We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
Modeling query concepts through term dependencies has been shown to have a significant positive effect on retrieval performance, especially for tasks such as web search, where rel...
Learning from streams of evolving and unbounded data is an important problem, for example in visual surveillance or internet scale data. For such large and evolving real-world data...
Chen Change Loy, Timothy M. Hospedales, Tao Xiang,...
State-of-the-art person re-identication methods seek robust person matching through combining various feature types. Often, these features are implicitly assigned with a single ve...
The goal of active learning is to determine the locations of training input points so that the generalization error is minimized. We discuss the problem of active learning in line...