The Relaxed Online Maximum Margin Algorithm (2000)


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by Yi Li , Philip M. Long
Venue:Machine Learning
Citations:73 - 1 self

Active Bibliography

87 A New Approximate Maximal Margin Classification Algorithm – Claudio Gentile - 2001
415 Large Margin Classification Using the Perceptron Algorithm – Yoav Freund, Robert E. Schapire - 1998
Machine Learning, 37(3):277-296, 1999. Large Margin Classification Using the Perceptron Algorithm – unknown authors
Examining Committee: – Frédéric Koriche, Antoine Cornuéjols, Christophe Fiorio, Alain Jean-marie, Jérôme Lang, Pierre Marquis, Abdel-illah Mouaddib, Pascal Poncelet
133 On the Generalization Ability of On-line Learning Algorithms – Nicolo Cesa-Bianchi, Alex Conconi, Claudio Gentile - 2001
4 Simple Learning Algorithms for Training Support Vector Machines – Colin Campbell, Nello Cristianini - 1998
Title: Kernel Methods for Unsupervised Learning – Francesco Camastra, Disi Università Di, Francesco Camastra, Ext Reviewers, Prof Marcello Pelillo, Dr. Massimiliano Pontil
373 An introduction to kernel-based learning algorithms – Klaus-Robert Müller, Sebastian Mika, Gunnar Rätsch, Koji Tsuda, Bernhard Schölkopf - 2001
88 Everything Old Is New Again: A Fresh Look at Historical Approaches – Ryan Michael Rifkin - 2002
67 A fast iterative nearest point algorithm for support vector machine classifier design – S. S. Keerthi, S. K. Shevade, C. Bhattacharyya, K. R. K. Murthy - 2000
10 Random Projection, Margins, Kernels, and Feature-Selection – Avrim Blum - 2005
1 Reduction techniques for training support vector machines – Kuan-ming Lin - 2002
1 Learning with Kernel Machine Architectures – Theodoros Evgeniou, Tomaso Poggio, Helen Whitaker, Professor Brain, Cognitive Sciences, Arthur C. Smith - 2000
9 Optimization Methods In Massive Datasets – P.S. Bradley, O. L. Mangasarian, D. R. Musicant
53 Parameter Estimation for Statistical Parsing Models: Theory and Practice of Distribution-Free Methods – Michael Collins - 2001
108 The analysis of decomposition methods for support vector machines – Chih-jen Lin, Nello Cristianini - 1999
136 Training Invariant Support Vector Machines – Dennis DeCoste, Bernhard Schölkopf, Nello Cristianini - 2002
1 Neural Networks in Economics: Background, Applications and New Developments – Ralf Herbrich, Max Keilbach, Thore Graepel, Peter Bollmann-Sdorra, Klaus Obermayer - 1998
1 A PAC Bound for Approximate Support Vector Machines – Dongwei Cao, Daniel Boley - 2007