82
optimization	70
propagation	59
eda-theory	53
bioinformatics	47
learning	47
ga-theory	44
bayesian-edas	40
kikuchi-approximations	39
graphs	35
inference	34
region-graphs	33
complexity	31
entropy	31
network	27
tree	24
boa	23
fitness	19
bayesian	18
clustering	18
mixtures	18
evolutionary-computation	17
umda	17
bayesian-networks	16
continuous-edas	16
fda	16
sampling	15
markov-network	13
constraints	12
multiobjective	11
protein-design	11
partial-evaluation	10
rotamers	10
sidechains	10
approximations	9
linkage	9
neuroscience	9
factor-graphs	8
interactions	8
selection	8
genetic-programming	7
hp-model	7
markov-chains	7
modularity	7
pada	7
classifier-systems	6
data-mining	6
ising	6
mean-field	6
sat	6
adaptation	5
monte-carlo	5
turing-machines	5
aco	4
frustration	4
gaussian	4
markov-fields	4
pbil	4
schema-theory	4
testors	4
vision	4
genetics	3
gibbs-sampling	3
ipf	3
mateda	3
neural-networks	3
pattern-recognition	3
snps	3
bmda	2
cavity-method	2
classifiers	2
decimation	2
dynamic-problems	2
heuristics	2
mutation	2
neighborhood-search	2
r	2
reinforcement-learning	2
second-life	2
software	2
swarms	2
testor	2
turing-machine	2
unitation-functions	2
visualization	2
vns	2
artificial-life	1
ba	1
causality	1
chordal-graphs	1
circuit-reconstruction	1
damping	1
dimensionality-reduction	1
dynamic-optimization	1
ecga	1
fuzzy	1
ica	1
inf	1
max-configurations	1
mdl	1
philosophy	1
qsar	1
random-forests	1
realizability	1
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