An O(log n) time, n processor randomized algorithm for computing the k-nearest neighbor graph of n points in d dimensions, for fixed d and k is presented. The method is based on t...
We study the problem of scheduling independent tasks on a set of related processors which have a probability of failure governed by an exponential law. We are interested in the bi-...
A lower bound on the minimum mean-squared error (MSE) in a Bayesian estimation problem is proposed in this paper. This bound utilizes a well-known connection to the deterministic e...
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Predictive models developed by applying Data Mining techniques are used to improve forecasting accuracy in the airline business. In order to maximize the revenue on a flight, the ...