R. Schapire shares ACM 2004 theory & practice award.
"This award recognizes the seminal work and distinguished contributions of Yoav Freund and Robert Schapire to the development of the theory and practice of boosting, a general and provably effective method of producing arbitrarily accurate prediction rules by combining weak learning rules. That this was possible at all, let alone in polynomial time, was not known until Schapire's breakthrough 1990 paper. A year later, Freund developed a more efficient boosting algorithm, and subsequent work culminated in Freund and Schapire's AdaBoost Algorithm. AdaBoost represents a significant contribution of computer science to statistics. Its elegance, wide applicability, simplicity of implementation and great success in practice have transformed boosting into one of the pillars of machine learning, broadly impacting various scientific communities and industry. The algorithm is already widely used, and still growing in its relevance and importance to the practice of machine learning."
See the ACM press release.
