Pointer to references on statistical learning and classifiers
This is NOT, by any means, an exhaustive list of references about statistical learning. It is
just meant as a primer for those interested in learning about classifiers and algorithms to
learn from examples.
An excellent and important book on statistical learning theory
V. Vapnik, The Nature of Statistical Learning Theory. 1995, New York: Springer.
GK1428
A more general book that includes some topics in statistical learning
C.M. Bishop, Neural Networks for Pattern Recognition. 1995, Oxford: Clarendon Press.
Gk637
C. Burges, A tutorial on support vector machines for pattern recognition. Data Mining
and Knowledge Discovery, 1998. 2: 121-167.
GK15041
T. Poggio and S. Smale, The mathematics of learning: dealing with data. Notices of the
AMS, 2003. 50: 537-544.
Gk15981
Mathworks
See “classify” function in matlab
An article using statistical learning to decode neuronal activity
Hung, C., Kreiman, G., Poggio, T., and DiCarlo, J. (2005). Fast Read-out of Object
Identity from Macaque Inferior Temporal Cortex. Science 310, 863-866.
Gk19961
About multiclass problems
R. Rifkin and A. Klautau, In defense of one-vs-all classification. Journal of Machine
Learning Research, 2004. 5: 101-110.
Gk16511
1
This refers to an internal reference number. Some (but not all) of these papers can be
downloaded in PDF format from http://ramonycajal.mit.edu/kreiman/papers/gk/