Efficient Learning of Label Ranking by Soft Projections onto Polyhedra


We discuss the problem of learning to rank labels from a real valued feedback associated with each label. We cast the feedback as a preferences graph where the nodes of the graph are the labels and edges express preferences over labels. We tackle the learning problem by defining a loss function for comparing a predicted graph with a feedback graph. This… (More)

9 Figures and Tables



Citations per Year

86 Citations

Semantic Scholar estimates that this publication has 86 citations based on the available data.

See our FAQ for additional information.

  • Presentations referencing similar topics