Multi-instance learning deals with problems that treat bags of instances as training examples. In single-instance learning problems, dimensionality reduction is an essential step ...
The next generation Internet is designed to accommodate flows that span across multiple domains with quality of service guarantees, in particular bandwidth. In this context, destin...
Kin-Hon Ho, Ning Wang, Panos Trimintzios, George P...
We present a new method for multi-object segmentation in a maximum a posteriori estimation framework. Our method is motivated by the observation that neighboring or coupling objec...
In the last few years, new view synthesis has emerged as an important application of 3D stereo reconstruction. While the quality of stereo has improved, it is still imperfect, and...
Samuel W. Hasinoff, Sing Bing Kang, Richard Szelis...
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...