Abstract. Most of the work in machine learning assume that examples are generated at random according to some stationary probability distribution. In this work we study the problem...
Otter-lambda is Otter modified by adding code to implement an algorithm for lambda unification. Otter is a resolution-based, clause-language first-order prover that accumulates de...
We develop theory and algorithms to incorporate image manifold constraints in a level set segmentation algorithm. This provides a framework to simultaneously segment every image o...
For the first time, we present an AM-FM image model that, in addition to being remarkably consistent with human visual perception, also provides perfect reconstruction of the imag...
Abstract. We present a new method for computing an optimal deformation between two arbitrary surfaces embedded in Euclidean 3-dimensional space. Our main contribution is in buildin...