Memetic algorithms with continuous local search methods have arisen as effective tools to address the difficulty of obtaining reliable solutions of high precision for complex cont...
Abstract--We adapt methods originally developed in information and coding theory to solve some testing problems. The efficiency of two-stage pool testing of items is characterized ...
Many approaches to active learning involve training one classifier by periodically choosing new data points about which the classifier has the least confidence, but designing a co...
We consider the problem of computing the k-sparse approximation to the discrete Fourier transform of an ndimensional signal. We show: • An O(k log n)-time randomized algorithm f...
Haitham Hassanieh, Piotr Indyk, Dina Katabi, Eric ...
Abstract-- In evolutionary algorithms, the fitness of a population increases with time by mutating and recombining individuals and by a biased selection of more fit individuals. Th...