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math.NA2026
Low-rank kernel methods for American option pricing
Michael Multerer, Paul Schneider, Chiara Segala
We propose a scalable and theoretically grounded low-rank conditional expectation model for recursive Monte Carlo optimal stopping problems, in particular American option pricing.…
math.NA2026
Tree-Adaptive Multiscale Kernel Lasso in Samplet Coordinates
Sara Avesani, Gaia Fumagalli, Michael Multerer +1
We develop a novel framework for sparse multiscale kernel approximation of large scattered data problems based on a samplet representation. Samplets form a multiresolution analysis…