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Boosting as a metaphor for algorithm designLEYTON-BROWN, Kevin; NUDELMAN, Eugene; ANDREW, Galen et al.Lecture notes in computer science. 2003, pp 899-903, issn 0302-9743, isbn 3-540-20202-1, 5 p.Conference Paper

Random subclass boundsMENDELSON, Shahar; PHILIPS, Petra.Lecture notes in computer science. 2003, pp 329-343, issn 0302-9743, isbn 3-540-40720-0, 15 p.Conference Paper

Exploring learnability between Exact and PACBSHOUTY, Nader H; JACKSON, Jeffrey C; TAMON, Christino et al.Lecture notes in computer science. 2002, pp 244-254, issn 0302-9743, isbn 3-540-43836-X, 11 p.Conference Paper

iboost : Boosting using an instance-based exponential weighting schemeKWEK, Stephen; NGUYEN, Chau.Lecture notes in computer science. 2002, pp 245-257, issn 0302-9743, isbn 3-540-44036-4, 13 p.Conference Paper

Pairwise classification as an ensemble techniqueFÜRNKRANZ, Johannes.Lecture notes in computer science. 2002, pp 97-110, issn 0302-9743, isbn 3-540-44036-4, 14 p.Conference Paper

Learning with an embedded reject optionSUNDARARAJAN, Ramasubramanian; PAL, Asim K.Lecture notes in computer science. 2004, pp 664-669, issn 0302-9743, isbn 3-540-22123-9, 6 p.Conference Paper

Probabilistic predicative programmingHEHNER, Eric C. R.Lecture notes in computer science. 2004, pp 169-185, issn 0302-9743, isbn 3-540-22380-0, 17 p.Conference Paper

New lower bounds for Statistical Query learningKE YANG.Lecture notes in computer science. 2002, pp 229-243, issn 0302-9743, isbn 3-540-43836-X, 15 p.Conference Paper

A few notes on statistical learning theoryMENDELSON, Shahar.Lecture notes in computer science. 2003, pp 1-40, issn 0302-9743, isbn 3-540-00529-3, 40 p.Conference Paper

Universal well-calibrated algorithm for on-line classificationVOVK, Vladimir.Lecture notes in computer science. 2003, pp 358-372, issn 0302-9743, isbn 3-540-40720-0, 15 p.Conference Paper

Ontology mapping: An integrated approachEHRIG, Marc; SURE, York.Lecture notes in computer science. 2004, pp 76-91, issn 0302-9743, isbn 3-540-21999-4, 16 p.Conference Paper

How to make AdaBoost.M1 work for weak base classifiers by changing only one line of the codeEIBL, Günther; PFEIFFER, Karl Peter.Lecture notes in computer science. 2002, pp 72-83, issn 0302-9743, isbn 3-540-44036-4, 12 p.Conference Paper

Highlighting hard patterns via AdaBoost weights evolutionCAPRILE, Bruno; FURLANELLO, Cesare; MERLER, Stefano et al.Lecture notes in computer science. 2002, pp 72-80, issn 0302-9743, isbn 3-540-43818-1, 9 p.Conference Paper

A discussion on the Classifier Projection Space for Classifier combiningPEKALSKA, Elzbieta; DUIN, Robert P. W; SKURICHINA, Marina et al.Lecture notes in computer science. 2002, pp 137-148, issn 0302-9743, isbn 3-540-43818-1, 12 p.Conference Paper

Neural network realization of support vector methods for pattern classificationYING TAN; YOUSHEN XIA; JUN WANG et al.IEEE-INNS-ENNS international joint conference on neural networks. 2000, pp Vol6.411-416, isbn 0-7695-0619-4, 6VolConference Paper

Probably approximate learning over classes of distributionsNATARAJAN, B. K.SIAM journal on computing (Print). 1992, Vol 21, Num 3, pp 438-449, issn 0097-5397Article

The neural correlates of reward-related trial-and-error learning : An fMRI study with a probabilistic learning taskKOCH, Kathrin; SCHACHTZABEL, Claudia; WAGNER, Gerd et al.Learning & memory (Cold Spring Harbor, N.Y.). 2008, Vol 15, Num 7-12, pp 728-732, issn 1072-0502, 5 p.Article

A non-local coarsening result in granular probabilistic networksBUTZ, Cory J; HONG YAO; HAMILTON, Howard J et al.Lecture notes in computer science. 2003, pp 686-689, issn 0302-9743, isbn 3-540-14040-9, 4 p.Conference Paper

Multiple-cue probabilistic learning in spider-fearful and in panic-prone individualsKOPP, Bruno; ALTMANN, René; HERMANN, Christiane et al.Journal of behavior therapy and experimental psychiatry. 2003, Vol 34, Num 2, pp 101-115, issn 0005-7916, 15 p.Article

Distributed pasting of small votesCHAWLA, N. V; HALL, L. O; BOWYER, K. W et al.Lecture notes in computer science. 2002, pp 52-61, issn 0302-9743, isbn 3-540-43818-1, 10 p.Conference Paper

Scaling boosting by margin-based inclusion of features and relationsHOCHE, Susanne; WROBEL, Stefan.Lecture notes in computer science. 2002, pp 148-160, issn 0302-9743, isbn 3-540-44036-4, 13 p.Conference Paper

Stochastic finite learningZEUGMANN, Thomas.Lecture notes in computer science. 2001, pp 155-171, issn 0302-9743, isbn 3-540-43025-3Conference Paper

Probability learning, event-splitting effects and the economic theory of choiceHUMPHREY, S. J.Theory and decision. 1999, Vol 46, Num 1, pp 51-78, issn 0040-5833Article

Interaction of data and hypotheses in probabilistic inference tastks : rejection of the hypothesis sampling model ?KNEZ, I.Scandinavian journal of psychology. 1991, Vol 32, Num 1, pp 57-69, issn 0036-5564Article

Universal consistency and bloat in GP : Some theoretical considerations about genetic programming from a statistical learning theory viewpointGELLY, Sylvain; TEYTAUD, Olivier; BREDECHE, Nicolas et al.Revue d'intelligence artificielle. 2006, Vol 20, Num 6, pp 805-827, issn 0992-499X, 23 p.Article

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