Efficient Learning of Label Ranking by Soft Projections onto Polyhedra

Abstract

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

Topics

Statistics

051015'06'07'08'09'10'11'12'13'14'15'16'17'18
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