Harmonic analysis and diffusion on discrete data has been shown to lead to state-of-theart algorithms for machine learning tasks, especially in the context of semi-supervised and ...
Arthur D. Szlam, Mauro Maggioni, Ronald R. Coifman
We propose a family of kernels between images, defined as kernels between their respective segmentation graphs. The kernels are based on soft matching of subtree-patterns of the r...
Graph based semi-supervised learning methods (SSL) implicitly assume that the intrinsic geometry of the data points can be fully specified by an Euclidean distance based local ne...
We consider the problem of performing learning and inference in a large scale knowledge base containing imperfect knowledge with incomplete coverage. We show that a soft inference...
Structural Statistical Software Testing (SSST) exploits the control flow graph of the program being tested to construct test cases. Specifically, SSST exploits the feasible paths...