In this paper, we present a novel, threshold-free robust estimation framework capable of efficiently fitting models to contaminated data. While RANSAC and its many variants have...
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
The accuracy of collaborative filtering recommender systems largely depends on two factors: the quality of the recommendation algorithm and the nature of the available item rating...
Current mainstream Evolutionary Algorithms (EA) are based on the concept of selection, encapsulated in the definition of a fitness function. Besides selection, however, the natur...
We analyze the properties of Small-World networks, where links are much more likely to connect “neighbor nodes” than distant nodes. In particular, our analysis provides new re...