Academics / Courses / DescriptionsCOMP_SCI 496: Algorithmic Aspects of Network Inference
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Prerequisites
COMP_SCI 336, ELEC ENG 422, or equivalent coursesDescription
Diverse communities like economics, social science, and computer science use network models for understanding the impact of interconnections between various entities on their actions. Moreover, many important dynamic processes are determined by an underlying network structure e.g., spread of epidemics, the dynamics of public opinions, the diffusion of information about social programs.
This is an inter-disciplinary course that will cover several approaches for inferring network structure and learning network models based on the observations of actions of these entities. We will also cover methods and techniques for reasoning about dynamic processes on networks, that will also help us answer questions of the form: What is the source of a rumor? Will a given disease spread widely? Who are the key influencers?
Pre-requisites:
The course will be a proof-based course, and assume sufficient mathematical sophistication and familiarity with topics like Graph theory, probability, linear algebra, and optimization. The student is expected to have taken COMP_SCI 336 or ELEC ENG 422 (for CS or ECE majors), or equivalent courses in other disciplines.
- Cross-listed with ELEC_ENG 495