We present a technique for transforming classical approximation algorithms into constant-time algorithms that approximate the size of the optimal solution. Our technique is applic...
Abstract. In this paper we propose an algorithm for personalized learning based on a user’s query and a repository of lecture subparts —i.e., learning objects— both are descr...
In this paper we present Clustering Protocol (CP) for sensor networks. Clustering techniques are used by different protocols and applications to increase scalability and reduce de...
We define an algorithmic paradigm, the stack model, that captures many primal-dual and local-ratio algorithms for approximating covering and packing problems. The stack model is ...
In the well-known "prisoners' problem", a representative example of steganography, two persons attempt to communicate covertly without alerting the warden. One appr...