We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
Support Vector Machines (SVMs) have been applied to solve the classification of volatile organic compounds (VOC) data in some recent studies. SVMs provide good generalization perfo...
Financial forecasting is the basis for budgeting activities and estimating future financing needs. Applying machine learning and data mining models to financial forecasting is both...
: In recent years the fusion of multimedia information from multiple real-time sources and databases has become increasingly important because of its practical significance in many...
Traffic Congestion is a multi-billion dollar national problem and worsening every year with population growth and increase in freight traffic. We present a model for realistic s...