http://www.bibsonomy.org/burst/user/schaul/and,BibSonomy BuRST Feed for /user/schaul/and,2008-07-26T04:44:34+02:00idsiahttp://www.bibsonomy.org/bibtex/20eaf250f52c44307eabd9be2a34e50e4/schaulschaul2008-02-26T11:58:58+01:00and, paper, lindenmayer, genetic, philosophy, poster, l-systems, juergen, programming algorithms, pedagogy, methodology, <span style="color:#555555;">G. R. <a href="http://www.bibsonomy.org/author/Harick">Harick</a> and F. G. <a href="http://www.bibsonomy.org/author/Lobo">Lobo</a> </span><em>Proceedings of the Genetic and Evolutionary Computation Conference, </em><em>2, </em><em>Orlando, Florida, USA, </em><em>Morgan Kaufmann, </em><em>JanuaryMarch-JanuaryJuly July1999. </em>Tue Feb 26 11:58:58 CET 2008Orlando, Florida, USAProceedings of the Genetic and Evolutionary Computation ConferenceJanuaryMarch-JanuaryJuly JulyA parameter-less genetic algorithm21999and, paper, lindenmayer, genetic, philosophy, poster, l-systems, juergen, programming algorithms, pedagogy, methodology, idsiahttp://www.bibsonomy.org/bibtex/2a6f77b57f9dd6af428692b40ecc13a73/schaulschaul2008-02-26T11:58:58+01:00expert, weights, juergen, bounds, online, of, loss, adaptive, with hierarchy, rate, advice, learning, adversary, sequential, follow, and, high, expected, alphabet, probability, general, perturbed, experts, prediction, the, leader, <span style="color:#555555;">M. <a href="http://www.bibsonomy.org/author/Hutter">Hutter</a> and J. <a href="http://www.bibsonomy.org/author/Poland">Poland</a> </span><em>Journal of Machine Learning Research</em>(<em>2005</em>)Tue Feb 26 11:58:58 CET 2008Journal of Machine Learning Research639--660Adaptive Online Prediction by Following the Perturbed Leader62005expert, weights, juergen, bounds, online, of, loss, adaptive, with hierarchy, rate, advice, learning, adversary, sequential, follow, and, high, expected, alphabet, probability, general, perturbed, experts, prediction, the, leader, idsiahttp://www.bibsonomy.org/bibtex/2b9394ee75dd5db37341b62745634de89/schaulschaul2008-02-26T11:58:58+01:00prediction, leader, perturbed, follow, online, and, weights, expected, with expert, alphabet, hierarchy, loss, general, probability, juergen, sequential, the, bounds, learning, adaptive, advice, of, rate, experts, high, <span style="color:#555555;">M. <a href="http://www.bibsonomy.org/author/Hutter">Hutter</a> and J. <a href="http://www.bibsonomy.org/author/Poland">Poland</a> </span><em>Proc. 15th International Conf. on Algorithmic Learning Theory (ALT'04), </em><em>volume3244ofLNAI, </em><em>page279--293. </em><em>Padova, </em><em>Springer, Berlin, </em>(<em>2004</em>)Tue Feb 26 11:58:58 CET 2008PadovaProc. 15th International Conf. on Algorithmic Learning Theory ({ALT'04})279--293LNAIPrediction with Expert Advice by Following the Perturbed Leader for General Weights32442004prediction, leader, perturbed, follow, online, and, weights, expected, with expert, alphabet, hierarchy, loss, general, probability, juergen, sequential, the, bounds, learning, adaptive, advice, of, rate, experts, high, idsiahttp://www.bibsonomy.org/bibtex/23e33239f0046b223f066a4fbe60edcd6/schaulschaul2008-02-26T11:58:58+01:00statistics, bayes, order, of, information, dirichlet, feature, and, juergen, filters, mutual, distribution, variance selection, naive, classifier, cross, expectation, bayesian, second, entropy, <span style="color:#555555;">Marcus <a href="http://www.bibsonomy.org/author/Hutter">Hutter</a> and Marco <a href="http://www.bibsonomy.org/author/Zaffalon">Zaffalon</a> </span><em>Computational Statistics \&amp; Data Analysis</em><em>48(3):633--657</em>(<em>2005</em>)Tue Feb 26 11:58:58 CET 2008Computational Statistics \& Data Analysis3633--657Distribution of Mutual Information from Complete and Incomplete Data482005statistics, bayes, order, of, information, dirichlet, feature, and, juergen, filters, mutual, distribution, variance selection, naive, classifier, cross, expectation, bayesian, second, entropy, idsiahttp://www.bibsonomy.org/bibtex/2f65403f6346a5b6747be35f3f4f3ac2f/schaulschaul2008-02-26T11:58:58+01:00variance statistics, credible, of, robust, selection, classifier, approach, dirichlet, distribution, bayesian, missing, naive, cross, information, bayes, expectation, filter, juergen, order, mutual, and, entropy, intervals, feature, data, second, <span style="color:#555555;">Marco <a href="http://www.bibsonomy.org/author/Zaffalon">Zaffalon</a> and Marcus <a href="http://www.bibsonomy.org/author/Hutter">Hutter</a> </span><em>Proc. 18th International Conf. on Uncertainty in Artificial Intelligence (UAI-2002), </em><em>page577--584. </em><em>Morgan Kaufmann, San Francisco, CA, </em>(<em>2002</em>)Tue Feb 26 11:58:58 CET 2008Proc. 18th International Conf. on Uncertainty in Artificial Intelligence (UAI-2002)577--584Robust Feature Selection by Mutual Information Distributions2002variance statistics, credible, of, robust, selection, classifier, approach, dirichlet, distribution, bayesian, missing, naive, cross, information, bayes, expectation, filter, juergen, order, mutual, and, entropy, intervals, feature, data, second, idsiahttp://www.bibsonomy.org/bibtex/2196353ab4f02ae1e2973c01d08d38c45/schaulschaul2008-02-26T11:58:58+01:00and, cross, expectation, mutual, of, juergen, order, entropy, distribution, information, dirichlet, second, variance <span style="color:#555555;">M. <a href="http://www.bibsonomy.org/author/Hutter">Hutter</a> </span><em>Advances in Neural Information Processing Systems 14, </em><em>page399--406. </em><em>Cambridge, MA, </em><em>MIT Press, </em>(<em>2002</em>)Tue Feb 26 11:58:58 CET 2008Cambridge, MAAdvances in Neural Information Processing Systems 14399--406Distribution of Mutual Information2002and, cross, expectation, mutual, of, juergen, order, entropy, distribution, information, dirichlet, second, variance