We investigate the degree sequences of scale-free random graphs. We obtain a formula for the limiting proportion of vertices with degree d, confirming non-rigorous arguments of Do...
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...
We analyze the convergence of the spectrum of large random graphs to the spectrum of a limit infinite graph. We apply these results to graphs converging locally to trees and deri...
We demonstrate a system capable of tracking, in real world image sequences, landmarks such as eyes, mouth, or chin on a face. In the standard version, knowledge previously collect...
When classifying high-dimensional sequence data, traditional methods (e.g., HMMs, CRFs) may require large amounts of training data to avoid overfitting. In such cases dimensional...