We present a practical, stratified autocalibration algorithm with theoretical guarantees of global optimality. Given a projective reconstruction, the first stage of the algorithm ...
Spearman’s footrule and Kendall’s tau are two well established distances between rankings. They, however, fail to take into account concepts crucial to evaluating a result set...
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
In designing dynamic situations such as cyberworlds, we the Incrementally Modular Abstraction Hierarchy (IMAH) to be an appropriate mathematical background to model dynamically ch...
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...