A gradient-based sample generation framework is proposed to identify macroeconomic conditions inducing specific behaviors in portfolio optimization pipelines.
arXiv preprint arXiv:2401.05080 , year =
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
DASH reduces problem dimensionality in MIQP subset selection to improve MIP solver incumbent quality on hard portfolio instances.
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Generating Input Distributions for Explaining Portfolio Optimization Pipelines
A gradient-based sample generation framework is proposed to identify macroeconomic conditions inducing specific behaviors in portfolio optimization pipelines.
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DASH: A Dimensionality Reduction Method for Large-scale Convex MIQP with Applications in Subset Portfolio Selection
DASH reduces problem dimensionality in MIQP subset selection to improve MIP solver incumbent quality on hard portfolio instances.