In this paper, we consider the link prediction problem, where we are given a partial snapshot of a network at some time and the goal is to predict the additional links formed at a ...
Janardhan Rao Doppa, Jun Yu, Prasad Tadepalli, Lis...
We propose Link Propagation as a new semi-supervised learning method for link prediction problems, where the task is to predict unknown parts of the network structure by using aux...
: Phylogenetic profiles of proteins strings of ones and zeros encoding respectively the presence and absence of proteins in a group of genomes have recently been used to id...
This paper introduces a new discriminative learning technique for link prediction based on the matrix alignment approach. Our algorithm automatically determines the most predictiv...
Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-...
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...