M.Sc. Thesis Defence: Visual Analysis of High-Dimensional Parameter Spaces - Thomas Torsney-Weir
We present a system called Tuner to systematically analyze the parameter space of complex computer simulations, which are time consuming to run and consequently cannot be exhaustively sampled.
We begin with a sparse initial sampling of the parameter space, then use these samples to create a fast emulator of the simulation. Analyzing this emulator gives the user insight on further sampling the simulation. Tuner guides the user through sampling and provides tools to find optimal parameter settings of up to two objective functions and perform sensitivity analysis. We present use-cases from the domain of image segementation algorithms.
Since our method must utilize samples of the simulation and relies on an inherently interactive visualization method, we perform a complexity analysis to see how many samples can be rendered while staying interactive. We also examined how rendering performance changes with the dimensionality, reconstruction kernel size, and number of sample points.