In high-dimensional and complex metric spaces, determining the nearest neighbor (NN) of a query object ? can be a very expensive task, because of the poor partitioning operated by...
We address the problem of designing data structures that allow efficient search for approximate nearest neighbors. More specifically, given a database consisting of a set of vecto...
The proposed feature selection method aims to find a minimum subset of the most informative variables for classification/regression by efficiently approximating the Markov Blanket ...
In this paper, we describe a new algorithm for sampling solutions from a uniform distribution over the solutions of a constraint network. Our new algorithm improves upon the Sampli...
We present a new estimator for counting the number of solutions of a Boolean satisfiability problem as a part of an importance sampling framework. The estimator uses the recently...