Adaptive joint distribution learning

Damir Filipović, Michael D. Multerer and Paul Schneider
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Damir Filipović: École Polytechnique Fédérale de Lausanne; Swiss Finance Institute
Michael D. Multerer: Swiss Finance Institute - USI Lugano
Paul Schneider: University of Lugano - Institute of Finance; Swiss Finance Institute

No 24-50, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We develop a new framework for estimating joint probability distributions using tensor product reproducing kernel Hilbert spaces (RKHS). Our framework accommodates a low-dimensional, normalized and positive model of a Radon-Nikodym derivative, which we estimate from sample sizes of up to several millions, alleviating the inherent limitations of RKHS modeling. Well-defined normalized and positive conditional distributions are natural by-products to our approach. Our proposal is fast to compute and accommodates learning problems ranging from prediction to classification. Our theoretical findings are supplemented by favorable numerical results.

Keywords: distribution estimation; tensor product RKHS; low-rank approximation (search for similar items in EconPapers)
JEL-codes: D15 (search for similar items in EconPapers)
Pages: 26 pages
Date: 2024-09
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp2450

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