Author Description

Recently organized competitions have been instrumental in pushing the state-of-the-art in machine learning, establishing benchmarks to fairly evaluate methods, and identifying techniques that really work. This volume in the Challenges in Machine Learning series harvests three years of effort of hundreds of researchers who have participated in three competitions organized around five datasets from various application domains, designed to explore issues of data representation, model selection, and performance prediction.