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stat.ML2025
Hybrid least squares for learning functions from highly noisy data
Ben Adcock, Bernhard Hientzsch, Akil Narayan +1
Motivated by the need for efficient estimation of conditional expectations, we consider a least-squares function approximation problem with heavily polluted data. Existing methods…
stat.CO2025
Optimally balancing exploration and exploitation to automate multi-fidelity statistical estimation
Thomas Dixon, Alex Gorodetsky, John Jakeman +2
Multi-fidelity methods that use an ensemble of models to compute a Monte Carlo estimator of the expectation of a high-fidelity model can significantly reduce computational costs co…