Everything Old Is New Again: A Fresh Look at Historical Approaches

Everything Old Is New Again: A Fresh Look at Historical Approaches (2002)

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[five-percent-nation.mit.edu]

by Ryan Michael Rifkin

Venue:	in Machine Learning. PhD thesis, MIT
Citations:	68 - 5 self

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@INPROCEEDINGS{Rifkin02everythingold,
    author = {Ryan Michael Rifkin},
    title = {Everything Old Is New Again: A Fresh Look at Historical Approaches},
    booktitle = {in Machine Learning. PhD thesis, MIT},
    year = {2002}
}

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2 Everything Old Is New Again: A Fresh Look at Historical

Citations

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159	Least squares support vector machine classifiers - Suykens, Vandewalle - 1999
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139	Improvements to platt’s SMO algorithm for SVM classifier design - Keerthi, Shevade, et al.
139	Sparse greedy matrix approximation for machine learning - Smola, Schölkopf - 2000
130	Practical Methods of Optimization, Second Edition - Fletcher - 1987
122	Support Vector Machines, Reproducing Kernel Hilbert Spaces and the randomized GACV - Wahba - 1997
116	Multicategory Support Vector Machines, Theory, and Application to the Classification of Microarray Data and Satellite Radiance Data - Lee, Lin, et al. - 2004
112	Spline Models for Observational Data, volume 59 - Wahba - 1990
109	Y: On the Learnability and Design of Output Codes for Multiclass Problems. Computational Learning Theory - Crammer, Singer
103	Another Approach to Polychotomous Classification - FRIEDMAN - 1996
96	A Generalized Representer Theorem - Schölkopf, Herbrich, et al.
81	The kernel-Adatron algorithm: a fast and simple learning procedure for support vector machines - Frieb, Cristianini, et al. - 1998
81	Networks and the best approximation property - Girosi, Poggio - 1989
80	Multisurface Proximal Support Vector Machine Classification via Generalized Eigenvalues - Mangasarian, Wild - 2006