Statistical machine learning is in the midst of a "relational revolution". After many decades of focusing on independent and identically-distributed (iid) examples, researchers are now studying problems in which the examples are linked together into complex networks. These networks can be a simple as sequences and 2-D meshes (such as those arising in part-of-speech tagging and remote sensing) or as complex as the collaboration structures produced by knowledge workers performing a variety of tasks in different contexts within an enterprise. In this talk, I will give an overview of this newly emerging research, focusing specifically on link mining tasks and algorithms.