Regularization networks and support vector machines (2000)

by Theodoros Evgeniou , Massimiliano Pontil , Tomaso Poggio
Venue:Advances in Computational Mathematics
Citations:266 - 33 self

Active Bibliography

50 A unified framework for Regularization Networks and Support Vector Machines – Theodoros Evgeniou, Massimiliano Pontil - 1999
1 Learning with Kernel Machine Architectures – Theodoros Evgeniou, Tomaso Poggio, Helen Whitaker, Professor Brain, Cognitive Sciences, Arthur C. Smith - 2000
309 Regularization Theory and Neural Networks Architectures – Federico Girosi, Michael Jones, Tomaso Poggio - 1995
2 Faithful Representations and Moments of Satisfaction: Probabilistic Methods in Learning and Logic – Lidror Troyansky, Prof Naftali Tishby - 1998
103 The mathematics of learning: Dealing with data – Tomaso Poggio, Steve Smale - 2003
35 A Review of Kernel Methods in Machine Learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
205 An equivalence between sparse approximation and Support Vector Machines – Federico Girosi - 1997
110 An introduction to boosting and leveraging – Ron Meir, Gunnar Rätsch - 2003
473 A tutorial on support vector regression – Alex J. Smola, Bernhard Schölkopf - 2004
7 VC Theory of Large Margin Multi-Category Classifiers – Yann Guermeur, Isabelle Guyon, Amir Saffari
1 A review of RKHS methods in machine learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
12 The Subspace Information Criterion for Infinite Dimensional Hypothesis Spaces – Masashi Sugiyama, Klaus-Robert Müller, Nello Cristianini - 2002
13 The Informational Complexity of Learning from Examples – Partha Niyogi - 1996
12 Regression and Classification with Regularization – Sayan Mukherjee, Ryan Rifkin, Tomaso Poggio - 2002
6 Large margin multi-category discriminant models and scale-sensitive Ψ-dimensions – Yann Guermeur - 2006
23 Support vector machine soft margin classifiers: Error analysis – Di-rong Chen, Qiang Wu, Yiming Ying, Ding-xuan Zhou - 2004
88 Everything Old Is New Again: A Fresh Look at Historical Approaches – Ryan Michael Rifkin - 2002
8 Empirical Risk Approximation: An Induction Principle for Unsupervised Learning – Joachim M. Buhmann - 1998
40 A Sparse Representation for Function Approximation – Tomaso Poggio, Federico Girosi - 1998