General Cost Functions for Support Vector Regression (1998)

Cached

Download Links

by Alex J. Smola , Bernhard Schölkopf , Klaus-Robert Müller
Venue:IN PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS
Citations:37 - 7 self

Active Bibliography

473 A tutorial on support vector regression – Alex J. Smola, Bernhard Schölkopf - 2004
146 The Connection between Regularization Operators and Support Vector Kernels – Alex J. Smola, Bernhard Schölkopf, Klaus-Robert Müller - 1998
77 On a Kernel-based Method for Pattern Recognition, Regression, Approximation, and Operator Inversion – Alex J. Smola, Bernhard Schölkopf - 1997
205 An equivalence between sparse approximation and Support Vector Machines – Federico Girosi - 1997
2272 A tutorial on support vector machines for pattern recognition – Christopher J. C. Burges - 1998
1 A review of RKHS methods in machine learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
35 A Review of Kernel Methods in Machine Learning – Thomas Hofmann, Bernhard Schölkopf, Alexander J. Smola - 2006
3 Convex Cost Functions for Support Vector Regression – Alex Smola, Bernhard Schölkopf, Klaus-Robert Müller - 1998
Contributed article The connection between regularization operators and support vector kernels – Alex J. Smola, Bernhard Schölkopf, Klaus-robert Müller - 1997
4 Primal-dual optimization methods in neural networks and support vector machines training – Theodore B. Trafalis - 1999
108 The analysis of decomposition methods for support vector machines – Chih-jen Lin, Nello Cristianini - 1999
73 The Relaxed Online Maximum Margin Algorithm – Yi Li, Philip M. Long - 2000
5 Mathematical Programming Approaches To Machine Learning And Data Mining – Paul S. Bradley - 1998
Title: Kernel Methods for Unsupervised Learning – Francesco Camastra, Disi Università Di, Francesco Camastra, Ext Reviewers, Prof Marcello Pelillo, Dr. Massimiliano Pontil
42 Support Vector Machine - Reference Manual – C. Saunders, M. O. Stitson, J. Weston, Royal Holloway, L. Bottou, B. Schölkopf, A. Smola, Rhul Y. Lecun (at - 1998
2 An Adaptive Support Vector Regression Filter: A Signal Detection Application – Roman Rosipal, Mark Girolami - 1999
4 How to Implement A Priori Information: A Statistical Mechanics Approach – Jörg C. Lemm - 1998
2 Faithful Representations and Moments of Satisfaction: Probabilistic Methods in Learning and Logic – Lidror Troyansky, Prof Naftali Tishby - 1998
4 Simple Learning Algorithms for Training Support Vector Machines – Colin Campbell, Nello Cristianini - 1998