Perceptron training is widely applied in the natural language processing community for learning complex structured models. Like all structured prediction learning frameworks, the ...
A challenging problem of multi-label learning is that both the label space and the model complexity will grow rapidly with the increase in the number of labels, and thus makes the...
We present an approach to synthesizing shapes from complex domains, by identifying new plausible combinations of components from existing shapes. Our primary contribution is a new...
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
Multi-camera networks bring in potentials for a variety of vision-based applications through provisioning of rich visual information. In this paper a method of image segmentation f...