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arXiv Machine Learning By Marcell T. Kurbucz

Adaptive Conditional Forest Sampling for Spectral Risk Optimisation under Decision-Dependent Uncertainty

Read the original on arXiv Machine Learning →

arXiv:2603. 12507v2 Announce Type: replace Abstract: Minimising a spectral risk objective, defined as a weighted combination of expected cost and Conditional Value-at-Risk (CVaR), is challenging when the uncertainty distribution is decision-dependent, making both surrogate modelling and simulation-based ranking sensitive to tail estimation error.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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