We present a theoretical analysis of supervised ranking, providing necessary and sufficient conditions for the asymptotic consistency of algorithms based on minimizing a surrogate...
Many learning systems suffer from the utility problem; that is, that time after learning is greater than time before learning. Discovering how to assure that learned knowledge wil...
We present algorithms for automatic feature selection for unsupervised structure discovery from video sequences. Feature selection in this scenario is hard because of the absence ...
PageRank is the best known technique for link-based importance ranking. The computed importance scores, however, are not directly comparable across different snapshots of an evolv...
Klaus Berberich, Srikanta J. Bedathur, Gerhard Wei...
Trust propagation is a fundamental topic of study in the theory and practice of ranking and recommendation systems on networks. The Page Rank [9] algorithm ranks web pages by propa...
Christian Borgs, Jennifer T. Chayes, Adam Tauman K...