In this paper, we present a general guideline to find a better distance measure for similarity estimation based on statistical analysis of distribution models and distance function...
Jie Yu, Jaume Amores, Nicu Sebe, Petia Radeva, Qi ...
Many problems in vision can be formulated as Bayesian inference. It is important to determine the accuracy of these inferences and how they depend on the problem domain. In recent...
Alan L. Yuille, James M. Coughlan, Song Chun Zhu, ...
This contribution develops a theoretical framework that takes into account the effect of approximate optimization on learning algorithms. The analysis shows distinct tradeoffs for...
Learning to rank is a new statistical learning technology on creating a ranking model for sorting objects. The technology has been successfully applied to web search, and is becom...
Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang...
One of the central problems in building broad-coverage story understanding systems is generating expectations about event sequences, i.e. predicting what happens next given some a...