This paper investigates a class of learning problems called learning satisfiability (LSAT) problems, where the goal is to learn a set in the input (feature) space that satisfies...
Frederic Thouin, Mark Coates, Brian Eriksson, Robe...
The paper considers robust optimization to cope with uncertainty about the stock return process in one period option hedging problems. The robust approach relates portfolio choice ...
In this paper, we demonstrate an integrated registration and clustering algorithm to compute an atlas of fiberbundles from a set of multi-subject diffusion weighted MR images. We ...
Ulas Ziyan, Mert R. Sabuncu, W. Eric L. Grimson, C...
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Gaussian mixture models have been widely used in image segmentation. However, such models are sensitive to outliers. In this paper, we consider a robust model for image segmentati...
Giorgos Sfikas, Christophoros Nikou, Nikolas P. Ga...