There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...
A maximal independent set on a graph is an inclusion-maximal set of mutually non-adjacent nodes. This basic symmetry breaking structure is vital for many distributed algorithms, w...
We analyze the properties of Small-World networks, where links are much more likely to connect “neighbor nodes” than distant nodes. In particular, our analysis provides new re...
Routing is one of the most challenging open problems in disruption-tolerant networks (DTNs) because of the shortlived wireless connectivity environment. To deal with this issue, r...
We derive PAC-Bayesian generalization bounds for supervised and unsupervised learning models based on clustering, such as co-clustering, matrix tri-factorization, graphical models...