In this paper, we propose a unified algorithmic framework for solving many known variants of MDS. Our algorithm is a simple iterative scheme with guaranteed convergence, and is m...
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasu...
We describe the design and evaluation of K-net, a social matching system to help people learn 'who knows what' in an organization by matching people with skills with tho...
N. Sadat Shami, Y. Connie Yuan, Dan Cosley, Ling X...
Kernel machines rely on an implicit mapping of the data such that non-linear classification in the original space corresponds to linear classification in the new space. As kernel ...
With the success of local features in object recognition, feature-set representations are widely used in computer vision and related domains. Pyramid match kernel (PMK) is an effi...
In this paper, we propose an extended local search framework to solve combinatorial optimization problems with data uncertainty. Our approach represents a major departure from sce...