Literature

Signature	Author(s)	year	Title
Schoelkopf/etal/2000a	Sch\"olkopf, Bernhard and Smola, Alex J. and Williamson, Robert C. and Bartlett, Peter L.	2000	New Support Vector Algorithms
Press/92a	Press, W. H.	1992	Numerical Recipes in C
Nadaraya/64a	Nadaraya, E. A.	1964	On estimating regression
Parzen/62a	Parzen, E.	1962	On estimation of a probability density function and mode
Engels/96a	Engels, Robert	1996	Planning Tasks for Knowledge Discovery in Databases; Performing Task--Oriented User--Guidance
Friedman/Stuetzle/81a	Friedman, Jerome H. and Stuetzle, W.	1981	Projection pursuit regression
Shavlik/etal/90a	Shavlik, J. W. and Noordewier, N. O. and Towell, G. G.	1990	Refinement of approximate domain theories by knowledge-based neural networks
Torgo/Gama/96a	Torgo, L. and Gama, J.	1996	Regression by Classification
Rosenblatt/56a	Rosenblatt, M.	1956	Remarks on some nonparametric estimates of a density function
Weiss/Indurkhya/93a	Sholom M. Weiss and Nitin Indurkhya	1993	Rule--Based Regression
Weiss/Indurkhya/95a	Weiss, S. and Indurkhya, N.	1995	Rule-based Machine Learning Methods for Functional Prediction
Watson/64a	Watson, G. S.	1964	Smooth Regression Analysis
Loader/Cleveland/95b	Loader, C. and Cleveland, W.	1995	Smoothing by Local Regression: Principles and Methods (with discussion)
Vapnik/98a	V. Vapnik	1998	Statistical Learning Theory
Joachims/98a	Joachims, Thorsten	1998	Text Categorization with Support Vector Machines: Learning with Many Relevant Features
Vapnik/95a	Vladimir N. Vapnik	1995	The Nature of Statistical Learning Theory
Shapire/99a	Robert E. Shapire	1999	Theoretical Views of Boosting and Applications
Joachims/99c	Thorsten Joachims	1999	Transductive Inference for Text Classification using Support Vector Machines