We define and study the link prediction problem in bipartite networks, specializing general link prediction algorithms to the bipartite case. In a graph, a link prediction functio...
For many supervised learning problems, we possess prior knowledge about which features yield similar information about the target variable. In predicting the topic of a document, ...
Ted Sandler, John Blitzer, Partha Pratim Talukdar,...
Research community on distributed systems, and in particular on peer-to-peer systems, needs tools for evaluating their own protocols and services, as well as against other protoco...
Systems biologic studies of gene and protein interaction networks have found that these networks are comprised of `modules' (groups of tightly interconnected nodes). Module i...
In this paper, we provide new complexity results for algorithms that learn discrete-variable Bayesian networks from data. Our results apply whenever the learning algorithm uses a ...
David Maxwell Chickering, Christopher Meek, David ...