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inference_and_control_in_complex_networks [2016/09/01 19:15] (current)
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 +Title: Inference and Control in Complex Networks
 +Abstract: A defining feature of the present is the interconnectedness of diverse physical or engineering networks, such as social, economic or information/​technological networks. The engineering challenge is to devise low complexity but efficient algorithms across all these network types, to understand them better and to achieve the best performance. In this talk we will outline our research on different problems in this space and detail two specific problems, one on the performance or control aspect and the other on the understanding or inference aspect. The first problem concerns resource allocation problems for call centers, Internet routers, wireless networks, semiconductor fabrication plants, job shops, supply chains and hospitals where server allocation or routing has to be performed with various combinatorial constraints on how different parts of the network can be activated. With this viewpoint, the resource allocation problems encountered can be addressed using the (stochastic) switched networks paradigm. We will present a refined analysis of the popular MaxWeight scheduling policy focusing on outage behavior. In the same context we will conclude with pointers to recent research on the performance of a completely distributed algorithm inspired by statistical physics methods. The second problem is on analyzing and inferring user behavior in a social network. Network games provide a basic framework for studying the diffusion of new ideas or behaviors through a population. In these models, agents decide to adopt a new idea based on optimizing pay-off that depends on the adoption decisions of their neighbors in an underlying network. Assuming such a model, we consider the problem of inferring early adopters or first movers given a snap shot of the adoption state at a given time. 
 +Speaker Bio: Vijay Subramanian is a Research Assistant Professor in the Electrical Engineering and Computer Science Department at Northwestern University. He received his Ph.D. degree from the University of Illinois at Urbana-Champaign in 1999. From 1999 to 2006, he was with the Networks Business, Motorola. From May 2006 to Nov 2010 he was a Research Fellow at the Hamilton Institute, NUIM, Ireland following which he was a Senior Research Associate at Northwestern University. His research interests include communication networks, social networks, queuing theory, mathematical immunology, information theory and applied probability.
inference_and_control_in_complex_networks.txt ยท Last modified: 2016/09/01 19:15 (external edit)