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Online Optimization in Dynamic Environments
High-velocity streams of high-dimensional data pose significant "big data" analysis challenges across a range of applications and settings.
Tracking Dynamic Point Processes on Networks
Recent work on online learning in dynamic environments is leveraged not only to exploit the dynamics within the underlying network, but also to track the network structure as it evolves.
Inference of High-dimensional Autoregressive Generalized Linear Models
For instance, each element of an observation vector could correspond to a different node in a network, and the parameters of an autoregressive model would correspond to the impact of the network structure on the time series evolution.
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