In order to understand AdaBoost’s dynamics, especially its ability to maximize margins, we derive an associated simplified nonlinear iterated map and analyze its behavior in lo...
Cynthia Rudin, Ingrid Daubechies, Robert E. Schapi...
Recommendation systems generally produce the results of their output to their users in the form of an ordinal list. In the interest of simplicity, these lists are often obscure, ,...
We consider in this paper a popular class of recommender systems that are based on Collaborative Filtering (CF for short). CF is the process of predicting customer ratings to item...
Predicting the interests of a user in information is an important process in personalized information systems. In this paper, we present a way to create prediction engines that al...
Mark van Setten, Mettina Veenstra, Anton Nijholt, ...
We present a group recommender system for vacations that helps group members who are not able to communicate synchronously to specify their preferences collaboratively and to arri...
Anthony Jameson, Stephan Baldes, Thomas Kleinbauer