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Indices of quadratic programs over reproducing kernel Hilbert spaces for fun and profit
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We give an abstract perspective on quadratic programming with an eye toward long portfolio theory geared toward explaining sparsity via maximum principles. Specifically, in optimal allocation problems, we see that support of an optimal distribution lies in a variety intersect a kind of distinguished boundary of a compact subspace to be allocated over. We demonstrate some of its intelligence by using it to solve mazes and interpret such behavior as the underlying space trying to understand some hypothetical platonic index for which the capital asset pricing model holds.
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Cited by 1 Pith paper
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Positive-Allocation Companion Predictors for Nonlinear Dynamics and Their Finite-Difference Diagnostics
A nonnegative, sum-to-one weighted average of past snapshots defines a companion predictor whose spectrum lies in the unit disk and includes 1 as an eigenvalue.
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