http://www.bibsonomy.org/burst/user/sb3000/seminalBibSonomy BuRST Feed for /user/sb3000/seminal2008-07-21T01:25:00+02:00A training algorithm for optimal margin classifiershttp://www.bibsonomy.org/bibtex/25e95eb501377a9fcd8513893f8250082/sb3000sb30002008-05-16T16:54:11+02:00svm seminal <span style="color:#555555;">Bernhard E. <a href="http://www.bibsonomy.org/author/Boser">Boser</a> and Isabelle M. <a href="http://www.bibsonomy.org/author/Guyon">Guyon</a> and Vladimir N. <a href="http://www.bibsonomy.org/author/Vapnik">Vapnik</a> </span><em>Proceedings of the 5th Annual Workshop on Computational Learning Theory (COLT '92), July 27-29, 1992, Pittsburgh, PA, USA, </em><em>page144--152. </em><em>ACM Press, New York, NY, USA, </em>(<em>1992</em>)Fri May 16 16:54:11 CEST 2008Proceedings of the 5th Annual Workshop on Computational Learning Theory (COLT '92), July 27-29, 1992, Pittsburgh, PA, USA144--152A Training Algorithm for Optimal Margin Classifiers1992svm seminal : mf : blob : » bibtexhttp://www.bibsonomy.org/bibtex/206a5a6751b3e61408455fca2ed8d87fc/sb3000sb30002008-05-16T13:57:01+02:00linear-classification neural-networks seminal <span style="color:#555555;">Marvin <a href="http://www.bibsonomy.org/author/Minsky">Minsky</a> and Seymour <a href="http://www.bibsonomy.org/author/Papert">Papert</a> </span><em>MIT Press, </em><em>Cambridge, MA, USA, </em>(<em>1969</em>)Fri May 16 13:57:01 CEST 2008Cambridge, MA, USAPerceptrons: An Introduction to Computational Geometry1969linear-classification neural-networks seminal http://www.bibsonomy.org/bibtex/2f138d4d67e0bed94bd3c726af83c0492/sb3000sb30002008-02-12T18:07:08+01:00algorithms seminal ml <span style="color:#555555;">T. <a href="http://www.bibsonomy.org/author/Cover">Cover</a> and P. <a href="http://www.bibsonomy.org/author/Hart">Hart</a> </span><em>IEEE Transactions on Information Theory</em>(<em>1967</em>)Tue Feb 12 18:07:08 CET 2008IEEE Transactions on Information Theory21- 27Nearest neighbor pattern classification131967algorithms seminal ml The nearest neighbor decision rule assigns to an unclassified sample point the classification of the nearest of a set of previously classified points. This rule is independent of the underlying joint distribution on the sample points and their classifications, and hence the probability of errorRof such a rule must be at least as great as the Bayes probability of errorR^{ast}--the minimum probability of error over all decision rules taking underlying probability structure into account. However, in a large sample analysis, we will show in theM-category case thatR^{ast} leq R leq R^{ast}(2 --MR^{ast}/(M-1)), where these bounds are the tightest possible, for all suitably smooth underlying distributions. Thus for any number of categories, the probability of error of the nearest neighbor rule is bounded above by twice the Bayes probability of error. In this sense, it may be said that half the classification information in an infinite sample set is contained in the nearest neighbor.http://www.bibsonomy.org/bibtex/26feb937c9fe413ded19ca9c0849c79ea/sb3000sb30002007-10-01T20:55:04+02:00seminal ontology knowledge-engineering knowledge-representation <span style="color:#555555;">T. R. <a href="http://www.bibsonomy.org/author/Gruber">Gruber</a> </span><em>International Journal of Human and Computer Studies</em><em>43(5/6):907-982</em>(<em>1995</em>)Mon Oct 01 20:55:04 CEST 2007International Journal of Human and Computer Studies5/6907-982Towards Principles for the Design of Ontologies Used for Knowledge Sharing431995seminal ontology knowledge-engineering knowledge-representation http://www.bibsonomy.org/bibtex/2a2a070a444033efe42447db739130d47/sb3000sb30002007-09-05T16:07:21+02:00ai book seminal <span style="color:#555555;">H. A. <a href="http://www.bibsonomy.org/author/Simon">Simon</a> </span><em>MIT Press, </em><em>Cambridge, MA, USA, </em><em>third edition, </em>(<em>1996</em>)Wed Sep 05 16:07:21 CEST 2007Cambridge, MA, USAthirdThe Sciences of the Artificial1996ai book seminal http://www.bibsonomy.org/bibtex/200c94cf42a12180b494e31e6d725b52d/sb3000sb30002007-06-29T21:12:08+02:00seminal ir <span style="color:#555555;">C. J. <a href="http://www.bibsonomy.org/author/van Rijsbergen">van Rijsbergen</a> </span><em>Butterworths, </em><em>London, </em><em>2 edition, </em>(<em>1979</em>)Fri Jun 29 21:12:08 CEST 2007London2Information Retrieval1979seminal ir http://www.bibsonomy.org/bibtex/2c9d8d78a8e1bb5adecc7602490f4323f/sb3000sb30002007-05-30T17:15:05+02:00seminal linear-classification <span style="color:#555555;">R. A. <a href="http://www.bibsonomy.org/author/Fisher">Fisher</a> </span><em>Annals of Eugenics</em><em>7(7):179-188</em>(<em>1936</em>)Wed May 30 17:15:05 CEST 2007Annals of Eugenics7179-188The Use of Multiple Measurements in Taxonomic Problems71936seminal linear-classification http://www.bibsonomy.org/bibtex/2a508c250a6e93d6185b4f37c01d27597/sb3000sb30002007-05-30T16:42:51+02:00linear-classification seminal neural-networks <span style="color:#555555;">F. <a href="http://www.bibsonomy.org/author/Rosenblatt">Rosenblatt</a> </span><em>Psychological Review</em>(<em>1958</em>)Wed May 30 16:42:51 CEST 2007Psychological Review386-408The perceptron: A probabilistic model for information storage and organization in the brain651958linear-classification seminal neural-networks http://www.bibsonomy.org/bibtex/2ff96d52c195563a280d57b6b3092c3fb/sb3000sb30002006-09-15T11:18:07+02:00seminal modelling database <span style="color:#555555;">Peter Pin-Shan <a href="http://www.bibsonomy.org/author/Chen">Chen</a> </span><em>ACM Trans. Database Syst.</em><em>1(1):9-36</em>(<em>1976</em>)Fri Sep 15 11:18:07 CEST 2006ACM Trans. Database Syst.19-36The Entity-Relationship Model - Toward a Unified View of Data11976seminal modelling database http://www.bibsonomy.org/bibtex/2cff16253f759e1012f3b472deae3a208/sb3000sb30002006-02-02T22:11:05+01:00text-mining nlp seminal <span style="color:#555555;">G. K. <a href="http://www.bibsonomy.org/author/Zipf">Zipf</a> </span><em>Journal of General Psychology</em><em>1945(33):251--256</em>(<em>1945</em>)Thu Feb 02 22:11:05 CET 2006Journal of General Psychology33251--256{The Meaning-Frequency Relationship of Words}19451945text-mining nlp seminal