We propose a network characterization of combinatorial fitness landscapes by adapting the notion of inherent networks proposed for energy surfaces [5]. We use the well-known fami...
In the traditional voting manipulation literature, it is assumed that a group of manipulators jointly misrepresent their preferences to get a certain candidate elected, while the ...
Learning function relations or understanding structures of data lying in manifolds embedded in huge dimensional Euclidean spaces is an important topic in learning theory. In this ...
We consider a discrete time state estimation problem over a packet-based network. In each discrete time step, a measurement packet is sent across a lossy network to an estimator u...
Michael Epstein, Ling Shi, Abhishek Tiwari, Richar...
We propose a natural generalisation of asynchronous bounded delay (ABD) network models. The commonly used ABD models assume a known bound on message delay. This assumption is ofte...