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Stability and Generalization of Bipartite Ranking Algorithms
[chapter]
2005
Lecture Notes in Computer Science
The problem of ranking, in which the goal is to learn a real-valued ranking function that induces a ranking or ordering over an instance space, has recently gained attention in machine learning. We study generalization properties of ranking algorithms, in a particular setting of the ranking problem known as the bipartite ranking problem, using the notion of algorithmic stability. In particular, we derive generalization bounds for bipartite ranking algorithms that have good stability properties.
doi:10.1007/11503415_3
fatcat:upnmlttjerfbrnpc2ek5zoykrq