Scalable Network Analysis

Unstructured data is being generated at a tremendous rate in modern applications as diverse as social networks, recommender systems, genomics, health care and energy management. Networks are an important example of unstructured data and may arise explicitly, as in social networks, or implicitly, as in recommender systems. These networks are challenging to handle; not only are they large-scale but they are constantly evolving, and many applications require difficult prediction tasks to be solved, such as link or ratings prediction. In this talk, I will discuss scalable solutions for a class of prediction tasks on large-scale networks, that involve algorithmic innovation in response to the demands of modern computer systems.