The study described in this paper, analyzed the urban and suburban air pollution principal causes and identified the best subset of features (meteorological data and air pollutants...
Giovanni Raimondo, Alfonso Montuori, Walter Moniac...
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. ...
Abstract--Recently, sparse approximation has become a preferred method for learning large scale kernel machines. This technique attempts to represent the solution with only a subse...
This paper describes one solution to the problem of how to select sequence, and link Web resources into a coherent, focused organization for instruction that addresses a user'...
Robert G. Farrell, Soyini D. Liburd, John C. Thoma...
Background: The search for cluster structure in microarray datasets is a base problem for the so-called “-omic sciences”. A difficult problem in clustering is how to handle da...