In this project, WNCG Prof. Joydeep Ghosh and his students and collaborators developed numerous discriminative and generative models for solving large scale transfer learning problems prevalent in text document analysis, social network study, recommender systems, object recognition from images, evolution of financial data and sports analytics.
Distributed storage systems for large clusters typically use replication to provide reliability. Recently, erasure codes have been used to reduce the large storage overhead of three-replicated systems. Reed-Solomon codes are the standard design choice and their high rebuild cost is often considered an unavoidable price to pay for high storage efficiency and high reliability.
Recent years have radically changed the way people socialize; in parts of the developed world that have good broadband and cellular penetration, the average person now spends more time on online social networks than on physical meetings with acquaintances outside their immediate family.
Social networks today face several fundamental problems. The research of WNCG Profs. Sujay Sanghavi and Sanjay Shakkottai and student collaborators sift through the information overload to bring sense to large-scale social networks in three primary ways.
When studying Social Networks, the public mind does not often consider the enormous impact the field of Electrical Engineering has on the development of these networks.
“Many tools that traditionally belonged to applied mathematics and electrical engineering have proven to be very useful in social networks,” WNCG Prof. Constantine Caramanis states.
Recent years have radically changed the way people socialize; in parts of the developed world that have good broadband and cellular penetration, the average person now spends more time on online social networks than on physical meetings with acquaintances outside their immediate family.
“We were socializing before social networks,” Prof. Sujay Sanghavi states. “But now we can automatically capture fine details of social interaction, such as when someone views a photo and how they share and interact with the image.”
The problem now is the issue of information overload.
WNCG Ph.D. student Chris Milling, along with WNCG Professors Constantine Caramanis and Sanjay Shakkottai, and Technion Professor Shie Mannor, have developed efficient algorithms for quickly and efficiently determining if an epidemic is spreading through a social network.
