This paper aims to conduct a study on the listwise approach to learning to rank. The listwise approach learns a ranking function by taking individual lists as instances and minimi...
This paper presents a theoretical framework for ranking, and demonstrates how to perform generalization analysis of listwise ranking algorithms using the framework. Many learning-...
Positive results from new object-oriented tools for scientific programming are reported. Using template classes, abstractions of matrix representations are available that subsume...
Peter Gottschling, David S. Wise, Michael D. Adams
Traditional ranking mainly focuses on one type of data source, and effective modeling still relies on a sufficiently large number of labeled or supervised examples. However, in m...
Bo Wang, Jie Tang, Wei Fan, Songcan Chen, Zi Yang,...
We present a novel solution to the inter-camera color calibration problem, which is very important for multi-camera systems. We propose a distance metric and a model function to e...