We analyze the application of ensemble learning to recommender systems on the Netflix Prize dataset. For our analysis we use a set of diverse state-of-the-art collaborative filt...
While many devices today increasingly have the ability to predict human activities, it is still difficult to build accurate personalized machine learning models. As users today wi...
In the past ten years, boosting has become a major field of machine learning and classification. This paper brings contributions to its theory and algorithms. We first unify a ...
Despite advances in the application of automated statistical and machine learning techniques to system log and trace data there will always be a need for human analysis of machine...
We present an algorithm, witch, that learns to detect spam hosts or pages on the Web. Unlike most other approaches, it simultaneously exploits the structure of the Web graph as we...
Jacob Abernethy, Olivier Chapelle, Carlos Castillo