This paper investigates the performance of machine learning methods for classifying rock types from hyperspectral data. The main objective is to test the impact on classification ...
Approximating pairwise, or k-wise, independence with sublinear memory is of considerable importance in the data stream model. In the streaming model the joint distribution is give...
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distributio...
We resolve an open question raised by Feige & Scheideler by showing that the best known approximation algorithm for flow shops is essentially tight with respect to the used low...
Localization is an important and extensively studied problem in ad-hoc wireless sensor networks. Given the connectivity graph of the sensor nodes, along with additional local info...
Amitabh Basu, Jie Gao, Joseph S. B. Mitchell, Giri...