This dissertation is mainly focused on assimilation of data into hydrodynamic models of water flow in open channel networks which is motivated by the need for accurate flow models in various applications such as emergency response and flood monitoring systems, automated gate sys…
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The related tasks of certifying bounds on optimization problems and refuting unsatisfiable systems of constraints have a long history in computer science and optimization, and deep mathematical roots in the proof complexity of algebraic systems. From the algorithmic perspective,…
Fitting multivariate autoregressive (AR) models is fundamental for analysis of time-series data in a wide range of applications in science, engineering, econometrics, signal processing, and data-science. This dissertation considers the problem of learning a p-lag multivariate AR…