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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

Semi-supervised learning by disagreementZHOU, Zhi-Hua; MING LI.Knowledge and information systems (Print). 2010, Vol 24, Num 3, pp 415-439, issn 0219-1377, 25 p.Conference Paper

Learner excellence biased by data set selection: A case for data characterisation and artificial data setsMACIA, Nuria; BERNADO-MANSILLA, Ester; ORRIOLS-PUIG, Albert et al.Pattern recognition. 2013, Vol 46, Num 3, pp 1054-1066, issn 0031-3203, 13 p.Article

Asymmetrical semi-supervised learning and prediction of disulfide connectivity in proteinsMAGNAN, Christophe N.Revue d'intelligence artificielle. 2006, Vol 20, Num 6, pp 673-695, issn 0992-499X, 23 p.Article

A Modified Semi-Supervised Learning Algorithm on Laplacian EigenmapsZHAO, Zhong-Qiu; LI, Jun-Zhao; JUN GAO et al.Neural processing letters. 2010, Vol 32, Num 1, pp 75-82, issn 1370-4621, 8 p.Article

Bias learning, knowledge sharingGHOSN, Joumana; BENGIO, Yoshua.IEEE-INNS-ENNS international joint conference on neural networks. 2000, pp Vol1.9-14, isbn 0-7695-0619-4, 6VolConference Paper

Literature mining of host―pathogen interactions: comparing feature-based supervised learning and language-based approachesTHIEU, Thanh; JOSHI, Sneha; WARREN, Samantha et al.Bioinformatics (Oxford. Print). 2012, Vol 28, Num 6, pp 867-875, issn 1367-4803, 9 p.Article

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

Safe semi-supervised learning based on weighted likelihoodKAWAKITA, Masanori; TAKEUCHI, Jun'ichi.Neural networks. 2014, Vol 53, pp 146-164, issn 0893-6080, 19 p.Article

Weakly Supervised Recognition of Daily Life Activities with Wearable SensorsSTIKIC, Maja; LARLUS, Diane; EBERT, Sandra et al.IEEE transactions on pattern analysis and machine intelligence. 2011, Vol 33, Num 12, pp 2521-2537, issn 0162-8828, 17 p.Article

A novel semi-supervised learning framework with simultaneous text representingYAN ZHU; JIAN YU; LIPING JING et al.Knowledge and information systems (Print). 2013, Vol 34, Num 3, pp 547-562, issn 0219-1377, 16 p.Article

Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised AssumptionsKE CHEN; SHIHAI WANG.IEEE transactions on pattern analysis and machine intelligence. 2011, Vol 33, Num 1, pp 129-143, issn 0162-8828, 15 p.Article

Biased LexRank : Passage retrieval using random walks with question-based priorsOTTERBACHER, Jahna; ERKAN, Gunes; RADEV, Dragomir R et al.Information processing & management. 2009, Vol 45, Num 1, pp 42-54, issn 0306-4573, 13 p.Article

Towards effective document clustering : A constrained K-means based approachGUOBIAO HU; SHUIGENG ZHOU; JIHONG GUAN et al.Information processing & management. 2008, Vol 44, Num 4, pp 1397-1409, issn 0306-4573, 13 p.Article

Investigating Problems of Semi-supervised Learning for Word Sense DisambiguationLE, Anh-Cuong; SHIMAZU, Akira; NGUYEN, Le-Minh et al.Lecture notes in computer science. 2006, pp 482-489, issn 0302-9743, isbn 3-540-49667-X, 1Vol, 8 p.Conference Paper

Search for multi-modality data in digital librariesJUN YANG; YUETING ZHUANG; QING LI et al.Lecture notes in computer science. 2001, Vol 2195, pp 482-489, issn 0302-9743, isbn 3-540-42680-9Conference Paper

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

Improved training rules for multilayered feedforward neural networksSU WHAN SUNG; LEE, Tai-Yong; PARK, Sunwon et al.Industrial & engineering chemistry research. 2003, Vol 42, Num 6, pp 1275-1278, issn 0888-5885, 4 p.Article

Apprentissage supervisé et rappel d'images simples avec le Réseau Neuronal AléatoireHUBERT, C.Comptes rendus de l'Académie des sciences. Série 1, Mathématique. 1993, Vol 316, Num 1, pp 93-96, issn 0764-4442Article

Relationship between phase and amplitude generalization errors in complex- and real-valued feedforward neural networks : Advances in Learning AlgorithmsHIROSE, Akira; YOSHIDA, Shotaro.Neural computing & applications (Print). 2013, Vol 22, Num 7-8, pp 1357-1366, issn 0941-0643, 10 p.Conference Paper

Image deblurring with matrix regression and gradient evolutionSHIMING XIANG; GAOFENG MENG; YING WANG et al.Pattern recognition. 2012, Vol 45, Num 6, pp 2164-2179, issn 0031-3203, 16 p.Article

Supervised Learning of Logical Operations in Layered Spiking Neural Networks with Spike Train EncodingGRINING, André; SPOREA, Ioana.Neural processing letters. 2012, Vol 36, Num 2, pp 117-134, issn 1370-4621, 18 p.Article

Credit rating modelling by kernel-based approaches with supervised and semi-supervised learningHAJEK, Petr; OLEJ, Vladimír.Neural computing & applications (Print). 2011, Vol 20, Num 6, pp 761-773, issn 0941-0643, 13 p.Conference Paper

Improving fuzzy clustering of biological data by metric learning with side informationCECCARELLI, Michele; MARATEA, Antonio.International journal of approximate reasoning. 2008, Vol 47, Num 1, pp 45-57, issn 0888-613X, 13 p.Article

Inducing heuristics to decide whether to scheduleCAVAZOS, John; MOSS, J. Eliot B.ACM SIGPLAN notices. 2004, Vol 39, Num 6, pp 183-194, issn 1523-2867, 12 p.Conference Paper

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