cross validation

[Grace Wahba]

Re: Cross validation and Generalized Cross Validation: 
These tools are widely used in the statistics literature
to resolve the bias - variance tradeoff in various 
contexts, including some which might be considered ml, 
and many image reconstruction algorithms, especially 
those which might be considered deconvolution. There 
is also some work on edge detection. 

You can read all about it in the context of multivariate
function estimation and regularization  (in reproducing kernel 
Hilbert spaces) 
in "Spline Models for Observational Data" - (see *** below) 
including 30 
pages of references, mostly to the smoothing and regularization 
literature. Thin plate splines (source of one of the 
popular radial basis functions) also get a chapter.

As a statistician new to the ml literature I am having fun 
reading the ml mail and observe that there is a growing overlap 
between the ml the statistics literature and all would 
benefit from seeing what the other side is doing...

..***....
Spline Models for Observational Data, by Grace Wahba
v. 59 in the CBMS-NSF Regional Conference
Series in Applied Mathematics, 
SIAM, Philadelphia, PA, March 1990. 
Softcover, 169 pages, bibliography, author index.
ISBN 0-89871-244-0

List Price $24.75, SIAM or CBMS* Member Price $19.80
(Domestic 4th class postage free, UPS or Air extra)

May be ordered from SIAM by mail, electronic mail, or phone:

SIAM
P. O. Box 7260
Philadelphia, PA 19101-7260
USA

SIAM at wharton.upenn.edu

1-800-447-7426 (8:30-4:45 Eastern Standard Time, 
toll-free from the US, I dont know if this works overseas)

May be ordered on American Express, Visa or Mastercard,
or may be billed (extra charge).

CBMS member organizations include AMATC, AMS, ASA, ASL, ASSM, 
IMS, MAA, NAM, NCSM, ORSA, SOA and TIMS.