The k-means algorithm is widely used for clustering because of its computational efficiency. Given n points in d-dimensional space and the number of desired clusters k, k-means see...
In this paper we deal with two problems which are of great interest in the field of distributed decision making and control. The first problem we tackle is the problem of achieving...
Kunal Srivastava, Angelia Nedic, Dusan M. Stipanov...
Coverage, fault tolerance and power consumption constraints make optimal placement of mobile sensors or other mobile agents a hard problem. We have developed a model for describin...
As a metabolic network reaches from a state to a steady state, a subset of its fluxes gradually change. The sequence of intermediate states, called the dynamic state, shows the pa...
Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pa...
Konrad Rieck, Tammo Krueger, Ulf Brefeld, Klaus-Ro...