Linear support vector machines (SVM) are useful for classifying large-scale sparse data. Problems with sparse features are common in applications such as document classification a...
Service composition is emerging as an important paradigm for constructing distributed applications by combining and reusing independently developed component services. One key issu...
Groundwater long-term monitoring (LTM) is required to assess the performance of groundwater remediation and human being health risk at post-closure sites where groundwater contami...
Clustering in gene expression data sets is a challenging problem. Different algorithms for clustering of genes have been proposed. However due to the large number of genes only a ...
We present an algorithm for large-scale equality constrained optimization. The method is based on a characterization of inexact sequential quadratic programming (SQP) steps that ca...