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 ...
Abstract-- When dealing with massive quantities of data, topk queries are a powerful technique for returning only the k most relevant tuples for inspection, based on a scoring func...
This paper proposes a method for computing fast approximations to support vector decision functions in the field of object detection. In the present approach we are building on an...
Maximizing only the relevance between queries and documents will not satisfy users if they want the top search results to present a wide coverage of topics by a few representative...
Yi Liu, Benyu Zhang, Zheng Chen, Michael R. Lyu, W...
This paper gives an efficient Bayesian method for inferring the parameters of a PlackettLuce ranking model. Such models are parameterised distributions over rankings of a finite s...