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CeliClassifier: supervised learning of cellular phenotypesRÄMÖ, Pauli; SACHER, Raphael; SNIJDER, Berend et al.Bioinformatics (Oxford. Print). 2009, Vol 25, Num 22, pp 3028-3030, issn 1367-4803, 3 p.Article

The rise and fall of supervised machine learning techniquesJUHL JENSEN, Lars; BATEMAN, Alex.Bioinformatics (Oxford. Print). 2011, Vol 27, Num 24, pp 3331-3332, issn 1367-4803, 2 p.Article

An Unsupervised Automated Essay-Scoring SystemCHEN, Yen-Yu; LIU, Chien-Liang; LEE, Chia-Hoang et al.IEEE intelligent systems. 2010, Vol 25, Num 5, pp 61-67, issn 1541-1672, 7 p.Article

A closed-form reduction of multi-class cost-sensitive learning to weighted multi-class learningFEN XIA; YANG, Yan-Wu; LIANG ZHOU et al.Pattern recognition. 2009, Vol 42, Num 7, pp 1572-1581, issn 0031-3203, 10 p.Article

Application of feature selection for unsupervised learning in prosecutors' officePENG LIU; JIAXIAN ZHU; LANJUAN LIU et al.Lecture notes in computer science. 2005, issn 0302-9743, isbn 3-540-28312-9, 2Vol, Part II, 35-38Conference Paper

A neurobiologically motivated model for self-organized learningEMMERT-STREIB, Frank.Lecture notes in computer science. 2005, pp 415-424, issn 0302-9743, isbn 3-540-29896-7, 1Vol, 10 p.Conference Paper

The imbalanced training sample problem: Under or over sampling?BARANDELA, Ricardo; VALDOVINOS, Rosa M; SANCHEZ, J. Salvador et al.Lecture notes in computer science. 2004, pp 806-814, issn 0302-9743, isbn 3-540-22570-6, 9 p.Conference Paper

Apprentissage supervisé de règles de décision multiclasses avec contraintes de performances évolutives = Supervised learning of multiclass decision rules with evolutive performance constraintsJRAD, Nisrine; GRALL-MAES, Edith; BEAUSEROY, Pierre et al.Colloque sur le traitement du signal et des images. 2009, 1Vol, p. 93Conference Paper

Ordinal regression based subpixel shift estimation for video super-resolutionDAS GUPTA, Mithun; RAJARAM, Shyamsundar; HUANG, Thomas S et al.EURASIP Journal on Advances in Signal Processing (Print). 2007, Vol 2007, Num 18, issn 1687-6172, B1-B9Article

Refining hierarchical taxonomy structure via Semi-supervised LearningRUIZHANG HUANG; ZHIGANG ZHANG; LAM, Wai et al.International ACM SIGIR conference on research and development in information retrieval. 2006, pp 653-654, isbn 1-59593-369-7, 1Vol, 2 p.Conference Paper

Graph based semi-supervised learning with sharper edgesSHIN, Hyunjung; HILL, N. Jeremy; RÄTSCH, Gunnar et al.Lecture notes in computer science. 2006, pp 401-412, issn 0302-9743, isbn 3-540-45375-X, 1Vol, 12 p.Conference Paper

Data preprocessing and kappa coefficientLEGRAND, Gaelle; NICOLOYANNIS, Nicolas.Lecture notes in computer science. 2005, issn 0302-9743, isbn 3-540-28653-5, 2Vol, Part I, 176-184Conference Paper

Efficient face orientation discriminationBALUJA, Shumeet; SAHAMI, Mehran; ROWLEY, Henry A et al.International Conference on Image Processing. 2004, isbn 0-7803-8554-3, 5Vol, Vol1, 589-592Conference Paper

Using a modified counter-propagation algorithm to classify conjoint dataPIERROT, Hans; HENDTLASS, Tim.Lecture notes in computer science. 2003, pp 337-347, issn 0302-9743, isbn 3-540-40455-4, 11 p.Conference Paper

Twin support vector machine with Universum dataZHIQUAN QI; YINGJIE TIAN; YONG SHI et al.Neural networks. 2012, Vol 36, pp 112-119, issn 0893-6080, 8 p.Article

Online Security Threats and Computer User IntentionsSTAFFORD, Thomas F; POSTON, Robin.Computer (Long Beach, CA). 2010, Vol 43, Num 1, pp 58-64, issn 0018-9162, 7 p.Article

Classification et apprentissage faiblement supervisé en acoustique halieutique = Classification and weakly supervised learning in halieutic acousticsLEFORT, Riwal; FABLET, Ronan; BOUCHER, Jean-Marc et al.Colloque sur le traitement du signal et des images. 2009, 1Vol, p. 138Conference Paper

Ensembles of multi-instance learnersZHOU, Zhi-Hua; ZHANG, Min-Ling.Lecture notes in computer science. 2003, pp 492-502, issn 0302-9743, isbn 3-540-20121-1, 11 p.Conference Paper

Similarity assessment for removal of noisy end user license agreementsLAVESSON, Niklas; AXELSSON, Stefan.Knowledge and information systems (Print). 2012, Vol 32, Num 1, pp 167-189, issn 0219-1377, 23 p.Article

Extraction from the Web of Articles Describing Problems, Their Solutions, and Their CausesMURATA, Masaki; TANJI, Hiroki; YAMAMOTO, Kazuhide et al.IEICE transactions on information and systems. 2011, Vol 94, Num 3, pp 734-737, issn 0916-8532, 4 p.Article

Semi-supervised learning improves gene expression-based prediction of cancer recurrenceMINGGUANG SHI; BING ZHANG.Bioinformatics (Oxford. Print). 2011, Vol 27, Num 21, pp 3017-3023, issn 1367-4803, 7 p.Article

An ensemble uncertainty aware measure for directed hill climbing ensemble pruningPARTALAS, Ioannis; TSOUMAKAS, Grigorios; VLAHAVAS, Ioannis et al.Machine learning. 2010, Vol 81, Num 3, pp 257-282, issn 0885-6125, 26 p.Article

Combining Label Information and Neighborhood Graph for Semi-supervised LearningLIANWEI ZHAO; SIWEI LUO; MEI TIAN et al.Lecture notes in computer science. 2006, pp 482-488, issn 0302-9743, isbn 3-540-34439-X, 7 p.Conference Paper

Solving semi-infinite linear programs using boosting-like methodsRATSCH, Gunnar.Lecture notes in computer science. 2006, pp 10-11, issn 0302-9743, isbn 3-540-46649-5, 1Vol, 2 p.Conference Paper

On Asymmetric Classifier Training for Detector CascadesGEE, Timothy F.Lecture notes in computer science. 2006, pp 843-850, issn 0302-9743, isbn 3-540-48628-7, 8 p.Conference Paper

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