Feature selection aims to reduce dimensionality for building comprehensible learning models with good generalization performance. Feature selection algorithms are largely studied ...
Learning in many multi-agent settings is inherently repeated play. This calls into question the naive application of single play Nash equilibria in multi-agent learning and sugges...
Irregular algorithms are organized around pointer-based data structures such as graphs and trees, and they are ubiquitous in applications. Recent work by the Galois project has pr...
Abstract—In this paper, we study algebraic aggregate computations in Sensor Networks. The main contribution is the presentation of an early-stopping protocol that computes the av...
This paper proposes the integration of semantic information drawn from a web application’s domain knowledge into all phases of the web usage mining process (preprocessing, patte...