83 search results - page 10 / 17 » Neural Network Learning: Testing Bounds on Sample Complexity |
MLDM
2001
Springer
13 years 12 months ago
2001
Springer
Abstract. This paper proposes a general local learning framework to effectively alleviate the complexities of classifier design by means of “divide and conquer” principle and ...
ICDM
2009
IEEE
13 years 5 months ago
2009
IEEE
Recently a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and ide...
BMCBI
2008
13 years 7 months ago
2008
Background: Bioactivity profiling using high-throughput in vitro assays can reduce the cost and time required for toxicological screening of environmental chemicals and can also r...
CORR
2007
Springer
13 years 7 months ago
2007
Springer
Results of neural network learning are always subject to some variability, due to the sensitivity to initial conditions, to convergence to local minima, and, sometimes more dramat...
GIS
2009
ACM
13 years 11 months ago
2009
ACM
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...