Abstract. We are interested in efficient algorithms for generating random samples from geometric objects such as Riemannian manifolds. As a step in this direction, we consider the ...
We present a new random search method for solving simulation optimization problems. Our approach emphasizes the need for maintaining the right balance between exploration and expl...
We present the results of an empirical study of several constraint satisfaction search algorithms and heuristics. Using a random problem generator that allows us to create instanc...
We describe a detailed experimental investigation of the phase transition for several different classes of randomly generated satisfiability problems. We observe a remarkable consi...
There has been increasing interest in the problem of building accurate data mining models over aggregate data, while protecting privacy at the level of individual records. One app...
Alexandre V. Evfimievski, Johannes Gehrke, Ramakri...