Although computer speed has steadily increased and memory is getting cheaper, the need for storage managers to deal efficiently with applications that cannot be held into main memo...
Dimitris G. Kapopoulos, Michael Hatzopoulos, Panag...
We extend the VC theory of statistical learning to data dependent spaces of classifiers. This theory can be viewed as a decomposition of classifier design into two components; the...
Adam Cannon, J. Mark Ettinger, Don R. Hush, Clint ...
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
A fundamental open problem in computational learning theory is whether there is an attribute efficient learning algorithm for the concept class of decision lists (Rivest, 1987; Bl...
A set of fundamental principles can act as an enabler in the establishment of a discipline; however, software engineering still lacks a set of universally recognized fundamental p...
Pierre Bourque, Robert Dupuis, Alain Abran, James ...