Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
The affine rank minimization problem consists of finding a matrix of minimum rank that satisfies a given system of linear equality constraints. Such problems have appeared in the ...
Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as op...
The problem of group ranking, a.k.a. rank aggregation, has been studied in contexts varying from sports, to multi-criteria decision making, to machine learning, to ranking web pag...
RankSVM (Herbrich et al, 2000; Joachims, 2002) is a pairwise method for designing ranking models. SVMLight is the only publicly available software for RankSVM. It is slow and, due ...