Robert Nowak ECE Dept., UW-Madison [email protected]www.ece.wisc.edu/~nowak Research Interests: statistical signal processing, machine learning, imaging and network science, and applications in communications, bio/medical imaging, and in silico genomics. Network Science, National Academies Press, 2006 The study of complex networked systems. Key Challenges : “Characterization of the dynamics and information flow in networked systems, modeling, analysis, and acquisition of experimental data for extremely large networks.” My take: In many large-scale problems we have limited prior knowledge, but a wealth of data. How much can we learn from data? Adaptivity to unknown system behavior is key.
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Robert Nowak ECE Dept., UW-Madison [email protected] ece.wisc/~nowak
Robert Nowak ECE Dept., UW-Madison [email protected] www.ece.wisc.edu/~nowak. Research Interests : statistical signal processing, machine learning, imaging and network science, and applications in communications, bio/medical imaging, and in silico genomics. . - PowerPoint PPT Presentation
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Research Interests: statistical signal processing, machine learning, imaging and network science, and applications in communications, bio/medical imaging, and in silico genomics. Network Science, National Academies Press, 2006
The study of complex networked systems.
Key Challenges : “Characterization of the dynamics and information flow in networked systems, modeling, analysis, and acquisition of experimental data for extremely large networks.”
My take: In many large-scale problems we have limited prior knowledge, but a wealth of data. How much can we learn from data? Adaptivity to unknown system behavior is key.
Challenge 1: Inferring Networks from Experimental Data
Network Tomography: Infer network behavior and structure from indirect and incomplete data